Explore Our Data - Lancet Countdown

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Welcome to the Lancet Countdown on Health and Climate Change data explorer. This platform allows users to engage with our findings and explore the latest global report data at country, regional and income group level. The data visualisations are free to use and share, and we encourage you to include them in your work.

Overview

Health Hazards, Exposures, and Impacts

Adaptation, Planning, and Resilience for Health

Mitigation Actions and Health Co-Benefits

Economics and Finance

Public and Political Engagement in Health and Climate Change

1.1 Health and Heat
- 1.1.1 Exposure of Vulnerable Populations to Heatwaves
- 1.1.2 Heat and Physical Activity
- 1.1.3 Change in Labour Capacity
- 1.1.4 Rising Nighttime Temperatures and Sleep Loss
- 1.1.5 Heat-Related Mortality
1.2 Health and Extreme Weather Events
- 1.2.1 Wildfires
- 1.2.2 Drought
- 1.2.3 Extreme Precipitation
- 1.2.4 Sand and Dust Storms
- 1.2.5 Extreme Weather and Sentiment
1.3 Climate Suitability for Infectious Disease Transmission
- 1.3.1 Dengue, chikungunya, Zika
- 1.3.2 Malaria
- 1.3.3 West Nile
- 1.3.4 leishmaniasis
- 1.3.5 Tick-borne disease
- 1.3.6 Vibrio
1.4. Food security and Undernutrition

2.1 Assessment and Planning of Health Adaptation
- 2.1.1 / 2.1.2 National Assessments of Climate Change Impacts, Vulnerability, and Adaptation for Health
- 2.1.2 National Adaptation Plans for Health
- 2.1.3 City-Level Climate Change Risk Assessments
2.2 Enabling conditions, Adaptation Delivery, and Implementation
- 2.2.1 Climate Information for Health
- 2.2.2 Air Conditioning: Benefits and Harms
- 2.2.3 Urban Green and Blue Spaces
- 2.2.4 Detection, Preparedness, and Response to Health Emergencies
- 2.2.5 Climate and Health Education and Training
2.3 Vulnerabilities, Health Risk, and Resilience to Climate Change
- 2.3.1 Vulnerability to Severe Mosquito-Borne Disease
- 2.3.2 Lethality of Extreme Weather Events
- 2.3.3 Migration, Displacement, and Rising Sea Levels

3.1 Energy Use, Energy Generation and Health
- 3.1.1 Energy Systems and Health
- 3.1.2 Household Energy Use
- 3.1.3 Sustainable and Healthy Road Transport
3.2 Air Pollution and Health Co-benefits
- 3.2.1 Mortality from Ambient Air Pollution
- 3.2.2 Household Air Pollution
3.3 Food, Agriculture, and Health
- 3.3.1 Emissions from Agricultural Production and Consumption
- 3.3.2 Diet and Health Co-Benefits
3.4. Tree Cover Loss
3.5. Healthcare Sector Emissions

4.1 The Economic Impact of Climate Change and its Mitigation
- 4.1.1 Economic Losses due to Climate-Related Extreme Events
- 4.1.2 Costs of Heat-related Mortality
- 4.1.3 Loss of Earnings from Heat-Related Labour Capacity Reduction
- 4.1.4 Costs of the Health Impacts of Air Pollution
4.2 The Transition to Net Zero-carbon, Health-supporting Economies
- 4.2.1 Employment in Renewable Energy and Fossil Fuel Industries
- 4.2.2 Compatibility of Fossil Fuel Company Strategies With the Paris Agreement
- 4.2.3 Stranded Assets from the Energy Transition
- 4.2.4 Country Preparedness for the Transition to Net Zero
- 4.2.5 Production-based and Consumption-based Attribution of CO2 and PM2.5 Emissions
4.3 Financial Transitions for a Healthy Future
- 4.3.1 Clean Energy Investment
- 4.3.2 Net Value of Fossil Fuel Subsidies and Carbon Prices
- 4.3.3 Fossil Fuel and Green Bank Lending
- 4.3.4 Health Adaptation Finance Flows and Disclosed Needs

5.1. Media Coverage of Health and Climate Change
5.2. Individual Engagement in Health and Climate Change
5.3 Scientific Engagement in Health and Climate Change
- 5.3.1 Scientific Articles on Health and Climate Change
- 5.3.2 Scientific Engagement on the Health Impacts of Climate Change
5.4 Political Engagement in Health and Climate Change
- 5.4.1 Government Engagement
- 5.4.2 Engagement by International Organisations
5.5. Corporate Sector Engagement in Health and Climate Change

1.1.1 Exposure of Vulnerable Populations to Heatwaves

Exposure to extreme heat has a range of health consequences including, heat stress and heat stroke, worsening heart disease, and acute kidney injury. Infants and older adults are particularly vulnerable to adverse health effects from heat exposure and are being increasingly exposed to heatwaves, defined as a period of 2 or more days where both the minimum and maximum temperatures are above the 95th percentile of 1986–2005. This indicator tracks the number of heatwave days and the exposure of these vulnerable populations, those under 1 and over 65, to heatwaves.

HEADLINE FINDINGS

In 2024, people older than 65 years and infants younger than 1-year experienced, on average, 304% and 389% more days of heatwaves per person, respectively, compared to 1986-2005.
DATA SOURCES

1. European Centre for Medium-Range Weather Forecasts Reanalysis 5th Generation monthly averaged data on single levels from 1959 to present. Copernicus Climate Change Service Climate Data Store.

2. Hybrid gridded demographic data for the world (1980-2000) 0.25˚ resolution, Lancet Countdown 2023

3. WorldPop Age and Sex Structure Unconstrained Global Mosaic data for 2000–2020
CAVEATS

As two distinct sources were used for population data to obtain estimates of both the spatial and temporal characteristics there may be some inconsistencies between the pre and post 2000 values.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator tracks changes in the number of heatwave days per year per vulnerable person and reflects the exposure of vulnerable populations to heatwaves expressed as person-days, this captures increasing durations of heatwaves as well as changes in frequency compared with the average number of events in the reference period (1986–2005).

DATA DOWNLOAD

Click here to download the data on heatwave days attributable to climate change.

Click here to download the data on vulnerable populations exposed to heatwave days.
INDICATOR AUTHORS

1) Dr. Andrew J Pershing, Joseph Giguere
2) Dr Federico Tartarini, Prof Ollie Jay

HEADLINE FINDINGS

In 2024, each person was exposed, on average, to a record-high 1,609 hours during which ambient heat posed at least a moderate heat stress risk during light outdoor exercise, 35.8% above 1990-1999.
DATA SOURCES

1. European Centre for Medium-Range Weather Forecasts Reanalysis 5th Generation monthly averaged data on single levels from 1959 to present. Copernicus Climate Change Service Climate Data Store.

2. Gridded Population of the World Version 4, 2021. Socioeconomic Data and Applications Center, National Aeronautics and Space Administration.

3. World Health Organisation Detailed Boundary ADM0 Shapefiles
CAVEATS

The estimation of heat stress risk for a given exercise category may not be uniform across the entire population, and risk estimates in particular may be different for older adults, young children, pregnant women, and those living with disabilities or chronic diseases. A more detailed interpretation model of heat effects on exercise would incorporate individual factors such as age, health status, physiology, and clothing.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator incorporates temperature, humidity, and solar radiation restricting analysis to local sunlight hours only to estimate and track the daily hours per person during which undertaking outdoor physcial activity would pose a heightened heat stress risk. The indicator uses “moderate” heat stress risk, as defined by the 2021 Sports Medicine Australia Extreme Heat Policy, which stratifies estimated heat stress risk based on ambient temperature and relative humidity.

DATA DOWNLOAD

Click here to download indicator data.
INDICATOR AUTHORS

Dr Troy J Cross, Dr Samuel H Gunther, Prof Ollie Jay, Dr Jason KW Lee

1.1.3 Change in Labour Capacity

Our capacity to work is affected by temperature and humidity, particularly in highly physical jobs in poorly coolled environments or outdoors with little to no shade in agriculture, industry, and manufacturing sectors. Reduced work productivity puts a strain on the socioeconomic determinants of health for individuals and communities. As the world continues to warm, this indicator tracks the change in potential work hours lost due to exposure to high temperatures.

HEADLINE FINDINGS

Heat exposure led to the loss of 640 billion potential labour hours in 2024, 98% above the 1990–1999 annual average
DATA SOURCES

1. European Centre for Medium-Range Weather Forecasts Reanalysis 5th Generation monthly averaged data on single levels from 1959 to present. Copernicus Climate Change Service Climate Data Store.

2. Gridded Population of the World (2018). Socioeconomic Data and Applications Center, National Aeronautics and Space Administration.

3. International Labour Organization International Statistics Database (ILOSTAT). ILO. Accessed in 2025

4. The Inter-Sectoral Impact Model Intercomparison Project. ISIMP3b Bias Adjustment. 2022.

5. Global, regional, national, and subnational occupational exposure to solar ultraviolet radiation for 195 countries/areas, and the global, regional, and national attributable burden of non-melanoma skin cancer for 183 countries, 2000-2019: a systematic analysis from WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury. 2023. Pega F, Momen NC, Stricher KN et al.

6. UN Population Division, World Population Prospects 2024
CAVEATS

The distribution of agricultural, construction manufacturing, and service sector workers used are country averages, applied evenly to the population of each grid cell, thus not accounting for sub-national variation in industry sector.

The numbers and percentages of workers captures those in the formal economy for regions and countries, unpaid work, to which women often dedicate more time than men, is not accounted for.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator has two distinct parts. The first monitors the number of outdoor workers (a population at risk) with estimates produced by WHO staff. The second calculates hours of work lost as a result of heat exposure in four sectors: agriculture, construction, manufacturing, and service. It monitors potential hours lost by linking Wet Bulb Globe Temperature (including temperature, humidity and solar radiation) with the amount of energy expended by workers through the typical metabolic rate of workers. It then combines this calculation with the proportion of people working over 15 years old in each of the four sectors in each country to estimate the potential work hours lost per year.

DATA DOWNLOAD

Click here to download data on potential work hours lost.

Click here to download data on outdoor workers.
INDICATOR AUTHORS

1) Dr Natalie C. Momen, Dr Frank Pega
2) Chris Freyberg, Dr Bruno Lemke, Matthias Otto

1.1.4 Rising Nighttime Temperatures and Sleep Loss

Sleep of adequate duration and quality is important for good human physical and mental health. High ambient temperatures are associated with worse sleep quantity and quality. With climate change resulting in nighttime temperatures rising faster than daytime temperatures in many world regions, the risk of adverse health outcomes from poor sleep quality is rising globally.

This indicator tracks the impact of suboptimal nighttime temperatures on sleep loss. It combines the global functional sleep response to nighttime temperature identified in a multi-country sleep study, with nighttime temperature data, and it statistically controls for individual-level demographic and environmental factors, including air conditioning access.

