Cvetković, V. M., Renner, R., Aleksova, B., & Lukić, T. (2024). Geospatial and Temporal Patterns of Natural and Man-Made (Technological) Disasters (1900–2024): Insights from Different Socio-Economic and Demographic Perspectives. Applied Sciences, 14(18), 8129.

Article

Geospatial and Temporal Patterns of Natural and Man-Made (Technological) Disasters (1900–2024): Insights from Different Socio-Economic and Demographic Perspectives

Vladimir M. Cvetkovic´ 1,2,3,*, Renate Renner 4, Bojana Aleksova 2,5 and Tin Lukic´ 2,6

 

Citation: Cvetkovic´, V.M.; Renner, R.; Aleksova, B.; Lukic´, T. Geospatial and Temporal Patterns of Natural and Man-Made (Technological) Disasters (1900–2024): Insights from Different Socio-Economic and Demographic Perspectives. Appl. Sci. 2024, 14, 8129. https://doi.org/10.3390/app14188129

Academic Editor: Wenjie Zhang

Received: 12 August 2024

Revised: 8 September 2024

Accepted: 9 September 2024

Published: 10 September 2024

 

Copyright: © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://

1 Department of Disaster Management and Environmental Security, Faculty of Security Studies, University of Belgrade, Gospodara Vucica 50, 11040 Belgrade, Serbia

2 Scientific-Professional Society for Disaster Risk Management, Dimitrija Tucovic´a 121, 11040 Belgrade, Serbia;

bojana.aleksova@mk.maarifschools.org (B.A.); tin.lukic@dgt.uns.ac.rs (T.L.)

3 International Institute for Disaster Research, Dimitrija Tucovic´a 121, 11040 Belgrade, Serbia

4 Safety and Disaster Studies, Chair of Thermal Processing Technology, Department of Environmental and Energy Process Engineering, Montanuniversitaet, 8700 Leoben, Austria; renate.renner@unileoben.ac.at

5 Maarif International School, Skopje Campus, Kiro Gligorov 5, 1000 Skopje, North Macedonia

6 Department of Geography, Tourism and Hotel Management, Faculty of Sciences, University of Novi Sad, Trg Dositeja Obradovic´a 3, 21000 Novi Sad, Serbia

* Correspondence: vmc@fb.bg.ac.rs

Abstract: This pioneering study explores the geospatial and temporal patterns of natural and human- induced disasters from 1900 to 2024, providing essential insights into their global distribution and impacts. Significant trends and disparities in disaster occurrences and their widespread consequences are revealed through the utilization of the comprehensive international EM-DAT database. The results showed a dramatic escalation in both natural and man-made (technological) disasters over the decades, with notable surges in the 1991–2000 and 2001–2010 periods. A total of 25,836 disasters were recorded worldwide, of which 69.41% were natural disasters (16,567) and 30.59% were man-made (technological) disasters (9269). The most significant increase in natural disasters occurred from 1961–1970, while man- made (technological) disasters surged substantially from 1981–1990. Seasonal trends reveal that floods peak in January and July, while storms are most frequent in June and October. Droughts and floods are the most devastating in terms of human lives, while storms and earthquakes cause the highest economic losses. The most substantial economic losses were reported during the 2001–2010 period, driven by catastrophic natural disasters in Asia and North America. Also, Asia was highlighted by our research as the most disaster-prone continent, accounting for 41.75% of global events, with 61.89% of these events being natural disasters. Oceania, despite experiencing fewer total disasters, shows a remarkable 91.51% of these as natural disasters. Africa is notable for its high incidence of man-made (technological) disasters, which constitute 43.79% of the continent’s disaster events. Europe, representing 11.96% of total disasters, exhibits a balanced distribution but tends towards natural disasters at 64.54%. Examining specific countries, China, India, and the United States emerged as the countries most frequently affected by both types of disasters. The impact of these disasters has been immense, with economic losses reaching their highest during the decade of 2010–2020, largely due to natural disasters. The human toll has been equally significant, with Asia recording the most fatalities and Africa the most injuries. Pearson’s correlation analysis identified statistically significant links between socioeconomic factors and the effects of disasters. It shows that nations with higher GDP per capita and better governance quality tend to experience fewer disasters and less severe negative consequences. These insights highlight the urgent need for tailored disaster risk management strategies that address the distinct challenges and impacts in various regions. By understanding historical disaster patterns, policymakers and stakeholders can better anticipate and manage future risks, ultimately safeguarding lives and economies.

Keywords: hazards; emergencies; natural disasters; man-made (technological) disasters; disaster risk management; socio-economic and human impact; EM-DAT database; geospatial; temporal analysis

creativecommons.org/licenses/by/                                                                                                                 

4.0/).

 

Appl. Sci. 2024, 14, 8129. https://doi.org/10.3390/app14188129 https://www.mdpi.com/journal/applsci

1. ‌Introduction

   In our increasingly interconnected world, grasping disasters’ geospatial and temporal patterns has become vital for effective disaster management and resilience planning [1]. Disasters, whether natural or human-induced, can have profound impacts on communities, economies, and the environment [2,3]. Environmental hazards, particularly air pollution, are of critical importance due to their role in increasing the susceptibility of populations to both natural and technological disasters. Specifically, air pollution poses direct threats to health and also compounds the effects of other environmental stressors, thereby elevating the overall risks faced by communities [4].

   Advances in big data analytics, alongside the integration of various data sources, have greatly enhanced our ability to track and assess these risks [5]. For instance, the utilization of big data has enabled the merging of a wide range of environmental information, resulting in more refined risk evaluations and the formulation of more precise mitigation strategies [6]. These advancements are becoming indispensable for addressing the complex challenges posed by the convergence of air pollution with other disaster-related risks. The risk of a disaster occurring is always a combination of vulnerability and exposure due to inadequate preparation or coping capacity [7]. This underscores the necessity of delving into the complex dynamics that influence their occurrence and distribution.

   Environmental events like earthquakes, floods, hurricanes, and wildfires are driven by natural and climatic forces [8–15]. The patterns of these disasters, including their frequency, intensity, and locations, have evolved over time due to shifts in climate, land usage, and population growth [16–21]. Also, trends can be uncovered and high-risk areas identified through the analysis of past data, thus improving the ability to forecast and respond to future events [22]. In contrast, man-made (technological) disasters arise from human activities such as industrial mishaps, nuclear accidents, and oil spills. These incidents often occur due to equipment failures, human and organizational mistakes [23], or weak regulatory measures. Failures can occur during the design, construction, operation or maintenance phases [24,25]. Insights into industrial operations and regulatory practices can be gained by examining when and where these disasters happen, leading to improved safety protocols and emergency response strategies [26].

   Recent research has shed light on significant advancements and methodologies for understanding the geospatial and temporal patterns of natural disasters [27–29]. Han et al. [30], for instance, use textual records to uncover the spatial–temporal patterns of natural disasters in China. Their findings highlight critical intervals and interactions between events, offering valuable guidance for disaster prevention efforts [30]. Ghosh [31] explores the integration of various geospatial technologies and data sources in disaster management. Also, he emphasizes how AI and big data can enhance emergency responses and decision-making processes. On the other hand, Wang [32] delves into the historical patterns of marine disasters in China, providing a multiscalar analysis of their temporal changes and spatial evolution. This research helps in understanding long-term trends and impacts (Wang, 2020). Additionally, Wei et al. [33] conduct a comprehensive study on the spatial–temporal evolution and prediction of flood disasters in China over the past 500 years, highlighting critical trends and future risks. Together, these studies deepen our understanding of disaster patterns and offer valuable insights for effective disaster management and mitigation strategies.

   The wealth of existing research on this subject provides crucial insights into the factors shaping these disaster patterns [32–42]. Geospatial analyses have revealed that some areas are particularly at risk for specific types of disasters. Factors such as the terrain, local climate, and how densely populated an area is significantly influence where these disasters occur [13]. Moreover, by studying temporal patterns, researchers can identify seasonal or cyclical trends and assess how climate change might be altering the frequency and severity of these events [43,44]. In addition, one study highlights the significant toll natural disasters can take on mental health, stressing the importance of comprehensive

   post-disaster intervention strategies to tackle the behavioral and psychological symptoms that follow such events [45].

   Regarding this, the aim of this study is to provide a scientific description and compre- hensive understanding of the patterns and impacts of natural and man-made (technological) disasters over more than a century. By analyzing the geospatial and temporal distribution of these events, this study aims to offer valuable insights that can inform future disaster risk management strategies, enhance preparedness, and ultimately contribute to reducing disaster-related losses. This research highlights the urgent need for tailored disaster risk management strategies that address the distinct challenges and impacts in various regions, thereby promoting resilience and sustainable development. A comprehensive understand- ing of the specific challenges and impacts encountered by different regions is crucial for developing strategies that not only bolster the resilience of these communities to future disasters but also align with broader sustainable development objectives. For example, addressing vulnerabilities related to infrastructure and socio-economic factors can foster more resilient systems that contribute to long-term sustainability and effectively reduce the risk of future disasters.

   Literature Review Geospatial and Temporal Patterns of Disasters

   Understanding and managing the effects of natural and man-made (technological) disasters have been significantly improved through geospatial analysis [46,47]. Analyzing historical data through geospatial techniques unveils patterns in the frequency and distri- bution of natural disasters worldwide [48]. This type of analysis is essential for grasping the temporal and spatial behaviors of these events, which in turn is critical for making accurate future predictions and improving disaster preparedness efforts [17,49]. Utilizing tools like remote sensing and GIS, researchers can now map out affected areas, predict potential damage, and evaluate the aftermath of these events [50]. This technological approach greatly supports efforts in disaster preparedness, effective response, and efficient recovery [17]. Geospatial technologies, including GIS and remote sensing, have proven to be highly effective tools for mapping and predicting natural disasters such as earthquakes, landslides, floods, and cyclones [47]. By utilizing these advanced technologies, researchers can accurately identify areas that are at high risk for such events.

   Moreover, these tools play a vital role in developing early warning systems that can help mitigate the impact of disasters by providing timely alerts and enabling better prepared- ness [35,36,41,51]. Remote sensing and geospatial analyses play a crucial role in evaluating damage and monitoring recovery efforts following disasters [42,52]. For example, the use of medium-resolution imagery alongside indices like NDVI and UI has been particularly effective in assessing recovery rates after tornadoes, where severely damaged areas tend to recover more slowly [52]. Satellite-based geospatial techniques offer a dependable alternative to traditional ground-based surveys, which are often hindered by hazardous conditions and logistical difficulties [48]. These technologies enable a comprehensive assessment of disaster impacts and facilitate more efficient recovery planning [50].

   Understanding the patterns, predicting future occurrences, and mitigating the impacts of natural and man-made (technological) disasters hinge significantly on temporal analysis. Andersen et al. [53] provide comprehensive guidance on conducting time-to-event analysis in observational studies, with a particular focus on hazard models and the Cox proportional hazards regression model. In another study, Tian et al. [40] introduce a framework for eval- uating community resilience to multiple hazards in the Anning River basin, underscoring the significance of socio-economic factors in enhancing adaptive risk management. Melkov et al. [54] analyze geophysical data in North Ossetia, Russia, and develop a complex hazard map aimed at improving risk assessments in the region. Also, Chen et al. [55] examine the temporal assessment of disaster risk, using case studies from China to demonstrate how risk varies over time and proposing long-term mitigation strategies.

   Over the past century, studies have shown a general uptick in both the frequency and intensity of natural disasters, with pronounced peaks in recent decades [37,56,57]. Tin et al. [58]

   found that from 1995 to 2022, there were 11,360 natural disasters, averaging 398 annually. They mentioned that Asia reported the highest number of disasters (4390) and the greatest number of fatalities (918,198). Also, hydrological disasters were the most frequent, totaling 4969, whereas geophysical disasters were the deadliest, with 770,644 deaths. Finally, they found that biological disasters, primarily affecting Africa, resulted in the highest number of injuries (2544) [58]. From another perspective, Jäger et al. [59] investigate disaster records from EM-DAT for 2000–2018 to understand multi-hazard risk patterns. Using an algorithm that considers hazard associations and their spatial and temporal overlaps, their study reveals that multi-hazard events are twice as frequent when there is at least a 25% spatial overlap and a time difference of up to 1 year. Also, they found that these events contribute to 78% of total damages, 83% of affected populations, and 69% of total fatalities [59].

   In a different view, Chen et al. [60] explored the occurrence of rainstorms and floods in the Tarim Basin from 1980 to 2019. Their findings show a notable rise in these events, especially between April and September. The western and northern regions of the basin are particularly vulnerable, with severe incidents significantly impacting the damage index. Similarly, Buszta et al. [46] conducted a geospatial analysis of 9962 natural disasters from 1960 to 2018, examining their frequency and impact across different continents. This study also provides a predictive outlook on future trends, highlighting the influence of climatic factors on disaster patterns. In addition, Summers et al. [38] investigated changes in the frequency, intensity, and spatial distribution of hazards like hurricanes, tropical storms, and droughts. Their research connects these variations to climate change, using empirical data to bolster previous theories. Furthermore, Herrera and Aristizábal [61] examined the relationship between precipitation patterns and landslides in the Aburrá Valley. Their study revealed that rainfall-induced landslides are affected by macroclimatic phenomena such as ENSO, with specific hotspots identified in the valley’s eastern hills.

   The geospatial and temporal distribution patterns of various disasters have been analyzed in multiple studies [37,46]. Over the past century, natural disasters like droughts, floods, and storms have generally become more frequent and severe, with a marked increase in intensity observed in recent decades [37,46,62]. Shen and Hwang [37] conducted a geospatial analysis of 9962 natural disasters occurring worldwide between 1960 and 2018, covering 39,953 locations. They found that Asia, particularly the southeastern region, was the most disaster-affected area, with countries like China, India, the Philippines, and Indonesia being heavily impacted. Also, this analysis highlighted a strong correlation between a region’s geographical location, its size, its population, and its susceptibility to specific natural disasters. For example, seismic activity was more prevalent in Asia, while storms were more common in the United States due to its diverse climate. Also, Nones et al. [63] uncovered rising trends over time in both droughts and wildfires, with their spatial distribution increasingly shaped by the effects of climate change and human activities. The study’s findings highlight how the economic damages from these disasters play a significant role in hindering the recovery process for the communities impacted. Furthermore, according to the 2023 annual report from the EM-DAT database [64], a total of 399 disasters were recorded, leading to 86,473 fatalities and impacting 93.1 million people globally. Among the most catastrophic events were the earthquake in Turkey and Syria and the severe drought in Indonesia, both of which had profound effects on human lives and the economies of the affected regions.

   A comprehensive review of the literature on various disasters reveals significant trends in their frequency, distribution, and impact, underscoring the need for enhanced preparedness and mitigation strategies worldwide [63,65]. For example, a study examining the geospatial and temporal distribution of disasters revealed that floods have become more frequent in recent decades, with Asia and Africa experiencing the highest fatality rates [63]. The findings highlight the urgent need to enhance drainage infrastructure and flood protection measures in these vulnerable regions. In another study, Winsemius, Van Beek, Jongman, Ward, and Bouwman [65] developed a comprehensive framework for assessing global flood risks, validated using data from the EM-DAT database. The study

   employed a global hydrological model and downscaling techniques to estimate flood hazards and their impacts, which were then cross-verified with recorded flood events from EM-DAT. This methodology enabled a thorough evaluation of flood risks on a global scale, taking into account both present and future climate conditions [65].

   Another study focused on utilizing the EM-DAT database to analyze global flood losses [66]. The researchers highlighted challenges in accurately capturing flood loss data, such as biased reporting and changes over time [66]. The study emphasized the critical importance of normalizing data to ensure reliable trend analysis and called for comprehensive and standardized flood data to improve disaster management efforts. On the other hand, using the EM-DAT database, one study compiled a detailed catalog and map of major flood disasters in Europe from 1950 to 2005 [67]. By providing a comprehensive overview of these events, the study significantly enhanced the understanding of flood risks, supporting more informed political and economic decisions for disaster mitigation [67]. These studies illustrate how the EM-DAT database plays a crucial role in providing vital data for analyzing flood patterns, which in turn support both global and regional flood risk assessments and inform disaster management strategies.

   Geospatial data are critical for understanding and analyzing the distribution of earth- quakes. One particularly intriguing study explored mutual information and clustering analysis to visualize and examine global seismic data [68]. By categorizing seismic events according to their geographic location and magnitude, the study generated intuitive maps that revealed intricate relationships within earthquake data—relationships that are often missed by traditional mapping methods [68]. Kripa et al. [69] found that WEED, a tool developed to geocode and analyze historical disaster data from the EM-DAT database, including earthquakes, allows for precise geocoding by associating latitude and longitude coordinates with disaster events. This advancement facilitates the integration of disaster data with geophysical and geospatial variables for more detailed analysis. In one study [68], global seismic data from 1962 to 2011 were analyzed using techniques such as mutual information and cluster analysis. The resulting visual maps offered an intuitive under- standing of complex relationships within earthquake data that are often difficult to discern on traditional geographic maps [68]. In Indonesia, hexagonal tessellation was applied for geovisualizing earthquake data [70]. This method enhanced the clarity of epicenter density visualization, making it easier to identify patterns in the spatial distribution of earthquakes and their proximity to tectonic faults.

   Another study analyzed global wildfire trends using the EM-DAT database, revealing that climate change—marked by rising temperatures and prolonged droughts—has a direct correlation with the increasing frequency and severity of wildfires [71]. The study provided vital insights into how climate change is exacerbating these disasters, underscoring the pressing need for decisive global climate action. On the other side, one study revealed a notable rise in residential fires and fire emergency situations in Serbia between 2012 and 2022 [72]. According to the results, there were 38,279 residential fires during this period, resulting in 665 fatalities, 1747 injuries, and 2134 rescues. The annual figures for fires and deaths are as follows: 2012 (946 fires/7 deaths), 2013 (836/6), 2014 (887/8), 2015 (827/5), 2016

   (872/10), 2017 (899/18), 2018 (842/14), 2019 (796/10), 2020 (842/23), and 2021 (828/21) [72].

   In contrast, one study utilized data from the EM-DAT database to analyze the economic impacts of different types of natural disasters [71]. The findings revealed that economic losses vary depending on the type of disaster, with earthquakes and floods causing the most significant damage [71]. While one study uses data from the EM-DAT database to analyze economic impacts, the study in [73] compares disaster damage records from two major databases, EM-DAT and DesInventar, for 70 countries from 1995 to 2013. Focusing on droughts, floods, earthquakes, and storms, it uses descriptive statistics to evaluate differences in recorded events, matched events, and large-scale events between the two databases, highlighting significant discrepancies in damage estimates. The comparison reveals that DesInventar records more events than EM-DAT for all events. However,

   for hand-matched events, EM-DAT reports higher mean disaster damages and a wider statistical range compared to DesInventar [73].

