In 2023, there was a total of *** natural disasters events recorded worldwide, down from *** recorded a year earlier. The Europe, Middle East and Africa region experienced the highest number of natural disasters that year. Deaths and costs of natural disasters Natural disasters affect almost every part of the world. In February 2023, Turkey and Syria were hit by earthquakes that resulted in the highest number of deaths due to natural disaster events that year. In terms of economic damage, Hurricane Katrina remains one of the most expensive natural disasters in the world, topped only by the earthquake/tsunami which hit Japan in 2011. Climate change and natural disasters Climate change has influenced the prevalence of natural disasters. Global warming can increase the risk of extreme weather, resulting in higher risk of droughts and stronger storms, such as tropical cyclones. For instance, higher levels of water vapor in the atmosphere give storms the power to emerge. Furthermore, the heat in the atmosphere and high ocean surface temperatures lead to increased wind speeds, which characterize tropical storms. Areas that are usually unaffected by the sea are becoming more vulnerable due to rising sea levels as waves and currents become stronger.

In 2024, there were roughly 18,100 reported fatalities caused by natural disaster events worldwide. This was well below the 21st-century average and significantly lower than the fatalities recorded in 2023, which were driven by the earthquakes that hit Turkey and Syria on February and became the deadliest catastrophes in 2023, with nearly ****** reported deaths. Economic losses due to natural disasters The economic losses due to natural disaster events worldwide amounted to about *** billion U.S. dollars in 2024. Although figures in recent years have remained mostly stable, 2011 remains the costliest year to date. Among the different types of natural disaster events, tropical cyclones caused the largest economic losses across the globe in 2024. What does a natural disaster cost? Hurricane Katrina has been one of the costliest disasters in the world, costing the insurance industry some *** billion U.S. dollars. The resilience of societies against catastrophes have been boosted by insurance industry payouts. Nevertheless, insurance payouts are primarily garnered by industrialized countries. In emerging and developing regions, disaster insurance coverage is still limited, despite the need for improved risk management and resilience as a method to mitigate the impact of disasters and to promote sustainable growth.

In 2024, the United States experienced 29 natural disasters, which made it the most natural catastrophe-prone country in the world that year. Indonesia and China came second on that list, with 20 and 18 natural disasters occurring in the same year, respectively. Storms were the most common type of natural disaster in 2024. Types of natural disasters There are many different types of natural disasters that occur worldwide, including earthquakes, droughts, storms, floods, volcanic activity, extreme temperatures, landslides, and wildfires. Overall, there were 398 natural disasters registered all over the world in 2023. Costs of natural disasters Due to their destructive nature, natural disasters take a severe toll on populations and countries. Tropical cyclones have the biggest economic impact in the countries that they occur. In 2024, tropical cyclones caused damage estimated at more than 145 billion U.S. dollars. Meanwhile, the number of deaths due to natural disasters neared 18,100 that year. The Heat Wave in Saudi Arabia had the highest death toll, with 1,301 fatalities. Scientists predict that some natural disasters such as storms, floods, landslides, and wildfires will be more frequent and more intense in the future, creating both human and financial losses.

The Geocoded Disasters (GDIS) Dataset is a geocoded extension of a selection of natural disasters from the Centre for Research on the Epidemiology of Disasters' (CRED) Emergency Events Database (EM-DAT). The data set encompasses 39,953 locations for 9,924 disasters that occurred worldwide in the years 1960 to 2018. All floods, storms (typhoons, monsoons etc.), earthquakes, landslides, droughts, volcanic activity and extreme temperatures that were recorded in EM-DAT during these 58 years and could be geocoded are included in the data set. The highest spatial resolution in the data set corresponds to administrative level 3 (usually district/commune/village) in the Global Administrative Areas database (GADM, 2018). The vast majority of the locations are administrative level 1 (typically state/province/region).