HEADLINE FINDINGS

Sleep hours lost due to high temperatures increased by 6% between 1986-2005 and 2020-2024, reaching a record 9% increase in sleep hours lost in 2024
DATA SOURCES

1. European Centre for Medium-Range Weather Forecasts Reanalysis 5th Generation monthly averaged data on single levels from 1959 to present. Copernicus Climate Change Service Climate Data Store.

2. Gridded Population of the World Version 4, 2021. Socioeconomic Data and Applications Center, National Aeronautics and Space Administration.

3. Rising temperatures erode human sleep globally. One Earth. 2022. Minor K, Bjerre-Nielsen A, Jonasdottir SS, Lehmann S, Obradovich N.
CAVEATS

As with other statistical samples, the indicator’s analytic approach assumes that the estimates obtained in the underlying global study of tens of thousands of individuals are likely to apply to the individuals not within the sample. This means that the original data may be more likely to include wealthier persons who can afford fitness trackers and less likely to include the world’s poorest than a truly representative sample, potentially underestimating the impact. Additionally, the relationship between ambient temperatures and human sleep may change in the future as individuals adapt and/or decompensate to altered future temperatures. An increased availability of air conditioning in the future, for example, might alter the global response curve. It is also possible, given the spatial resolution of the indicator, that areas with high air conditioning/fan penetration already reflect some expected adaptation particularly at the higher end of the temperature distribution.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator tracks the relationship between human sleep and warmer nighttime temperatures employing estimates from published research that monitors fitness tracking bands to measure over ten billion sleep observations across over 40,000 individuals living in 68 countries around the world between 2015–2017. The indicator estimates percentage change in annual total number of hours of sleep lost globally due to warmer than opitmal nighttime tempertature relative to the 1986-2005 baseline average in this metric.

DATA DOWNLOAD

Click here to download indicator data.
INDICATOR AUTHORS

Dr Kelton Minor and Dr Nick Obradovich

1.1.5 Heat-Related Mortality

Populations are finding themselves increasingly vulnerable to extreme heat. Exposure to extremes of heat can result in a range of health consequences, including heat stress and heat stroke, worsening heart disease, and acute kidney injury and leads to an increase in all-cause mortality. As the world continues to warm and populations age, this indicator tracks heat-related mortality around the world and the proportion of those that were made more likely by human-induced climate change.

HEADLINE FINDINGS

In 2012-2021, global heat-related mortality reached an estimated average 546,000 deaths annually, up 63.2% from 335,000 in 1990-1999.
DATA SOURCES

1. European Centre for Medium-Range Weather Forecasts Reanalysis 5th Generation monthly averaged data on single levels from 1959 to present. Copernicus Climate Change Service Climate Data Store.

2. Gridded Population of the World Version 4, 2021. Socioeconomic Data and Applications Center, National Aeronautics and Space Administration.

3. Yearly, country-level mortality and population data obtained from the Global Burden of Disease 2021

4. Mortality data from United Nations Population Division EUROSTAT

5.All-cause mortality data from the World Mortality dataset, 2015

6. The World Bank Group. World Development Indicators. 2015
CAVEATS

The analysis for heat-related mortality assumes the exposure-response function is constant. It does not capture changes in response to heat exposure that might happen over time, as a result of acclimation and adaptation. Not capturing these changes could result in an over-estimation of heat-related deaths in later calendar years. Annual average mortality rates are used, rather than daily mortality rates. Given baseline mortality can be higher in colder months, this may lead to an overestimation of overall mortalities.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator monitors heat-related mortality using a newly-developed model framework that builds on a mortality database for 120 countries. It then applies state-of-the-art meta-prediction models to consistently estimate the association between temperature and mortality from all causes in all countries globally, and combines them with yearly mortality estimates from the Global Burden of Disease, making it the most comprehensive global estimate of heat-related mortality yet.

DATA DOWNLOAD

Click here to download indicator data.
INDICATOR AUTHORS

Dr Joan Ballester, Prof Xavier Basagaña, Jorge Ruiz-Cabrejos

1.2.1 Wildfires

Wildfires cause a range of health impacts, from direct thermal injuries through to exacerbation of acute and chronic lung disease from smoke and pollution, in addition to the loss of essential and health-supporting physical infrastructures and emergency services. They often cause substantial social and economic impacts. Climate change-driven increases in temperature and changes in rainfall patterns are increasing the intensity, frequency, duration, of life-threatening weather-related events and increasing the risk of wildfires. This indicator monitors change in wildfire danger and the number of people exposed to wildfires and wildfire smoke, globally. With updated methodology, this indicator no longer captures non-fire hot spots such as industry-related recordings increasing the accuracy.

HEADLINE FINDINGS

In 2020-2024, exposure to days of at least very high wildfire risk increased by 6.6% on average globally, with 6 days per person more compared to 2003–2012. Deaths from wildfire-derived PM2.5 air pollution reached a record-high 154,000 in 2024, up by 36% from the 2003-2012 average.
DATA SOURCES

1. NASA MODIS Aqua and Terra Thermal Anomalies/Fire Locations product; Daymet daily surface meteorology
2. Fire Weather Index historical data (v4.1) produced by the Copernicus Emergency Management Service for the European Forest Fire Information System (EFFIS)
3. Population data from the NASA Socioeconomic Data and Applications Center (SEDAC) Gridded Population of the World (GPWv4)
4. MODIS Fire Radiative Power (FRP) observations MOD14/MYD14 from the NASA Fire Information for Resource Management System (FIRMS)
5. Cloud cover data from the EarthEnv Global 1-km Cloud dataset
CAVEATS

The Fire Weather Index (FWI) quantifies fire potential based on meteorological conditions. It does not account for human influences such as land use changes, urban expansion, fire suppression practices, and human-induced ignition. Additionally, the FWI does not incorporate the effects of rising atmospheric CO2 levels or shifts in lightning strike frequency. Variations in local topography, vegetation types, and socioeconomic factors influencing fire preparedness and resilience are excluded. The exposure assessment is based on active fire spots detected by MODIS which do not distinguish between wildfires and prescribed burns. The indicator’s spatial resolution many not fully capture finer-scale variations in wildfire exposure.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator uses model-based wildfire danger, satellite-observed exposure, and modelled exposure to wildfire fine particles, accounting for cloud cover in the detection of wildfire spots. It incorporates atmospheric modelling to track exposure to wildfire smoke (PM2.5). Climatological wildfire danger is estimated by combining daily very high or extremely high wildfire danger (a fire danger index score of 5 or 6) with climate and population data. Human exposure to wildfires, in person-days (with one person-day being one person exposed to a wildfire in one day) is tracked using satellite and population data.

DATA DOWNLOAD

Click here to download the wildfire exposure and risk data.

Click here to download the wildfire smoke data.

Click here for wildfire smoke days data.

Click here to download the wildfire mortality data.
INDICATOR AUTHORS

Dr. Yang Liu, Dr. Yun Hang, Dr. Qiao Zhu
Dr Risto Hänninen, Dr Rostislav Kouznetsov, Prof Mikhail Sofiev.

1.2.2 Drought

Climate change alters hydrological cycles, tending to make dry areas drier and wet areas wetter. Drought poses multiple risks for health, threatening drinking water supplies and sanitation, crop and livestock productivity, enhancing the risk of wildfires, and potentially leading to forced migration. In many water-insecure settings, women and girls are often the ones charged with collecting water, in areas that face harsh droughts this means further to travel, if water can be sourced at all, putting those women and girls in potential danger of gender violence and physical harms. As climate change alters rainfall patterns and increases temperatures, this indicator tracks the change in months of drought globally showing no continent is unaffected by drought.

HEADLINE FINDINGS

The percentage of the global land area affected by at least one month of extreme drought reached a record-breaking 60.7% in 2024, 299% above the 1951-1960 average.
DATA SOURCES

1. SPEI6 data from the Global SPEI Database, SPEIbase (Consejo Superior de Investigaciones Cientificas)
CAVEATS

This indicator only captures the impacts of climate change on meteorological drought and not hydrological or agricultural drought. It does not measure the direct relationship between a drought and the population living in, or depending on, drought-affected areas. It is not possible to do a population-based weighting because many people affected by a drought may not live in the area affected, e.g., in the case of droughts affecting agricultural areas (which are generally sparsely populated) with impacts on the food supply.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator measures changes in the number of months of extreme meteorological drought, using the 6-monthly Standard Precipitation Evapotranspiration Index, compared with a 1986-2005 baseline.

DATA DOWNLOAD

Click here to download the indicator data.
INDICATOR AUTHORS

Dr Marina Romanello, Maria Walawender

1.2.3 Extreme Precipitation

Climate change alters the hydrological cycle, increasing the frequency and intensity of both droughts and extreme precipitation over most land areas. Extreme precipitation is associated with adverse physical and mental health outcomes. When leading to floods, it can increase the risk of injury or drowning, infrastructural damage, environmental degradation, waterborne disease outbreaks and disruption to social, ecological and economic life support systems, affecting lives and livelihoods. This indicator tracks changes in extreme precipitation events, defined as those exceeding the 99th percentile of 1961-1990, using ERA Land data.

HEADLINE FINDINGS

In 2015–24, a record 64% of global land area saw increases in extreme precipitation events from 1961–90, and in 2024 the average annual number of >99th-percentile events per 79 km² reached a record high of five.
DATA SOURCES

1. European Centre for Medium-Range Weather Forecasts Reanalysis 5th Generation-Land (ERA5-Land). Copernicus Climate Change Service Climate Data Store.
CAVEATS

ERA5-Land does not incorporate direct rain-gauge measurements, instead relying on the ECMWF’s Inegrated Forecasting System (IFS Cy41r2) to assimilate short-range forecast observations.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator monitors changes in extreme precipitation over all land globally, tracking the occurrence of global daily precipitation extremes and changes in relative frequency. The indicator employs gridded, high resolution daily precipitation data from the reanalysis data source (ERA Land) and uses this data to track both the change in the average frequency of extreme precipitation events per decade over global land area in the past 30 years compared to the precipitation baseline of 1961-1990, and the average percentage of global land that has had an increase in the occurrence of extreme precipitation from this historical baseline.

DATA DOWNLOAD

Click here to download the indicator data.
INDICATOR AUTHORS

Dr Kelton Minor and Dr Nick Obradovich

1.2.4 Sand and Dust Storms

Drought, poor land management and increased wildfire-burned areas are increasing the risk of sand and dust storms (SDS). The major component of particulate matter (PM) during a SDS is the mineral (also known as crustal) fraction. Mineral dust contributes to PM10 air pollution, exposure to which increases the risk of asthma, cardiovascular disease, and premature death. Transported mineral dust can also spread soil–dwelling pathogens, and cause transportation accidents through reduced visibility. This indicator uses a state–of–the–art multi–model reanalysis ensemble to estimate PM10 emissions from arid and semi-arid regions (referred to hereafter as dust-PM10), and overlays it with population data to estimate human exposure.

