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 60,000 reported deaths. Economic losses due to natural disasters The economic losses due to natural disaster events worldwide amounted to about 368 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 102 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.

From 1950 to 2023, 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 makes 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.

Due to its geography and various climates, China is exposed to an array of natural disasters, including earthquakes, floods, forest fires, and typhoons. In 2024, around 856 people lost their lives due to natural disasters in China. In recent decades, China has experienced some of the most devastating natural calamities worldwide. The Sichuan earthquake in 2008 led to about 84 thousand deaths and a direct economic loss of more than 800 billion yuan. Geological disasters in China Geological disasters refer to hazards caused by movements and deformation of the earth's crust, such as such as earthquakes, tsunami, and landslides. The occurrence and frequency of geological disasters in China varies by location and time. The southwest mountainous land area and plateau region experienced a higher number of geological disasters compared to other regions. In 2013, the economic impact of geological disasters in China reached an unprecedented 10.88 billion yuan in direct damage due to severe droughts and earthquakes Government emergency management About one-third of Chinese believed that a major disaster could happen in their hometown. Therefore, the Chinese government shifted towards a proactive disaster risk management system. The Chinese government is leveraging new technologies, such as drones, to strengthen the early-warning systems and emergency response scheme.

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.

Analysis of ‘Natural Disasters Data Explorer’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/mathurinache/natural-disasters-data-explorer on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context

Disasters include all geophysical, meteorological and climate events including earthquakes, volcanic activity, landslides, drought, wildfires, storms, and flooding. Decadal figures are measured as the annual average over the subsequent ten-year period.

Content

Thanks to Our World in Data, you can explore death from natural disasters by country and by date.

Acknowledgements

https://www.acacamps.org/sites/default/files/resource_library_images/naturaldisaster4.jpg" alt="Natural Disasters">