From 1950 to 2024, the cyclone Bhola that hit Bangladesh in 1970 was the deadliest natural disaster in the world. The exact death toll is impossible to calculate, but it is estimated that over 300,000 lives were lost as a result of the cyclone. The Tangshan earthquake in China in 1976 is estimated to have caused the second-highest number of fatalities. The Haiti earthquake The fifth-deadliest natural disaster during this period was the earthquake in Haiti in 2010. However, death tolls vary between 100,000 and 316,000, meaning that some estimates make it the deadliest natural disaster in the world since 1950, and the deadliest earthquake since 1900. Sixty percent of the country’s hospitals and eighty percent of the country’s schools were destroyed. It was the worst earthquake to hit the Caribbean in 200 years, with a magnitude of 7.0 at its epicenter only 25 kilometers away from Haiti’s capital, Port-au-Prince. Poor construction practices were to blame for many of the deaths; Haiti’s buildings were not earthquake resistant and were not built according to building code due to a lack of licensed building professionals. High population density was also to blame for the high number of fatalities. One fourth of the country’s inhabitants lived in the Port-au-Prince area, meaning half of the country’s population was directly affected by the earthquake. Increasing extreme weather As global warming continues to accelerate climate change, it is estimated that natural catastrophes such as cyclones, rainfalls, landslides, and heat waves will intensify in the coming years and decades. For instance, the economic losses caused by natural disasters worldwide increased since 2015. Moreover, it is expected that countries in the Global South will be affected the most by climate change in the coming years, and many of these are already feeling the impact of climate change.

Natural Disasters Deaths

People killed in natural disasters by country by year

About this dataset

How much do natural disasters cost us? In lives, in dollars, in infrastructure? This dataset attempts to answer those questions, tracking the death toll and damage cost of major natural disasters since 1985. Disasters included are storms ( hurricanes, typhoons, and cyclones ), floods, earthquakes, droughts, wildfires, and extreme temperatures

How to use the dataset

This dataset contains information on natural disasters that have occurred around the world from 1900 to 2017. The data includes the date of the disaster, the location, the type of disaster, the number of people killed, and the estimated cost in US dollars

Research Ideas

• An all-in-one disaster map displaying all recorded natural disasters dating back to 1900.
• Natural disaster hotspots - where do natural disasters most commonly occur and kill the most people?
• A live map tracking current natural disasters around the world

Acknowledgements

License

See the dataset description for more information.

This comprehensive dataset provides a detailed overview of the relative risk of natural disasters faced by countries worldwide. It encompasses a comprehensive range of natural hazards, including earthquakes, hurricanes, tsunamis, floods, droughts, wildfires, and volcanic eruptions. The dataset offers a granular analysis of the factors contributing to these risks, such as geographical location, climate patterns, population density, and infrastructure development. By examining these factors, the dataset enables a deeper understanding of the vulnerabilities of different countries to natural disasters and facilitates the development of effective mitigation strategies.

Data published by Our World in Data based on EM-DAT, CRED / UCLouvain, Brussels, Belgium – www.emdat.be (D. Guha-Sapir)

Variable time span 1900 – 2010

This dataset has been calculated and compiled by Our World in Data based on raw disaster data published by EM-DAT, CRED / UCLouvain, Brussels, Belgium – www.emdat.be (D. Guha-Sapir). EM-DAT publishes comprehensive, global data on each individual disaster event – estimating the number of deaths; people affected; and economic damages, from UN reports; government records; expert opinion; and additional sources. Our World in Data has calculated annual aggregates, and decadal averages, for each country based on this raw event-by-event dataset. Decadal figures are measured as the annual average over the subsequent ten-year period. This means figures for ‘1900’ represent the average from 1900 to 1909; ‘1910’ is the average from 1910 to 1919 etc. We have calculated per capita rates using population figures from Gapminder (gapminder.org) and the UN World Population Prospects (https://population.un.org/wpp/). Economic damages data is provided by EM-DAT in concurrent US$. We have calculated this as a share of gross domestic product (GDP) using the World Bank’s GDP figures (also in current US$) (https://data.worldbank.org/indicator). Definitions of specific metrics are as follows: – ‘All disasters’ includes all geophysical, meteorological, and climate events including earthquakes, volcanic activity, landslides, drought, wildfires, storms, and flooding. – People affected are those requiring immediate assistance during an emergency situation. – The total number of people affected is the sum of injured, affected, and homeless.Link www.emdat.be

In 2024, the most common natural disaster type in the world were storms, with 147 events reported that year. Floods were the type of natural disaster with the second-highest occurrence, with 142 events.