HEADLINE FINDINGS

Between 2003–2012 and 2019–2023, the average annual number of days that people were exposed to desert dust levels above WHO guidance levels rose in 38% of countries and declined in 19%.
DATA SOURCES

1. CAMS-RA, 2022. Copernicus Atmosphere Monitoring Service Reanalysis.
2. Naval Research Laboratory Navy Aerosol Analysis and Prediction System Reanalysis (NAAPS-RA), 2024. US Naval Research Laboratory.
3. Modern-Era Retrospective analysis for Research and Applications, Version 2 (NASA MERRA-2), 2022. National Aeronautics and Space Administration.
4. System for Integrated modeLling of Atmospheric composition (SILAM). Finnish Meteorological Institute.
5. Gridded Population of the World Version 4, 2021. Socioeconomic Data and Applications Center, National Aeronautics and Space Administration.
CAVEATS

Model prediction is limited by the physical mechanisms and quality of input parameters, satellite observations assimilated are limited by temporal coverage (once or twice a day) and cloud cover, and ground observations by spatial coverage.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator uses a state–of–the–art multi–model reanalysis ensemble to estimate PM10 emissions from arid and semi-arid regions (referred to as dust-PM10), and overlays it with population data to estimate human exposure.

DATA DOWNLOAD

Click here to downlaod indicator data.
INDICATOR AUTHORS

Dr. Melanie Ades, Dr. Sophie Gumy, Dr. Siqi Ma, Dr. Andreas Uppstu

HEADLINE FINDINGS

In 2024, extreme heat events cumulatively worsened human sentiment by a record 132% relative to the 2006–22 baseline.
DATA SOURCES

1. European Centre for Medium-Range Weather Forecasts Reanalysis 5th Generation monthly averaged data on single levels from 1959 to present. Copernicus Climate Change Service Climate Data Store.
2. Geolocated Tweets collected via the Twitter Streaming Application Programming Interface, 2015-2022
3. Population count data from the Gridded Population of the World, version 4, from the Center for International Earth Science Information Network at Columbia University.
CAVEATS

While sentiment is related to mental wellbeing, it should not be confused as a measure of it and should be interpreted as an indicative proxy of the mental implications of extremes of heat. Countries that did not have Twitter broadly available to the public, such as China, were underrepresented despite the addition of Mandarin tweets this year. Furthermore, geo-tagged tweets constituted approximately 2% of all tweets and thus may be somewhat limited in their generalisability due to opt-in geo-localization. The vast majority of the Twitter observations were posted in wealthy countries who have greater access to adaptive amenities and potentially underestimates the sentiments of those most disproportionately exposed to some of the hottest conditions in poorer socioeconomic contexts.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator monitors expressed sentiment on Twitter, using billions of geolocated tweets collected between 2015 and 2022. It deploys a multivariate ordinary least squares fixed effects model to estimate the annual effect of heatwaves (as defined in indicator 1.1.2) and extreme precipitation (exceeding the 99th percentile of local daily precipitation), on online sentiment expression. It compares sentiment expression between heatwave days and non-heatwave days and between extremely wet days and non-extremely wet days.

DATA DOWNLOAD

Click here to download the indicator data.
INDICATOR AUTHORS

Dr Kelton Minor, Dr Nick Obradovich

1.3.1 Dengue, chikungunya, Zika

Changing climatic conditions, such as shifts in seasonal tempertures and precipitation levels, are altering the transmission potential of many vector-, water-, food-, and air-borne infectious diseases. Dengue is a mosquito-borne disease that can cause febrile illnesses and, in severe cases, organ failure and death, with children under five particularly at risk. With temperatures changing across the globe, this indicator tracks how this is affecting the climate suitability for these infections.

HEADLINE FINDINGS

The average climate-defined transmission potential of dengue by Aedes albopictus and Aedes aegypti increased by 48.5% and 17.0%, respectively, from 1951-60 to 2015-24.
DATA SOURCES

1. European Centre for Medium-Range Weather Forecasts Reanalysis 5th Generation-Land daily and monthly averaged data, 1951-2024, 0.1 grids.
2. Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a), 1951-2021.
CAVEATS

The model depends on climatic factors for explaining disease dynamics. It excludes humidity and socioeconomic elements. The indicator exclusively focuses on Aedes aegypti and Aedes albopictus and their spatial dispersion, excluding other Aedes species which are proven to be important for dengue transmission. The model computes R_0 independently for both vectors and does not assess overall transmission risk in regions where these vectors overlaps. The R_0 values predicted by this model represent potential outbreak risks rather than actual transmission rates, since real-world R_0 values result from complex interactions between socioeconomic conditions and climatic factors, which the current model does not encompass.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator tracks the environmental suitability for the transmission of arboviruses (dengue, chikungunya, and Zika). It uses an improved model to capture the influence of temperature and rainfall on vectorial capacity and vector abundance, and overlays it with human population density data to estimate the R0 (the expected number of secondary infections resulting from one infected person).

DATA DOWNLOAD

Click here to download the indicator data.
INDICATOR AUTHORS

Pratik Singh, Dr. Henrik Sjödin, and Prof. Joacim Rocklöv

1.3.2 Malaria

Changing climatic conditions, such as shifts in seasonal temperatures and precipitation levels, are altering the transmission potential of many vector-, water-, food-, and air-borned infectious diseases. Malaria is transmitted by mosquitoes and can cause serious illness and death. With temperatures changing across the globe, this indicator tracks how this is affecting the climate suitability for these infections and the fluctuations in the length of the malaria transmission season using climatic and environmental conditions required by the vector and the parasite.

HEADLINE FINDINGS

While changes in climatically suitable areas for malaria transmission have marginally increased globally from 1951-1960 to 2015-2024, there were pronounced increases in highland areas, with a 13.9% increase for Plasmodium falciparum and 13.0% increase for Plasmodium vivax.
DATA SOURCES

1. Copernicus Climate Data Store via ERA5 monthly re-analysis for the full time-series (1951-2025)
2. Copernicus Land Monitoring Service, Global Land Cover raster files at 100m resolution.
CAVEATS

These results are not based on case data, they represent the climatic suitablity for malaria transmission based on climatic data and consensus thresholds. This indicator models the suitability for transmission, it does not at present take into account control efforts that might limit the impact of climate changes on malaria, however, conversly, the influence that control efforts have could be hampered by an increasingly warm world.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

Malaria is widely recognised as a climate-sensitive infectious diesase due to the climate sensitivity observed in both the vector, Anopheles mosquitoes, and the Plasmodium parasites. With temperature, precipitation, and relative humidity all climate factors that influence the abundance and feeding cycle rate of Anopheles mosquitoes and temperature also driving the development rate of Plasmodioum parasties within the mosquito vectors. This indicator tracks the influence of the changing climate on the length of the transmission season for Plasmodium falciparum malaria with a threshold-based model that incoporates precipitation accumulation, average temperature, and relative humidity.

DATA DOWNLOAD

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INDICATOR AUTHORS

Dr. Gina E C Charnley, Prof. Rachel Lowe

1.3.3 West Nile

Changing climatic conditions, such as shifts in seasonal tempertures and precipitation levels, are altering the transmission potential of many vector-, water-, food-, and air-borned infectious diseases. WNV is a mosquito-transmitted pathogen that can cause severe disease with central nervous system involvement in birds, humans, and other mammals. With temperatures changing across the globe, this indicator tracks how this is affecting the climate suitability for these infections.

HEADLINE FINDINGS

The temperature suitability for West Nile virus transmission has increased by 0.7% from 1951-1960 to 2015-2024.
DATA SOURCES

1. European Centre for Medium-Range Weather Forecasts Reanalysis 5th Generation-Land monthly averaged data from 1981 to present. Copernicus Climate Change Service Climate Data Store. Accessed in 2023.
2. Transmission of West Nile and five other temperate mosquito-borne viruses peaks at temperatures between 23oC and 26oC. eLife 2020. Shocket MS, Verwillow AB, Numazu MG et al.
CAVEATS

Although the indicator considers three key WNV mosquito species that enable good spatial coverage, some regionally important species are not included such as Cx. modestus in Europe and Cx. annulirostris in Australia. This indicator uses the climatic impact of temperature on the WNV transmission but as yet does not include other changes in climatic conditions such as altered precipitation patterns and frequency of droughts which can also affect local conditions for WNV mosquitos and transmission.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator tracks the thermal suitability of WNV taking into account the mosquito species-specific responses to temperature and models changes in its basic reproduction number driven by the changing climate to estimate the R0 (the expected number of secondary infections resulting from one infected person).

DATA DOWNLOAD

Click here to download the indicator data.
INDICATOR AUTHORS

Julian Heidecke, Prof Joacim Rocklöv, Dr Marina Treskova

HEADLINE FINDINGS
DATA SOURCES
CAVEATS
INDICATOR DESCRIPTION
INDICATOR AUTHORS

HEADLINE FINDINGS

Compared to 1951-1960, the area climatically suitable for Rhipicephalus sanguineus and Hyalomma ticks in 2015-2024 had expanded by 6.9% and 3.2%, respectively – putting an additional 364 million people at risk
DATA SOURCES

1. European Centre for Medium-Range Weather Forecasts Reanalysis 5th Generation-Land monthly averaged data from 1981 to present. Copernicus Climate Change Service Climate Data Store.
2. Global Biodiversity Information Facility Ticksbase. 2005-2024
3. United Nations Development Programme. Human Development Index 1990-2024
4. NASA. NASA Shuttle Radar Topography Mission Global 1 arc second. 2014.
5. Copernicus Land Monitoring Service. Global Dynamic Land Cover Service. 2019.
6. NASA Socioeconomic Data and Applications Center Gridded Population of the World (GPWv4) 2000-2020
CAVEATS

This indicator shows the potential boundaries for tick transmission, not actual disease presence, as factors like wildlife hosts and geographic barriers are not included. The presence of ticks doesn’t guarantee infection with diseases. A constant land use is assumed due to limited long-term data, but plans for sensitivity analyses will explore land cover changes over time. Validation was limited to tick presence data from 2005–2024. Further validation using human case records tied to specific tick vectors is possible but may be challenging for diseases with low case numbers.

This indicator is new to the 2025 report and was last updated in October 2025
INDICATOR DESCRIPTION

This new indicator tracks the environmental suitability for tick species that act as the primary vectors for the majority of human cases of tick-borne disease globally (Ixodes spp., Hyalomma spp., Rhipicephalus sanguineus, and Amblyomma cajennense) It uses a threshold-based model that incorporates temperature, humidity, daylength, and land cover requirements specific to different tick species.