Inspiration

List of variables for inspiration: Number of deaths from drought Number of people injured from drought Number of people affected from drought Number of people left homeless from drought Number of total people affected by drought Reconstruction costs from drought Insured damages against drought Total economic damages from drought Death rates from drought Injury rates from drought Number of people affected by drought per 100,000 Homelessness rate from drought Total number of people affected by drought per 100,000 Number of deaths from earthquakes Number of people injured from earthquakes Number of people affected by earthquakes Number of people left homeless from earthquakes Number of total people affected by earthquakes Reconstruction costs from earthquakes Insured damages against earthquakes Total economic damages from earthquakes Death rates from earthquakes Injury rates from earthquakes Number of people affected by earthquakes per 100,000 Homelessness rate from earthquakes Total number of people affected by earthquakes per 100,000 Number of deaths from disasters Number of people injured from disasters Number of people affected by disasters Number of people left homeless from disasters Number of total people affected by disasters Reconstruction costs from disasters Insured damages against disasters Total economic damages from disasters Death rates from disasters Injury rates from disasters Number of people affected by disasters per 100,000 Homelessness rate from disasters Total number of people affected by disasters per 100,000 Number of deaths from volcanic activity Number of people injured from volcanic activity Number of people affected by volcanic activity Number of people left homeless from volcanic activity Number of total people affected by volcanic activity Reconstruction costs from volcanic activity Insured damages against volcanic activity Total economic damages from volcanic activity Death rates from volcanic activity Injury rates from volcanic activity Number of people affected by volcanic activity per 100,000 Homelessness rate from volcanic activity Total number of people affected by volcanic activity per 100,000 Number of deaths from floods Number of people injured from floods Number of people affected by floods Number of people left homeless from floods Number of total people affected by floods Reconstruction costs from floods Insured damages against floods Total economic damages from floods Death rates from floods Injury rates from floods Number of people affected by floods per 100,000 Homelessness rate from floods Total number of people affected by floods per 100,000 Number of deaths from mass movements Number of people injured from mass movements Number of people affected by mass movements Number of people left homeless from mass movements Number of total people affected by mass movements Reconstruction costs from mass movements Insured damages against mass movements Total economic damages from mass movements Death rates from mass movements Injury rates from mass movements Number of people affected by mass movements per 100,000 Homelessness rate from mass movements Total number of people affected by mass movements per 100,000 Number of deaths from storms Number of people injured from storms Number of people affected by storms Number of people left homeless from storms Number of total people affected by storms Reconstruction costs from storms Insured damages against storms Total economic damages from storms Death rates from storms Injury rates from storms Number of people affected by storms per 100,000 Homelessness rate from storms Total number of people affected by storms per 100,000 Number of deaths from landslides Number of people injured from landslides Number of people affected by landslides Number of people left homeless from landslides Number of total people affected by landslides Reconstruction costs from landslides Insured damages against landslides Total economic damages from landslides Death rates from landslides Injury rates from landslides Number of people affected by landslides per 100,000 Homelessness rate from landslides Total number of people affected by landslides per 100,000 Number of deaths from fog Number of people injured from fog Number of people affected by fog Number of people left homeless from fog Number of total people affected by fog Reconstruction costs from fog Insured damages against fog Total economic damages from fog Death rates from fog Injury rates from fog Number of people affected by fog per 100,000 Homelessness rate from fog Total number of people affected by fog per 100,000 Number of deaths from wildfires Number of people injured from wildfires Number of people affected by wildfires Number of people left homeless from wildfires Number of total people affected by wildfires Reconstruction costs from wildfires Insured damages against wildfires Total economic damages from wildfires Death rates from wildfires Injury rates from wildfires Number of people affected by wildfires per 100,000 Homelessness rate from wildfires Total number of people affected by wildfires per 100,000 Number of deaths from extreme temperatures Number of people injured from extreme temperatures Number of people affected by extreme temperatures Number of people left homeless from extreme temperatures Number of total people affected by extreme temperatures Reconstruction costs from extreme temperatures Insured damages against extreme temperatures Total economic damages from extreme temperatures Death rates from extreme temperatures Injury rates from extreme temperatures Number of people affected by extreme temperatures per 100,000 Homelessness rate from extreme temperatures Total number of people affected by extreme temperatures per 100,000 Number of deaths from glacial lake outbursts Number of people injured from glacial lake outbursts Number of people affected by glacial lake outbursts Number of people left homeless from glacial lake outbursts Number of total people affected by glacial lake outbursts Reconstruction costs from glacial lake outbursts Insured damages against glacial lake outbursts Total economic damages from glacial lake outbursts Death rates from glacial lake outbursts Injury rates from glacial lake outbursts Number of people affected by glacial lake outbursts per 100,000 Homelessness rate from glacial lake outbursts Total number of people affected by glacial lake outbursts per 100,000 Total economic damages from disasters as a share of GDP Total economic damages from drought as a share of GDP Total economic damages from earthquakes as a share of GDP Total economic damages from extreme temperatures as a share of GDP Total economic damages from floods as a share of GDP Total economic damages from landslides as a share of GDP Total economic damages from mass movements as a share of GDP Total economic damages from storms as a share of GDP Total economic damages from volcanic activity as a share of GDP Total economic damages from volcanic activity as a share of GDP Entity Year deaths_rate_per_100k_storm injured_rate_per_100k_storm total_affected_rate_per_100k_all_disasters

--- Original source retains full ownership of the source dataset ---

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.

In 2023, severe convective storms caused the most expensive damage in the United States. Severe convective storms, for instance, caused overall losses of ** billion U.S. dollars. Meanwhile, wildfire, drought, and heatwaves, resulted in economic losses of ** billion U.S. dollars. Tropical cyclone damage amounted to under **** billion U.S. dollars in 2023, a significant dropdown from a previous high in 2022. Impact of severe thunderstorms in the U.S. Severe thunderstorms pose a great risk to public safety and often result in fatalities. People can be harmed in many ways during a thunderstorm, such as directly struck by lightning or hurt when a building collapses/tree falls down. In 2019, ** people were killed as a result of severe thunderstorms. Lightning strikes alone caused ** deaths and *** injuries in that year. How much was paid out due to thunderstorms? The high risk of damage posed by thunderstorms means that insurance cover is an important tool in reducing the losses incurred. In 2020 alone, approximately ****** homeowner insurance claims were paid due to lightning losses.

A drought in South Africa in 1990 incurred an economic loss of about 1.96 billion U.S. dollars. Storm Idai, in Mozambique in 2019, also had an economic impact of 1.96 billion U.S. dollars. These two events resulted in the largest economic losses from climate disasters recorded in Africa between 1970 and 2019.

Drought risk in Africa

Droughts have caused an enormous number of human losses. The deadliest natural events in Africa are droughts and caused thousands of fatalities, especially in the 1970s and 1980s in the Horn of Africa and Eastern Africa. Many countries with the highest risk of droughts are in Africa. In 2020, Somalia was the most endangered country in the world. Among the ten countries most at risk of droughts, eight were African.