   There is strong evidence pointing to a sharp rise in economic damages from extreme natural events, especially in temperate regions, driven by their increasing severity [56]. Patterns of droughts and floods reveal alternating positive and negative correlations over time, with a notable lag effect where floods tend to follow droughts by about 4–5 years [74]. The number of people affected by natural disasters has surged, leading to more fatalities, injuries, and property damage [74]. People’s information-seeking behavior during disasters shifts across different phases, underscoring the need for varied communication strategies before, during, and after such events [34]. To analyze the temporal and spatial distribution of disasters, researchers are increasingly turning to advanced methods like time series analysis, spatial statistics, and big data techniques [75,76].

   In addition to all these studies, it has been found that some authors examine the quality of these databases. The researchers Jones et al. [77] analyzed the EM-DAT database, which records natural disasters from 1990 to 2020, and uncovered notable gaps, particularly in the data related to economic losses. They determined that the year, income classification, and type of disaster were significant predictors of these data gaps. To address these issues, they emphasized the importance of employing advanced statistical methods to minimize bias and enhance the reliability of the data [77].

   Although the existing literature offers valuable insights into disaster patterns, there are still some notable gaps that need to be addressed. For example, many studies tend to focus on individual types of disasters, such as floods or earthquakes, without providing a comprehensive analysis that considers multiple disaster types within a single framework. This research intends to address that gap by examining both natural and human-made disasters over the past century. Moreover, there is a noticeable lack of studies that effectively integrate geospatial and temporal analysis to predict future disaster patterns, particularly when considering the use of emerging technologies like AI and big data. This study aims to close that gap by providing an integrated approach that could improve disaster preparedness and response strategies. Although some studies examine disaster patterns, there is a lack of research evaluating how different regions implement disaster management strategies based on these patterns. This study will explore this by offering a comparative analysis.

   Recent advancements in AI and machine learning have revolutionized disaster man- agement by enabling more precise predictions and real-time response strategies. However, integrating these technologies with traditional geospatial analysis is still in its early stages, and further research is necessary to explore their full potential in disaster risk management. While previous studies have contributed significantly to understanding disaster patterns, many are constrained by their reliance on historical data without accounting for the dy- namic nature of climate change and human activities. This study aims to overcome these limitations by incorporating recent data and advanced analytical methods to provide a more accurate and comprehensive understanding of disaster risks. Also, insights from analyzing the geospatial and temporal patterns of disasters are crucial for informing policy decisions and enhancing disaster preparedness. However, more research is needed to trans- late these findings into practical strategies for policymakers. This study aims to contribute to this area by offering policy recommendations based on a comprehensive analysis of disaster patterns.

2. ‌Methods

   The subject of this research encompasses an extensive analysis of both natural and man-made (technological) disasters from 1900 to 2024. The primary objective is to identify geospatial and temporal patterns of these disasters, examining their frequency, distribution, and impact across various geographic regions and periods. In addition, the subject of this research is to examine the influence of various socio-economic factors, such as GDP per capita, governance quality, population density, and urbanization rate, on the distribution and consequences of disasters, including the number of affected people, deaths, and injuries.

   Utilizing the EM-DAT database, this study aims to uncover significant trends and disparities in disaster occurrences and their widespread consequences on a global scale.

   In a narrower sense, this research delves into the historical data of natural and man- made disasters, categorizing them by type, region, and period. It explores specific trends such as the escalation of natural disasters from 1960–1970 and man-made (technological) disasters from 1981–1990. Furthermore, it identifies seasonal trends, assesses the economic and human impacts of these disasters, and examines the specific vulnerabilities of different continents and countries.

   1. ‌Hypothetical Framework

      This study is based on the general hypothesis that the geospatial and temporal pat- terns of natural and man-made (technological) disasters exhibit significant variations in frequency, distribution, and impact across different geographic regions and periods, which reflect changes in natural conditions and socio-economic factors. The specific hypotheses include the following:

      H1: Natural disasters occur more frequently and have a greater impact on human and economic resources compared to technological disasters.

      H2: The frequency and distribution of disasters differ between continents, with certain regions experiencing higher frequencies of specific types of disasters.

      H3: There are significant temporal changes in the frequency of natural and technological disasters, with particular periods showing notable increases or decreases in the number of events.

      H4: Certain natural disasters show seasonal variations in frequency, reflecting climatic and weather patterns.

      H5: Different types of disasters have varying impacts on economic losses and human resources, with some disasters causing more severe consequences than others.

      H6: Different socio-economic factors (GDP per capita (USD), governance quality, population density (people per km2) and urbanization rate (%)), have a significant role in influencing the distribution and consequences of disasters, including the number of affected people, deaths, and injuries.

   2. ‌Data Collection and Preparation

      The data for this study were sourced from the international EM-DAT (Emergency Events Database). EM-DAT is a comprehensive global database that tracks and records all types of natural and human-induced (technological) disasters. It is maintained and regularly updated by the Centre for Research on the Epidemiology of Disasters (CRED) at the University of Louvain, Belgium. A diverse range of sources, including UN agencies, non- governmental organizations, reinsurance firms, research institutions, and media outlets, were used to assemble the database [78]. The dataset can be accessed directly through their website (https://www.emdat.be/, accessed on 15 June 2024).

      The database contains information on disasters that have occurred worldwide since 1900 and meet at least one of the following criteria: 10 fatalities, 100 people affected, dec- laration of a state of emergency, and an international request for assistance. Each entry in EM-DAT includes detailed information about the disaster type, the number of affected individuals, economic losses, geographical distribution, and other relevant parameters [79]. CRED [80] outlines the various impacts of disasters as significant threats to sustainable development. Among these impacts are damages, which refer to the destruction or harm caused to property, crops, and livestock. Another crucial impact is on affected popula- tions, including those who are rendered homeless—people whose homes are destroyed or severely damaged, necessitating immediate shelter—and others requiring urgent assistance.

      Additionally, the category of injuries covers individuals who suffer from physical harm, trauma, or illness that needs medical attention as a direct outcome of the disaster. Lastly, fatalities represent the tragic loss of life resulting from natural hazards.

      Numerous advantages are offered by the EM-DAT database for researchers and decision-makers [81]. Its comprehensiveness and standardization have allowed for the long-term monitoring of natural and technological disasters on a global scale, making it a valuable tool for trend analysis and comparative studies across different regions [73,82]. The database is made publicly accessible, provides wide geographical coverage, and is frequently utilized as a reference source in scientific research due to the breadth and quality of its data [83].

      However, certain drawbacks are also associated with EM-DAT [84]. Despite its ex- tensive nature, generalized information with limited details on specific events may be contained within the database, potentially restricting deeper analysis [83]. The quality of the data is dependent on the sources from which they are collected, which can lead to inconsistencies between different regions [78]. Additionally, the inclusion of events is limited to those meeting specific criteria, possibly resulting in the exclusion of smaller or less severe incidents. Older data may be affected by retrospective bias, and delays in the entry of the most recent events can impact the timeliness of current trend analysis [83,85,86]. For this study, a total of 25,836 disasters from 1900 to 2024 were analyzed. The data were cleaned and prepared for analysis using the Statistical Package for the Social Sciences (IBM SPSS Statistics, Version 26, New York, NY, USA) software after being downloaded. The data preparation process included several key steps: (a) identifying and removing duplicates and missing values to ensure data accuracy and consistency; (b) converting all data into a uniform format to facilitate easier analysis and interpretation, classifying disasters by type, intensity, geographical area, and period. During the data processing phase, all numerical values were standardized to ensure consistent interpretation of results across different time periods and geographic regions. Additionally, categorical data were coded to facilitate their integration into regression models and other quantitative analyses. More specifically stated, listwise deletion was employed to handle missing values in critical data points, while mean imputation was utilized as needed to preserve the integrity of the dataset. Outliers were detected through the use of z-scores, with those surpassing

      ±3 standard deviations carefully examined and removed to avoid skewing the results. Duplicates, especially those associated with identical disaster events, were identified based on matching criteria across key variables and were subsequently eliminated to prevent double-counting. The assumptions underlying the data processing, such as the assumption that missing values were missing at random (MAR) and that the exclusion of outliers would not significantly alter the observed patterns, were also documented. These measures were implemented to enhance the reliability and validity of the analysis.

      Identification and Sourcing of Key Socio-Economic Indicators

      In this study, key socio-economic indicators with the potential to significantly influence disaster outcomes were identified. Among these, GDP per capita was considered, as it reflects the economic capacity of individuals within a country, which can directly affect their preparedness and response to disasters. Data for this indicator were sourced from reputable institutions, including the World Bank (https://data.worldbank.org/indicator/ NY.GDP.PCAP.CD, accessed on 1 September 2024) and the International Monetary Fund (IMF) (https://www.imf.org/en/Data, accessed on 1 September 2024).

      Another crucial indicator was governance quality, measuring how efficiently and effectively a government manages resources and responds to crises. These data were obtained from the World Governance Indicators (WGIs) provided by the World Bank (https://info.worldbank.org/governance/wgi/, accessed on 1 September 2024). On the other hand, population density, defined as the number of people per square kilometer, was also included to gauge the potential vulnerability of regions with high population concen- trations. Data on population density were gathered from sources such as Worldometer

      (https://www.worldometers.info/world-population/population-by-country/, accessed on 5 September 2024) and the United Nations (https://population.un.org/wpp/, accessed on 1 September 2024).

      Lastly, the urbanization rate, representing the proportion of the population residing in urban areas, was analyzed because higher urbanization can enhance the disaster response efficiency but also heighten risks due to population and infrastructure concentration. Data for this indicator were collected from platforms such as Statista (https://www.statista.com/ statistics/270860/urbanization-by-country/, accessed on 6 September 2024) and the World Bank (https://data.worldbank.org/indicator/sp.urb.totl.in.zs, accessed on 6 September 2024).

      Following data collection, these indicators were compiled into an Excel file, with each country in the dataset assigned its corresponding socio-economic indicators. The Excel file was structured to include all relevant variables, such as total damage, number of deaths, injuries, and natural and man-made (technological) disasters. The data underwent a thorough cleaning process to ensure accuracy and completeness. This involved checking for missing values, identifying and managing outliers, and ensuring consistency across all variables. Missing data were addressed using mean imputation where applicable, while outliers identified through z-scores were carefully reviewed and processed to prevent any distortion of the results.

   3. ‌Analyses

      Statistical analyses were performed using a two-tailed approach with a significance level set at p < 0.05, utilizing IBM SPSS Statistics (Version 26, New York, NY, USA). Pearson’s correlation was used to examine the relationship between different socio-economic factors (GDP per capita (USD), governance quality, population density (people per km2), and urbanization rate (%)) and their significant impact on the distribution and consequences of disasters, including the number of deaths, injuries, and natural disasters. Also, the assumptions for Pearson’s correlation, such as linearity, homoscedasticity, and normality of the variables, were met before conducting the analysis.

      The data were analyzed using descriptive statistics to identify the geospatial and temporal patterns of natural and technological disasters. The statistical analysis included the following steps:

      • Analysis of the geographical distribution of disasters by continents for the period from 1900 to 2024. This included calculating the total number and percentage of different types of disasters on each continent. The geographical distribution was analyzed to identify regions with the highest frequency of disasters and to determine the specific characteristics of disasters in those regions, including their type, frequency, severity, and the resulting impacts on local communities and infrastructure.
      • Detailed analysis of the frequency of disasters by countries, including the identification of countries most affected by different types of disasters. The analysis included quantifying the number of events by country and assessing their impact on human and economic resources.
      • Analysis of temporal trends in the frequency of natural and technological disasters in 10- and 5-year intervals. This analysis enabled the identification of changes in the frequency and types of disasters over time, as well as the identification of periods with the highest disaster frequency.

      The results are presented in tables and charts, illustrating the spatial and temporal patterns of disasters. The graphical representations included the following: (a) visualization of the geographical patterns of natural and technological disasters by continents and countries; and (b) a display of changes in the frequency of different types of disasters over time, with a particular focus on decadal and five-year intervals. The results of the analysis were validated using multiple data sources to ensure the accuracy and reliability of the findings. This included comparison with similar studies and the literature. Additionally, cross-validation methods were used to verify the consistency and reliability of the results obtained.

3. ‌Results

   The results of this study encompass a comprehensive overview of the geospatial and temporal patterns of natural and technological disasters, revealing key trends in their frequency, distribution, and impact across different geographic regions and periods. These findings provide valuable insights into the variations in and dynamics of disaster events, contributing to a better understanding of their historical patterns and informing future disaster risk management strategies.

   Based on the methodological framework and study design above, the results were divided into two main sections, each with two subsections: (a) geographical distribution of natural and man-made (technological) disasters (in-depth analysis of disaster distribution by continent and country with comprehensive supporting data); and (b) temporal distri- bution of natural and man-made (technological) disasters (yearly and monthly trends in occurrences and consequences of natural and man-made (technological) disasters).

   1. ‌Geographical Distribution of Natural and Man-Made (Technological) Disasters

      1. ‌In-Depth Analysis of Disaster Distribution by Continent with Comprehensive Supporting Data

         The geospatial distribution of both natural and man-made (technological) disasters across continents from 1900 to 2024 reveals significant trends and patterns in the frequency and spread of various disaster types (Table 1 and Figures 1 and 2). A total of 25,836 disasters were recorded worldwide, of which 69.41% were natural disasters (16,567) and 30.59% were man-made (technological) disasters (9269). Key trends and patterns in the frequency and spread of various disaster types can be discerned through the examination of these data. Asia was found to have experienced the highest number of disasters, with 10,786 events, representing 41.75% of all recorded events. Following Asia, Africa encountered 5540 disas- ters (21.44%), and North America had 3575 events (13.84%). Oceania reported the fewest disasters, with 730 events, accounting for just 2.83%.

          

         Disasters

          

         ‌Table 1. Geospatial distribution of natural and man-made (technological) disasters by continent (1900–2024).

         Continent

         Total Disasters Natural Disasters Man-Made (Tech.)

         	n	%	n	%	n	%
         North America	3575	13.84	2708	75.75	867	24.25
         Asia	10,786	41.75	6675	61.89	4111	38.11
         Africa	5540	21.44	3114	56.21	2426	43.79
         Europe	3091	11.96	1995	64.54	1096	35.46
         South America	2114	8.18	1407	66.56	707	33.44
         Oceania	730	2.83	668	91.51	62	8.49
         Total	25,836	100	16,567	69.41	9269	30.59

         Natural disasters predominantly occurred in Oceania, where they comprised 91.51% of all recorded disasters. In North America, natural disasters constituted 75.75% of the total, while Asia and Europe had slightly lower percentages, at 61.89% and 64.54%, respectively. Africa had the smallest proportion of natural disasters at 56.21%.

         In contrast, man-made (technological) disasters were most prevalent in Africa, account- ing for 43.79% of all disasters on the continent. Asia followed with 38.11%, while Europe and South America reported 35.46% and 33.44%, respectively. Oceania had the lowest percentage of man-made (technological) disasters at just 8.49%. From the comprehensive data, it is evident that natural disasters dominate most continents, particularly in Oceania and North America. Despite Asia having the highest total number of disasters, it also had a significant proportion of man-made (technological) disasters (38.11%), highlighting the presence of technological accidents in the region. Africa’s notable percentage of man-made

         (technological) disasters (43.79%) may reflect various socio-economic factors and levels of infrastructural development (Table 1 and Figure 2).

          

         ‌Figure 1. Geospatial distribution of natural and man-made (technological) disasters by continent (1900–2024).

          

         ‌Figure 2. Geospatial distribution of natural and man-made (technological) disasters by continent (1900–2024).

         An analysis of the geospatial distribution of both natural and man-made (techno- logical) disasters across the continents from 1900 to 2024 reveals significant insights into regional vulnerabilities and disaster management challenges.

         Natural disasters vary widely across continents, each facing unique challenges and frequencies. Here is a detailed look at the occurrences of different natural disasters (Table 2 and Figures 1 and 2):

         1. Earthquakes: Asia recorded the highest number of earthquakes (3.68%), followed by Europe (0.63%) and North America (0.65%). Oceania experienced the fewest earthquakes (0.22%);
         2. Volcanic activity: volcanic activity was most prevalent in Asia (0.43%), while North America and South America each reported 45 events (0.17%). Europe had the least volcanic activity (0.04%);
         3. Floods: floods were most frequent were in Asia (9.40%), with significant occurrences in Africa (4.80%) and North America (2.66%). Oceania had the fewest flood events (0.62%);
         4. Water-related disasters (This category includes a wide range of water-related disasters, not just floods. It also covers incidents like glacial lake outburst floods and coastal erosion. The common thread is that water plays a crucial role in causing these events): these disasters were predominantly seen in Asia (2.72%), followed by Africa (2.17%) and North America (0.38%). Oceania experienced the least (0.05%);
         5. Mass movement (wet): Asia experienced the most mass movement (wet) events (1.70%), followed by South America (0.60%) and Africa (0.26%). Oceania had the fewest (0.07%);
         6. Drought: Africa reported the highest number of droughts (1.40%), while Asia had 0.69% and North America had 0.39% events. Oceania recorded the least, with 34 events (0.13%);
         7. Extreme temperature: Europe led in extreme temperature events (1.15%), followed by Asia (0.77%) and North America (0.27%). On the other hand, Oceania had the fewest events (0.03%);
         8. Storms: North America experienced the most storms (5.18%), followed by Asia (7.35%) and Europe (2.23%). South America reported the least, with 0.41 events;
         9. Epidemics: epidemics were most common were in Africa (3.48%), followed by Asia (1.40%) and North America (0.39%). Oceania recorded the fewest, with 0.09% of events;
         10. Wildfires: North America led in wildfire events (0.56%), followed by Europe (0.48%) and South America (0.19%). Asia had the fewest wildfires, with only 69 events (0.27%).

         America

          

         ‌Table 2. Distribution of individual natural and man-made (technological) disasters by continent (1900–2024).

          

         Disaster Type

         North America

         Asia Africa Europe South

         Oceania Total

         	(n)	(%)	(n)	(%)	(n)	(%)	(n)	(%)	(n)	(%)	(n)	(%)	(n)	(%)
         Earthquake	167	0.65	951	3.68	75	0.29	163	0.63	154	0.60	57	0.22	1567	6.07
         Volcanic activity	45	0.17	112	0.43	19	0.07	11	0.04	45	0.17	32	0.12	264	1.00
         Flood	688	2.66	2429	9.40	1240	4.80	650	2.52	685	2.65	160	0.62	5852	22.65
         Water-related	99	0.38	703	2.72	561	2.17	163	0.63	63	0.24	14	0.05	1603	6.19
         Mass movement (wet)	45	0.17	440	1.70	68	0.26	77	0.30	155	0.60	18	0.07	803	3.10
         Drought	102	0.39	179	0.69	361	1.40	49	0.19	74	0.29	34	0.13	799	3.09
         Extreme temperature	70	0.27	200	0.77	20	0.08	297	1.15	48	0.19	8	0.03	643	2.49
         Glacial lake outburst flood	0	0.00	3	0.01	0	0.00	1	0.00	0	0.00	0	0.00	4	0.01
         Storm	1338	5.18	1899	7.35	311	1.20	576	2.23	105	0.41	290	1.12	4519	17.49
         Epidemic	100	0.39	361	1.40	899	3.48	44	0.17	84	0.33	24	0.09	1512	5.86
         Wildfire	145	0.56	69	0.27	38	0.15	123	0.48	49	0.19	41	0.16	465	1.81
         Air	187	0.72	312	1.21	169	0.65	233	0.90	124	0.48	21	0.08	1046	4.04
         Animal incident	0	0.00	0	0.00	0	0.00	0	0.00	0	0.00	0	0.00	0	0.00

         Disaster Type

         Table 2. Cont.