DATA DOWNLOAD

Click here to download indicator data.
INDICATOR AUTHORS

Dr Adrià San José Plana, Dr Gina E C Charnley, Prof. Jan Semenza & Prof. Rachel Lowe

1.3.6 Vibrio

Changing climatic conditions, such as shifts in seasonal tempertures and precipitation levels, are altering the transmission potential of many vector-, water-, food-, and air-borned infectious diseases. Vibrio bacteria are found in brackish marine waters and cause a range of human infections, including gastroenteritis, wound infections, sepsis and cholera. With temperatures changing across the globe, this indicator tracks how this is affecting the environmental suitability for pathogenic Vibrio in coastal areas.

HEADLINE FINDINGS

A record-high 91,195 km of coastline waters showed environmental conditions suitable for Vibrio transmission in 2024 – a 3·2% increase from the previous record in 2023.
DATA SOURCES

1. Global Ocean OSTIA Sea Surface Temperature and Sea Ice Reprocessed dataset between 1982-2022. Accessed in 2023.
2. Mercator Ocean Reanalysis, 2021. Copernicus Marine Service.
3. AWI-CM-1-1-HR and CNRM-CM6-1-HR sea surface temperatures and sea surface salinity from CMIP6 (2015-2100) SSP126 and SSP370 experiments.
4. The Inter-Sectoral Impact Model Intercomparison Project. ISIMP3b Bias Adjustment. 2022.
5. The World Factbook. 2023. CIA
CAVEATS

These results are not based on case data, they represent the suitability for pathogenic Vibrio infections on the basis of sea surface temperature and sea surface salinity conditions. This indicator does not include other potentially important drivers (e.g. globalisation).

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

The environmental suitability for infections from Vibrio species incorporates sea surface temperature and salinity to report the lengths of coastlines in Km that experience suitable conditions for Vibrio infections and the period of time in days per year of suitable conditions for Vibrio infections.

DATA DOWNLOAD

Click here to download the indicator data.
INDICATOR AUTHORS

Prof Jaime Martinez-Urtaza, Prof Jan C. Semenza, Joaquin A. Trinanes

Food security and Undernutrition

The number of undernourished people worldwide has been steadily increasing since 2014. This indicator uses changes in climate to track risks to marine food security and separately, to track the impact on incidence of food insecurity. Through multiple and interconnected pathways, climate change is exacerbating food insecurity; by undermining crop yields, affecting labour capacity of agricultural workers, elevating coastal sea surface temperatures, reducing oxygenation of the world's oceans, causing ocean acidification and coral reef bleaching, and disrupting supply chains. As climate change increases temperatures and alters weather patterns impacting food production, this indicator tracks the change in global food insecurity.

HEADLINE FINDINGS

The higher frequency of heatwave days and drought months in 2023 compared to 1981–2010, is associated with 123.7 million more people experiencing moderate or severe food insecurity
DATA SOURCES

1. European Centre for Medium-Range Weather Forecasts Reanalysis 5th Generation (ERA5) hourly and monthly climate data (2m air temperature). Copernicus Climate Change Service (C3S) Climate Data Store (CDS).
2. Food and Agricultural Organization of the United Nations Food Insecurity Experience Scale.
3. Ocean Reanalysis System 5 Global Ocean Reanalysis Monthly Data from 1958 to 2024. C3S CDS.
4. FAO Fisheries and Agriculture, global aquaculture production value (1984-2022)
5. 2019 Global Burden of Disease Study, 2020. Institute for Health Metrics and Evaluation.
6. 12-month Standardised Precipitation Evapotranspiration Index (SPEI-12)
7. FAO Fisheries and Agriculture, global capture production value (1984-2022)
CAVEATS

For the marine food component of the indicator, fish production data was used as a proxy for fish consumption, whilst this is not a completely accurate assumption, there is no comprehensive alternative source of data for all the investigated countries. For the food insecurity component of the indicator, it is possible that there is recall bias in the survey data and additional bias may have been introduced to interviews during the pandemic because interviews were conducted by phone instead of in-person visits.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator consists of two sub-indicators:
1) Terrestrial food security and undernutrition: Tracks change in the proportion of the population reporting moderate or severe food insecurity due to anomalies in heatwave days and frequency of drought months occurring during four major crop (maize, rice, sorghum, and wheat) growing seasons compared to 1981-2010.
2) Marine food security and undernutrition: Tracks risks to marine food security by monitoring changes in sea surface temperature and the consumption of farmed- or catch-based fish products.

DATA DOWNLOAD

Click here to download the indicator data.
INDICATOR AUTHORS

Prof Shouro Dasgupta, Prof Elizabeth Robinson, Prof Maziar Moradi-Lakeh, Dr Fereidoon Owfi, Dr Mahnaz Rabbaniha, Prof Meisam Tabatabei

2.1.1 / 2.1.2 National Assessments of Climate Change Impacts, Vulnerability, and Adaptation for Health

The health impacts of climate change vary by location and population need, vulnerability and adaptation assessments form an essential first step in building local resilience tailored to the location. This indicator tracks the development of national health and climate change strategies and plans, and barriers to implementation, as well as the number of countries that report having conducted a climate change and health vulnerability and adaptation assessment adn those with national adaptation plans for health.

HEADLINE FINDINGS

As of March 2025, 58.0% (112/193) of WHO member states reported having ever completed a vulnerability and adaptation assessment.
DATA SOURCES

1. World Health Organization. Alliance for action on climate change and health (ATACH). Accessed 2025
2. 2021 World Health Organization Health (WHO) and Climate Change Global Survey Report, 2021. WHO.
CAVEATS

The global survey sample is not a representative sample of all countries as this survey was voluntary; however, the inclusion of 95 countries in this survey, despite a global pandemic, demonstrates significant global coverage.
Data for this indicator represent the total number of countries that had made a commitment to the COP26 Health Programme as of March 2024. For the most recent list of commitments please see the ATACH website at: https://www.atachcommunity.com/our-impact/progress-tracker/

This indicator was last updated in March 2025
INDICATOR DESCRIPTION

This indicator draws on the 2021 World Health Organization (WHO) Health and Climate Country Survey, which was completed by 90 member states and non-member territories with representation from all 6 WHO regions as a baseline for the COP26 commitments with updates on the progress until 2025 coming from regional and country reporting through The Alliance for Transformative Action on Climate and Health (ATACH). It tracks the development of national health and climate change assessments and completion of a health national adaptation plan.
INDICATOR AUTHORS

Dr Diarmid Campbell-Lendrum

HEADLINE FINDINGS

As of March 2025, 60.1% (116/193) of WHO member states reported having ever completed a Health National Adaptation Plan (HNAP).
DATA SOURCES

1. World Health Organization. Alliance for action on climate change and health (ATACH). Accessed 2025
2. 2021 World Health Organization Health (WHO) and Climate Change Global Survey Report, 2021. WHO.
CAVEATS

The global survey sample is not a representative sample of all countries as this survey was voluntary; however, the inclusion of 95 countries in this survey, despite a global pandemic, demonstrates significant global coverage.
Data for this indicator represent the total number of countries that had made a commitment to the COP26 Health Programme as of March 2024. For the most recent list of commitments please see the ATACH website at: https://www.atachcommunity.com/our-impact/progress-tracker/

This indicator was last updated in March 2025
INDICATOR DESCRIPTION

This indicator draws on the 2021 World Health Organization (WHO) Health and Climate Country Survey, which was completed by 90 member states and non-member territories with representation from all 6 WHO regions as a baseline for the COP26 commitments with updates on the progress until 2025 coming from regional and country reporting through The Alliance for Transformative Action on Climate and Health (ATACH). It tracks the development of national health and climate change assessments and completion of a health national adaptation plan.
INDICATOR AUTHORS

Dr Diarmid Campbell-Lendrum

HEADLINE FINDINGS

In 2024, 834 (97%) of 858 cities reported having completed, being in the process of conducting, or expecting to conduct city-level climate risk and vulnerability assessment .
DATA SOURCES

1. 2024 Carbon Disclosure Project (CDP) Annual Cities Survey, 2024. CDP.
CAVEATS

This is a self-reported, non-compulsory survey so data provided may be subjective and response rates can fluctuate, with low uptake in certain areas, particularly the Eastern Mediterranean Region and among cities in low human development index countries.

This indicator was last updated in May 2025
INDICATOR DESCRIPTION

This indicator draws on data from the Carbon Disclosure Project annual Cities Questionnaire, assessing the number of global cities that have undertaken a city-wide climate change risk or vulnerability assessment and the reported climate-related health impacts and vulnerabilities of these cities.
INDICATOR AUTHORS

Prof Karyn Morrisey

2.2.1 Climate Information for Health

Climate services for health are essential to help the health sector conduct research and make climate informed decisions for planning, preparedness, and response to climate-senstivie diseases, extreme weather, and other environmental hazards. They can also provide early warning systems, triggering responses in communication to the public and preparedness of health services and human resources. This indicator tracks the number of national meteorological and hydrological services that are providing services to the health sector.

HEADLINE FINDINGS

In 2024, 161 (83%) of 193 World Meteorological Organization members reported providing climate services for the health sector.
DATA SOURCES

1. World Meteorological Organization (WMO) Climate Services Dashboard (Accessed 30 March 2025)
CAVEATS

The current data source from WMO only considers climate services ) national meteorological and hydrological services (NMHS). It is unclear the degree to which other providers, such as academic institutions and research projects, private sector products, products from other Ministries, or regional and global products and services are being used, in proportion to services made available by NMHS. The open questionnaire can be updated at any time by WMO members, therefore the figures reported here may change over the year. As each country may update their profile information at different moments in time, snapshots do not reflect progress for any given year but rather information provided until a certain date.

The current questionnaire does not record the number of WMO members that do not provide climate services to the health sector and as the data is self-reported by countries it may therefore include reporting bias

This indicator was last updated in October 2025; the underlying WMO data were last updated in September 2023
INDICATOR DESCRIPTION

This indicator reports on the number of World Meteorological Organization (WMO) national meteorological and hydrological services (NMHS) providing climate services to the health sector and is calculated based on self-reported information provided by NMHS through the Country Profile Database Integrated questionnaire. The data reflect answers to a question about which user sectors NMHS provide with climate information. The questionnaire is one of the main sources of information to the WMO Country Profile database and is open all year round for WMO members to update their profile information.
INDICATOR AUTHORS

Dr Joy Shumake-Guillemot

2.2.2 Air Conditioning: Benefits and Harms

Heatwaves are among the most immediate and severe of the health impacts of climate change. A variety of adaptation strategies exist, from effective ventilation and building regulations to air conditioning for selected populations. Access to household air conditioning is highly protective against heatwave-related mortality. However, its use also contributes to air pollution, greenhouse gas emissions, increased urban heat island effect, and can widen health inequities and energy poverty. This indicator tracks the coverage of household air conditioning use, premature deaths from ambient PM 2.5 exposure due to electricity use and CO2 emissions due to air conditioning.