Economic impact of droughts

Between 1970 and 2019, droughts have impacted heavily the economies of various African countries, including Zimbabwe, Ethiopia, Namibia, and South Africa. During the last decades, droughts cost Zimbabwe 0.14 percent of the country's GDP. Five of the 10 most expensive weather, climate, and water -related disasters in Africa over the last decades were droughts.

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.

This metadata considers the data on total and insured economic losses and the number of fatalities from weather- and climate-related events in EU Member States and EEA member countries since 1980. Weather- and climate-related hazards considered are those types classified as meteorological hazards (e.g. storms), hydrological hazards (e.g. floods) and climatological hazards (e.g. heatwaves) based on the classification by the International Council for Science (ICSU). The geophysical hazards (e.g. earthquakes and volcanoes) are included for comparison purposes. An event can occur in several countries, but the information is split per country.

The data is based on the RiskLayer CATDAT and the MunichRe NatCatSERVICE datasets (both received under institutional agreement), and on the Eurostat collection of economic indicators, whereas data from earlier years not covered by Eurostat have been completed using data from the Annual Macro-Economic Database of the European Commission (AMECO), the International Monetary Fund’s (IMF) World Economic Outlook (WEO), the Total Economy Database (TED) and the World Bank database. The average population of a country over the period of the time series is used.

The data contains details related to EEA’s indicator “Economic losses from climate-related events in Europe” (https://www.eea.europa.eu/ims/economic-losses-from-climate-related), updated annually. Additional detail on the data and the indicator can be found in the EEA briefing "Economic losses and fatalities from weather- and climate-related events in Europe", 2022 (https://www.eea.europa.eu/publications/economic-losses-and-fatalities-from/economic-losses-and-fatalities-from).

"Disaster data for countries along the belt and road, mainly from the global disaster database.The records information of disaster database are from the United Nations, government and non-governmental organizations, research institutions and the media. It's documented in detail such as the country where the disaster occurred, the type of disaster, the date of the disaster, the number of deaths and the estimated economic losses. This study extracts the natural disaster records of the countries along the One Belt And One Road line one by one from the database, and finally forms the disaster database of 9 major disasters of the 65 countries. The natural disaster records collected can be roughly divided into nine categories, including: floods, landslides, extreme temperatures, storms, droughts, forest fires, earthquakes, mass movements and volcanic activities. From 1900 to 2018, a total of 5,479 disaster records were recorded in countries along the One Belt And One Road. From 2000 to 2015, there were 2,673 disaster records. On this basis, the natural disasters of the countries along the belt and road are investigated from four aspects, including disaster frequency, death toll, disaster-affected population and economic loss assessment. Overall, since 1900, a total of 5479 natural disasters have occurred in countries along the One Belt And One Road, resulting in about 19 million deaths and economic losses of about 950 billion us dollars. Among them, the most frequent occurrence is flood and storm; the biggest economic losses are floods and earthquakes; the most affected people are flood and drought; drought and flooding are the leading causes of death