          

         America

          

         North America

         Asia Africa Europe South

         Oceania Total

         	(n)	(%)	(n)	(%)	(n)	(%)	(n)	(%)	(n)	(%)	(n)	(%)	(n)	(%)
         Chemical spill	47	0.18	20	0.08	4	0.02	29	0.11	3	0.01	1	0.00	104	0.40
         Collapse (industrial)	3	0.01	88	0.34	70	0.27	7	0.03	15	0.06	0	0.00	183	0.71
         Collapse (miscellaneous)	29	0.11	156	0.60	61	0.24	30	0.12	25	0.10	2	0.01	303	1.18
         Explosion (industrial)	57	0.22	509	1.97	59	0.23	108	0.42	32	0.12	4	0.02	769	2.98
         Explosion (miscellaneous)	17	0.07	118	0.46	40	0.15	35	0.14	10	0.04	0	0.00	220	0.86
         Fire (industrial)	22	0.09	137	0.53	15	0.06	35	0.14	7	0.03	0	0.00	216	0.85
         Fire (miscellaneous)	111	0.43	395	1.53	117	0.45	117	0.45	42	0.16	7	0.03	789	3.05
         Fog	0	0.00	0	0.00	0	0.00	0	0.00	0	0.00	0	0.00	0	0.00
         Gas leak	13	0.05	38	0.15	0	0.00	10	0.04	0	0.00	1	0.00	62	0.24
         Industrial accident	7	0.03	89	0.34	16	0.06	5	0.02	8	0.03	1	0.00	126	0.48
         Infestation	0	0.00	0	0.00	0	0.00	0	0.00	0	0.00	0	0.00	0	0.00
         Mass movement (dry)	0	0.00	0	0.00	0	0.00	0	0.00	0	0.00	0	0.00	0	0.00
         Miscellaneous accident	23	0.09	129	0.50	68	0.26	31	0.12	19	0.07	1	0.00	813	2.10
         Oil spill	3	0.01	2	0.01	0	0.00	2	0.01	1	0.00	0	0.00	24	0.03
         Poisoning	6	0.02	50	0.19	6	0.02	10	0.04	4	0.02	0	0.00	228	0.29
         Radiation	1	0.00	4	0.02	0	0.00	0	0.00	1	0.00	0	0.00	18	0.01
         Rail	74	0.29	288	1.11	111	0.43	122	0.47	15	0.06	5	0.02	1845	2.38
         Road	168	0.65	1073	4.15	1129	4.37	159	0.62	338	1.31	5	0.02	8616	11.21

         Man-made (technological) disasters, resulting from human activities, also show dis- tinct patterns across continents (Table 2 and Figure 3):

         1. Air disasters: Asia reported the highest number of air disaster events (1.21%), followed by Europe (0.90%) and North America (0.72%). Oceania had the fewest, with 0.08% of events;
         2. Chemical spills: North America recorded the most chemical spill events (0.18%), while Asia reported 0.08% of events. Oceania had the least, with one incident (0.00%);
         3. Industrial and miscellaneous collapses: Asia led in industrial collapses (0.34%) and miscellaneous collapses (0.60%). Africa followed by industrial collapses (0.27%) and miscellaneous collapses (0.24%);
         4. Explosions: industrial explosions were most frequent in Asia with 509 events (1.97%), while miscellaneous explosions were also highest in Asia with 118 events (0.46%). Oceania had the fewest events in both categories, with four industrial explosions and zero miscellaneous explosions;
         5. Fires (industrial and miscellaneous): North America recorded the most industrial fire events (0.09%) and miscellaneous fire events (0.43%). Oceania had the fewest events in both categories, with zero industrial fires and seven miscellaneous fires;
         6. Gas leaks and oil spills: gas leaks were most common in Asia (0.15%), while oil spills were rare globally, with North America and Asia each reporting only a few events (three and two, respectively);
         7. Poisoning and radiation events: Poisoning events were highest in Asia (0.19%), and ra- diation events were minimal worldwide, with North America and Asia each reporting only a few events (one and four, respectively);
         8. Rail and road disasters: road disasters were highly prevalent in Asia (4.15%) and in Africa (4.37%). Rail disasters were more common in Asia (1.11%) and in Europe (0.47%).

         These detailed distributions reveal specific regional vulnerabilities and can inform targeted disaster risk reduction strategies. For instance, Asia’s high frequency of both natural and man-made (technological) disasters highlights the need for comprehensive disaster management plans. Similarly, Africa’s significant number of man-made (techno- logical) disasters indicates a need for improved technological safety and infrastructure development (Table 2 and Figure 3).

          

         ‌Figure 3. Distribution of individual natural and man-made (technological) disasters by continent (1900–2024).

      2. ‌In-Depth Analysis of Disaster Distribution by Country with Comprehensive Supporting Data

         A comprehensive overview of the distribution of total, natural, and man-made (tech- nological) disasters by country from 1900 to 2024 highlights the most disaster-prone nations and the types of disasters they frequently encounter. Total disasters encompass all recorded events, both natural and man-made, that have occurred within a given country. This measure provides insight into the overall disaster burden each country faces and helps in identifying areas that may require enhanced disaster preparedness and mitigation efforts (Table 3 and Figures 4 and 5):

         1. China ranks first with a total of 1996 disaster events, comprising 7.54% of the global total. Natural disasters make up 50.70% (1012 events) of China’s total, while man- made (technological) disasters account for 49.30% (984 events). The top five disasters in China included industrial accidents (15.08%), storms (14.73%), floods (14.53%), droughts (14.28%), and epidemics (14.23%);
         2. India follows with 1581 disaster events (5.97% of the global total). Natural disasters represent 49.08% (776 events), and man-made (technological) disasters represent 50.92% (805 events). The most frequent disasters were epidemics (15.50%), industrial accidents (14.86%), droughts (14.80%), floods (14.29%), and epidemics again (14.17%);
         3. The USA is third with 1513 disaster events (5.72% of the global total). Natural disasters dominate with 76.14% (1152 events), and man-made (technological) disasters consti- tute 23.86% (361 events). The top disasters included epidemics (15.27%), industrial accidents (14.87%), droughts (14.47%), floods (14.41%), and wildfires (13.88%);
         4. The Philippines ranks fourth with 938 disaster events (3.54% of the global total). Natural disasters account for 74.41% (698 events), and man-made (technological) disasters account for 25.59% (240 events). The leading disasters were industrial

            accidents (16.10%), storms (14.71%), droughts (14.50%), epidemics (14.39%), and

            wildfires (14.18%);

         5. Indonesia is fifth with 878 disaster events (3.32% of the global total). Natural disasters make up 70.73% (621 events), while man-made (technological) disasters account for 29.27% (257 events). The most common disasters were floods (16.40%), earthquakes (15.15%), droughts (15.03%), epidemics (14.81%), and wildfires (13.44%);
         6. Bangladesh ranks sixth with 588 disaster events (2.22% of the global total). Natural disasters constitute 61.73% (363 events), and man-made (technological) disasters account for 38.27% (225 events). The top disasters included floods (15.99%), droughts (15.14%), industrial accidents (15.14%), epidemics (14.97%), and storms (13.27%);
         7. Nigeria is seventh with 523 disaster events (1.98% of the global total). Man-made disasters are prevalent, accounting for 72.66% (380 events), while natural disasters make up 27.34% (143 events). The leading disasters were wildfires (16.63%), storms (16.44%), industrial accidents (14.72%), epidemics (14.53%), and droughts (13.38%);
         8. Pakistan is eighth with 504 disaster events (1.90% of the global total). Natural disasters represent 50.40% (254 events), and man-made (technological) disasters represent 49.60% (250 events). The most frequent disasters included floods (15.08%), wildfires (15.08%), storms (14.88%), industrial accidents (14.29%), and epidemics (13.89%);
         9. Mexico ranks ninth with 481 disaster events (1.82% of the global total). Natural disasters make up 63.20% (304 events), and man-made (technological) disasters make up 36.80% (177 events). The top disasters were wildfires (17.88%), epidemics (15.59%),

            floods (15.18%), droughts (13.51%), and epidemics again (12.89%);

         10. Japan is tenth with 464 disaster events (1.75% of the global total). Natural disasters are dom- inant, comprising 83.84% (389 events), while man-made (technological) disasters account for 16.16% (75 events). The leading disasters included wildfires (17.24%), earthquakes (15.73%), storms (15.09%), droughts (14.44%), and industrial accidents (13.79%).

         ‌Table 3. Distribution of total, natural, and man-made (technological) disasters by country (1900–2024).

          

         Country (Rang)

         Total Disasters

         Natural Disasters

         Man-Made (Tech.) Disasters

         Top 5 Disasters by Country

         	(n)	(%)	(n)	(%)	(n)	(%)	1st	2nd	3rd	4th	5th
         1. China	1996	7.54	1012	50.70	984	49.30	IA (15.08)	S (14.73)	F (14.53)	D (14.28)	E (14.23)
         2. India	1581	5.97	776	49.08	805	50.92	E (15.50)	IA (14.86)	D (14.80)	F (14.29)	E (14.17)
         3. USA	1513	5.72	1152	76.14	361	23.86	E (15.27)	IA (14.87)	D (14.47)	F (14.41)	W (13.88)
         4. Philippines	938	3.54	698	74.41	240	25.59	IA (16.10)	S (14.71)	D (14.50)	E (14.39)	W (14.18)
         5. Indonesia	878	3.32	621	70.73	257	29.27	F (16.40)	E (15.15)	D (15.03)	E (14.81)	W (13.44)
         6. Bangladesh	588	2.22	363	61.73	225	38.27	F (15.99)	D (15.14)	IA (15.14)	E (14.97)	S (13.27)
         7. Nigeria	523	1.98	143	27.34	380	72.66	W (16.63)	S (16.44)	IA (14.72)	E (14.53)	D (13.38)
         8. Pakistan	504	1.90	254	50.40	250	49.60	F (15.08)	W (15.08)	S (14.88)	IA (14.29)	E (13.89)
         9. Mexico	481	1.82	304	63.20	177	36.80	W (17.88)	E (15.59)	F (15.18)	D (13.51)	E (12.89)
         10. Japan	464	1.75	389	83.84	75	16.16	W (17.24)	E (15.73)	S (15.09)	D (14.44)	IA (13.79)
         11. Brazil	462	1.75	283	61.26	179	38.74	E (15.15)	IA (15.15)	W (14.94)	D (14.72)	F (14.50)
         12. Iran	442	1.67	265	59.95	177	40.05	D (17.87)	E (15.61)	W (15.16)	IA (14.48)	F (13.35)
         13. Russia	417	1.58	178	42.69	239	57.31	E (17.27)	W (15.35)	S (15.11)	D (14.63)	IA (13.43)
         14. Peru	397	1.50	217	54.66	180	45.34	F (15.87)	E (15.37)	E (14.36)	S (14.11)	IA (13.85)
         15. Türkiye	390	1.47	217	55.64	173	44.36	D (16.67)	IA (15.13)	W (15.13)	S (14.36)	F (13.33)
         16. Congo	342	1.29	155	45.32	187	54.68	S (17.54)	W (14.91)	D (14.04)	IA (14.04)	E (13.45)
         17. Colombia	339	1.28	232	68.44	107	31.56	IA (16.52)	E (16.22)	D (14.45)	E (14.45)	S (14.45)
         18. Viet Nam	338	1.28	264	78.11	74	21.89	S (16.86)	E (16.57)	D (15.98)	W (15.38)	F (14.79)
         19. South Africa	326	1.23	129	39.57	197	60.43	D (16.56)	S (15.64)	F (14.72)	IA (14.72)	E (14.42)
         20. France	296	1.12	203	68.58	93	31.42	W (20.27)	IA (14.53)	E (14.19)	D (13.85)	S (13.51)
         21. Italy	285	1.08	187	65.61	98	34.39	F (17.54)	IA (17.54)	S (15.44)	D (13.68)	E (13.33)
         22. Afghanistan	274	1.04	219	79.93	55	20.07	E (17.88)	F (16.06)	S (14.60)	D (14.23)	W (13.14)
         23. Thailand	274	1.04	172	62.77	102	37.23	E (20.07)	W (17.88)	E (13.50)	S (13.14)	D (12.77)

         Table 3. Cont.

          

         Total Natural

         Man-Made

         Country (Rang)

         Disasters

         Disasters

         (Tech.) Disasters

         Top 5 Disasters by Country

         	(n)	(%)	(n)	(%)	(n)	(%)	1st	2nd	3rd	4th	5th
         24. Australia	257	0.97	223	86.77	34	13.23	E (17.51)	D (15.18)	F (14.01)	S (14.01)	E (13.23)
         25. Egypt	252	0.95	36	14.29	216	85.71	E (20.24)	E (15.08)	IA (13.89)	W (13.49)	S (12.70)
         26. Canada	246	0.93	153	62.20	93	37.80	F (17.89)	D (15.04)	S (14.23)	E (13.82)	IA (13.82)
         27. Kenya	231	0.87	126	54.55	105	45.45	IA (17.75)	F (16.88)	E (16.02)	S (13.85)	D (13.42)
         28. Nepal	215	0.81	139	64.65	76	35.35	E (18.14)	S (16.74)	D (14.88)	E (14.88)	IA (12.56)
         29. Tanzania	214	0.81	122	57.01	92	42.99	W (20.56)	IA (16.36)	E (14.49)	F (14.49)	E (13.08)
         30. Great Britain	204	0.77	105	51.47	99	48.53	E (19.12)	E (15.69)	F (15.69)	D (14.22)	W (13.24)
         31. Rep. Korea	202	0.76	132	65.35	70	34.65	E (17.82)	F (17.82)	W (14.85)	E (13.86)	IA (13.37)
         32. Haiti	196	0.74	138	70.41	58	29.59	W (18.37)	IA (17.35)	E (14.80)	F (13.78)	E (13.27)
         33. Sudan	196	0.74	108	55.10	88	44.90	IA (18.88)	S (18.37)	F (15.82)	D (14.29)	E (12.76)
         34. Uganda	191	0.72	111	58.12	80	41.88	S (17.80)	F (16.23)	E (15.18)	IA (13.61)	D (12.57)
         35. Spain	188	0.71	112	59.57	76	40.43	F (17.55)	E (14.89)	E (14.36)	S (14.36)	W (13.83)
         36. Taiwan	187	0.71	136	72.73	51	27.27	IA (18.18)	W (14.97)	F (14.44)	D (13.90)	E (13.37)
         37. Argentina	180	0.68	131	72.78	49	27.22	W (19.44)	E (18.33)	D (14.44)	F (13.33)	IA (13.33)
         38. Ecuador	166	0.63	119	71.69	47	28.31	E (15.06)	E (15.06)	F (15.06)	W (15.06)	IA (13.86)
         39. Guatemala	165	0.62	127	76.97	38	23.03	W (16.97)	D (15.76)	S (15.76)	E (13.94)	E (13.33)
         40. Ethiopia	163	0.62	127	77.91	36	22.09	D (20.25)	E (17.18)	E (14.72)	F (14.72)	S (14.11)
         41. Greece	163	0.62	111	68.10	52	31.90	S (19.02)	E (16.56)	W (15.95)	E (14.11)	IA (12.27)
         42. Myanmar	159	0.60	89	55.97	70	44.03	E (18.24)	D (17.61)	F (15.09)	IA (14.47)	S (13.21)
         43. Bolivia	157	0.59	112	71.34	45	28.66	F (15.92)	IA (14.65)	W (14.65)	D (14.01)	E (14.01)
         44. Sri Lanka	157	0.59	131	83.44	26	16.56	E (21.02)	W (15.92)	S (14.65)	D (14.01)	E (13.38)
         45. Algeria	156	0.59	93	59.62	63	40.38	E (16.03)	W (16.03)	S (15.38)	D (14.74)	F (14.74)
         46. Belgium	156	0.59	72	46.15	84	53.85	E (17.31)	IA (17.31)	E (14.74)	D (14.10)	F (14.10)
         47. Morocco	156	0.59	63	40.38	93	59.62	W (17.31)	E (16.67)	IA (16.03)	S (16.03)	D (11.54)
         48. Mozambique	156	0.59	125	80.13	31	19.87	D (19.23)	E (15.38)	F (15.38)	W (14.74)	S (13.46)
         49. Chile	152	0.57	125	82.24	27	17.76	F (18.42)	E (15.79)	D (14.47)	E (14.47)	W (13.16)
         50. Malaysia	152	0.57	109	71.71	43	28.29	IA (21.05)	S (19.74)	F (15.79)	D (13.82)	W (13.82)

         Note: industrial accident (IA); storm (S); flood (F); drought (D); epidemic (E); wildfire (W); earthquake (E).

         Natural disasters include events such as earthquakes, floods, droughts, storms, and other environmental phenomena (Table 3 and Figures 4–6). These events are often influ- enced by geographical and climatic factors unique to each country. China ranks first in natural disasters with 1012 events (50.70% of its total), primarily including floods, storms, and droughts. The USA had the second-highest number of natural disaster events with 1152 (76.14% of its total), with major events being epidemics, storms, and floods. India follows with 776 natural disaster events (49.08% of its total), with frequent occurrences of epidemics, floods, and droughts. The Philippines reported 698 natural disaster events (74.41% of its to- tal), dominated by storms, floods, and droughts. Indonesia had 621 natural disaster events (70.73% of its total), primarily floods, earthquakes, and droughts. Bangladesh experienced 363 natural disaster events (61.73% of its total), with floods, droughts, and storms being the most common. Japan reported 389 natural disaster events (83.84% of its total), with wildfires, earthquakes, and storms as the leading types. Mexico had 304 natural disaster events (63.20% of its total), with wildfires, floods, and epidemics being the most prevalent. Pakistan had 254 natural disaster events (50.40% of its total), mainly floods, wildfires, and storms. Brazil reported 283 natural disaster events (61.26% of its total), with the most common being epidemics, wildfires, and droughts (Table 3 and Figures 4–6).

          

         ‌Figure 4. Distribution of total disasters by country (Rang, with red numbers) in percentage for the period 1900–2024.

          

         ‌Figure 5. Distribution of total, natural, and man-made (technological) disasters for the top five countries (Rang) for the period 1900–2024.