HEADLINE FINDINGS

Since 2000, the share of households with air conditioning has nearly doubled, reaching 37% in 2023, potentially saving 114,000 lives annually.
While 48% of households in High and Very High HDI countries had air conditioning, only 2% in Low HDI countries did.
DATA SOURCES

1. Cooling dataset from 2000-2023, 2023. International Energy Agency.
CAVEATS

The data available for electricity final consumption for air conditioning were at the country or region level. Thus, in a given country/region, it was assumed that the electricity market is completely connected, so that the share of electricity used for air conditioning can be equally applied to power plant emissions throughout the country/region. This assumption may not be accurate, especially for larger countries/regions. This indicator does not consider the generation of electricity by renewable energy and/or more efficient air conditioning technology, which would reduce both CO2 emissions and the number of premature deaths due to PM 2.5 emissions from air conditioning.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

Using data from the International Energy Agency, this indicator calculates the global proportion of households using air conditioning. It also uses this International Energy Agency data to estimate electricity usage and PM 2.5-attributable premature mortality due to air conditioning use.
INDICATOR AUTHORS

Dr. Matthew R. Smith

2.2.3 Urban Green and Blue Spaces

Access to urban green space provides benefits to human health by reducing exposure to air and noise pollution, relieving stress, providing a setting for social interaction and physical activity, and reducing all-cause mortality. In addition, green space sequesters carbon and provides local cooling that disrupts urban heat islands and reduces the risk of urban floods by reducing water runoff, benefiting heat and climate adaptation. This indicator tracks the availability of greenspace in urban areas around the world.

HEADLINE FINDINGS

In 2024, exposure to urban greenspace remained practically unchanged from the 2015-2020 average (+0.2%), with individual city changes ranging from -34% to +69%.
DATA SOURCES

1. Global Human Settlement Programme of the European Commission (GHS) used to identify urban centers.
2. Population size identified from JRC GHSL.
3. Satellite data were downloaded from the publicly available Landsat satellite, a joint program of the US Geological Survey and NASA.
4. MODIS landcover data set.
5. Global climate regions from the Köppen Climate Classification System.
CAVEATS

This indicator does not provide information on quality or type of green space, nor on its accessibility. In tracking urban areas as defined by the Global Human Settlement Program, this indicator does not focus on administrative city boundaries, but rather on effective urban developments. Missing values from the GHS or Landsat data due to cloud cover or other factors limit the generalisability of the findings.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator reports population-weighted Normalized Difference Vegetation Index (NDVI) as a proxy for green space exposure in 1,038 urban centres that have more than 500,000 inhabitants or are the most populous centres in countries unrepresented by the 500,000 threshold, as identified by the Global Human Settlement programme of the European Commission. Green space is detected through remote sensing of green vegetation, making use of the satellite-based NDVI.

DATA DOWNLOAD

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INDICATOR AUTHORS

Dr Greta K. Martin, Dr Jennifer D. Stowell, Prof Patrick Kinney

2.2.4 Detection, Preparedness, and Response to Health Emergencies

Health sector preparedness and response to acute public health emergencies related to climate change is an essential component of any adaptation response. With the climate suitability for the transmission of multiple infectious diseases increasing in many locations, reducing the risk of outbreaks and epidemics requires robust health emergency preparedness. This indicator reports on the implementation of the legally-binding International Health Regulation core capacities on health emergency management.

HEADLINE FINDINGS

In 2024, 135 (69%) of 196 WHO member states reported having high-to-very-high implementation of health emergency management capacity, an increase of 4 countries with respect to 2023.
DATA SOURCES

1. International Health Regulations (2005) Annual Reporting. Data were downloaded from the electronic IHR State Parties Self-Assessment Annual reporting Tool (e-SPAR) for 2023.31 https://extranet.who.int/e-spar
CAVEATS

IHR monitoring questionnaire responses are self-reported, and the responding countries differ from year to year. The core capacities tracked by this indicator are not specific to climate-driven risk changes, and they capture potential capacity – not action. Finally, it does not measure the quality of surveillance, nor the effectiveness of emergency response plans.

This indicator was last updated in March 2025
INDICATOR DESCRIPTION

This indicator monitors the implementation of the International Health Regulation core capacities on health emergency management tracked through the World Health Organization annual monitoring questionnaire. The survey is a checklist of 20 indicators specifically developed to monitor the development and implementation of 13 IHR capacities. This method of estimation calculates the proportion of attributes reported to be in place in a country.
INDICATOR AUTHORS

Dr Yasna Palmeiro-Silva

HEADLINE FINDINGS

In 2024, 66% of 454 public health and 72% of 147 medical institutions worldwide provided climate and health education, reaching 20% of students enrolled in public health and 64% of those in medical education.
DATA SOURCES

1. The data utilized for analysis is derived from survey responses provided by 454 degree-granting public health institutions and 147 degree-granting medical institutions between October 2024 and February 2025.
CAVEATS

The results from these surveys provide valuable insights into the current state of climate and health education and training at public health and medical institutions. However, there are several potential limitations inherent in the methodology. Fewer institutions in countries with a low or medium HDI responded to the surveys compared to those with a high or very high HDI. Importantly, because the survey relies on voluntary participation, results may be biased towards responses from institutions already providing climate and health education and training, who may be more motivated to participate. Further, the indicator relies upon self-reported information from faculty or curriculum committee members. This introduces the potential for bias, as respondents may overestimate or underestimate the extent of climate and health education offered at their institution. Efforts to enable global participation by partnering with regional public health and medical associations, as well as offering the survey in multiple languages, were made. However, language barriers and distribution challenges could still have limited participation from certain regions or institutions. Furthermore, public health institutions saw higher participation rates compared to medical schools, with the public health survey available in more languages and in its second year of data collection. In contrast, the medical schools survey was launched this year and still requires additional translations for broader accessibility.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator builds on an international survey of degree-granting public health education institutions to assess the current state of climate and health education and training among them. To enable global participation and dissemination of the survey instrument, the Global Consortium on Climate and Health Education (GCCHE) partnered with the Global Network for Academic Public Health, which consists of eight regional public health associations, representing over 550 public health schools from 105 countries. Responses to the survey in 2023 were received from 279 public health education institutions.

DATA DOWNLOAD

Click here to download indicator data.
INDICATOR AUTHORS

Dr Cecilia Sorensen, Dr Ying Zhang

2.3.1 Vulnerability to Severe Mosquito-Borne Disease

The spread of Aedes-borne diseases is rapidly increasing, fuelled by climatic changes (indicator 1.3), people movement, and urbanisation. Vulnerability to dengue infections in particular are affected by physiological, social, financial, and geographical factors, as well as a community’s capacity to adapt. This indicator captures the relative vulnerability to severe Aedes-borne disease outcomes by combining increased susceptibility from urbanisation, and coping capacity from improved healthcare access and quality.

HEADLINE FINDINGS

Global vulnerability to severe dengue increased by 32% from 1990-1999 to 2015-2024, with High HDI countries seeing the largest increase (56.3%).
DATA SOURCES

1. Global Burden of Disease Collaborative Network. Global Burden of Disease Study 2021 (GBD 2021) Results. Seattle, United States: Institute for Health Metrics and Evaluation (IHME), 2021. Available from https://vizhub.healthdata.org/gbd-results/. [Visited on 31 March 2025]
2. World Bank, World Development Indicators. Urban population (% of total population). Available from: https://data.worldbank.org/indicator/SP.URB.TOTL.IN.ZS Urban population refers to people living in urban areas as defined by national statistical offices. The data are collected and smoothed by United Nations Population Division. [Visited on 17 February 2025]
3. World Bank, World Development Indicators. Population, total. Available from: https://data.worldbank.org/indicator/SP.POP.TOTL [Visited on 17 February 2025]
CAVEATS

This indicator is extrapolated to country level; no estimations at subnational level to differentiate vulnerability between rural and urban settings were performed.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator tracks the vulnerability of countries to severe adverse health outcomes from Aedes-borne diseases (Dengue, Chikungunya, and Zika) considering urban population as a susceptibility variable and health care access and quality as a coping capacity variable, during the period of consideration 1990-2021.

DATA DOWNLOAD

Click here to download indicator data.
INDICATOR AUTHORS

Prof Jan C. Semenza, Dr Yasna Palmeiro-Silva

2.3.2 Lethality of Extreme Weather Events

The frequency, intensity, and duration of extreme weather events is increasing worldwide due to anthropogenic climate change. Droughts, storms, wildfires, floods, and extreme temperatures all impact human health. Well-implemented adaptive measures can help avoid a proportional increase in deaths. As the world faces increasingly turbulent weather patterns, this indicator tracks the changing risk of death from climate-related extreme events – defined as the proportion of people affected that died in the event – and the proportion of events that were deadly.

HEADLINE FINDINGS

Adjusted for HDI, countries with Health Early Warning Systems (HEWS) showed a significantly faster decline in the annual mortality rate from floods and storms from 2000 to 2024 than countries without HEWS (3.2% vs 1.6% decrease per year, p<0.001).
DATA SOURCES

1. EM-DAT at the Centre for Research on the Epidemiology of Disasters (CRED) at the Université Catholique de Louvain, Belgium.

2. World Bank, World Development Indicators. Population, total.

3. 2021 WHO Health and Climate Change Global Survey.
CAVEATS

There is a possible bias in missing some disaster events because of under-reporting. Similarly, there are likely biases in how countries report both the number of deaths and people affected. Numbers of deaths may not include mortality from the cascading risks of natural disasters that occur as a result of longer causal chains from the hazard. Estimates of the numbers of people affected have different biases for different countries because of how the concept of “affected people” is defined.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator captures the number of occurrences of weather-related disasters (drought, storms, wildfires, floods and extreme temperatures), the number of people affected in each disaster, and the lethality of these events.

DATA DOWNLOAD

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INDICATOR AUTHORS

Prof Dominic Kniveton, Dr Yasna Palmeiro-Silva

2.3.3 Migration, Displacement, and Rising Sea Levels

Sea level rise can affect human health through episodic flooding, permanent inundation, erosion, soil and drinking water contamination, vector- and water-borne disease, livelihood security, and mental health impacts. In a world where sea levels are rising and populations are growing in areas at risk, this indicator tracks current population exposure to future rising sea levels. Populations can adapt in situ to rising sea levels, however, environmental factors can cause people to relocate – either forced or otherwise – or render them immobile. Reviewing national policies serves as an indicator of how governments perceive the climate change, (im)mobility, and health links and monitors policies that connect climate change and migration.