Source: The Emergency Events Database (EM-DAT) , Centre for Research on the Epidemiology of Disasters (CRED) / Université catholique de Louvain (UCLouvain), Brussels, Belgium – www.emdat.be.Category: Climate and WeatherData series: Climate related disasters frequency, Number of Disasters: TOTAL  Climate related disasters frequency, Number of Disasters: Drought  Climate related disasters frequency, Number of Disasters: Extreme temperature  Climate related disasters frequency, Number of Disasters: Flood  Climate related disasters frequency, Number of Disasters: Landslide  Climate related disasters frequency, Number of Disasters: Storm  Climate related disasters frequency, Number of Disasters: Wildfire Climate related disasters frequency, People Affected: Drought  Climate related disasters frequency, People Affected: Extreme temperature  Climate related disasters frequency, People Affected: Flood  Climate related disasters frequency, People Affected: Landslide  Climate related disasters frequency, People Affected: Storm  Climate related disasters frequency, People Affected: Wildfire Climate related disasters frequency, People Affected: TOTAL  Disaster IntensityMetadata:EM-DAT: The International Disasters Database - Centre for Research on the Epidemiology of Disasters (CRED), part of the University of Louvain (UCLouvain) www.emdat.be, Brussels, Belgium. Only climate related disasters (Wildfire, Storm, Landslide, Flood, Extreme Temperature, and Drought) are covered. See the CID Glossary for the definitions. EM-DAT records country level human and economic losses for disasters with at least one of the following criteria: i.          Killed ten (10) or more people  ii.         Affected hundred (100) or more people  iii.        Led to declaration of a state of emergency iv.        Led to call for international assistance   The reported total number of deaths “Total Deaths” includes confirmed fatalities directly imputed to the disaster plus missing people whose whereabouts since the disaster are unknown and so they are presumed dead based on official figures. “People Affected” is the total of injured, affected, and homeless people. Injured includes the number of people with physical injuries, trauma, or illness requiring immediate medical assistance due to the disaster. Affected includes the number of people requiring immediate assistance due to the disaster. Homeless includes the number of people requiring shelter due to their house being destroyed or heavily damaged during the disaster. Disaster intensity is calculated by summing “Total Deaths” and 30% of the “People Affected”, and then dividing the result by the total population. For each disaster and its corresponding sources, the population referred to in these statistics and the apportionment between injured, affected, homeless, and the total is checked by CRED staff members. Nonetheless, it is important to note that these are estimates based on certain assumptions, which have their limitations. For details on the criteria and underlying assumptions, please visit https://doc.emdat.be/docs/data-structure-and-content/impact-variables/human/. Methodology:Global climate related disasters are stacked to show the trends in climate related physical risk factors.

Overview

This dataset provides a curated collection of natural events around the world recorded from 2000 to 2025, compiled from the NASA Earth Observatory Natural Event Tracker (EONET). It includes detailed geospatial and temporal information about wildfires, floods, tropical storms, cyclones, and typhoons observed globally.

Each record corresponds to an individual event occurrence, with coordinates, date, and time of observation. This dataset is ideal for climate data visualization, disaster tracking, spatial analysis, and machine learning applications such as event prediction or classification.

Potential Use Cases

• Tack tropical storm trajectories using geospatial time series.
• Map global wildfire activity with geolocation data.
• Analyze flood distribution patterns over time and regions.
• Build interactive dashboards for climate event visualization.
• Train ML models for event classification or prediction. |

For example use case is at this dashboard as well

Overview

The Global Disaster & Emergency Response Dataset (2018–2024) offers a comprehensive synthetic simulation of worldwide natural disasters and corresponding humanitarian responses. It spans 7 years and includes 50,000 unique records across 20 countries, covering multiple disaster types such as earthquakes, floods, wildfires, droughts, hurricanes, and volcanic eruptions.

Each record represents a real-world–like event, containing details on intensity, human impact, economic damage, aid efforts, and recovery efficiency. This dataset was generated using probabilistic modeling and random distributions to ensure realistic variability while maintaining a balanced, clean structure for analysis.

Dataset Highlights

-Years covered: 2018–2024

-Regions: 20 countries across all continents

-Records: 50,000 simulated disaster events

-Attributes: 12 descriptive and numeric variables

-Goal: Support ML, visualization, and risk-prediction research

Columns & Descriptions

Possible Use Cases

This dataset is ideal for:

• Disaster prediction and classification models

• Risk assessment and economic loss estimation

• Geospatial visualization and mapping

• Response time forecasting and optimization

• Humanitarian aid efficiency analysis

• Benchmarking deep learning models on synthetic time-series data

-- Data Generation

All records are synthetically generated using the Faker, NumPy, and random sampling libraries. Country-based parameters were adjusted to reflect realistic differences in disaster frequency, average losses, and aid efficiency.

No real-world confidential data is used; this dataset serves as a clean, consistent, and simulation-ready foundation for experimentation.

A CSV file containing worldwide CO2 emissions as well as the number of natural disasters per year.