          

         ‌Figure 6. Distribution of total, natural, and man-made (technological) disasters by country (1900–2024).

         Man-made (technological) disasters refer to events caused by human activity, such as industrial accidents, chemical spills, and other incidents related to technological failures or human error (Table 3 and Figures 4–6). Regarding this, China ranks first in man-made (technological) disasters with 984 events (49.30% of its total), dominated by industrial accidents and chemical spills. India had 805 man-made disaster events (50.92% of its total), with the leading types being industrial accidents and chemical spills. Nigeria experienced 380 man-made disaster events (72.66% of its total), with the most common being industrial accidents and fires. The USA reported 361 man-made disaster events (23.86% of its total), primarily industrial accidents and chemical spills. Indonesia had 257 man-made disaster events (29.27% of its total), mainly industrial accidents and fires. Bangladesh recorded 225 man-made disaster events (38.27% of its total), with the top events being industrial accidents and chemical spills. Russia had 239 man-made disaster events (57.31% of its total), with common types including industrial accidents and fires. Japan reported 75 man-made disaster events (16.16% of its total), primarily industrial accidents and chemical spills. Mexico experienced 177 man-made disaster events (36.80% of its total), dominated by industrial accidents and fires. Pakistan had 250 man-made disaster events (49.60% of its total), with the leading types being industrial accidents and fires (Table 3 and Figures 4–6).

         These insights emphasize the importance of tailoring disaster risk reduction strategies to the specific needs and vulnerabilities of each country. For instance, countries with high natural disaster frequencies, such as Japan and Australia, may prioritize early warning systems and infrastructure resilience, while those with a higher prevalence of man-made (technological) disasters, like Nigeria and Egypt, may focus on industrial safety and emer- gency response protocols.

   2. ‌Temporal Distribution of Natural and Man-Made (Technological) Disasters

      1. ‌Yearly and Monthly Trends in Occurrences of Natural and Man-Made Disasters

         A temporal analysis of natural and man-made (technological) disasters over 10-year intervals from 1900 to 2024 highlights the trends and changes in the frequency and distri- bution of disasters over time (Table 4 and Figure 7). This analysis offers insights into how disaster patterns have evolved and what factors may influence these trends.

         ‌Table 4. Temporal analysis of natural and man-made (technological) disasters in 10-year intervals (1900–2024): trend assessments and insights.

          

         Decade

         Natural Disasters

         Man-Made (Technological) Disasters

         Total Trend

         	(n)	(%)	(n)	(%)	(n)	(%)	Rate (%)
         1900–1910	79	78.22	22	21.78	101	0.38	Stable (0.00%)
         1911–1920	78	64.46	43	35.54	121	0.46	Increasing (19.57%)
         1921–1930	106	80.30	26	19.70	132	0.50	Increasing (7.40%)
         1931–1940	133	61.29	84	38.71	217	0.82	Increasing (42.20%)
         1941–1950	171	60.85	110	39.15	281	1.06	Increasing (11.73%)
         1951–1960	310	82.01	68	17.99	378	1.43	Increasing (10.05%)
         1961–1970	594	86.09	96	13.91	690	2.61	Increasing (13.59%)
         1971–1980	871	76.14	273	23.86	1144	4.32	Increasing (6.10%)
         1981–1990	1755	64.57	963	35.43	2718	10.27	Increasing (5.33%)
         1991–2000	2957	59.20	2038	40.80	4995	18.87	Increasing (1.71%)
         2001–2010	4464	58.35	3187	41.65	7651	28.91	Increasing (0.70%)
         2011–2020	3758	65.78	1955	34.22	5713	21.59	Decreasing (−0.44%)
         2021–2024	1747	75.20	576	24.80	2323	8.78	Decreasing (−2.49%)

         1. From 1900–1910, there were 101 total disaster events, with natural disasters comprising 78.22% (79 events) and man-made (technological) disasters 21.78% (22 events). The overall trend was stable, with no significant change in the rate of disasters;
         2. Between 1911–1920, a total of 121 disaster events were recorded, showing an increase of 19.57% from the previous decade. Natural disasters made up 64.46% (78 events), while man-made (technological) disasters accounted for 35.54% (43 events). This decade marks the beginning of an upward trend in disaster events;
         3. During the 1921–1930 period, the number of disaster events increased to 132, a 7.40% rise from the previous decade. Natural disasters constituted 80.30% (106 events), and man-made (technological) disasters constituted 19.70% (26 events). The upward trend continued;
         4. From 1931–1940, there were 217 disaster events, representing a significant increase of 42.20%. Natural disasters made up 61.29% (133 events), while man-made (technologi- cal) disasters accounted for 38.71% (84 events). This decade saw a substantial rise in the number of disasters;
         5. In the 1941–1950 decade, the number of disasters increased to 281, an 11.73% rise from the previous decade. Natural disasters comprised 60.85% (171 events), and man-made (technological) disasters comprised 39.15% (110 events). The trend of increasing disaster events persisted;
         6. From 1950–1960, there were 378 disaster events, marking a 10.05% increase. Natural disasters accounted for 82.01% (310 events), while man-made (technological) disasters accounted for 17.99% (68 events). This decade continued the upward trend;
         7. The 1961–1970 period saw the number of disasters rise to 690, a 13.59% increase. Natural disasters constituted 86.09% (594 events) and man-made (technological) disasters 13.91% (96 events). The trend of increasing disasters continued;
         8. Between 1970–1980, a total of 1144 disaster events were recorded, a 6.10% rise from the previous decade. Natural disasters made up 76.14% (871 events), while man-made

            (technological) disasters accounted for 23.86% (273 events). The upward trend in disaster frequency persisted;

         9. From 1981–1990, the number of disasters significantly increased to 2718, a 5.33% rise from the previous decade. Natural disasters constituted 64.57% (1755 events), and man-made (technological) disasters 35.43% (963 events). This decade saw a substantial rise in disaster events;
         10. In the 1991–2000 period, there were 4995 disaster events, a 1.71% increase. Natural disasters made up 59.20% (2957 events), while man-made (technological) disasters were 40.80% (2038 events). The trend of increasing disasters continued;
         11. From 2001–2010, the number of disasters rose to 7651, a 0.70% increase. Natural disas- ters accounted for 58.35% (4464 events), while man-made (technological) disasters accounted for 41.65% (3187 events). This decade continued the upward trend;
         12. Between 2011–2020, the number of disasters decreased to 5713, marking a decrease of 0.44%. Natural disasters made up 65.78% (3758 events), and man-made (techno- logical) disasters made up 34.22% (1955 events). This decade saw the beginning of a downward trend;

         13. From 2021–2024, there were 2323 disaster events, marking a decrease of 2.49%. Natural disasters constituted 75.20% (1747 events), and man-made (technological) disasters accounted for 24.80% (576 events). It is important to recognize that this analysis for this period is based on a period of only four years, which is notably shorter than the previous decades under review. This limited timeframe may not adequately reflect longer-term trends and could be subject to short-term fluctuations in disaster occurrences. As a result, while the data suggest a decline, it is advisable to interpret these findings with caution and avoid drawing definitive conclusions from such a brief period. (Table 4 and Figure 7).

         The early 20th century (1900–1940) experienced relatively fewer disaster events with a stable but gradually increasing trend. The increase in man-made (technological) disasters began to become more noticeable during these periods. In addition, the mid-20th century (1940–1970) saw a significant rise in disaster events, with both natural and man-made (technological) disasters contributing to the increase.

         Technological advancements and industrial activities likely influenced the rise in man- made (technological) disasters. Likewise, the late 20th century (1970–2000) experienced the highest increases in disaster events, particularly in the 1980s and 1990s. This period saw a peak in both natural and man-made (technological) disasters, indicating heightened vulnerability—referring to the susceptibility of communities to suffer harm—and exposure, which refers to the extent to which people, property, and infrastructure are in harm’s way (Table 4 and Figure 7).

         The early 21st century (2000–2020) continued the trend of increasing disaster events, although the rate of increase began to slow down by 2010. There was a noticeable shift with a higher proportion of man-made (technological) disasters. Conversely, the most recent decade (2021–2024) shows a decreasing trend in the number of disaster events, with a significant reduction in both natural and man-made (technological) disasters. This decrease may be attributed to improved disaster management practices, early warning systems, and increased global awareness of disaster risks (Table 4 and Figure 7).

         Overall, the temporal analysis revealed a dynamic pattern of disaster occurrences, with significant increases in the mid-to-late 20th century followed by a gradual decline in recent years. These trends underscore the importance of continuous improvement in disaster risk reduction and management strategies to mitigate the impact of both natural and man-made (technological) disasters (Table 4 and Figure 7).

         A temporal analysis of natural and man-made (technological) disasters over 5-year intervals from 1900 to 2024 revealed trends and changes in the frequency and distribution of disasters over shorter periods (Table 5 and Figure 8). This analysis offers more granular insights into how disaster patterns have evolved and what factors may influence these trends.

          

         ‌Figure 7. Temporal analysis of natural and man-made (technological) disasters in 10-year intervals (1900–2024).‌

         Table 5. Temporal analysis of natural and man-made (technological) disasters in 5-year intervals (1900–2024).

          

         Period (5-Year

         Natural Disasters

         Man-Made (Technological) Disasters

         Total Trend

         Intervals)	(n)	(%)	(n)	(%)	(n)	(%)	(%)
         1900–1905	35	81.40	8	18.60	43	0.16	Stable (0.00%)
         1906–1910	44	75.86	14	24.14	58	0.22	Increasing (34.88%)
         1911–1915	47	77.05	14	22.95	61	0.23	Increasing (5.17%)
         1916–1920	31	51.67	29	48.33	60	0.23	Decreasing (−1.64%)
         1921–1925	47	77.05	14	22.95	61	0.23	Increasing (1.67%)
         1926–1930	59	83.10	12	16.90	71	0.27	Increasing (16.39%)
         1931–1935	68	77.27	20	22.73	88	0.33	Increasing (23.94%)
         1936–1940	65	50.39	64	49.61	129	0.49	Increasing (46.59%)
         1941–1945	77	48.12	83	51.88	160	0.60	Increasing (24.03%)
         1946–1950	94	77.69	27	22.31	121	0.46	Decreasing (−24.38%)
         1951–1955	157	81.77	35	18.23	192	0.73	Increasing (58.68%)
         1956–1960	153	82.26	33	17.74	186	0.70	Decreasing (−3.12%)

         Period (5-Year

         Table 5. Cont.

          

         Natural Disasters

         Man-Made (Technological) Disasters

         Total Trend

         Intervals)	(n)	(%)	(n)	(%)	(n)	(%)	(%)
         1961–1965	204	85.71	34	14.29	238	0.90	Increasing (27.96%)
         1966–1970	390	86.28	62	13.72	452	1.71	Increasing (89.92%)
         1971–1975	336	77.24	99	22.76	435	1.64	Decreasing (−3.76%)
         1976–1980	535	75.46	174	24.54	709	2.68	Increasing (62.99%)
         1981–1985	774	76.71	235	23.29	1009	3.81	Increasing (42.31%)
         1986–1990	981	57.40	728	42.60	1709	6.46	Increasing (69.38%)
         1991–1995	1314	58.53	931	41.47	2245	8.48	Increasing (31.36%)
         1996–2000	1643	59.75	1107	40.25	2750	10.39	Increasing (22.49%)
         2001–2005	2291	56.72	1748	43.28	4039	15.26	Increasing (46.87%)
         2006–2010	2173	60.16	1439	39.84	3612	13.65	Decreasing (−10.57%)
         2011–2015	1864	63.66	1064	36.34	2928	11.06	Decreasing (−18.94%)
         2015–2020	1894	68.01	891	31.99	2785	10.52	Decreasing (−4.88%)
         2020–2024	1747	75.20	576	24.80	2323	8.78	Decreasing (−16.59%)

          

         ‌Figure 8. Temporal analysis of natural and man-made (technological) disasters in 5-year intervals (1900–2024).

         From 1900 to 1905, there were 43 total disaster events, with natural disasters comprising 81.40% (35 events) and man-made (technological) disasters 18.60% (8 events). The overall trend was stable, with no significant change in the rate of disasters. Moving into the next five years, a total of 58 disaster events were recorded between 1905 and 1910, showing a 34.88% increase from the previous period. Natural disasters made up 75.86% (44 events), while man-made (technological) disasters accounted for 24.14% (14 events). From 1910 to 1915, the number of disaster events rose to 61, a 5.17% rise from the previous period. Natural disasters constituted 77.05% (47 events), and man-made (technological) disasters accounted for 22.95% (14 events). The period from 1915 to 1920 saw a slight decrease to 60 disaster events, representing a 1.64% decline. Natural disasters made up 51.67% (31 events), while man-made (technological) disasters accounted for 48.33% (29 events).

         From 1920 to 1925, the number of disaster events increased again to 61, a 1.67% rise from the previous period. Natural disasters comprised 77.05% (47 events), and man-made (technological) disasters comprised 22.95% (14 events). Between 1925 and 1930, the number of disaster events rose to 71, marking a 16.39% increase. Natural disasters accounted for 83.10% (59 events), while man-made (technological) disasters accounted for 16.90% (12 events). The period from 1930 to 1935 saw the number of disasters increase to 88, a 23.94% rise. Natural disasters constituted 77.27% (68 events), and man-made (technological) disasters accounted for 22.73% (20 events). From 1935 to 1940, a significant increase to 129 disaster events was recorded, a 46.59% rise. Natural disasters made up 50.39% (65 events), while man-made (technological) disasters accounted for 49.61% (64 events). Between 1940 and 1945, there were 160 disaster events, representing a 24.03% increase. Natural disasters comprised 48.12% (77 events), and man-made (technological) disasters comprised 51.88% (83 events).

         The period from 1945 to 1950 saw a decrease to 121 disaster events, marking a 24.38% decline. Natural disasters accounted for 77.69% (94 events), while man-made (technological) disasters accounted for 22.31% (27 events). Between 1950 and 1955, there were 192 disaster events, a 58.68% increase. Natural disasters made up 81.77% (157 events), and man- made (technological) disasters accounted for 18.23% (35 events). From 1955 to 1960, the number of disasters slightly decreased to 186, a 3.12% decline. Natural disasters comprised 82.26% (153 events), and man-made (technological) disasters comprised 17.74% (33 events). Between 1960 and 1965, the number of disasters increased to 238, a 27.96% rise. Natural disasters accounted for 85.71% (204 events), while man-made (technological) disasters accounted for 14.29% (34 events). From 1965 to 1970, there were 452 disaster events, a significant 89.92% increase. Natural disasters made up 86.28% (390 events), and man-made (technological) disasters accounted for 13.72% (62 events).

         The period from 1970 to 1975 saw a slight decrease to 435 disaster events, a 3.76% decline. Natural disasters constituted 77.24% (336 events), and man-made (technological) disasters accounted for 22.76% (99 events). From 1975 to 1980, there were 709 disaster events, marking a 62.99% increase. Natural disasters accounted for 75.46% (535 events), while man-made (technological) disasters accounted for 24.54% (174 events). Between 1980 and 1985, the number of disasters increased to 1009, a 42.31% rise. Natural disasters comprised 76.71% (774 events), and man-made (technological) disasters comprised 23.29% (235 events). From 1985 to 1990, there were 1709 disaster events, a significant 69.38% increase. Natural disasters made up 57.40% (981 events), and man-made (technological) disasters accounted for 42.60% (728 events). Between 1990 and 1995, the number of disasters increased to 2245, a 31.36% rise. Natural disasters constituted 58.53% (1314 events), while man-made (technological) disasters accounted for 41.47% (931 events).

         The period from 1995 to 2000 saw a total of 2750 disaster events, a 22.49% increase. Natural disasters accounted for 59.75% (1643 events), and man-made (technological) disas- ters accounted for 40.25% (1107 events). Between 2000 and 2005, the number of disasters rose to 4039, marking a 46.87% increase. Natural disasters made up 56.72% (2291 events), while man-made (technological) disasters accounted for 43.28% (1748 events). From 2005 to 2010, the number of disasters slightly decreased to 3612, a 10.57% decline. Natural disasters constituted 60.16% (2173 events), and man-made (technological) disasters accounted for

         39.84% (1439 events). Between 2010 and 2015, there were 2928 disaster events, an 18.94% decrease. Natural disasters comprised 63.66% (1864 events), and man-made (technological) disasters comprised 36.34% (1064 events). From 2015 to 2020, the number of disasters slightly decreased to 2785, a 4.88% decline. Natural disasters made up 68.01% (1894 events), while man-made (technological) disasters accounted for 31.99% (891 events). Between 2020 and 2025, there were 2323 disaster events, marking a 16.59% decline. Natural disasters con- stituted 75.20% (1747 events), and man-made (technological) disasters comprised 24.80% (576 events) (Table 5 and Figure 8).

         Short-term fluctuations in disaster occurrences, such as sudden increases or decreases in the number of events, can have a significant impact on long-term trends and must be carefully analyzed to understand their broader implications. These variations may be influenced by factors such as natural phenomena like El Niño [87], which can temporarily increase certain types of disasters like floods and droughts, or socio-political events that affect how disasters are reported and responded to. For example, advancements in early warning systems [36,88–90] or changes in land use policies [91–93] could reduce the impact of disasters in the short term, leading to a perceived decrease in their frequency. How- ever, these fluctuations might either indicate emerging trends or simply reflect temporary deviations from the overall pattern.

         As previously mentioned, a steady increase in disaster events was observed in the early 20th century, with natural disasters predominating and the rise in man-made (technological) disasters becoming more noticeable. Significant increases during 1930–1945 highlight the impact of technological advancements and urbanization. Following this, the post- World War II period saw a significant rise in disaster events, peaking around 1940–1945, followed by a slight decline likely due to post-war recovery efforts and improvements in infrastructure and disaster management.

         From 1965 to 1985, there was a rapid increase in the number of disaster events, especially natural disasters. This growth was driven by factors such as population growth, urbanization, and increased industrial activity, leading to heightened exposure and vulnerability to disasters. The period between 1985 and 2005 marked the peak and subsequent stabilization of disas- ter events. Both natural and man-made (technological) disasters saw significant increases, reflecting the complexities of modern societal and environmental challenges.

         In recent years, specifically from 2005 to 2025, there has been a gradual decline in the number of disaster events, with notable decreases in both natural and man-made (technological) disasters. This trend may be attributed to improved disaster risk reduction strategies, advancements in early warning systems, and increased global awareness and preparedness for disaster risks. These insights highlight the dynamic nature of disaster occurrences over time, emphasizing the need for continuous adaptation and improve- ment in disaster management practices to address both natural and man-made challenges. The periods of significant increase and subsequent decline underscore the importance of sustained efforts in building resilient communities and mitigating disaster impacts.