HEADLINE FINDINGS

In 2024, 156.7 million people were living less than 1 m above current sea levels.
As of December 2024, 59 national policies identified across 44 countries connected climate change and migration while mentioning health.
DATA SOURCES

1. GMSLR: Estimated global mean increases in sea-levels.

2. Elevation: Coastal Digital Elevation Model (CoastalDEM)

3. Hybrid gridded demographic data for the world.

4. Global Administrative Areas (GADM) version 4.0.4, http://www.gadm.org/
CAVEATS

Estimates of population exposure to global mean sea level rise vary according to the input datasets, timeframes and geographic scales, the parameters that are set for emissions and socioeconomic scenarios, and methods of analysis. Many factors, including adaptive strategies, influence population displacement due to sea level rise and some populations may not move due to lack of necessary resource to escape sites of risk or may remain in location due to social, cultural or political reasons. Additionally, other climate impacts and demographic factors contribute to migration into low-lying coastal sites.
The analysis of national-level policies was mainly confined to those documents written in English, with a few other languages on occasion – the numbers reported must therefore be taken as the minimum.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

The first part of this indicator uses a bathtub model, overlaying future global mean sea level rise of 1m with coastal elevation to define areas of potential inundation, then uses gridded population data to estimate the current population at risk of exposure to 1m global mean sea level rise. The second part looking at national policies connecting climate change and migration reports on the number of national-level policies that include legislation for migrants related to climate change (including displaced and relocated peoples) and the number of such policies that mention health or well-being.

DATA DOWNLOAD

Click here to download data on populations living within 1m of sea level.

Click here to download data on migration policies.
INDICATOR AUTHORS

Dr Sonja Ayeb-Karlsson, Dr Shouro Dasgupta, Prof Ilan Kelman, Prof Celia McMichael

3.1.1 Energy Systems and Health

The energy sector is the largest single contributor to global greenhouse gas (GHG) emissions, accounting for approximately 68% of the total. The transition towards zero-emission energy is key for human health and survival: it can not only result in reduced emissions and increased efficiency, but can also improve air quality, equitable and stable access to energy, and ultimately reduce inequities, improve health, and protect people from the life-threatening risks of climate change.

Coal combustion continues to be a major contributor to emissions from the energy sector and is a major contributor to premature mortality due to air pollution. Coal phase-out is therefore crucial to protect people’s health from immediate harms, as well as for those posed by climate change.

Continued growth in renewable energy, particularly wind and solar sources, is key to replacing fossil fuels to increase access to clean energy and electricity generation for a more equitable and decentralised modern energy system.

HEADLINE FINDINGS

Global energy-related emissions grew by 1.6% during 2023, pushing associated CO2 emissions to a new all-time high.
DATA SOURCES

1. CO2 Emissions From Fuel Combustion: CO2 Indicators. International Energy Agency.
2. World Extended Energy Balances, 2024. International Energy Agency.
CAVEATS

IEA data are generated using both direct input from national governments and modelling. As such, while they represent the best available data on national CO2 emissions from fuel, they are subject to caveats which vary by energy commodity and country. Full details are given in the CO2 Emissions from Fuel Combustion documentation & IEA World Energy Balances documentation.

This documentation also covers changes to methodology in previous editions of IEA World Energy Balances. A typical example of the way data can be impacted by methodology updates by reporting countries is as follows, relating to Belgium ‘New data on consumption cause breaks in time series for primary solid biofuels between 2011 and 2012’. However, since data are aggregated, the impacts on overall trends is minimal.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

“This indicator includes three components: 1) the carbon intensity of the energy system, 2) coal phase out, and 3) use of renewables.

This indicator tracks the carbon intensity of the energy system, both at global and regional scales, expressed as the CO2 emitted per terajoule of the total primary energy supply from 1990-2022 and global CO2 emissions from energy combustion by fuel in GtCO2 from 1990-2022.

This indicator also reports on progress towards a global phase-out of coal, tracking the total primary energy supply from coal and coal’s share of total electricity generation.

Finally, this indicator tracks electricity generation and the share of total electricity generation from all low-carbon sources (nuclear and all renewables, including hydro) and renewables (wind and solar, excluding hydro and biomass).

DATA DOWNLOAD

Underlying data can be accessed from the International Energy Agency’s CO2 Emissions in 2023 report.
INDICATOR AUTHORS

Dr Shih-Che Hsu, Dr Harry Kennard, Professor Ian Hamilton

HEADLINE FINDINGS

The proportion of household energy coming from harmful solid biomass dropped from 28% in 2016 to 26% in 2022. However, 88% of the energy in Low, and 64% of the energy in Medium HDI countries still came from solid biomass in 2022.
DATA SOURCES

1. Healthy fuels for cooking were provided by the WHO.
2. World Extended Energy Balances, 2024. International Energy Agency.
CAVEATS

IEA data are generated using both direct input from national governments and modelling. As such, they are subject to caveats which vary by energy commodity and country. Full details are given in the IEA World Energy Balances documentation.

This documentation also covers changes to methodology in previous editions of IEA World Energy Balances. A typical example of the way data can be impacted by methodology updates by reporting countries is as follows, relating to Belgium ‘New data on consumption cause breaks in time series for primary solid biofuels between 2011 and 2012’. However, since data are aggregated here by HDI level, the impacts on overall trends is minimal.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator draws on data from the IEA extended global residential modelling to monitor the sources of energy used in people’s homes, using WHO guidance to assess what fuels are “clean.” The indicator is also underpinned by the national surveys collected by World Health Organization and tracks the proportion of the population who use clean fuels and technologies for cooking, defined as those that have emission rate targets meeting World Health Organization’s 2005 guidelines for air quality.
INDICATOR AUTHORS

Dr Shih-Che Hsu, Dr Harry Kennard, Professor Ian Hamilton

3.1.3 Sustainable and Healthy Road Transport

Building cities and transport systems which encourage cycling and physical activity will help respond to climate change and improve public health. Transitioning to cleaner fuels for road transport will work alongside this to reduce the health impacts of air pollution. However, unless active travel infrastructure is rolled out with consideration of sociocultural inequities, the benefits may not be equally manifested across all groups.

HEADLINE FINDINGS

Despite rapid uptake of electric vehicles, less than 0.38% of global road transport energy was supplied by electricity in 2022, up from 0.28% in 2021.
DATA SOURCES

1. Fuel use data is from the IEA, World Extended Energy Balances 2024.
2. UN Population estimates, 2022 edition.
CAVEATS

This indicator captures change in total fuel use and type of fuel use for transport, but it does not capture shifts in modes of transport used. In particular, it does not capture walking and cycling for short trips, which can yield substantial health benefits through increased physical activity.

Alongside the fossil fuel combustion pollutants, tyre wear accounts for an estimated 3–7% of airborne PM2.5 particulates worldwide.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator tracks the share of overall road transport energy by fuel type using data from the IEA.
INDICATOR AUTHORS

Dr Shih-Che Hsu, Dr Harry Kennard, Professor Ian Hamilton

HEADLINE FINDINGS

Deaths attributable to ambient PM2.5 from fossil fuel combustion decreased by 5.8 % from 2.68 million in 2010 to 2.52 million in 2022.
DATA SOURCES

1. Energy: IEA World Energy Balances for 2024 and World Energy Statistics 2024
2. Non-energy related activities: Agricultural livestock data are based on FAO statistics and projections and fertiliser use is based on data from the International Fertilizer Association
3. WHO household energy database for splitting urban and rural use of fuels for cooking
4. UN World Population Prospects, 2017 update
CAVEATS

The indicator relies on model calculations which are inherently uncertain. The resolution of approximately seven to ten km is deemed appropriate for urban background levels of PM2.5 but may underestimate exposure in case of strong local PM2.5 increments. The meteorology year is fixed to 2015 (outside Europe) and 2016-2020 (Europe domain).

Uncertainty in the shape of concentration-response functions make the quantification of health burden inherently uncertain. Different risk models (like integrated exposure-response relationships used by Global Burden of Disease studies, the Fusion risk model used here, or linear relationships recommended by WHO Europe) lead to different estimates of attributable deaths.
Premature mortality from exposure to fossil fuel based ambient air pollution calculated for the Lancet Countdown results in significantly lower estimates of premature mortality compared to a recent paper by Lelieveld et al. (2023) which utilises the same CRFs.297 Many aspects of the approaches between Lelieveld et al. (2023) and Lancet Countdown differ. A full analysis and quantification of differences is beyond the scope of the current study, however, the most important factors are:
(1) Emission estimates of source pollutants
(2) Modelling of ambient PM2.5
(3) The treatment of natural PM2.5 and application of a theoretical minimum-risk exposure level (TMREL)
(4) The research question and approach taken

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator quantifies contributions of individual source sectors and fuels to ambient PM2.5 exposure and its health impacts. Estimates of sectoral source contributions to annual mean exposure to ambient PM2.5 were calculated using the GAINS model, which combines bottom-up emission calculations with atmospheric chemistry and dispersion coefficients. Concentration-response functions (CRFs) for calculating human health impacts were taken from the “Fusion” risk model described by Burnett et al. (2022), which takes a meta-analysis of cohort studies and applies a fusion model to the log-linear function relating to PM2.5 exposure with mortality. Particularly this model decreases the derivative responses at high PM2.5 concentrations, which allows for the limiting of the attributable risk at extremely high PM2.5 concentrations. The Fusion CRFs are given for six mortality endpoints related to air pollution exposure (IHD, COPD, stroke, lung cancer, ALRI, and type 2 diabetes) as well as total non-communicable disease plus lower respiratory infection (NCD LRI). The mortality rate for each of the six disease endpoints was also calculated from the Fusion CRFs and these results were compared with those using the Global Burden of Disease (GBD) 2019 exposure-response relationships.

DATA DOWNLOADS

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INDICATOR AUTHORS

Dr Gregor Kiesewetter, Dr Shaohui Zhang

3.2.2 Household Air Pollution

Globally, 2.4 billion people still use dirty fuels and inefficient technologies to meet their household energy needs, leading to high concentrations of indoor air pollution. The persistent use of dirty fuels and inefficient technologies in the household sector leads to high levels of exposure to indoor PM2.5 air pollution (including the highly-toxic black carbon). With women and girls often tasked with household energy-related activities, the burden of disease associated with the air pollution from dirty fuels in the domestic sector falls disproportionately on them.

HEADLINE FINDINGS

In 2022, household use of dirty fuels and inefficient technologies for cooking and heating resulted in 2.3 million deaths and accounted for 7% of global CO2 emissions.
DATA SOURCES

1. Final energy use for each fuel types from IIASA GAINS model
2. Fuel Type: IIASA GAINS model via IEA
3. Stove Type
4. Emission factors for biomass and charcoal
5. Emission factors for coal and gas/LPG
6. Emission factors for country-based electricity mix generation
7. Country-based faction of the unsustainably harvested biomass, that is, non-renewable biomass

5. Global Household Air Pollution (HAP) database. World Health Organization.

6. Global Burden of 87 Risk Factors in 204 Countries and Territories, 1990–2019: A Systematic Analysis for the Global Burden of Disease Study 2019, 2020. GBD 2019 Risk Factors Collaborators.