Weather DescriptionThis feature service depicts the National Weather Service (NWS) watches, warnings, and advisories within the United States. Watches and warnings are classified into 43 categories.A warning is issued when a hazardous weather or hydrologic event is occurring, imminent or likely. A warning means weather conditions pose a threat to life or property. People in the path of the storm need to take protective action.A watch is used when the risk of a hazardous weather or hydrologic event has increased significantly, but its occurrence, location or timing is still uncertain. It is intended to provide enough lead time so those who need to set their plans in motion can do so. A watch means that hazardous weather is possible. People should have a plan of action in case a storm threatens, and they should listen for later information and possible warnings especially when planning travel or outdoor activities.An advisory is issued when a hazardous weather or hydrologic event is occurring, imminent or likely. Advisories are for less serious conditions than warnings, that cause significant inconvenience and if caution is not exercised, could lead to situations that may threaten life or property.SourceNational Weather Service RSS-CAP Warnings and Advisories: Public AlertsNational Weather Service Boundary Overlays: AWIPS Shapefile DatabaseUpdate FrequencyThe services is updated every 5 minutes using the Aggregated Live Feeds methodology.The overlay data is checked and updated daily from the official AWIPS Shapefile Database.Area CoveredUnited States and TerritoriesWhat can you do with this layer?Customize the display of each attribute by using the Change Style option for any layer.Query the layer to display only specific types of weather watches and warnings.Add to a map with other weather data layers to provide insight on hazardous weather events.Use ArcGIS Online analysis tools, such as Enrich Data, to determine the potential impact of weather events on populations.This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency.LayersUSA Weather Watches and Warnings - Public Forecast ZonesUSA Weather Watches and Warnings - Fire Forecast ZonesUSA Weather Watches and Warnings - US CountiesUSA Weather Watches and Warnings - US States and TerritoriesUSA Weather Watches and Warnings - Coastal and Offshore Marine ZonesUSA Weather Watches and Warnings - Events Ordered by Size and SeverityUSA Weather Watches and Warnings - Extreme EventsUSA Weather Watches and Warnings - Severe EventsUSA Weather Watches and Warnings - Moderate EventsUSA Weather Watches and Warnings - Minor EventsUSA Weather Watches and Warnings - Other EventsWSM (Night w/yellow boundaries)World HillshadeWorld Street Map Canvas (Night w/yellow boundaries)Flood DescriptionThis feature service depicts the National Weather Service (NWS) watches, warnings, and advisories within the United States. Watches and warnings are classified into 43 categories.A warning is issued when a hazardous weather or hydrologic event is occurring, imminent or likely. A warning means weather conditions pose a threat to life or property. People in the path of the storm need to take protective action.A watch is used when the risk of a hazardous weather or hydrologic event has increased significantly, but its occurrence, location or timing is still uncertain. It is intended to provide enough lead time so those who need to set their plans in motion can do so. A watch means that hazardous weather is possible. People should have a plan of action in case a storm threatens, and they should listen for later information and possible warnings especially when planning travel or outdoor activities.An advisory is issued when a hazardous weather or hydrologic event is occurring, imminent or likely. Advisories are for less serious conditions than warnings, that cause significant inconvenience and if caution is not exercised, could lead to situations that may threaten life or property.SourceNational Weather Service RSS-CAP Warnings and Advisories: Public AlertsNational Weather Service Boundary Overlays: AWIPS Shapefile DatabaseUpdate FrequencyThe services is updated every 5 minutes using the Aggregated Live Feeds methodology.The overlay data is checked and updated daily from the official AWIPS Shapefile Database.Area CoveredUnited States and TerritoriesWhat can you do with this layer?Customize the display of each attribute by using the Change Style option for any layer.Query the layer to display only specific types of weather watches and warnings.Add to a map with other weather data layers to provide insight on hazardous weather events.Use ArcGIS Online analysis tools, such as Enrich Data, to determine the potential impact of weather events on populations.This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency.LayersUSA Weather Watches and Warnings - Events Ordered by Size and SeverityTopographicWorld HillshadeWorld Street Map Canvas (Night w/yellow boundaries)Tornado DescriptionThis map contains continuously updated U.S. tornado reports, wind storm reports and hail storm reports. You can click on each to receive information about the specific location and read a short description about the issue.Each layer is updated 4 times hourly from data provided by NOAA’s National Weather Service Storm Prediction Center.A full archive of storm events can be accessed from the NOAA National Centers for Environmental Information.SourceNOAA Storm Prediction Center https://www.spc.noaa.gov/climo/reportsUpdate FrequencyThe service is updated every 15 minutes using the Aggregated Live Feeds MethodologyArea CoveredCONUS (Contiguous United States)What can you do with this layer?This map service is suitable for data discovery and visualization.Change the symbology of each layer using single or bi-variate smart mapping. For instance, use size or color to indicate the intensity of a tornado.You can click on each to receive information about the specific location and read a short description about the issue.Query the attributes to show only specific event types or locations.This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency.LayersUSA Storm Reports - NOAA TORNADO Storm Reports (24 hours)USA Storm Reports - NOAA WIND Storm Reports (24 hours)USA Storm Reports - NOAA TORNADO Storm Reports (past week)TopographicWorld HillshadeWorld Street Map Canvas (Night w/yellow boundaries)Wildfire DescriptionThis layer presents recent wildfire activity for the United States, featuring data from GeoMAC. Wildfire activity is downloaded from the GeoMAC Outgoing Datasets from the USGS. GeoMAC was designed to give fire managers near real-time information based on agency reports and fire perimeter data. GeoMAC is updated daily based upon input from incident intelligence sources, GPS data, and infrared (IR) imagery from fixed wing and satellite platforms.Fire Perimeter is a product of Geospatial Multi-Agency Coordination (GeoMAC). In order to give fire managers near real-time information, fire perimeter data is updated daily based upon input from incident intelligence sources, GPS data, infrared (IR) imagery from fixed wing and satellite platforms. We gather this data from the USGS feed (NIFC large fires, NIFC situation reports, perimeters). These shape files from the feed are parsed using the Aggregated Live Feeds methodology to take the returned information and serve the data through ArcGIS Server as a map service.See more information about GeoMAC.To find out more about the Esri Disaster Response Program, visit https://www.esri.com/services/disaster-response.From GeoMAC: Information presented on this website is a representation of the existing wildfire situation in the continental United States including Alaska. While every effort is made to provide accurate and complete information, proximity of fires to populated areas may not be accurately portrayed.Earthquake DescriptionIn addition to displaying earthquakes by magnitude, this service also provide earthquake impact details. Impact is measured by population as well as models for economic and fatality loss. For more details, see: PAGER Alerts.Events are updated as frequently as every 5 minutes and are available up to 30 days with the following exceptions:Events with a Magnitude LESS than 3.0 are retained for 3 daysEvents with a Magnitude LESS than 4.5 are retained for 7 daysIn addition to event points, ShakeMaps are also provided. These have been dissolved by Shake Intensity to reduce the Layer Complexity.The specific layers provided in this service have been Time Enabled and include:Events by Magnitude: The event’s seismic magnitude value.Contains PAGER Alert Level: USGS PAGER (Prompt Assessment of Global Earthquakes for Response) system provides an automated impact level assignment that estimates fatality and economic loss.Contains Significance Level: An event’s significance is determined by factors like magnitude, max MMI, ‘felt’ reports, and estimated impact.Shake Intensity: The Instrumental Intensity or Modified Mercalli Intensity (MMI) for available events.For field terms and technical details, see: ComCat DocumentationThis map is provided for informational purposes and is not monitored 24/7 for accuracy and currency. Always refer to USGS source for official guidance.LayersRecent Earthquakes - Events by MagnitudeRecent Earthquakes - Shake IntensityTopographicWorld HillshadeWorld Street Map Canvas (Night w/yellow boundaries)Hurricane DescriptionHurricane tracks and positions provide information on where the storm has been, where it is currently located, and where it is predicted to go. Each storm location is depicted by the sustained wind speed, according to the Saffir-Simpson Scale. It should be noted that the Saffir-Simpson Scale only applies to hurricanes in the Atlantic and Eastern Pacific basins, however all storms are still symbolized