         In addition to the observed trends, several interesting insights and considerations can be drawn from the temporal analysis of natural and man-made (technological) disasters from 1900 to 2024. The mid-20th century saw a sharp increase in man-made (technological) disasters, particularly from 1940–1945 and 1985–2005, corresponding with significant technological and industrial advancements (Table 5 and Figure 8). This period indicates that rapid industrialization and technological development can contribute to a higher incidence of man-made (technological) disasters. The gradual decline in disaster events post 2005 suggests the effectiveness of global policies, international cooperation, and enhanced disaster risk reduction (DRR) frameworks, such as the Sendai Framework for Disaster Risk Reduction adopted in 2015.

         Table 6 provides a detailed look at the total number of various natural and man-made (technological) disasters recorded each decade from 1900 to 2020. This analysis sheds light on the types and frequency of different disasters over time, offering insights into how disaster patterns have evolved and revealing trends in specific types of disasters.

         ‌Table 6. Total number of different natural and man-made (technological) disasters worldwide by decade (1900–2024).

          

         1900–1910

          

         1911–1920

          

         1921–1930

          

         1931–1940

          

         1941–1950

          

         1951–1960

          

         1961–1970

          

         1971–1980

          

         1981–1990

          

         1991–2000

          

         2001–2010

          

         2011–2020

          

         2021–2024

          

         Disaster Type Total

         Air	0	15	7	59	75	6	16	29	155	300	248	158	23	1091
         Animal incident	0	0	0	0	0	0	0	0	0	0	0	1	0	1
         Chemical spill	0	0	0	0	0	0	1	17	33	34	16	7	0	108
         Collapse (indust.)	0	0	0	0	0	3	0	2	12	21	60	66	20	184
         Collapse (miscell.)	1	3	2	0	0	4	7	16	36	78	87	55	16	305
         Drought	4	10	4	2	13	0	52	61	126	140	170	169	62	813
         Earthquake	38	32	42	65	73	68	88	110	173	265	289	262	112	1617
         Epidemic	5	6	10	2	3	2	37	59	124	385	590	258	45	1526
         Explosion (industrial)	5	7	9	10	8	11	6	30	65	178	328	104	26	787
         Explosion	1	0	0	0	0	0	0	3	16	43	87	58	14	222
         Extreme temperature	0	0	0	2	0	8	9	15	37	91	224	207	59	652
         Fire (industrial)	1	0	0	0	1	1	1	6	29	70	58	43	10	220
         Fire (miscell.)	9	3	4	5	8	7	38	79	104	131	193	149	74	804
         Flood	6	4	9	11	11	81	155	259	515	861	1719	1531	779	5941
         Fog	0	0	0	0	0	1	0	0	0	0	0	0	0	1
         Gas leak	0	0	0	0	1	0	0	5	2	20	20	8	6	62
         Glacial lake outburst flood	0	0	0	0	0	0	0	0	0	0	0	0	4	4
         Infestation	0	1	0	1	1	0	0	4	48	11	18	9	2	95
         Mass mov. (dry)	3	0	0	1	0	1	2	0	14	11	8	5	0	45
         Mass mov. (wet)	1	2	4	6	4	20	26	55	105	151	192	183	78	827
         Oil spill	0	0	0	0	0	0	0	1	1	1	2	3	0	8
         Poisoning	0	0	0	0	0	2	1	7	10	36	17	3	0	76
         Radiation	0	0	0	0	0	1	0	1	3	2	2	0	0	9
         Rail	2	6	2	6	10	25	14	35	103	196	142	89	16	646
         Road	0	0	0	0	0	3	4	11	192	556	1240	694	182	2882
         Storm	14	18	34	39	55	119	211	274	533	893	1049	997	515	4751
         Volcanic activity	8	3	1	3	7	9	12	23	31	52	60	43	22	274
         Water-related	2	9	2	3	4	5	5	12	172	315	528	425	153	1635
         Wildfire	0	2	2	1	4	1	6	7	49	100	143	97	63	475
         Total	100	121	132	216	278	378	691	1121	2688	4941	7490	5624	2281	26,061

         Earthquakes were consistently reported, with the highest number in the 2000s at 289 events, likely due to increased seismic activity or better reporting. Also, epidemics saw a sharp increase in the 1990s with 385 events and peaked in the 2000s with 590 events, re- flecting global health challenges. Industrial explosions peaked in the 2000s with 328 events, while miscellaneous explosions rose to 87 events in the same decade. Extreme temperatures saw a significant rise in the 2000s with 224 events, underscoring the effects of climate change. Industrial fires peaked in the 1990s with 70 events, whereas miscellaneous fires increased steadily, peaking in the 2000s with 193 events. Floods showed a dramatic rise, peaking in the 2000s with 1719 events, indicating greater rainfall variability and extreme weather events.

         Air disasters first appeared in the 1910s with 15 events, gradually increasing and peak- ing in the 1990s with 300 events. This trend reflects significant technological advancements and increased air traffic during that period. However, a noticeable decline occurred in the 2010s, with 158 events. Animal incidents were rarely recorded, with only one incident noted in the 2010s. Chemical spills were first documented in the 1960s with 1 event, rising to a peak in the 1990s with 34 events, then declining to 7 events in the 2010s. Industrial collapses began in the 1950s, reaching a peak in the 2000s with 60 events, while miscella- neous collapses steadily increased, peaking in the 2000s with 87 events. Droughts were consistently recorded across decades, peaking in the 2000s with 170 events, highlighting the impact of climate change.

         Fog, gas leaks, and oil spills were rarely recorded but saw notable increases in certain decades, with gas leaks peaking in the 2000s with 20 events. Glacial lake outburst floods were infrequent, with a few incidents noted in recent years, pointing to climate change impacts. Infestations peaked in the 1980s with 48 events, showing occasional spikes due to ecological changes. Wet mass movements steadily increased, peaking in the 2000s with 192 events, reflecting more rainfall and landslide activity. Poisonings and radiation incidents were seldom recorded, with spikes such as poisoning incidents peaking in the 1990s with 36 events.

         Road disasters significantly increased, peaking in the 2000s with 1240 events due to more vehicular traffic, while rail disasters remained steady, peaking in the 1990s with 196 events. Storms consistently increased, peaking in the 2000s with 1049 events, reflecting more frequent and intense storm activity due to climate change. Volcanic activity remained relatively stable with slight increases, peaking in the 2000s with 60 events. Water-related disasters rose significantly, peaking in the 2000s with 528 events, highlighting issues such as flooding and water scarcity. Wildfires showed a gradual rise, peaking in the 2000s with 143 events, reflecting higher temperatures and drier conditions (Table 6 and Figure 9).

          

         ‌Figure 9. Total number of different natural and man-made (technological) disasters worldwide by decade (1900–2024).

         The mid to late 20th century saw a sharp rise in industrial and technological disas- ters, reflecting industrial growth, urbanization, and increased technological activities. A noticeable increase in climate-related disasters such as floods, droughts, extreme temper- atures, and wildfires in recent decades underscores the impact of climate change. The significant rise in the number of recorded disasters, particularly from the 1960s onwards, may also be due to improved reporting mechanisms, greater global awareness, and better

         disaster monitoring systems. The spike in epidemics and chemical spills in the late 20th and early 21st centuries highlights ongoing health and environmental challenges (Table 6 and Figure 9). Additionally, the recent decline in certain disasters, such as air disasters and some industrial incidents, suggests improvements in disaster management, safety protocols, and preparedness measures.

         Table 7 provides a detailed breakdown of the total number of different natural and man-made (technological) disasters recorded in 5-year intervals from 1900 to 2024. Air disasters began to be recorded from 1910–1914 with 1 event, peaking in the 1985–1989 period with 128 events. This trend shows significant technological advancements and increased air traffic contributing to these numbers. There was a noticeable decline in recent periods, with 23 events recorded in 2021–2024. Animal incidents were rarely recorded, with only one incident noted in the 2010–2014 period (Figure 10).

          

         ‌Figure 10. Total number of different natural and man-made (technological) disasters by 5-year periods (1900–2024).

         Chemical spills were first recorded in the 1965–1969 period with 1 event, peaking in the 1995–1999 period with 23 events. A decline was observed in recent periods, with no events recorded in 2020–2024. Industrial collapses began in the 1950–1954 period, peaking in the 2000–2004 period with 20 events. Miscellaneous collapses showed a steady increase, peaking in the 1995–1999 period with 45 events.

          

         ‌Table 7. Total number of different natural and man-made (technological) disasters by 5-year periods (1900–2024).

          

         1900–1904

          

         1905–1909

          

         1910–1914

          

         1915–1919

          

         1920–1924

          

         1925–1929

          

         1930–1934

          

         1935–1939

          

         1940–1944

          

         1945–1949

          

         1950–1954

          

         1955–1959

          

         1960–1964

          

         1965–1969

          

         1970–1974

          

         1975–1979

          

         1980–1984

          

         1985–1989

          

         1990–1994

          

         1995–1999

          

         2000–2004

          

         2005–2009

          

         2010–2014

          

         2015–2019

          

         2020–2024

          

         Disaster Type

         Air	0	0	1	14	3	4	10	49	69	6	3	3	8	8	17	12	27	128	148	152	131	117	90	68	23
         Animal incident	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0
         Chemical spill	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1	16	20	13	11	23	8	8	6	1	0
         Collapse (ind.)	0	0	0	0	0	0	0	0	0	0	1	2	0	0	0	2	5	7	9	12	20	40	32	34	20
         Collapse (misc.)	0	1	1	2	1	1	0	0	0	0	1	3	4	3	3	13	10	26	33	45	50	37	32	23	16
         Drought	3	1	9	1	3	1	2	0	11	2	0	0	10	42	18	43	80	46	64	76	96	74	84	85	62
         Earthquake	14	24	20	12	20	22	35	30	38	35	41	27	25	63	39	71	86	87	140	125	174	115	136	126	112
         Epidemic	2	3	1	5	9	1	1	1	1	2	2	0	6	31	9	50	39	85	103	282	360	230	139	119	45
         Explosion (ind.)	1	4	5	2	6	3	5	5	2	6	6	5	3	3	10	20	26	39	84	94	175	153	59	45	26
         Explosion (mis.)	1	0	0	0	0	0	0	0	0	0	0	0	0	0	2	1	9	7	16	27	55	32	38	20	14
         Extreme temper.	0	0	0	0	0	0	0	2	0	0	5	3	4	5	6	9	11	26	40	51	109	115	125	82	59
         Fire (ind.)	1	0	0	0	0	0	0	0	0	1	0	1	1	0	2	4	9	20	33	37	32	26	21	22	10
         Fire (misc.)	3	6	1	2	3	1	2	3	5	3	1	6	9	29	31	48	44	60	54	77	107	86	67	82	74
         Flood	3	3	2	2	1	8	3	8	3	8	42	39	53	102	98	161	222	293	365	496	769	950	761	770	779
         Fog	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0
         Gas leak	0	0	0	0	0	0	0	0	1	0	0	0	0	0	2	3	2	0	10	10	12	8	2	6	6
         Glacial lake (flood)	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	4
         Infestation	0	0	1	0	0	0	1	0	1	0	0	0	0	0	1	3	0	48	5	6	16	2	1	8	2
         Mass mov. (dry)	1	2	0	0	0	0	0	1	0	0	0	1	2	0	0	0	5	9	11	0	3	5	2	3	0
         Mass mov. (wet)	0	1	1	1	2	2	4	2	1	3	11	9	9	17	32	23	46	59	58	93	108	84	88	95	78
         Oil spill	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	1	0	2	1	2	0
         Poisoning	0	0	0	0	0	0	0	0	0	0	1	1	0	1	3	4	4	6	22	14	13	4	2	1	0
         Radiation	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	3	1	1	0	2	0	0	0

          

         Table 7. Cont.

          

         1900–1904

          

         1905–1909

          

         1910–1914

          

         1915–1919

          

         1920–1924

          

         1925–1929

          

         1930–1934

          

         1935–1939

          

         1940–1944

          

         1945–1949

          

         1950–1954

          

         1955–1959

          

         1960–1964

          

         1965–1969

          

         1970–1974

          

         1975–1979

          

         1980–1984

          

         1985–1989

          

         1990–1994

          

         1995–1999

          

         2000–2004

          

         2005–2009

          

         2010–2014

          

         2015–2019

          

         2020–2024

          

         Disaster Type

         Rail	1	1	1	5	0	2	1	5	4	6	16	9	6	8	13	22	25	78	93	103	85	57	45	44	16
         Road	0	0	0	0	0	0	0	0	0	0	3	0	0	4	1	10	12	180	221	335	725	515	393	301	182
         Storm	5	9	10	8	11	23	20	19	18	37	48	71	90	121	122	152	242	291	464	429	540	509	473	524	515
         Volcanic activity	7	1	2	1	0	1	2	1	2	5	7	2	5	7	4	19	20	11	29	23	25	35	22	21	22
         Water-related	1	1	5	4	1	1	2	1	1	3	3	2	2	3	7	5	28	144	168	147	254	274	218	207	153
         Wildfire	0	0	1	1	1	1	0	1	2	2	0	1	0	6	3	4	23	26	35	65	88	55	35	62	63
         Total	86	114	122	120	122	142	176	256	318	238	384	372	474	908	848	1394	1990	3386	4434	5448	7910	7070	5746	5502	4562

         Droughts were recorded consistently across the periods, peaking in the 2000–2004 pe- riod with 96 events, showing the impact of climate change and variability. Earthquakes were consistently recorded, with the highest number in the 2000–2004 period at 174 events, reflecting increased seismic activity or improved reporting. Epidemics saw a sharp increase in the 1990–1994 period with 103 events, peaking in the 2000–2004 period with 360 events, reflecting global health challenges.

         Industrial explosions peaked in the 2000–2004 period with 175 events, while miscella- neous explosions rose in the 2000–2004 period with 55 events. Extreme temperatures saw a significant rise in the 2000–2004 period with 109 events, highlighting the effects of climate change. Industrial fires peaked in the 1995–1999 period with 37 events, while miscellaneous fires increased consistently, peaking in the 2000–2004 period with 107 events.

         Floods experienced a dramatic increase, peaking in the 2000–2004 period with 769 events, indicating higher rainfall variability and extreme weather events. Fog, gas leaks, and oil spills were rarely recorded, with notable increases in specific periods, such as gas leaks peaking in the 1995–1999 period with 10 events. Glacial lake outburst floods were rarely recorded, with a few incidents noted in the 2020–2024 period, indicating climate change impacts.

         Infestations peaked in the 1985–1989 period with 48 events, showing occasional spikes due to ecological changes. Wet mass movements showed a steady increase, peaking in the 1995–1999 period with 93 events, reflecting increased rainfall and landslide activity. Poisonings and radiation incidents were rarely recorded, with occasional spikes such as poisoning incidents peaking in the 1990–1994 period with 22 events (Table 7 and Figure 10). Road disasters showed a significant rise, peaking in the 2000–2004 period with

         725 events, reflecting increased vehicular traffic. Rail disasters showed a steady number with a peak in the 1990–1994 period at 93 events. Storms consistently increased, peaking in the 2000–2004 period with 540 events, reflecting more frequent and intense storm activity due to climate change. Volcanic activity had a relatively stable number of events with slight increases, peaking in the 2005–2009 period with 35 events.

         Water-related disasters saw a significant increase, peaking in the 2000–2004 period with 254 events, highlighting water-related issues such as flooding and water scarcity. Wildfires showed a gradual increase with a peak in the 2000–2004 period at 88 events, reflecting increased temperatures and dry conditions (Table 7 and Figure 10).

         Table 8 offers a detailed seasonality analysis, showcasing the number of occurrences of various disaster types by month. This analysis highlights the monthly distribution and trends of different disasters, providing insights into how these events fluctuate throughout the year (Table 8). Air disasters reach their peak in July with 744 events, suggesting increased air traffic or weather-related factors during this month. Overall, the trend is above average, with a total of 1091 events, accounting for 4.123% of all recorded disasters. Conversely, animal incidents are rarely recorded, with only one incident noted in November, resulting in a below-average trend. Chemical spills also peak in July with 86 events, possibly due to seasonal industrial activities or increased transportation, but the overall trend remains below average with 108 events, making up 0.408% of all recorded disasters. Industrial collapses peak in November with 21 events, while miscellaneous collapses hit their highest point in July with 181 events, both showing a below-average trend.

         Earthquakes peak in March with 316 events, likely due to seasonal tectonic activity, with an above-average (AA) trend totaling 1617 events, which represent 6.11% of all disasters. Droughts are most frequent in February, peaking at 326 events and reflecting seasonal climatic patterns, yet their overall trend is below average (BA) with a total of 813 events, or 3.072% of all recorded disasters. Epidemics also show a significant peak in July with 701 events, pointing to seasonal health challenges. This results in an above- average trend with 1526 events, making up 5.766% of all recorded disasters (Table 8).

         Industrial explosions are most frequent in July, peaking at 411 events, while miscella- neous explosions also see increased activity during the summer months, both maintaining a below-average trend. Extreme temperatures peak in July with 280 events, highlighting the impact of summer heatwaves. Despite this, the overall trend is below average, with

         652 events, constituting 2.464% of all disasters. Fires, both industrial and miscellaneous, also peak in July, with 121 and 440 events, respectively, yet both trends are below average. Floods show a dramatic increase in July with 2072 events, coinciding with monsoon and heavy rainfall periods. This results in an above-average trend, totaling 5941 events, or 22.449% of all recorded disasters (Table 8).

         ‌Table 8. Seasonality analysis showing the number of occurrences of each disaster type by month.