Sources:

Global Carbon Atlas

DOI: http://doi.org/10.17616/R3434K

URL: http://www.globalcarbonatlas.org/en/CO2-emissions

Last accessed: 2023-05-09

EM-DAT

DOI: http://doi.org/10.17616/R3QQ1X

URL: https://public.emdat.be/data (registration necessary)

Last accessed: 2023-05-14

GitHub Project

DOI: http://doi.org/10.5281/zenodo.7934702

URL: https://github.com/jkopec/global-emission-and-disaster-analysis

In 2024, the economic losses due to natural disasters worldwide amounted to about *** billion U.S. dollars. Natural disasters occur as a result of natural processes on Earth. Many different types of natural disasters can occur, including floods, hurricanes, earthquakes, and tsunamis. Natural disasters in 2024 Tropical cyclones generated the highest amount of economic losses in 2024 with *** billion U.S. dollars worldwide. Hurricanes Helene and Milton were the most destructive events worldwide that year with over 100 billion U.S. dollars in economic losses. Flooding events ranked second in the costliest events in 2024, with flooding in Valencia, Spain, and South and Central China being the worst examples. Asia hardest hit by natural disasters A highly destructive force, Asia is one of the most susceptible regions to natural disasters. The repercussions of natural disasters are not only physical, but also economic. Costs may be high – depending on the severity – as areas affected by natural disasters might need to be rebuilt. Lower income countries are more likely to be affected by natural disasters for a multitude of reasons, including a lack of developed infrastructure, inadequate housing, and lack of back-resources.

Disaster Management Market Outlook

According to our latest research, the global disaster management market size reached USD 178.4 billion in 2024, driven by escalating natural and man-made disasters worldwide. The sector is demonstrating robust momentum, with a compound annual growth rate (CAGR) of 7.2% anticipated from 2025 through 2033. By the end of this forecast period, the disaster management market is projected to achieve a value of USD 332.9 billion by 2033. The increasing frequency and severity of disasters, coupled with the growing integration of advanced technologies, are key growth catalysts shaping the global landscape of disaster management solutions and services.

The primary growth driver for the disaster management market is the rising incidence of both natural and anthropogenic disasters. Over recent years, climate change has led to more frequent and severe weather events such as hurricanes, floods, wildfires, and earthquakes, necessitating robust disaster management infrastructure. Additionally, urbanization and population growth in high-risk zones have heightened vulnerability, compelling governments and private entities to invest in comprehensive disaster preparedness and response systems. The need for timely and effective emergency response, coupled with increasing public awareness and regulatory mandates, is further propelling market demand for advanced solutions such as geospatial technologies, real-time surveillance systems, and emergency notification platforms.

Another significant factor fueling market expansion is the rapid technological advancement and digitization of disaster management processes. The integration of artificial intelligence, IoT, cloud computing, and big data analytics has revolutionized disaster risk assessment, early warning systems, and post-disaster recovery operations. These innovations enable real-time data collection, predictive analytics, and automated response mechanisms, which significantly enhance the efficiency and accuracy of disaster management efforts. Furthermore, the proliferation of mobile devices and high-speed internet connectivity has made it easier to disseminate critical information to affected populations and coordinate multi-agency responses, contributing to the overall growth of the disaster management market.

The increasing collaboration between public and private sectors has also played a pivotal role in market development. Governments are partnering with technology providers, consulting firms, and non-governmental organizations to build resilient infrastructure and streamline disaster response protocols. International aid and funding from organizations like the United Nations, World Bank, and regional development banks are supporting the deployment of sophisticated disaster management solutions in both developed and emerging economies. This collaborative ecosystem not only accelerates the adoption of cutting-edge technologies but also fosters innovation and knowledge sharing, thereby strengthening the global disaster management framework.

From a regional perspective, North America currently dominates the disaster management market due to its advanced technological infrastructure, stringent regulatory frameworks, and high disaster risk profile. However, Asia Pacific is expected to witness the fastest growth during the forecast period, driven by increasing investments in disaster preparedness, rising urbanization, and frequent natural calamities in countries such as China, India, Japan, and Indonesia. Europe, Latin America, and the Middle East & Africa are also experiencing steady market growth, supported by government initiatives, cross-border collaborations, and the growing adoption of digital disaster management solutions. The regional dynamics are shaped by unique risk profiles, economic capabilities, and policy environments, which collectively influence market opportunities and challenges across the globe.