Series Name: Number of missing persons due to disaster (number)Series Code: VC_DSR_MISSRelease Version: 2021.Q2.G.03 This dataset is part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 11.5.1: Number of deaths, missing persons and directly affected persons attributed to disasters per 100,000 populationTarget 11.5: By 2030, significantly reduce the number of deaths and the number of people affected and substantially decrease the direct economic losses relative to global gross domestic product caused by disasters, including water-related disasters, with a focus on protecting the poor and people in vulnerable situationsGoal 11: Make cities and human settlements inclusive, safe, resilient and sustainableFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

A drought in Ethiopia in 1983 caused 300 thousand deaths, the deadliest natural disaster recorded in Africa between 1970 and 2019. Drought was the natural disaster that caused the largest number of deaths in Africa, much more than floods and landslides. Some of the deadliest droughts occurred in the 1970s and 1980s, especially in the Horn of Africa and Eastern Africa. The Horn of Africa has been largely affected by floods, landslides, and tropical cyclones. For instance, thousands of people, mainly in South Sudan, Sudan, and Somalia, were displaced due to various hazards and climate-induced disasters.

Africa’s vulnerability to climate change

Africa is particularly vulnerable to climate change. A large share of the population lives in poverty and its livelihood depends on activities extremely sensitive to climate changes and weather conditions, such as agriculture, forestry, and fishing. Climate conditions for agricultural production have worsened in the last years, according to five out of 10 Africans. People living in rural areas and working directly in agriculture are more observant of this phenomenon.

Economic impact of natural disasters

The majority of natural disasters that affect Africa are floods, which represent 60 percent of all reported natural disasters recorded over the last decades. Natural disasters such as droughts, storms, and landslides have a huge economic impact. A drought in South Africa in 1990 and Cyclone Idai, in Mozambique in 2019, were the most expensive climate disasters recorded in Africa between 1970 and 2019. Each of these two events caused an economic loss of almost two billion U.S. dollars.