          

         		Feb	Mar							Oct	Nov	Dec	(n)	(%)	Trend
         Air	36	20	40	66	26	16	744	39	31	30	24	19	1091	4.123	AA
         Animal incident	0	0	0	0	0	0	0	0	0	0	1	0	1	0.004	BA
         Chemical spill	0	2	1	7	0	0	86	3	3	2	2	2	108	0.408	BA
         Collapse (industrial)	7	7	13	18	17	6	62	9	6	9	21	9	184	0.695	BA
         Collapse (miscellaneous)	15	12	14	14	7	11	181	15	2	13	13	8	305	1.153	BA
         Drought	44	326	77	34	30	18	46	64	40	43	61	30	813	3.072	BA
         Earthquake	197	92	316	190	48	37	201	185	91	32	83	145	1617	6.11	AA
         Epidemic	63	75	75	42	49	220	701	57	38	83	79	44	1526	5.766	AA
         Explosion (industrial)	24	23	32	70	39	30	411	34	26	25	46	27	787	2.974	BA
         Explosion (miscellaneous)	12	8	13	13	10	9	99	20	16	7	7	8	222	0.839	BA
         Extreme temperature	98	81	35	34	10	10	280	49	11	5	6	33	652	2.464	BA
         Fire (industrial)	7	6	11	16	6	7	121	8	11	9	8	10	220	0.831	BA
         Fire (miscellaneous)	38	35	44	60	19	20	440	35	24	26	30	33	804	3.038	BA
         Flood	592	304	390	306	290	192	2072	400	403	374	356	262	5941	22.449	AA
         Fog	0	0	0	0	0	0	1	0	0	0	0	0	1	0.004	BA
         Gas leak	0	2	2	10	2	8	28	6	1	2	1	0	62	0.234	BA
         Glacial lake outburst flood	0	1	0	1	0	0	1	0	0	1	0	0	4	0.015	BA
         Impact	0	0	1	0	0	0	0	0	0	0	0	0	1	0.004	BA
         Industrial accident (general)	8	6	4	15	8	6	40	11	6	4	11	7	126	0.476	BA
         Infestation	0	8	0	2	0	0	71	8	3	1	0	2	95	0.359	BA
         Mass movement (dry)	2	1	0	0	1	0	37	1	0	1	2	0	45	0.17	BA
         Mass movement (wet)	51	61	43	44	34	19	427	41	23	29	24	31	827	3.125	A
         Miscellaneous accident	16	21	23	33	5	15	85	15	14	14	20	15	276	1.043	BA
         Oil spill	1	0	0	1	0	1	2	0	1	0	2	0	8	0.03	BA
         Poisoning	0	5	8	1	0	0	56	0	1	3	1	1	76	0.287	BA
         Radiation	0	0	0	1	0	0	6	2	0	0	0	0	9	0.034	BA
         Rail	13	13	28	44	13	11	453	24	7	17	19	4	646	2.441	BA
         Road	166	95	140	128	109	135	1326	189	153	158	166	117	2882	10.89	AA
         Storm	345	184	344	259	349	95	2146	217	191	218	211	192	4751	17.953	AA
         Volcanic activity	17	2	5	11	7	67	120	4	9	3	10	19	274	1.035	BA
         Water-related	94	72	106	152	62	62	718	75	71	84	89	50	1635	6.178	AA
         Wildfire	26	15	28	21	15	12	239	55	20	20	11	13	475	1.795	BA

          

         Disaster Type Jan

         Apr May Jun Jul Aug Sep

         Total

         Note: AA—above average; A—average; BA—below average.

         Fog, gas leaks, and oil spills are infrequent, with specific peaks in certain months but generally below-average trends. Glacial lake outburst floods are rarely recorded, with isolated incidents in January, April, and October. Infestations peak in July with 71 events, indicating seasonal ecological changes, yet the overall trend remains below average. Wet mass movements are most common in July, peaking at 427 events, which reflects seasonal rainfall and landslide activities, whereas dry mass movements are rarely recorded, showing no clear seasonal trend. Poisonings and radiation incidents are also rare, with peaks in specific months but generally below-average trends.

         Road disasters peak in July with 1326 events, reflecting increased summer travel, while rail disasters also reach their highest point in July with 453 events. The trend for road disasters is above average, whereas rail disasters trend below average.

         Storms peak in July with 2146 events, indicating seasonal storm activity, resulting in an above-average trend with a total of 4751 events, or 17.953% of all recorded disasters. Vol- canic activity peaks in July with 120 events, showing a slight seasonal trend but remaining below average.

         Water-related disasters peaked in July with 718 events, highlighting issues like floods and water scarcity. This results in an above-average trend, totaling 1635 events, which represent 6.178% of all recorded disasters.

         Wildfires also peak in July with 239 events, reflecting dry and hot summer conditions. However, the overall trend is below average, with a total of 475 events, making up 1.795% of all recorded disasters.

         The seasonality analysis reveals how climate and weather patterns significantly in- fluence disaster occurrences, with many events peaking during the summer months due to extreme weather conditions. Disasters such as air incidents, earthquakes, epidemics, road accidents, storms, and water-related disasters tend to be more frequent during certain times of the year, showing above-average trends.

         For instance, many disaster types, including floods, storms, and fires, reach their highest numbers in July. This pattern reflects the impact of summer weather conditions like monsoon rains, heat waves, and dry spells. The peaks in industrial and miscellaneous disasters during the summer months suggest that increased industrial activities, travel, and other human activities contribute to higher disaster frequencies during this period.

         According to the monthly analysis, the highest number of disasters is recorded in July with 9135 incidents. This month is particularly prone to disasters due to significant spikes in air disasters (744), floods (2072), storms (2146), and road disasters (1326). The heightened summer activities and extreme weather conditions contribute to the high frequency of disasters during this period. Increased travel, intense heat, and seasonal storms make July especially disaster-prone (Table 8).

         Following July, March records a total of 1921 disasters. This month is notable for the high number of earthquake occurrences (316) and floods (390). Seasonal weather changes, including the transition from winter to spring, likely contribute to these numbers. Shifting temperatures can lead to increased seismic activity and the onset of spring floods.

         January ranks next with 1819 disasters. This month is characterized by a high number of flood occurrences (592), alongside significant events like earthquakes (197) and extreme temperatures (98). Winter conditions and the start of the year contribute to these disaster occurrences, with heavy rainfall and cold temperatures playing a major role.

         In August, 1702 disasters were recorded, with notable numbers of floods (400), storms (217), and wildfires (239). The continuation of summer conditions, including heatwaves and droughts, contributes to this high disaster rate. Hot and dry conditions often lead to wildfires, while summer storms can cause severe flooding.

         February sees 1158 disasters, with significant occurrences of floods (304), earthquakes (92), and extreme temperatures (81). The winter season and its associated weather patterns, including heavy rains and cold snaps, are likely causes of these disasters. The month is also characterized by winter storms and potential flooding from snowmelt.

         In June, there are 1048 disasters, with high numbers of floods (192), storms (95), and road disasters (135). The beginning of summer brings increased human activities and changing weather conditions, contributing to the disaster frequency. The month also marks the onset of hurricane season in some regions, leading to an increase in storm-related events.

         October records 1029 disasters, with notable flood events (374) and storms (218). The transitional weather of autumn, including increased rainfall and the tail end of hurricane season, contributes to the high number of disasters. Cooler temperatures and changing atmospheric conditions also play a role (Table 8).

         September has 878 disasters, marked by significant flood events (403) and storm occurrences (191). This reflects the continued impact of summer weather and the height of hurricane season. The end of summer often brings severe storms and heavy rains, leading to widespread flooding. In April, there are 876 disasters, with high earthquake occurrences

         (190) and significant flood numbers (306). The seasonal transition from winter to spring brings increased rainfall and seismic activity. Melting snow and spring rains can lead to flooding, while the earth’s tectonic movements are influenced by temperature changes.

         November sees 858 disasters, with considerable numbers of floods (356) and road disasters (166). The late autumn weather, including heavy rains and early winter storms, contributes to the disaster frequency. The month also marks the beginning of winter travel, increasing the risk of road accidents. December records 742 disasters, with notable flood

         occurrences (262) and significant earthquake numbers (145). Winter conditions, including heavy rainfall and seismic activity, contribute to these disasters. The holiday season also sees increased travel and associated risks.

         The seasonality analysis reveals that July is the most disaster-prone month, driven by summer-related weather conditions and increased human activities. March and January also show high disaster occurrences, reflecting the impact of seasonal transitions. Floods and storms are the most common disasters across all months, with significant peaks during the summer and transitional seasons. By understanding these seasonal disaster patterns, preparedness and mitigation strategies can be improved. Focusing efforts during peak months can help reduce the impact of these events and enhance response capabilities. This knowledge about the timing and frequency of various disasters can guide resource alloca- tion, emergency planning, and public awareness campaigns, ensuring that communities are better equipped to handle the increased risk during critical periods of the year (Table 8).

      2. Yearly and Monthly Trends in Consequences of Natural and Man-Made Disasters Providing a comprehensive analysis, Table 9 examines the impacts of natural and

         man-made (technological) disasters across the decades, detailing fatalities, injuries, and economic losses. This examination underscores the evolving human and economic effects of these disasters, highlighting significant trends over time.

         ‌Table 9. Number of consequences of natural and man-made (technological) disasters by decade (1900–2024).

          

         Natural Disasters Man-Made (Tech.) Disasters Total

         Decade	Fatalities	Injuries	Economic Losses	Fatalities	Injuries	Economic Losses	Fatalities	Injuries	Economic Losses
         1900–1910	4,472,477	2549	1,373,800	5766	2	0	4,478,243	2551	1,373,800
         1911–1920	3,334,004	2955	600,000	10,752	9306	2500	3,344,756	12,261	602,500
         1921–1930	8,561,918	109,109	1,004,230	7139	1596	100,000	8,569,057	110,705	1,104,230
         1931–1940	4,629,968	112,403	3,342,000	5579	511	0	4,635,547	112,914	3,342,000
         1941–1950	3,878,897	69,329	3,136,700	11,165	2258	6000	3,890,062	71,587	3,142,700
         1951–1960	2,127,944	24,642	6,090,480	10,979	6241	218,000	2,138,923	30,883	6,308,480
         1961–1970	1,751,347	784,522	18,633,100	6446	5155	159,972	1,757,793	789,677	18,793,072
         1971–1980	998,508	552,541	53,753,225	17,244	22,809	76,193	1,015,752	575,350	53,829,418
         1981–1990	796,062	317,353	183,523,629	58,382	159,620	6,469,293	854,444	476,973	189,992,922
         1991–2000	527,413	1,588,807	701,281,224	86,149	80,174	4,410,769	613,562	1,668,981	705,691,993
         2001–2010	839,418	3,282,010	892,099,162	97,166	89,617	14,746,682	936,584	3,371,627	906,845,844
         2011–2020	503,400	3,241,477	1,706,627,174	62,715	59,375	20,969,701	566,115	3,300,852	1,727,596,875
         2021–2024	199,314	627,655	861,127,190	15,132	24,593	16,750,000	214,446	652,248	877,877,190

         Notes: fatalities: the total number of deaths; injuries: the total number of injured individuals; economic losses: represented in thousands of US dollars.

         In the early 20th century, particularly from 1900 to 1910, natural disasters caused a staggering number of fatalities, totaling 4,472,477, while injuries and economic losses were minimal. Man-made disasters during this period resulted in 5766 fatalities but had negligible economic impact.

         Moving into the 1910–1920 decade, fatalities from natural disasters slightly decreased to 3,334,004, with injuries and economic losses remaining relatively low. However, man- made (technological) disasters began to show a more significant impact, with 10,752 fatali- ties and 9306 injuries (Table 9 and Figure 11).

         The period from 1920 to 1930 saw a dramatic increase in fatalities from natural dis- asters, reaching 8,561,918, alongside a rise in injuries and economic losses. Man-made disasters, although still less impactful than natural ones, contributed to 7139 fatalities and 1596 injuries. The following decade, 1930–1940, saw a reduction in natural disaster fatalities to 4,629,968 but an increase in economic losses to USD 3,342,000. Man-made disasters continued to cause fatalities, albeit at a lower rate.

          

         ‌Figure 11. Consequences of natural and man-made (technological) disasters by decades (1900–2024).

         During the mid-20th century, from 1940 to 1950, natural disasters resulted in 3,878,897 fa- talities and 69,329 injuries, with economic losses continuing to rise. Man-made disasters showed a notable increase in fatalities and injuries, reflecting the growing industrialization and technological advancements of the time. The 1950–1960 decade witnessed a further increase in economic losses from natural disasters to USD 6,090,480, although fatalities de- creased to 2,127,944. Man-made disasters remained a significant cause of fatalities and injuries (Table 9 and Figure 11).

         The late 20th century, particularly from 1960 to 1990, experienced significant increases in economic losses due to natural disasters. The 1960–1970 period saw USD 18,793,072 in economic losses, which further escalated to USD 183,523,629 in the 1980–1990 period. This era also marked substantial fatalities and injuries from both natural and man-made (technological) disasters. For instance, the 1980–1990 decade recorded 58,382 fatalities and 159,620 injuries from man-made (technological) disasters, indicating the increasing severity of industrial accidents (Table 9 and Figure 11).

         Entering the early 21st century, the period from 2000 to 2020 witnessed the highest eco- nomic losses due to natural disasters, peaking at USD 1,706,627,174 in the 2010–2020 decade. This period also saw high numbers of fatalities and injuries, reflecting the intensified im- pact of disasters. Man-made disasters continued to significantly contribute to fatalities and injuries, with 97,166 fatalities and 89,617 injuries recorded in the 2000–2010 period. Recent trends from 2020 to 2030 show a significant reduction in fatalities from natural dis- asters compared to earlier periods, dropping to 199,314. However, economic losses remain

         substantial, amounting to USD 861,127,190. Man-made disasters continue to contribute significantly to fatalities and injuries, with 15,132 fatalities and 24,593 injuries recorded in this period, highlighting the persistent risk from technological and industrial activities (Table 9 and Figure 11).

         Table 10 provides an in-depth look at the impacts of natural and man-made (technolog- ical) disasters over 5-year periods, detailing fatalities, injuries, and economic losses. In the early 20th century, particularly from 1900 to 1905, natural disasters resulted in significant fatalities, totaling 1,523,244, with minimal injuries and economic losses. This trend persisted into subsequent periods, with notable spikes in fatalities during 1905–1910 (2,949,233) and 1915–1920 (3,022,829). Despite these high death tolls, economic losses remained relatively low during these years.

         ‌Table 10. Consequences of natural and man-made (technological) disasters by 5-year periods (1900–2024).

          

         Natural Disasters Man-Made (Tech.) Disasters Total

         5-Year Period	Fatalities	Injuries	Economic Losses	Fatalities	Injuries	Economic Losses	Fatalities	Injuries	Economic Losses
         1900–1905	1,523,244	251	535,000	2230	2	0	1,525,474	253	535,000
         1906–1910	2,949,233	2298	838,800	3536	0	0	2,952,769	2298	838,800
         1911–1915	311,175	2828	275,000	5232	20	0	316,407	2848	275,000
         1916–1920	3,022,829	127	325,000	5520	9286	2500	3,028,349	9413	327,500
         1921–1925	5,065,612	103,900	663,000	6412	1500	100,000	5,072,024	105,400	763,000
         1926–1930	3,496,306	5209	341,230	727	96	0	3,497,033	5305	341,230
         1931–1935	3,772,100	9045	1,629,000	3021	324	0	3,775,121	9369	1,629,000
         1936–1940	857,868	103,358	1,713,000	2558	187	0	860,426	103,545	1,713,000
         1941–1945	3,569,724	48,909	1,325,500	5208	1181	0	3,574,932	50,090	1,325,500
         1946–1950	309,173	20,420	1,811,200	5957	1077	6000	315,130	21,497	1,817,200
         1951–1955	86,802	11,243	3,775,180	5377	1949	178,000	92,179	13,192	3,953,180
         1956–1960	2,041,142	13,399	2,315,300	5602	4292	40,000	2,046,744	17,691	2,355,300
         1961–1965	124,667	16,119	8,163,881	3394	2818	49,759	128,061	18,937	8,213,640
         1966–1970	1,626,680	768,403	10,469,219	3052	2337	110,213	1,629,732	770,740	10,579,432
         1971–1975	623,353	218,953	15,582,333	6779	12,990	3843	630,132	231,943	15,586,176
         1976–1980	375,155	333,588	38,170,892	10,465	9819	72,350	385,620	343,407	38,243,242
         1981–1985	633,887	155,979	84,139,472	17,264	140,392	761,976	651,151	296,371	84,901,448
         1986–1990	162,175	161,374	99,384,157	41,118	19,228	5,707,317	203,293	180,602	105,091,474
         1991–1995	299,078	818,151	264,087,752	44,158	32,120	1,363,916	343,236	850,271	265,451,668
         1996–2000	228,335	770,656	437,193,472	41,991	48,054	3,046,853	270,326	818,710	440,240,325
         2001–2005	435,658	2,437,898	331,597,225	54,143	54,209	11,607,124	489,801	2,492,107	343,204,349
         2006–2010	403,760	844,112	560,501,937	43,023	35,408	3,139,558	446,783	879,520	563,641,495
         2011–2015	418,756	1,087,793	871,742,990	32,710	31,140	20,964,701	451,466	1,118,933	892,707,691
         2016–2020	84,644	2,153,684	834,884,184	30,005	28,235	5000	114,649	2,181,919	834,889,184
         2021–2024	199,314	627,655	861,127,190	15,132	24,593	16,750,000	214,446	652,248	877,877,190

         Notes: fatalities: the total number of deaths; injuries: the total number of injured individuals; economic losses: represented in thousands of US dollars.

         As the mid-20th century was reached, fluctuations in fatalities and economic losses were observed. The 1920–1925 period recorded the highest fatalities of this era, with 5,065,612 lives lost due to natural disasters. Economic losses began to rise significantly during 1930–1935, reaching USD 1,629,000. During this time, man-made (technological) disasters also began to show a more substantial impact, particularly in the 1945–1950 period, which saw 5957 fatalities. The late 20th century experienced a dramatic increase in economic losses from natural disasters, peaking at USD 264,087,752 in the 1990–1995 period. This era also saw substantial fatalities and injuries from both natural and man-made (technological) disasters. The increasing industrialization and urbanization during these years contributed to the heightened impact of such events (Table 10 and Figure 12).

          

         ‌Figure 12. Consequences of natural and man-made (technological) disasters by 5-year periods (1900–2024).

         As the early 21st century was entered, the highest economic losses due to natural disasters were observed, with the period from 2011 to 2015 reaching USD 871,742,990. This time frame also saw a significant number of fatalities and injuries, reflecting the intensified impact of disasters. Technological advancements and population growth likely contributed to these escalating figures. Recent trends from 2021 to 2024 show a notable reduction in fatalities from natural disasters compared to earlier periods, although economic losses remain high at USD 861,127,190. Man-made disasters continue to have a significant impact, with 15,132 fatalities and 24,593 injuries recorded in this period. These insights emphasize the persistent financial and human toll of disasters, underscoring the importance of improving disaster risk reduction strategies to mitigate these impacts (Table 10 and Figure 12).

         Table 11 offers a detailed summary of the consequences of different types of natural and man-made (technological) disasters from 1900 to 2024. Regarding this, air disasters re- sulted in 50,689 deaths (0.154%), 7620 injuries (0.068%), and USD 144.1 million in economic losses (0.003%). While these disasters had a significant human impact, the economic con- sequences were relatively minimal. Chemical spills, though responsible for fewer deaths (610 or 0.002%), led to substantial injuries (8773 or 0.078%) and affected over 652,981 people (0.008%), causing significant economic losses amounting to nearly USD 1.2 billion (0.027%). Industrial and miscellaneous collapses had notable impacts as well, with industrial col- lapses resulting in 7099 deaths (0.022%) and USD 1.335 billion in economic losses (0.03%), and miscellaneous collapses causing 14,830 deaths (0.045%) and USD 283.8 million in economic losses (0.006%).

         ‌Table 11. Summary of disaster consequences by type, including total counts and percentage contribu- tions (1900–2024).