7. Global Burden of Disease Study 2019 Results Tool. Institute for Health Metrics and Evaluation.
CAVEATS

The indicator captures variations in household PM2.5 exposure by fuel, stove type, and location, linking them to climate and health impacts.
1. Biomass CO2 uncertainty: Estimating CO2 from solid fuels is limited by unknown shares of non-renewable biomass. GAINS separates woodfuel, residues, and dung, but unsustainable harvesting data are incomplete. Biomass types were aggregated, except for countries like India where dung use is significant.

This indicator was last updated in October 2025
2. Energy data limits: Most GAINS household data are country-level; only 44 subnational datasets exist (e.g., China, India). Regional data apply one representative country, reducing precision.
3. Electricity CO2 excluded: CO2 from electricity isn’t estimated because the energy-source mix for household use is unclear and emission factors vary across countries and years. Regional data in GAINS prevent accurate national estimates.
INDICATOR DESCRIPTION

This indicator uses a Bayesian hierarchical model to estimate exposure to household air pollution by source of emission in 65 of the countries most dependent on dirty fuels and inefficient technologies for cooking and heating. The model accounts for socio-demographic and epidemiological characteristics and estimates attributable mortality through a comparative risk assessment.

DATA DOWNLOAD

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INDICATOR AUTHORS

Dr Nahid Mohajeri, Dr Shih-Che Hsu, Dr James Milner, Dr Jonathon Taylor, Prof Michael Davies

3.3.1 Emissions from Agricultural Production and Consumption

Food systems contribute around 30% of global greenhouse gas emissions, most of which originate from meat and dairy livestock, remaining incompatible with mitigation targets. As food systems become increasingly strained by environmental changes, supporting healthy, low-carbon diets will require shifts towards less polluting, more inclusive and resource-efficient foods and food production systems, with sustainable management practices and reduced reliance on fossil fuels. This will require robust regulation of the agricultural and food industries, protecting smallholder farmers and Indigenous food systems, and promoting equitable and inclusive access to agricultural technology that aligns with local cultures and beliefs.

HEADLINE FINDINGS

Global agricultural GHG emissions increased by 36% from 2000 to 2022, with red meat and dairy responsible for 55% of agricultural emissions in 2022
DATA SOURCES

1. National annual production of animal products items (tonnes) – FAOSTAT (2024 update)
2. National annual trade (country-country) of animal products items (tonnes) – FAOSTAT (2024 update)
3. Correspondence of items across item lists with different grouping – FAOSTAT
4. GHG production estimates including grassland and feed crop emissions (via Herrero et al. 2013 and Dalin et al. 2019) Definitions: Animal types: bovine cattle (beef and buffalo), sheep and goat ruminants, pigs, poultry (chicken, ducks, geese and turkeys)
5. National annual production of crops (tonnes) – FAOSTAT (2024 update)
6. National annual trade (country-country) of crop products (tonnes) – FAOSTAT (2024 update)
7. GHG emissions intensity of crop products for each country– provided Carlson et al. (2017)
8. Dalin C, Tuninetti M, Carlson K, et al. Variability, drivers and interactions of key environmental stressors from food production worldwide. EGU2019; 2019; Vienna: 21st EGU General Assembly; 2019
9. Carlson KM, Gerber JS, Mueller ND, et al. Greenhouse gas emissions intensity of global croplands. Nature Climate Change 2017; 7(1): 63
CAVEATS

This indicator measures GHG emissions from national food consumption, defined as domestic production plus net imports, excluding emissions from individual consumption. It includes production and organic soil cultivation but excludes transport, processing, storage, decomposition, and land-use change. Consumption-based emissions are on average 2.25% higher than production-based estimates. Food losses during production and transport are included, but decomposition emissions are excluded. Globally, 8–10% of anthropogenic GHG emissions are linked to food loss and waste, disproportionately higher in high-income countries.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

The methods to obtain GHG emission estimates for food products are in two sections, one covering livestock and the second covering crops. Since the 2023 update of this indicator, GHG emissions from agricultural production and consumption incorporate numerous fruits, vegetables, nuts, pulses and legumes and other crops. While these crops tend to have much lower GHG emission intensity than animal derived products, their inclusion provides a fuller picture of the agricultural commodities used in the global food system.

DATA DOWNLOAD

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INDICATOR AUTHORS

Dr Carole Dalin, Dr Harry Kennard

HEADLINE FINDINGS

Between 2021 and 2022, deaths related to unhealthy diets increased from 148 to 150 per 100,000 people, reaching 11.8 million, including 1.9 million deaths from excessive red meat and dairy intake
DATA SOURCES

1. Food consumption data: Food availability data adjusted for food wasted at the point of consumption, and for the energy requirements to sustain measured levels of body weight, height, and physical activity.
2. Weight estimates: Baseline data from pooled analysis of measurement studies differentiated by sex and age with global coverage.
3. Relative risk estimates: Adopted from meta-analysis of prospective cohort studies. The certainty of evidence for the risk-disease associations were rated as moderate to high by NutriGrade.
4. Mortality and population data: Adopted from the Global Burden of Disease project by country, sex, and age group.

7. Body-mass Index and All-cause Mortality: Individual-participant-data Meta-analysis of 239 Prospective Studies in Four Continents, 2016. The Global Mortality Collaboration.

Full data sources can be found in the report appendix.
CAVEATS

In this comparative risk assessment, relative risk factors from nutritional epidemiology were used, acknowledging limitations such as small effect sizes, measurement errors, and potential residual confounding. Risk-disease relationships were assumed to be causal, supported by dose-response meta-analyses, biological plausibility, and experimental evidence. Associations that lost significance in fully adjusted models, particularly for milk and fish intake, were omitted. Evidence quality for all included risk-disease pairs was rated moderate or high (NutriGrade), with ten of twelve associations considered probable or convincing by expert groups. Exposure data were derived from food availability estimates adjusted for consumption waste, providing a comparable proxy across countries and reflecting regional energy intake differences, while avoiding underreporting issues inherent to dietary surveys.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator is based on a comparative risk assessment of diet and weight-related diseases using risk-disease relationships from meta-analyses of epidemiological cohort studies, updated data on food intake, body weight, and population numbers, and projections of cause-specific mortality. Baseline food consumption was estimated by adopting estimates of food availability from the Food and Agriculture Organization of the United Nations’ food balance sheets, linking food consumption data disaggregated by sex and age and adjusted for food waste at point of consumption to estimate exposure.

DATA DOWNLOAD

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INDICATOR AUTHORS

Prof Marco Springmann

Tree Cover Loss

Trees and forests are crucial carbon sinks and biodiversity reservoirs. They can also be a source of food, medicine, and knowledge, especially for Indigenous Peoples. Poor tree cover and forest conservation exacerbates climate change, and increases the risk of forest fires, zoonotic diseases, and allergies. Understanding the patterns of tree cover loss is vital for supporting climate strategies and public health. This indicator uses satellite data to track the loss of vegetation.

HEADLINE FINDINGS

In 2023, global tree cover loss increased to over 28 million hectares (up 24% from 23 million in 2022), with unprecedented wildfire-driven losses in Canada.
DATA SOURCES

1. Tree cover loss: Hansen/UMD/Google/USGS/NASA
2. Administrative boundaries: Global Administrative Areas database (GADM), version 3.6.
3. Tree Cover Loss by Driver: The Sustainability Consortium, World Resources Institute, and University of Maryland.
CAVEATS

1. Exclusion of Certain Disturbances: The model does not include disturbances such as insect outbreaks, wind and ice storms, flooding, or rivers changing course. These disturbances were found to be highly localized and temporally restricted, affecting only 1% of all model validation sample cells.

2. Misclassification Issues: There was low model accuracy for the commodity-driven deforestation class in Africa, with much of this deforestation misclassified as shifting agriculture. In northern forests, especially in Russia, distinguishing between drivers was challenging in areas where wildfires spread through previously logged areas or where logging occurred after a fire event.

3. Lack of Detailed Differentiation: The study did not map changes in forest conditions over time in landscapes dominated by shifting agriculture, nor did it differentiate primary from secondary forest clearing within this land-use class. Differentiating key drivers like row crops from pasturelands in South America or tree plantations from disturbed natural forests in Southeast Asia could enhance the analysis.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator uses satellite data to track the loss of vegetation five meters or taller, in areas with at least 30% tree cover density. As such, it covers the loss of forests, open woodlands, trees in agricultural settings and urban areas, and small patches of trees. To identify the various types of tree cover loss, such as deforestation, forestry, wildfire, urbanisation, and shifting agriculture, a decision tree model (recursive partitioning model) was used. Tree cover loss was defined as the disturbance of a stand or the complete removal of the tree cover canopy at the pixel scale of the satellite image. This loss can occur due to human activities, such as forestry practices like timber harvesting and deforestation, as well as natural causes like disease or storm damage. The data set does not indicate the stability or condition of land cover after the tree cover loss occurs or distinguish between natural and anthropogenic wildfires.

DATA DOWNLOAD

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INDICATOR AUTHORS

Prof David Rojas-Rueda

Healthcare Sector Emissions

The healthcare sector, which accounts for approximately one-tenth of global GDP, contributes to polluting emissions through its activities. To achieve decarbonisation and healthcare quality goals, health systems must tackle their emissions while improving healthcare access and quality. By prioritising improvements in energy efficiency, reducing inappropriate care, and selecting goods with fewer emissions, immediate benefits to care quality with fewer emissions can be realised.

HEADLINE FINDINGS

Following spikes in emissions related to the COVID-19 pandemic, healthcare-associated GHG emissions fell by 162% between 2021 and 2022, to 4.2% of global emissions.
DATA SOURCES

1. Environmentally extended multi-region input-output tables: EXIOBASE v3.9.4 model for year 2021.
2. Consumer Price Indices from the World Bank
3. Life Expectancy at Birth from the World Health Organization Global Health Observatory; the latest reporting year is 2021.
4. Per capita health expenditure data is from the World Health Organization’s Global Health Expenditure Database; the latest reporting year is 2021.
5. UN Sustainable Development Goal Indicator 3.8.1 Coverage of Essential Health Services from the World Health Organization’s Global Health Observatory; the latest reporting year is 2021.
CAVEATS

As only total health expenditure data are available from WHO, all expenditures are assigned to Final Demand, with no separation for investment. MRIO models are built from aggregated top-down statistical data. Results do not reflect individual health care systems’ power purchase agreements for renewable energy or any offsetting activities. Results do not include direct emissions of waste anaesthetic gases from clinical operations nor emissions from metered dose inhalers, as these are not currently reported consistently in national emissions inventories.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator quantifies healthcare sector emissions of GHGs, ozone and PM2.5 using a top-down spend-based method employing the environmentally-extended multi-region input-output (EE-MRIO) model EXIOBASE and health expenditure data, alongside epidemiological models of air pollution-related health damages. For the first time, it also estimates emissions by GHG Protocol Scope 1 (direct on-site emissions); Scope 2 (purchased energy); and Scope 3 (value chain). It matches per-capita greenhouse gas emissions data with the United Nations Development Programme Human Development Index to report healthcare-associated greenhouse gas emissions per capita per year, including direct emissions from healthcare facilities as well as emissions from the consumption of goods and services supplied by other sectors.