Human mobility is influenced by environmental change and natural disasters. Researchers have used trip distance distribution, radius of gyration of movements, and individuals' visited locations to understand and capture human mobility patterns and trajectories. However, our knowledge of human movements during natural disasters is limited owing to both a lack of empirical data and the low precision of available data. Here, we studied human mobility using high-resolution movement data from individuals in New York City during and for several days after Hurricane Sandy in 2012. We found the human movements followed truncated power-law distributions during and after Hurricane Sandy, although the β value was noticeably larger during the first 24 hours after the storm struck. Also, we examined two parameters: the center of mass and the radius of gyration of each individual's movements. We found that their values during perturbation states and steady states are highly correlated, suggesting human mobility data obtained in steady states can possibly predict the perturbation state. Our results demonstrate that human movement trajectories experienced significant perturbations during hurricanes, but also exhibited high resilience. We expect the study will stimulate future research on the perturbation and inherent resilience of human mobility under the influence of hurricanes. For example, mobility patterns in coastal urban areas could be examined as hurricanes approach, gain or dissipate in strength, and as the path of the storm changes. Understanding nuances of human mobility under the influence of such disasters will enable more effective evacuation, emergency response planning and development of strategies and policies to reduce fatality, injury, and economic loss.

The data set of earthquake disaster in mainland China records the basic information of the earthquake disaster events themselves and the disaster information caused by the human society based on the various earthquake disaster events in mainland China from 1990 to 2020. The basic information indicators of earthquake disaster events includes: Region Name, Earthquake Year, Earthquake Date, Earthquake Time, Earthquake Magnitude, Focal Depth, Epicenter Location, the Main Disaster Counties, Economy, Population, Area; Earthquake loss indicators include: Casualties, Deaths, Direct Economic Losses, Affected Areas, House Damage, Rural Houses Damage, Urban Houses Damage, Lifeline Projects Economic Losses, Rural housing Economic Losses, Urban Housing Economic Losses.

The HANZE dataset covers riverine, pluvial, coastal and compound floods that have occurred in 42 European countries between 1870 and 2020. The data was collected by extensive data-collection from more than 800 sources ranging from news reports through government databases to scientific papers. The dataset includes 2521 events characterized by at least one impact statistic: area inundated, fatalities, persons affected or economic loss. Economic losses are presented both in the original currencies and price levels as well as inflation and exchange-rate adjusted to 2020 value of the euro. The spatial footprint of affected areas is consistently recorded using more than 1400 subnational units corresponding, with minor exceptions, to the European Union’s Nomenclature of Territorial Units for Statistics (NUTS), level 3. Daily start and end dates, information on causes of the event, notes on data quality issues or associated non-flood impacts, and full bibliography of each record supplement the dataset. Apart from the possibility to download the data, the database can be viewed, filtered and visualized online: https://naturalhazards.eu. The dataset is designed to be complimentary to HANZE-Exposure, a high-resolution model of historical exposure changes (such as population and asset value), and be easily usable in statistical and spatial analyses.

The dataset contains the following files (CSV comma-delimited, UTF8, and ESRI shapefiles in zipped folders)

HANZE flood events database

HANZE_events.csv - Flood event data

HANZE_references.csv - List of all references

HANZE_events_regions_2010.zip - Flood event data as GIS file (regions v2010)

HANZE_events_regions_2021.zip - Flood event data as GIS file (regions v2021)

Supplementary data

S1_countries_codes_and_names.csv - Country codes/names

S2_regions_codes_and_names_v2010.csv - Region codes/names, v2010

S3_regions_codes_and_names_v2021.csv - Region codes/names, v2021

S4_list_of_all_currencies_by_country.csv - Data on all currencies used in the study area since 1870

S5_currency_conversion_rates.csv - Conversion rates applied to compute losses in 2020 euros

S6_GDP_deflators_by_country.csv - Gross domestic product deflator by country, 1870-2020

S7_floods_removed_from_HANZE.csv - Flood events in HANZE v1, which were excluded from v2

Regions_v2010_simplified.zip - Map of subnational regions used in the database, v2010

Regions_v2021_simplified.zip - Map of subnational regions used in the database, v2021

Note: this is a minor update of the original upload. It corrects the erroneous rendering of NUTS regions for event 2751, fixes some geometry problems with the GIS files and makes some small changes to the flood data (2 events were added and the regional codes for Kosovo in version 2021 were modified based on the upcoming NUTS 2024 classification).