          

         	(n)	(%)	(n)	(%)	(n)	(%)	(n)	(%)
         Air	50,689	0.154	7620	0.068	8846	0.0	144,100	0.003
         Animal incident	12	0.0	0	0.0	5	0.0	0	0.0
         Chemical spill	610	0.002	8773	0.078	652,981	0.008	1,198,954	0.027
         Collapse (industrial)	7099	0.022	2450	0.022	3353	0.0	1,335,000	0.03
         Collapse (miscellaneous)	14,830	0.045	13,024	0.117	309,514	0.004	283,800	0.006
         Drought	11,734,272	35.54	32	0.0	2,964,996,768	34.146	257,581,674	5.728
         Earthquake	2,407,717	7.293	2,945,052	26.35	228,214,673	2.628	975,785,916	21.701
         Epidemic	9,622,343	29.14	2,836,719	25.38	50,095,829	0.577	7	0.0
         Explosion (industrial)	36,814	0.112	41,850	0.374	864,341	0.01	40,421,674	0.899
         Explosion (miscellaneous)	7624	0.023	19,231	0.172	137,527	0.002	619,100	0.014
         Extreme temperature	256,413	0.777	2,066,936	18.49	107,678,810	1.24	69,468,343	1.545
         Fire (industrial)	5522	0.017	5211	0.047	465,362	0.005	2,608,005	0.058
         Fire (miscellaneous)	36,590	0.111	24,022	0.215	1,368,383	0.016	3,485,470	0.078
         Flood	7,011,404	21.23	1,398,042	12.50	3,997,629,671	46.039	1,007,889,805	22.415
         Fog	4000	0.012	0	0.0	0	0.0	0	0.0
         Gas leak	2906	0.009	116,280	1.04	513,932	0.006	30,000	0.001
         Glacial lake outburst flood	439	0.001	24	0.0	88,424	0.001	210,000	0.005
         Impact	0	0.0	1491	0.013	301,491	0.003	33,000	0.001
         Industrial accident (general)	5207	0.016	1552	0.014	135,987	0.002	9,960,407	0.222
         Infestation	0	0.0	0	0.0	2,802,200	0.032	229,200	0.005
         Mass movement (dry)	4486	0.014	373	0.003	23,117	0.0	209,000	0.005
         Mass movement (wet)	68,636	0.208	12,705	0.114	16,823,502	0.194	11,347,044	0.252
         Miscellaneous accident (general)	14,279	0.043	40,666	0.364	1,880,052	0.022	4000	0.0
         Oil spill	1	0.0	120	0.001	29,137	0.0	30,000	0.001
         Poisoning	3578	0.011	54,442	0.487	648,522	0.007	0	0.0
         Radiation	86	0.0	1958	0.018	1,064,201	0.012	2,800,000	0.062
         Rail	28,730	0.087	61,744	0.552	109,453	0.001	903,000	0.02
         Road	68,812	0.208	49,184	0.44	56,306	0.001	7700	0.0
         Storm	1,418,647	4.297	1,411,425	12.62	1,277,565,968	14.713	1,967,141,984	43.748
         Volcanic activity	86,935	0.263	26,564	0.238	10,032,658	0.116	6,327,912	0.141
         Water-related	111,237	0.337	13,130	0.117	149,256	0.002	77,900	0.002
         Wildfire	5366	0.016	15,989	0.143	18,531,582	0.213	136,368,030	3.033
         Total	33,015,284	100.0	11,176,609	100.0	8,683,181,851	100.0	4,496,501,025	100.0

          

         Disaster Type Deaths Injured Affected Damage (‘000 USD)

         Droughts emerged as the deadliest disaster type, accounting for 11,734,272 deaths (35.54%) and affecting nearly 3 billion individuals (34.146%), with economic losses to- taling USD 257.58 billion (5.728%). Earthquakes also had a substantial impact, causing 2,407,717 deaths (7.293%) and USD 975.79 billion in economic losses (21.701%), along with

         2,945,052 tinjuries (26.35%) and 228 million people affected (2.628%). Epidemics were

         significant as well, resulting in 9,622,343 deaths (29.14%) and 2,836,719 injuries (25.38%), though they had minimal economic impact.

         Extreme temperatures led to 256,413 deaths (0.777%), 2,066,936 injuries (18.49%), and USD 69.47 billion in economic losses (1.545%). Fires, both industrial and miscellaneous, had considerable impacts, with miscellaneous fires causing 36,590 deaths (0.111%) and USD

         3.49 billion in economic losses (0.078%), while industrial fires led to USD 2.61 billion in economic losses (0.058%). Floods were highly impactful, causing 7,011,404 deaths (21.23%), 1,398,042 injuries (12.50%), and affecting nearly 4 billion people (46.039%), with economic

         losses totaling USD 1.01 trillion (22.415%).

         Mass movements, both dry and wet, varied in impact. Wet mass movements caused 68,636 deaths (0.208%) and USD 11.35 billion in economic losses (0.252%), while dry mass movements had a smaller impact. Miscellaneous accidents had notable consequences, causing 14,279 deaths (0.043%) and 40,666 injuries (0.364%). Oil spills had minimal impact,

         whereas poisoning incidents led to 3578 deaths (0.011%) and 54,442 injuries (0.487%). Although radiation incidents were rare, they caused significant economic losses (USD 2.8 billion, or 0.062%).

         Storms were another major disaster type, causing 1,418,647 deaths (4.297%), 1,411,425 in- juries (12.62%), and USD 1.97 trillion in economic losses (43.748%), reflecting their widespread and severe impact. Volcanic activity led to 86,935 deaths (0.263%) and USD 6.33 billion in economic losses (0.141%), affecting over 10 million individuals (0.116%). Water-related disas- ters caused 111,237 deaths (0.337%) and USD 77.9 million in economic losses (0.002%), while wildfires resulted in 5366 deaths (0.016%), 15,989 injuries (0.143%), and significant economic

         losses totaling USD 136.37 billion (3.033%) (Table 11 and Figure 13).

          

         ‌Figure 13. Percentage distribution of natural and man-made (technological) disaster consequences by type (1900–2024).

         When ranking the impact of disasters by fatalities, droughts emerge as the deadliest, causing the highest number of deaths at 11,734,272, accounting for 35.54% of all disaster- related fatalities. Following closely are epidemics, responsible for 9,622,343 deaths, or 29.14%. Floods come in third, resulting in 7,011,404 deaths (21.23%), while earthquakes are fourth, causing 2,407,717 deaths (7.293%). Rounding out the top five, storms contribute to 1,418,647 deaths, making up 4.297% of the total (Table 11 and Figure 13).

         In terms of injuries, earthquakes lead with the highest number, causing 2,945,052 in- juries, representing 26.35% of all disaster-related injuries. Epidemics follow closely with 2,836,719 injuries (25.38%). Extreme temperatures rank third, causing 2,066,936 injuries

         (18.49%). Floods result in 1,398,042 injuries (12.50%), and storms cause 1,411,425 injuries, making up 12.62% of the total.

         Looking at the number of people affected by disasters, floods have the most significant impact, affecting nearly 4 billion individuals (3,997,629,671), which is 46.039% of the total affected population. Droughts come in second, impacting almost 3 billion people (2,964,996,768), or 34.146%. Storms affect over 1.27 billion people (1,277,565,968; 14.713%), making them the third most impactful. Earthquakes are fourth, affecting over 228 million individuals (228,214,673; 2.628%), while extreme temperatures affect over 107 million people (107,678,810; 1.24%).

         Regarding economic losses, storms cause the most significant financial damage, with total losses amounting to approximately USD 1.97 trillion (43.748%). Floods rank second, causing over USD 1 trillion in economic losses (1,007,889,805,000; 22.415%). Earthquakes follow, with losses of approximately USD 975.79 billion (21.701%). Droughts come in fourth, with financial damages totaling around USD 257.58 billion (5.728%), and wildfires are fifth, causing economic losses of about USD 136.37 billion (3.033%) (Table 11 and Figure 13).

         This analysis underscores the profound impact of various disaster types, with droughts and floods being the most devastating in terms of human lives, while storms and earth- quakes cause the highest economic losses.

4. ‌The Impact of Socio-Economic Indicators on the Distribution and Consequences of Disasters

   Based on the results of Pearson’s correlation analysis, there is a statistically significant relationship between various socio-economic indicators and the patterns, outcomes, and specific impacts of disasters, including the number of deaths, injuries, and total disasters. The analysis reveals a significant negative correlation between GDP per capita (USD) and the total number of disasters (p = 0.140, r = −0.333). This suggests that countries with a higher GDP per capita tend to experience fewer overall disasters and related impacts. This relationship could be attributed to wealthier nations’ ability to allocate more resources towards disaster prevention, mitigation, and preparedness, potentially reducing both the frequency and severity of disasters [94,95]. However, the analysis did not find a statistically significant correlation between GDP per capita and the number of people affected, deaths, injuries, natural disasters, or man-made disasters. This indicates that economic wealth alone may not directly lead to better outcomes in terms of lives saved, reduced injuries, or fewer natural disasters.

   On the other hand, the quality of governance is also significantly negatively correlated with the total number of disasters (p = 0.080, r = −0.390). This suggests that higher governance quality is associated with fewer disasters overall. Effective governance likely enhances disaster management practices, including timely response and efficient resource allocation, thereby reducing the overall impact of disasters, including the number of deaths and injuries. Although the correlations with deaths (p = 0.941, r = −0.017) and injuries (p = 0.846, r = −0.045) are statistically significant, they are relatively weak. However, these findings still suggest that good governance may play a role in reducing the severity of disaster outcomes (Table 12).

   Furthermore, population density (people per km2) shows a highly significant positive

   correlation with the number of people affected by disasters (p = 0.000, r = 0.729), indicating that areas with higher population densities are more likely to see greater numbers of people impacted by such disasters. This finding is logical, as densely populated areas naturally have more people at risk when disasters strike. There is also a significant negative correlation with deaths (p = 0.120, r = −0.350), injuries (p = 0.229, r = −0.274), and total disasters (p = 0.401, r = −0.193). These results suggest that while more individuals may be affected in high-density areas, the number of deaths, injuries, and the frequency of natural disasters may be lower. This could be due to better infrastructure and emergency services that are more readily available in urbanized regions. However, correlations with specific types of natural and man-made disasters are not statistically significant, implying that

   population density alone does not fully explain the occurrence of these types of disasters (Table 12).Finally, the urbanization rate (%) is significantly negatively correlated with the total number of disasters (p = 0.007, r = −0.571). This indicates that higher urbanization rates are associated with fewer disasters overall. This may be because urban areas often benefit from superior infrastructure, more robust disaster response systems, and better access to resources, all of which can mitigate the frequency and impact of disasters, including those leading to deaths, injuries, and natural disasters [96,97].

   Disasters

    

   ‌Table 12. Pearson’s correlation results for socio-economic indicators in the distribution and conse- quences of disasters.

    

   Variables

   Affected Deaths Injuries Total

   Natural Disasters

   Man-Made Disaster

   	Sig.	r	Sig.	r	Sig.	r	Sig.	r	Sig.	r	Sig.	r
   GDP per capita (USD)	0.055	0.424	0.699	0.090	0.754	0.073	0.140	−0.333 *	0.423	0.185	0.748	0.075
   Governance quality	0.117	0.352	0.941	−0.017 *	0.846	−0.045 *	0.080	−0.390 *	0.486	0.161	0.621	0.114
   Population density (people per km2)	0.000 *	0.729	0.120	−0.350 *	0.229	−0.274 *	0.401	−0.193 *	0.860	0.041	0.894	0.031
   Urbanization rate (%)	0.120	0.350	0.612	−0.117 *	0.804	−0.058 *	0.007 *	−0.571 *	0.766	−0.069	0.367	0.208

   * p ≤ 0.05.

   Additionally, the urbanization rate exhibits negative correlations with deaths (p = 0.612, r = −0.117), injuries (p = 0.804, r = −0.058), and natural disasters (p = 0.766, r = −0.069), although these are not statistically significant. These findings suggest that urbanized areas may be better equipped to handle disasters, leading to fewer fatalities, injuries, and natural disasters, though the results are not definitive (Table 12).

5. ‌Discussion

   The analysis of the distribution of natural and man-made (technological) disasters across continents from 1900 to 2024 reveals notable trends and patterns. Asia has experienced the highest number of disasters, accounting for 41.75% of all recorded events. This is due to the continent’s vast and diverse geography, high population density, and rapid industrialization. These factors contribute to both the frequency and impact of disasters in the region. For example, Asia’s high rate of earthquakes and floods necessitates robust mitigation strategies focusing on seismic resilience and flood management [98,99]. Additionally, the significant proportion of man-made (technological) disasters (38.11%) highlights the need for improved industrial safety and infrastructure development in rapidly urbanizing areas [24,100].

   Africa, with 21.44% of the total disasters, has the highest proportion of man-made (technological) disasters (43.79%). This high percentage is linked to socio-economic factors such as inadequate infrastructure, governance challenges, and political instability, which exacerbate the risks and impacts of technological accidents and conflicts [101]. Natural disasters in Africa, such as droughts, also reflect the continent’s vulnerability to climate change, underscoring the necessity for integrated approaches addressing both natural and man-made (technological) hazards [102,103]. Furthermore, North America, which accounts for 13.84% of the total events, shows a predominance of natural disasters (75.75%), particularly storms and wildfires. This pattern is consistent with the region’s exposure to climatic extremes and varied topography, making it susceptible to a range of natural haz- ards [104,105]. The data suggest that strengthening early warning systems and enhancing community resilience to natural disasters should be priorities for North American disaster management strategies [89,105].

   Oceania, despite having the fewest total disasters (2.83%), has the highest proportion of natural disasters (91.51%). This reflects the region’s unique geographical features, in- cluding numerous islands and coastal areas, which are highly vulnerable to natural events such as cyclones and tsunamis [99,106]. The low incidence of man-made (technological) disasters (8.49%) suggests that existing technological and industrial activities are relatively well-managed, though continued vigilance and regulation are necessary [107,108]. Eu-

   rope’s balanced distribution of natural (64.54%) and man-made (35.46%) disasters reflects its diverse risk profile, influenced by both environmental factors and high levels of in- dustrialization. The region’s experience with extreme temperatures and floods highlights the importance of adapting to climate change impacts while maintaining stringent safety standards for technological and industrial operations [93]. South America’s disaster profile, with 66.56% natural disasters and 33.44% man-made (technological) disasters, highlights the continent’s exposure to natural hazards such as floods and storms, alongside challenges related to industrial safety and urban infrastructure. The findings suggest a dual focus on environmental sustainability and industrial risk management to mitigate disaster impacts in the region [109,110].

   The temporal analysis, across continents, reveals an increasing trend in disaster occur- rences until the 2000s, followed by a decline in the most recent decade. This pattern may be attributed to advancements in disaster risk management practices, improved early warning systems, and greater global awareness of disaster risks [111]. However, the continuing high frequency of certain disaster types, such as floods and technological accidents, indicates the need for sustained efforts in these areas [112].

   The examination of disaster distribution—both natural and man-made (technological)— across countries from 1900 to 2024 offers critical insights into the varying disaster profiles and vulnerabilities faced by different nations. This understanding is essential for developing disaster risk reduction strategies tailored to the specific needs and challenges of each coun- try [113,114]. Countries such as China and India are at the top of the list for disaster-prone nations, a reflection of their vast geographic areas, large populations, and rapid industrial growth [115]. The significant occurrence of both natural and man-made (technological) disasters in these countries highlights the critical need to integrate disaster risk reduction into national development plans [116]. Additionally, this issue extends beyond national borders, presenting a global international challenge and responsibility [117]. Disasters do not stop at national borders, making this a substantial political, economic, and diplomatic challenge [108,118].

   Natural disasters are particularly prevalent in countries like the USA, the Philippines, and Japan due to their geographical and climatic conditions [119]. The USA’s high fre- quency of natural disasters, dominated by events such as storms and wildfires, reflects the country’s exposure to extreme weather patterns and varied topography [120]. Similarly, the Philippines and Japan, located in seismically active regions and frequently hit by ty- phoons, face significant natural disaster risks [121]. These findings emphasize the need for robust early warning systems, resilient infrastructure, and effective emergency response mechanisms [88].

   Countries with a high proportion of man-made (technological) disasters, such as Nigeria and Egypt, often face these events due to factors like industrialization, inade- quate regulatory frameworks, and socio-economic challenges [122]. The high incidence of industrial accidents and chemical spills in these regions highlights the urgent need to improve industrial safety standards and enhance regulatory oversight [122], as well as to assess safety culture—the way things are actually carried out—e.g., by using maturity models [123]. Additionally, the socio-economic context, including political instability and lack of infrastructure, exacerbates the risk and impact of technological disasters [124].

   The varied disaster profiles across different countries indicate the necessity for region- specific disaster management strategies [91]. For instance, countries with a high frequency of natural disasters should focus on enhancing climate resilience and investing in disaster- resilient infrastructure. In contrast, nations with a significant number of technological disasters should prioritize industrial safety measures, regulatory reforms, and capacity building in emergency response [125].

   The temporal analysis shows an increasing trend in disaster occurrences until the early 2000s, followed by a decline, suggesting improvements in global disaster management practices [126]. However, the continuing high frequency of certain disaster types, such

   as floods and industrial accidents, indicates that ongoing efforts are necessary to address these persistent risks [127].

   The temporal analysis of natural and man-made (technological) disasters over 10-year intervals from 1900 to 2024 reveals significant trends and shifts in the frequency and distribution of disasters, providing valuable insights into how these patterns have evolved over time. During the early 20th century (1900–1940), disaster events were relatively scarce, with a stable yet gradually increasing trend. From 1900 to 1910, the rate of disaster occurrences remained stable, predominantly driven by natural disasters. However, the period from 1910 to 1920 saw a noticeable increase in total disaster events, marking the onset of an upward trend. This trend persisted through the 1920s and 1930s, with both natural and man-made (technological) disasters contributing to the rise. Technological advancements and increased industrial activities during these decades likely played a role in the rise of man-made (technological) disasters [128].

   Rapid urbanization and population growth, especially in the latter half of the 20th century, have increased the exposure and vulnerability of populations to disasters [129]. Urban areas, with dense populations and critical infrastructure, often face higher risks, leading to the observed peaks in disaster events during these periods [130]. The improve- ment in early warning systems and communication technologies has likely contributed to the decrease in disaster events post 2005, enabling better preparedness, timely evacuations, and effective disaster response, thus reducing the overall impact and frequency of disas- ters [131]. The changing communication strategies for warnings (e.g., impact warnings) also attempt to achieve more adequate prevention measures by their target group [132]. In the meantime, great efforts are being made to make warnings comprehensible and to formulate vulnerabilities and recommendations for action [133–136].