Solution Analysis

The disaster management market is segmented by solution into su

The earthquake and subsequent tsunami in Japan in 2011 was the costliest natural disaster since 1900, with losses reaching 235 billion U.S. dollars. The tsunami hit the nuclear plant at Fukushima, causing a nuclear disaster in the area. Hurricane Katrina, which hit the Gulf Coast of the United States in 2005, and Hurricane Harvey, which hit the North American country in 2017, tied with the second-largest economic losses in the period, each with 125 billion U.S. dollars.

This collection contains six separate datasets of global natural disasters, sourced from the Global Disaster Alert and Coordination System (GDACS). Each dataset focuses on a specific disaster type, allowing researchers and practitioners to explore patterns and impacts both individually and comparatively.

Dataset Files: (Unclean version) - Drought.csv – 1,780 rows - Earthquake.csv – 20,296 rows - Eruption.csv – 186 rows - Flood.csv – 2,441 rows - Forest Fires.csv – 3,055 rows - Tropical Cyclone.csv – 405 rows

Total rows across all datasets: 28,163

Source: All data comes from GDACS, a real-time platform that monitors natural disasters worldwide and provides alerts to governments, humanitarian agencies, and the public.

BackgroundThe contemporary world is challenged by natural disasters accelerated by climate change, affecting a growing world population. Simultaneously, cancer remains a persistent threat as a leading cause of death, killing 10 million people annually. The efficacy of radiotherapy, a cornerstone in cancer treatment worldwide, depends on an uninterrupted course of therapy. However, natural disasters cause significant disruptions to the continuity of radiotherapy services, posing a critical challenge to cancer treatment. This paper explores how natural disasters impact radiotherapy practice, compares them to man-made disasters, and outlines strategies to mitigate adverse effects of natural disasters. Through this analysis, the study seeks to contribute to developing resilient healthcare frameworks capable of sustaining essential cancer treatment amidst the challenges posed by natural disasters.MethodWe conducted a Structured Literature Review to investigate this matter comprehensively, gathering and evaluating relevant academic publications. We explored how natural disasters affected radiotherapy practice and examined the experience of radiotherapy centres worldwide in resuming operations after such events. Subsequently, we validated and extended our research findings through a global online survey involving radiotherapy professionals.ResultsThe Structured Literature Review identified twelve academic publications describing hurricanes, floods, and earthquakes as the primary disruptors of radiotherapy practice. The analysis confirms and complements risk mitigation themes identified in our previous research, which focused on the continuity of radiotherapy practice during the COVID-19 pandemic. Our work describes nine overarching themes, forming the basis for a taxonomy of 36 distinct groups. The subsequent confirmative online survey supported and solidified our findings and served as a basis for developing a conceptual framework for natural disaster-resilient radiotherapy as well as a checklist for practitioners.DiscussionThe growing threat posed by natural disasters underscores the need to develop business continuity programs and define risk mitigation measures to ensure the uninterrupted provision of radiotherapy services. By drawing lessons from past disasters, we can better prepare for future hazards, supporting disaster management and planning efforts, particularly enhancing the resilience of radiotherapy practice. Additionally, our study can serve as a resource for shaping policy initiatives aimed at mitigating the impact of natural hazards.

The impact of global warming, caused by climate change, is significantly affecting the occurrence of heavy flooding worldwide, including in China. The extent of flooding in China is greater than in any other country. Each year, this devastating flooding claims numerous lives, damages countless homes, destroys roads, bridges, and buildings, and affects millions of people, resulting in substantial economic losses. Our research reveals that approximately 66% of China’s landmass is submerged by flooding, affecting about 50% of the population. Furthermore, the financial toll of flooding now accounts for approximately 1.42% of the annual gross domestic product (GDP), which is almost 40 times higher than the corresponding figure for the United States. In recent years, numerous regions in China have been affected by a series of devastating floods that have caused significant damage. This includes central northern Henan province and various areas in southern China. Our study specifically concentrated on these regions due to their high susceptibility to flooding. Our study indicates that floods in China exhibit a wide range of variations in terms of their extent, ranging from localized incidents in specific areas to more extensive regional or basin-wide occurrences. We have observed that Zhengzhou city in Henan province, which faced a devastating flood in 2021, received a significant amount of rainfall, specifically a total of 552.5 mm within a 24-hour period. In a similar manner, the significant flooding that occurred in southern China in 2020 impacted approximately 7.1 million individuals across eight provinces and resulted in 54 fatalities, the collapse of 6,700 houses, and incurred a direct economic loss of US$3.33 billion. In this paper, we have stridden to analyze the causes and impacts of flooding in China’s flood-prone regions and pointed out some mitigation strategies to reduce the repercussions of distressing flood events.