The dataset and R codes to investigate the effects of the false alarm ratio (FAR) and missed event ratio (MER) on flood damage by applying Bayesian regression analyses to open data on the 2018 Japan Floods in 127 municipalities in four prefectures (i.e., Okayama, Hiroshima, Ehime, and Fukuoka).

The data for FAR and MER were collected from the real-time flood warning map (Kouzui Kikikuru in Japanese) during the 2018 Japan Floods, which provides limited open data on warning performance.

The data for disaster damage, namely (1) fatalities, (2) injuries, (3) economic losses to general assets, and (4) economic losses to crops during the 2018 Japan Floods, were collected from technical disaster damage reports compiled by the prefectures and the Cabinet Office.

Additional detailed instructions are provided in a readme file.

Goal 11Make cities and human settlements inclusive, safe, resilient and sustainableTarget 11.1: By 2030, ensure access for all to adequate, safe and affordable housing and basic services and upgrade slumsIndicator 11.1.1: Proportion of urban population living in slums, informal settlements or inadequate housingEN_LND_SLUM: Proportion of urban population living in slums (%)Target 11.2: By 2030, provide access to safe, affordable, accessible and sustainable transport systems for all, improving road safety, notably by expanding public transport, with special attention to the needs of those in vulnerable situations, women, children, persons with disabilities and older personsIndicator 11.2.1: Proportion of population that has convenient access to public transport, by sex, age and persons with disabilitiesTarget 11.3: By 2030, enhance inclusive and sustainable urbanization and capacity for participatory, integrated and sustainable human settlement planning and management in all countriesIndicator 11.3.1: Ratio of land consumption rate to population growth rateIndicator 11.3.2: Proportion of cities with a direct participation structure of civil society in urban planning and management that operate regularly and democraticallyTarget 11.4: Strengthen efforts to protect and safeguard the world’s cultural and natural heritageIndicator 11.4.1: Total per capita expenditure on the preservation, protection and conservation of all cultural and natural heritage, by source of funding (public, private), type of heritage (cultural, natural) and level of government (national, regional, and local/municipal)Target 11.5: By 2030, significantly reduce the number of deaths and the number of people affected and substantially decrease the direct economic losses relative to global gross domestic product caused by disasters, including water-related disasters, with a focus on protecting the poor and people in vulnerable situationsIndicator 11.5.1: Number of deaths, missing persons and directly affected persons attributed to disasters per 100,000 populationVC_DSR_MISS: Number of missing persons due to disaster (number)VC_DSR_AFFCT: Number of people affected by disaster (number)VC_DSR_MORT: Number of deaths due to disaster (number)VC_DSR_MTMP: Number of deaths and missing persons attributed to disasters per 100,000 population (number)VC_DSR_MMHN: Number of deaths and missing persons attributed to disasters (number)VC_DSR_DAFF: Number of directly affected persons attributed to disasters per 100,000 population (number)VC_DSR_IJILN: Number of injured or ill people attributed to disasters (number)VC_DSR_PDAN: Number of people whose damaged dwellings were attributed to disasters (number)VC_DSR_PDYN: Number of people whose destroyed dwellings were attributed to disasters (number)VC_DSR_PDLN: Number of people whose livelihoods were disrupted or destroyed, attributed to disasters (number)Indicator 11.5.2: Direct economic loss in relation to global GDP, damage to critical infrastructure and number of disruptions to basic services, attributed to disastersVC_DSR_GDPLS: Direct economic loss attributed to disasters (current United States dollars)VC_DSR_LSGP: Direct economic loss attributed to disasters relative to GDP (%)VC_DSR_AGLH: Direct agriculture loss attributed to disasters (current United States dollars)VC_DSR_HOLH: Direct economic loss in the housing sector attributed to disasters (current United States dollars)VC_DSR_CILN: Direct economic loss resulting from damaged or destroyed critical infrastructure attributed to disasters (current United States dollars)VC_DSR_CHLN: Direct economic loss to cultural heritage damaged or destroyed attributed to disasters (millions of current United States dollars)VC_DSR_CDAN: Number of damaged critical infrastructure attributed to disasters (number)VC_DSR_HFDN: Number of destroyed or damaged health facilities attributed to disasters (number)VC_DSR_EFDN: Number of destroyed or damaged educational facilities attributed to disasters (number)VC_DSR_CDYN: Number of other destroyed or damaged critical infrastructure units and facilities attributed to disasters (number)VC_DSR_BSDN: Number of disruptions to basic services attributed to disasters (number)VC_DSR_ESDN: Number of disruptions to educational services attributed to disasters (number)VC_DSR_HSDN: Number of disruptions to health services attributed to disasters (number)VC_DSR_OBDN: Number of disruptions to other basic services attributed to disasters (number)VC_DSR_DDPA: Direct economic loss to other damaged or destroyed productive assets attributed to disasters (current United States dollars)Target 11.6: By 2030, reduce the adverse per capita environmental impact of cities, including by paying special attention to air quality and municipal and other waste managementIndicator 11.6.1: Proportion of municipal solid waste collected and managed in controlled facilities out of total municipal waste generated, by citiesEN_REF_WASCOL: Municipal Solid Waste collection coverage, by cities (%)Indicator 11.6.2: Annual mean levels of fine particulate matter (e.g. PM2.5 and PM10) in cities (population weighted)EN_ATM_PM25: Annual mean levels of fine particulate matter in cities, urban population (micrograms per cubic meter)Target 11.7: By 2030, provide universal access to safe, inclusive and accessible, green and public spaces, in particular for women and children, older persons and persons with disabilitiesIndicator 11.7.1: Average share of the built-up area of cities that is open space for public use for all, by sex, age and persons with disabilitiesIndicator 11.7.2: Proportion of persons victim of physical or sexual harassment, by sex, age, disability status and place of occurrence, in the previous 12 monthsTarget 11.a: Support positive economic, social and environmental links between urban, peri-urban and rural areas by strengthening national and regional development planningIndicator 11.a.1: Number of countries that have national urban policies or regional development plans that (a) respond to population dynamics; (b) ensure balanced territorial development; and (c) increase local fiscal spaceSD_CPA_UPRDP: Countries that have national urban policies or regional development plans that respond to population dynamics; ensure balanced territorial development; and increase local fiscal space (1 = YES; 0 = NO)Target 11.b: By 2020, substantially increase the number of cities and human settlements adopting and implementing integrated policies and plans towards inclusion, resource efficiency, mitigation and adaptation to climate change, resilience to disasters, and develop and implement, in line with the Sendai Framework for Disaster Risk Reduction 2015–2030, holistic disaster risk management at all levelsIndicator 11.b.1: Number of countries that adopt and implement national disaster risk reduction strategies in line with the Sendai Framework for Disaster Risk Reduction 2015–2030SG_DSR_LGRGSR: Score of adoption and implementation of national DRR strategies in line with the Sendai FrameworkSG_DSR_SFDRR: Number of countries that reported having a National DRR Strategy which is aligned to the Sendai FrameworkIndicator 11.b.2: Proportion of local governments that adopt and implement local disaster risk reduction strategies in line with national disaster risk reduction strategiesSG_DSR_SILS: Proportion of local governments that adopt and implement local disaster risk reduction strategies in line with national disaster risk reduction strategies (%)SG_DSR_SILN: Number of local governments that adopt and implement local DRR strategies in line with national strategies (number)SG_GOV_LOGV: Number of local governments (number)Target 11.c: Support least developed countries, including through financial and technical assistance, in building sustainable and resilient buildings utilizing local materials

The hurricanes in the U.S. and Mexico in September and October incurred an economic loss of about 110 billion U.S. dollars, the most of any natural disaster event in 2024. Three of the ten most expensive catastrophes in that year were hurricanes. Weather, climate, water related disaster The disasters that caused mortality in large numbers include droughts, storms, floods, and extreme temperatures. Hurricanes alone generated 35 percent of the total economic losses among the leading disasters over these 50 years. The global cost of natural disaster losses was primarily financial losses. Low-income countries are more affected by natural disasters when compared to the richer countries in the world. American Hurricanes Floods were the most common weather-related disasters recorded, yet storms had the highest human and economic losses. As the most common cause of damage, storms are the only disaster for which the attribution component grows. As of 2023, Hurricane Katrina was by far the most destructive hurricane in the United States. Officials confirmed more than 1,800 deaths, estimated damages of about 200 billion U.S. dollars, the destruction of approximately 350,000 homes, and displaced almost a million individuals.