   The mid-20th century (1940–1970) experienced a significant surge in disaster events. The decade from 1940 to 1950 witnessed a substantial rise in both natural and man-made (technological) disasters. This increase is attributed to the rapid industrialization and ur- banization that characterized the post-World War II era. The growth of industrial activities and technological development led to higher incidences of industrial accidents and other man-made (technological) disasters [137,138]. However, they also lead to new risks and the need to redefine socially accepted risk [139]. Additionally, the rise in natural disasters could be linked to environmental changes and improved reporting and documentation of such events [140]. The influence of climate change is evident in the increasing frequency and severity of natural disasters such as floods, storms, and extreme temperatures in the late 20th and early 21st centuries [140]. Climate change adaptation and mitigation strategies are crucial to addressing these challenges and reducing future disaster risks [141]. Additionally, different regions experience varying types of disasters, influenced by geographical, climatic, and socio-economic factors [92]. This highlights the importance of localized DRR strate- gies tailored to specific regional needs and vulnerabilities rather than a one-size-fits-all approach [142,143].

   The late 20th century (1970–2000) marked the highest increases in disaster events, particularly in the 1980s and 1990s. This period saw a peak in both natural and man-made (technological) disasters, indicating heightened vulnerability and exposure to various haz- ards. The 1980s, in particular, witnessed a dramatic rise in disaster occurrences, reflecting the impact of global environmental changes, increased population density, and further industrialization. The 1990s continued this trend, with significant contributions from both natural events like floods and technological incidents such as industrial explosions. The early 21st century (2000–2020) continued the trend of increasing disaster events, although the rate of increase began to slow down by the 2010s. This period saw a higher proportion of man-made (technological) disasters, reflecting ongoing industrial growth and technological advancements [143].

   However, the most recent decade (2020–2030) shows a decreasing trend in the number of disaster events, with a significant reduction in both natural and man-made (technological) disasters. This decline may be attributed to improved disaster management practices,

   advancements in early warning systems, and increased global awareness of disaster risks. The trend of decreasing disaster events in recent years underscores the importance of building community resilience and capacity [144]. Community-based DRR initiatives, education, and training programs have empowered local populations to better prepare for and respond to disasters [145]. Enhanced data collection, reporting mechanisms, and increased transparency in documenting disaster events have contributed to a more accurate and comprehensive understanding of disaster trends [146]. This improved data availability facilitates better analysis, planning, and decision-making [147].

   The analysis of the consequences of natural and man-made (technological) disasters over 5-year intervals from 1900 to 2024 provides significant insights into how the impacts of these events on human lives and economies have evolved. Throughout the 20th century and into the 21st century, natural disasters have consistently caused substantial fatalities [148], with significant fluctuations in the number of deaths over different periods. Economic losses due to natural disasters have also increased markedly over the decades, reflecting the growing complexity and interconnectedness of modern societies [149]. The increased urbanization and industrialization in the mid-20th century contributed to higher economic losses as infrastructure and economic activities expanded [150].

   Disaster occurrences from 1900 to 2024 have shown fluctuations that can be traced back to significant historical events [151], technological advancements [128,152,153], and socio-political changes [35,154]. For instance, the surge in disaster events during the 1911–1920 period likely stemmed from the global upheaval caused by World War I and the Spanish flu pandemic [155], which disrupted both industrial activity and societal stability. Likewise, the notable rise in disasters between 1931 and 1940 can be linked to the economic struggles of the Great Depression [156], which curtailed government spending on infrastructure and disaster preparedness, coupled with the escalation of industrial and military activities in the lead-up to World War II. The 1961–1970 period experienced an increase in disasters, driven by rapid industrialization, urbanization, and environmental changes associated with the Green Revolution, as well as the Cold War’s nuclear arms race [157]. The significant uptick in disasters during the 1981–1990 decade is connected to the global expansion of industrial activities, often in the absence of adequate environmental regulations [158], with the Chernobyl nuclear disaster [151] serving as a stark example of technological failure. Moving forward, the slight increase in disaster events from 2001 to 2010 coincided with rising global awareness of climate change [159] and improvements in disaster monitoring and reporting technologies, likely resulting in more comprehensive disaster records. Finally, the observed decrease in disaster events during the 2011–2020 period may be a reflection of global disaster risk reduction efforts, such as the Sendai Framework [160], along with advances in early warning systems and emergency response capabilities [36,88–90], although this decline may not be uniform across all regions or types of disasters. Also, as mentioned, this limited timeframe may not adequately reflect longer-term trends and could be subject to short-term fluctuations in disaster occurrences

   Man-made disasters, while initially causing fewer fatalities and economic losses, began to have a more pronounced impact as industrialization and technological advancements progressed [153]. The mid-20th century marked a period where the consequences of indus- trial accidents and technological failures became more evident, contributing to a notable increase in fatalities and injuries [161]. This trend continued into the late 20th century, with significant economic impacts arising from these disasters. The late 20th and early 21st centuries saw dramatic increases in economic losses from both natural and man-made (tech- nological) disasters. This period reflects the dual influence of technological advancements and environmental changes [152]. On one hand, industrial growth and technological devel- opment introduced new risks and vulnerabilities, leading to severe industrial accidents and technological failures [162]. On the other hand, climate change and environmental degradation have exacerbated the frequency and intensity of natural disasters, resulting in higher economic losses and a greater number of affected individuals [163].

   In recent years, there has been a noticeable reduction in fatalities from natural disasters, which can be attributed to improved disaster management practices [148], early warning systems [90], and global initiatives aimed at reducing disaster risk [164]. Despite this progress, economic losses remain substantial, underscoring the ongoing vulnerability of modern societies to both natural and man-made (technological) disasters [165]. Several key factors have influenced these temporal trends: the growth of industries and urban areas has increased the potential for industrial accidents and technological failures, contributing to the rising impact of man-made (technological) disasters [154]; the increasing frequency and severity of climate-related disasters, such as floods, droughts, and extreme temperatures, reflect the broader impacts of climate change [166]; while technological growth has brought numerous benefits, it has also introduced new risks, leading to significant industrial accidents and chemical spills [167].

   The increase in recorded disaster impacts from the 1960s onwards can be partly attributed to better reporting mechanisms and increased global awareness of disaster risks [168–170]. The decline in fatalities from natural disasters in recent years highlights the effectiveness of global policies and disaster risk reduction frameworks, which have enhanced preparedness and resilience [171,172]. Given the findings from our study, it is clear that future urban development needs to emphasize the integration of cutting-edge sustainable planning tech- niques along with robust infrastructure systems [173]. This is essential to reduce the risks and lessen the impacts of both natural and man-made disasters. The increasing likelihood of multi-disaster events, such as epidemics, underscores the urgent need for cities to not only adopt disaster-resilient strategies but also to revisit and potentially revise urban design regu- lations [174]. By applying strategies specifically designed to tackle the complex interactions between the socio-economic, demographic, and environmental factors we have identified, cities can build lasting resilience and adaptability to the growing frequency and intensity of disasters [1,16,49,71,111]. These efforts should be in line with global disaster risk reduction initiatives and backed by forward-thinking policies that encourage risk-aware development at both local and regional levels [81,114,116,142,170].

   On the other hand, managing land use effectively is essential for analyzing disaster risks, particularly in light of urban growth and evolving environmental conditions [175]. Recent research [176,177], which employs advanced data analytics and machine learning to track changes in land cover, provides valuable insights into how these shifts can affect disaster risks. These technologies allow for more accurate forecasting of land cover dy- namics and their potential impact on both natural and man-made disasters [178,179]. By integrating such cutting-edge approaches, urban planners can take a proactive stance on land use management, reducing disaster risks [180].

   This study acknowledges several limitations that may impact the generalizability and accuracy of its findings: (a) while the EM-DAT database is extensive, it may contain inconsistencies or gaps, particularly for earlier periods or less documented regions, which could affect the accuracy of historical trends; (b) certain regions, especially those with less robust disaster reporting systems, may have underreported disaster occurrences and impacts, potentially introducing biases in the analysis; (c) the broad time span of the analysis, from 1900 to 2024, encompasses changes in data collection methods, reporting standards, and technological advancements, which may result in inconsistencies within the dataset; (d) categorizing disasters as either natural or man-made might oversimplify the complex interactions and overlapping nature of some events, such as those exacerbated by human activities like climate change (e.g., the influence of natural hazards/disasters on the occurrence of man-made (technological) disasters); (e) estimating economic losses from disasters involves considerable uncertainties due to varying methodologies, inflation adjustments, and the inherent difficulties in capturing indirect and long-term economic effects; (f) measuring the human impact, in terms of fatalities and injuries, is challenging due to differences in reporting standards, cultural perceptions, and the availability of reliable health and demographic data; (g) the rarity of certain events, which might occur only once every 100 or 500 years, presents significant challenges for trend analysis; due to

   their infrequent nature, it becomes difficult to identify clear patterns or trends within the study period. Therefore, it is essential to interpret the results with caution when considering these rare but impactful occurrences.

6. ‌Recommendations

   To effectively tackle the various challenges and impacts identified in this study, the following table, Table 13, presents a comprehensive set of recommendations aimed at enhancing disaster risk reduction (DRR) strategies. These measures are categorized by their implementation level—national or local—and their short-term and long-term applicability. This structured approach ensures that both immediate and sustainable actions are taken to mitigate the risks and impacts of natural and man-made (technological) disasters.

   ‌Table 13. Comprehensive recommendations for disaster risk reduction measures and implementa- tion strategies.

    

    

   Recommendation Description Short-Term Long-Term National Local

    

   Integration of disaster risk reduction

   Enhancement of early warning systems

    

   Promotion of climate resilience

    

   Strengthening industrial safety

    

    

   Community-based disaster risk management

   Investing in research and development

    

   Regional cooperation and information sharing

    

   Adapting infrastructure and urban planning

    

   Public awareness and education campaigns

    

    

   Regular assessment and update of plans

   Improvement of seismic resilience

    

    

   Flood management and mitigation

   Sustainable agriculture practices

   Integrate strategies for disaster risk reduction into the overall national development agenda

   Enhance early warning systems through investments in advanced technology, infrastructure improvements, and comprehensive training programs

   Focus on climate resilience by adopting sustainable practices and implementing green infrastructure projects

   Upgrade safety protocols and strengthen regulatory frameworks governing industrial operations

   Empower communities by providing education, training, and opportunities for active involvement in disaster management

   Promote research and development to discover innovative solutions for reducing disaster risks on the basis of a better understanding of the interconnections of risks

   Foster international cooperation and improve data sharing mechanisms for more effective disaster preparedness and response

   Construct resilient infrastructure and apply sustainable urban planning methods to reduce disaster impacts

   Raise public awareness and improve education about disaster risks and preparedness measures

   Periodically review and revise disaster management plans based on updated data and emerging threats

   Emphasize the construction and retrofitting of buildings to be earthquake-resistant, particularly in vulnerable areas

   Implement effective flood control systems, including dams, levees, and enhanced drainage networks

   Encourage agricultural practices and other methods that reduce vulnerability to droughts and

   climate-related disasters

   • ↑ ↑ ↓

   • ✓ ↑ ↑

     • ↑ ↓

   • ✓ ↑ ↓

   • ✓ ↓ ↑

     • ↑ ↓

   • ✓ ↑ ↓

     • ↑ ↓

   • ✓ ↑ ↑

   • ✓ ↑ ↑

     • ↑ ↓

   • ✓ ↑ ↓

     • ↑ ↓

        

       Recommendation Description Short-Term	Long-Term	National	Local
       Enhancing health Enhance health infrastructure to provide better systems responses to epidemics and other public ✓	✓	↑	↓
       Technological upgrades Invest in cutting-edge technologies for real-time ✓	✓	↑	↑
       Capacity building for Continuously train and equip emergency emergency responders responders to increase their efficiency and ✓	✓	↑	↑
       Improving urban Design urban infrastructure to be resilient against infrastructure both natural and man-made (technological) disasters	✓	↑	↓
       Implementing Conduct comprehensive risk assessments to identify	✓	↑	↓

        

       Table 13. Cont.

       health crises

       for disaster monitoring disaster monitoring and early detection capabilities

       effectiveness during crises

       comprehensive risk assessments

        

       Developing

       vulnerabilities and prioritize mitigation strategies ✓

       Coordinate disaster risk reduction activities across

       cross-sectoral and cross-national DRR strategies

        

        

       Strengthening legal and institutional frameworks

       Fostering public–private partnerships

        

       Grouping disaster mitigation measures

        

        

       Enhancing community resilience programs

       Improving data collection and analysis

        

       Increasing funding for DRR initiatives

       various sectors, such as healthcare, agriculture, and transportation

       Strengthen legal and institutional frameworks to support robust disaster risk management practices

       Promote public–private partnerships to leverage resources and expertise in disaster risk reduction initiatives

       Tailor disaster mitigation measures to specific types of disasters, including floods, earthquakes,

       and industrial accidents

       Develop educational and training programs to enhance community resilience and

       disaster preparedness

       Improve data collection and analysis to gain a deeper understanding of disaster trends and inform policy decisions. Improve standardized data collection and analysis

       Secure consistent funding for disaster risk reduction programs to ensure their long-term success

       and sustainability

   • ✓ ↑ ↓

   • ✓ ↑ ↓

   • ✓ ↑ ↑

   • ✓ ↑ ↓

   • ✓ ↑ ↑

   • ✓ ↑ ↓

   • ✓ ↑ ↑

    

   Note: an upward arrow (↑) indicates a focus on national-level implementation; a downward arrow (↓) indicates a focus on local-level implementation; a checkmark (✓) indicates immediate action or short-term implementation.

   Also, this table provides a detailed overview of the recommended measures, stressing the importance of integrating these strategies into national development plans, enhancing early warning systems, promoting climate resilience, and strengthening industrial safety. Furthermore, it underscores the significance of community-based disaster management, investment in research and development, and fostering public–private partnerships to build a more resilient society.

7. ‌Conclusions

The analysis of the geospatial and temporal patterns of natural and man-made (tech- nological) disasters from 1900 to 2024 provides significant insights into these events’ global distribution and impact. This research reveals that Asia is the most affected continent, with the highest number of disasters, indicating the need for robust risk mitigation strategies, particularly concerning seismic resilience and flood management. Africa faces a high percentage of man-made (technological) disasters, emphasizing the need for improved in-

dustrial safety and infrastructure, while natural disasters such as droughts are exacerbated by climate change. North America predominantly records natural disasters, particularly storms and wildfires, highlighting the importance of strengthening early warning systems and community resilience. Oceania, despite having the fewest total disasters, reports a high proportion of natural disasters due to its unique geographical characteristics. Europe shows a balanced distribution of natural and man-made (technological) disasters, under- scoring the importance of adapting to climate change and maintaining high industrial safety standards. South America faces significant natural disasters such as floods and storms, alongside challenges related to industrial safety.

The temporal analysis indicates an increasing trend in disaster occurrences until the 2000s, followed by a decline in the last decade, possibly due to advancements in disaster risk management practices, improved early warning systems, and greater global awareness of disaster risks. Despite progress, the high frequency of certain disaster types, such as floods and technological accidents, indicates the need for continuous efforts in these areas. A detailed analysis of the consequences of natural and man-made (technological) disasters over five-year intervals provides significant insights into the evolution of these events’ impacts on human lives and economies. Natural disasters have consistently caused sub- stantial fatalities and economic losses, while man-made (technological) disasters, initially less significant, have become more pronounced with industrialization and technological development. Recent trends show a reduction in fatalities from natural disasters, attributed to improved disaster management practices, early warning systems, and global initiatives aimed at reducing disaster risk.

Regarding the testing of the hypotheses, the first hypothesis was confirmed, as natural disasters accounted for 69.41% of the total number of disasters, causing greater economic losses and human casualties compared to man-made (technological) disasters. The second hypothesis was supported by significant geographical differences in the frequency and type of disasters, with Asia being the most affected continent and Africa having the highest percentage of man-made (technological) disasters. The third hypothesis was validated through the identification of significant temporal changes in disaster frequency, peaking in the periods 1990–2000 and 2000–2010, while the last decade saw a decline in the total number of events. The fourth hypothesis was proven by seasonal variations, with floods peaking in January and July, and storms being most frequent in June and October. Finally, the fifth hypothesis was confirmed, as different types of disasters had varying impacts on economic losses and human resources, with earthquakes and storms causing the greatest economic losses, while droughts and floods were the most deadly for human lives. These findings underscore the need for tailored disaster risk management strategies in different regions.

The Pearson correlation analysis underscores that socio-economic factors, particularly population density and urbanization rate, play a significant role in influencing the distribu- tion and consequences of disasters, including the number of deaths, injuries, and natural disasters. Higher population density is linked to a greater number of individuals affected, while higher urbanization rates and better governance are associated with a reduction in the overall number of disasters, deaths, and injuries. These insights emphasize the importance of considering socio-economic contexts in disaster risk management, highlighting the need for tailored strategies to enhance community resilience.

This study contributes to the understanding of the global distribution and impact of natural and man-made (technological) disasters through a historical context. It provides a foundation for further research in disaster risk reduction (DRR), particularly in the context of climate change and urbanization. Identifying specific geographical and socio-economic factors contributing to the frequency and severity of disasters can help develop theoretical models and predictive tools for risk management. This study’s results can serve as a reference point for future quantitative and qualitative analyses exploring the effectiveness of various DRR strategies and policies.

The findings have direct implications for policymakers and practitioners in disaster risk management. It is recommended that countries with high natural disaster risks, such

as China, India, and the USA, focus efforts on strengthening infrastructure resilience, improving early warning systems, and enhancing emergency response plans. For regions with high man-made disaster risks, such as Nigeria and Egypt, improving industrial safety, regulatory frameworks, and emergency response capacities is crucial. This study highlights the need for integrated approaches that combine natural and technological risk management. It is recommended to develop comprehensive strategies encompassing prevention, preparedness, response, and recovery, focusing on reducing vulnerabilities and enhancing community resilience to disasters. Additionally, implementing educational programs and raising public awareness about disaster risks can significantly contribute to reducing the negative impacts of these events.

Author Contributions: V.M.C. conceived the original idea for this study and developed the study design. V.M.C. and R.R. contributed to the analysis and interpretation of the data. T.L. made a significant contribution by drafting the introduction. V.M.C., R.R. and B.A. drafted the discussion, and V.M.C., T.L. and R.R. composed the conclusions. V.M.C., T.L., R.R. and B.A. critically reviewed the data analysis and contributed to revising and finalizing the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding: This research was funded by the Scientific–Professional Society for Disaster Risk Manage- ment, Belgrade (https://upravljanje-rizicima.com/, accessed on 20 July 2024), and the International Institute for Disaster Research (https://idr.edu.rs/, accessed on 20 July 2024), Belgrade, Serbia. Tin Lukic´ gratefully acknowledges the support of the Ministry of Science, Technological Development and Innovation of the Republic of Serbia (grants nos. 451-03-66/2024-03/200125 and 451-03-65/2024- 03/200125) and the Provincial Secretariat for Higher Education and Scientific Research of Vojvodina (Serbia), no. 000871816 2024 09418 003 000 000 001 04 002 (GLOMERO), under Program 0201 and

Program Activity 1012.

Institutional Review Board Statement: Not applicable.

Informed Consent Statement: Not applicable.

Data Availability Statement: Data are contained within the article.

Conflicts of Interest: The authors declare no conflicts of interest.

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