DATA DOWNLOAD

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INDICATOR AUTHORS

Dr Matthew Eckelman, Dr Jodi D. Sherman

4.1.1 Economic Losses due to Climate-Related Extreme Events

Climate-related extreme events can result in direct injury and death, increase the spread of water-borne diseases, and destroy habitats and infrastructure. Compounding this, these events often result in large economic costs, exacerbating the direct health impacts they produce through disruption of essential services and impacts on the socioeconomic determinants of health. This indicator tracks the insured and uninsured economic losses from weather-related exteme events, using data provided by Swiss Re.

HEADLINE FINDINGS

Global economic losses due to weather-related extreme events were US$304 billion in 2024. While 52.1% of losses were insured in Very High HDI countries in 2024, only 2.9%, 0.9%, and 7.2% of losses were insured in Low, Medium, and High HDI countries respectively.
DATA SOURCES

1. Sigma Explorer: Catastrophes Database, 2025. Swiss Re Institute.
2. World Economic Outlook Databases, 2024. International Monetary Fund.
CAVEATS

Only events with measurable economic losses above the threshold levels are included. Where these are available, data is taken from official institutions, but where not, estimates are calculated. In cases where only low-quality information is available, such as a description of the number of homes damaged or destroyed, assumptions on value and costs are made.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator tracks the total annual economic losses (insured and uninsured) relative to gross domestic product that result from climate-related extreme events, referring to an event caused by natural forces. The scale of the losses resulting from a weather-related event depends not only on the severity, but also on man-made structures such as building design or the efficiency of the disaster response and control in the affected region. Total economic loses reported by Swiss Re are all the financial losses directly attributable to a major event – damage to buildings, infrastructure , vehicles etc – and also includes losses doe to buisness interruptions as a direct consequence of the property damage.
INDICATOR AUTHORS

Dr Daniel Scamman

HEADLINE FINDINGS

At US$ 261 billion, the average annual monetised global losses due to heat related mortality for 2020-2024 were 208% higher than the 2000-2004 average.
DATA SOURCES

1. Heat-realted mortality data from indicator 1.1.5.
2. Population, Total, 2024. World Bank Group.
3. World average GDP per capita (USD), 2024. World Bank Group.
4. Inflation rate, yearly, 2024. World Bank Group.
5. Gross domestic product (GDP), 2024. Organisation for Economic Co-operation and Development (OECD).
6. Mortality Risk Valuation in Environment, Health and Transport Policies, 2012. Organisation for Economic Co-operation and Development (OECD).
7. World Health Organization methods and data sources for global burden of disease estimates 2000-2015, 2017. World Health Organization.
CAVEATS

Inequality embedded within the economic costs of heat-related mortalities across different social groups are ignored in this indicator due to lack of data. This indicator only considered the direct costs from mortalities of elder population, ignoring the potential costs that might derived from it. This indicator currently calculates Value of Statistical Life Year (VSLY) for different ageing groups using the same remaining life at death.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator combines estimates on heat-related mortality from indicator 1.1.5 and the value of statistical life-year (VSLY) estimated for the member countries of the Organisation for Economic Cooperation and Development. It uses a fixed ratio of the VSLY to gross domestic product per capita. The value of mortality is presented as a dollar amount, a proportion of total gross domestic product, and as number of peoples’ incomes the loss would be equivalent to in a given country and region.

DATA DOWNLOAD

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INDICATOR AUTHORS

Prof Wenjia Cai, Dr Shihui Zhang

HEADLINE FINDINGS

The global potential income loss from labour capacity reduction due to extreme heat was US$ 1.09 trillion in 2024, breaching $1 trillion for the first time. The agricultural sector was the most severely affected, incurring 74% and 65% of the average losses in low and medium HDI countries, respectively.
DATA SOURCES

1. Potential working hours lost data from indicator 1.1.3.
2. International Labour Organization (ILO) International Statistics Database, 2025. ILO.
3. International Finance Statistics, 2025. International Monetary Fund.
4. World Economic Outlook Databases, 2024. International Monetary Fund.
5. Country and Lending Groups, 2025. World Bank.
CAVEATS

Results reflect potential loss of earnings in formal paid sectors, rather than actual loss, and do not include informal and unpaid labour that is significant in many countries. Such activites could include domestic work which disproportionately falls on women and small-scale agriculture. There are data gaps in the International Labour Organization Earnings and Labour Income dataset for the years studied for each country and thus several assumptions were incorporated in order to fill these data gaps. The indicator does not measure time off work actually taken.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator combines data from indicator 1.1.3 on heat-related labour capacity loss, in terms of work hours lost (WHLs), at country scale across four sectors (services, manufacturing, constructon, and agriculture) with data on average earnings per hour per country, sector, and year. The total lost earnings are expressed as a percentage of the country’s GDP in each relevant year.

DATA DOWNLOAD

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INDICATOR AUTHORS

Dr Daniel Scamman

HEADLINE FINDINGS

In 2022, the monetised costs of premature mortality due to air pollution amounted to US$ 4.84 trillion, the equivalent of 4.7% of gross world product
DATA SOURCES

1. Ambient air pollution death data from indicator 3.2.1.
2. World Population Prospects 2025. United Nations Department of Economic and Social Affairs.
3. World Economic Outlook Databases, 2024. International Monetary Fund.
CAVEATS

Inequality embedded within the economic costs of heat-related mortalities across different social groups are ignored in this indicator due to lack of data. This indicator only considered the direct costs from mortalities of elder population, ignoring the potential costs that might be derived from it. This indicator currently calculates Value of Statistical Life Year (VSLY) for different ageing groups using the same remaining life at death.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator estimates the change in Years of Life Lost (YLL) due to anthropogenic PM2.5 for 140 countries for each year between 2007 and 2022. It combines data from indicator 3.2.1 and the value of statistical life-year (VSLY) estimated for the member countries of the Organisation for Economic Cooperation and Development (Organisation for Economic Co-operation and Development) using a fixed ratio of the value of VSLY to gross domestic product (gross domestic product) per capita. The value of mortality is presented a dollar amount, a proportion of total gross domestic product, and as number of peoples’ incomes the loss would be equivalent to in a given country and region.

DATA DOWNLOAD

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INDICATOR AUTHORS

Dr Gregor Kiesewetter, Dr Daniel Scamman

4.2.1 Employment in Renewable Energy and Fossil Fuel Industries

Employees in some fossil fuel extraction industries, particularly coal mining, and their local communities, have a greater incidence of cardiovascular and cerebrovascular disease, respiratory disease, and cancers than the general population. Investments in renewable energies and energy efficiency are estimated to create almost three times more jobs per unit of spend than investments in fossil fuel industries. This indicator uses data from IRENA and IBISWorld to compare employment in renewable energy and fossil fuel extraction.

HEADLINE FINDINGS

Direct and indirect employment in renewable energy grew 18.3% in 2023 to a record-high of 16.2 million employees, while direct employment in fossil fuel extraction decreased 0.7% to 9.1 million.
DATA SOURCES

1. Renewable Energy and Jobs, Annual Review 2024, 2024. International Renewable Energy Agency.
2. Global Coal Mining, 2025. IBISWorld.
3. Global Oil & Gas Exploration & Production, 2025. IBISWorld.
CAVEATS

Fossil fuel extraction values include direct employment, whereas renewable energy jobs include direct and indirect employment (e.g., equipment manufacturing), with the exception of hydropower.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator draws on International Renewable Energy Agency and IBISWorld to track the number of jobs in renewable and fossil fuel extraction sectors, respectively.

DATA DOWNLOAD

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INDICATOR AUTHORS

Dr Daniel Scamman

4.2.2 Compatibility of Fossil Fuel Company Strategies With the Paris Agreement

Emissions from oil and gas need to be reduced dramatically to keep global mean temperature rise below 1.5°C, and enable a healthy future. This indicator assess the alignment of current oil and gas company production strategies with the Paris Agreement goals using data on actual commercial activities from the Rystad Energy database for the 100 largest oil and gas companies and their projected 2030 and 2040 production.

HEADLINE FINDINGS

The strategies of the 100 largest oil and gas companies as of March 2025 would lead to production exceeding levels consistent with 1.5°C of heating by 189% in 2040, an increase from 183% from March 2024.
DATA SOURCES

1. UCube Database, 2025. Rystad Energy.
2. World Energy Outlook 2024, 2024. International Energy Agency.
3. World Energy Balances 2024, 2024. International Energy Agency.
CAVEATS

Even if oil and gas firms follow the Paris-compliant pathways outlined here, there is still a substantial chance that temperature targets will be exceeded. Oil and gas firms are assumed here to have constant market shares. This assumption is typical for this sort of analysis but can be expected to introduce errors for at least some firms. These uncertainties are likely to increase over time, meaning projections in the long-term are less certain than in the shorter-term.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

The indicator tracks the gap between the projected production of oil and gas companies based on their actual activities, and production trajectories consistent with the Paris target of 1.5°C of heating. The indicator is expressed as a percentage of the projected production of each company is above or below a pathway consistent with the Paris targets. The indicator analyses both international, publicly traded oil companies and national oil companies, which in many cases have larger production volumes than IOCs but are subject to less public or shareholder scrutiny.
INDICATOR AUTHORS

Dr Daniel Scamman

4.2.3 Stranded Assets from the Energy Transition

On a path that supports a healthy future and keeps within the 1.5°C goal of the Paris Agreement, many of today’s fossil fuel assets must cease operating. This must often occur well before their economic life ends, thus stranding the remaining capital investment. Continuing to invest in fossil fuels therefore not only hampers mitigation efforts and causes millions of deaths each year from exposure to air pollution, but also harms the economy by increasing the economic value of stranded assets.

HEADLINE FINDINGS

Reflecting ongoing coal investment over the last year, the value of global coal-fired power sector assets projected to become stranded in 2030 grew from US$ 16 billion in 2023 to US$ 22.4 billion in 2024.
DATA SOURCES

Main data sources include:

1. Building an open guide to the world’s energy system. Global Energy Monitor.

2. Geographic information. Open Street Map.

3. SSP Database (Shared Socioeconomic Pathways) – Version 2.0 hosted by IIASA. IIASA.

4. International Institute for Applied Systems Analysis Representative Concentration Pathways (RCP) database (version 2.0). IIASA.

5. Synthesis report of the IPCC Sixth Assessment Report (AR6), 2023. IPCC.

6. Overnight Cost of Capital (OCC) for coal-fired power plants from variety of sources

Full data sources can be found in the 2025 report appendix.
CAVEATS

This indicator has several caveats, which are listed in full in the report’s appendix. This indicator only considered stranded assets of coal-fired power plants in the power generation sector. The analysis includes only stranded assets generated by existing coal-fired units and does not include planned units.

This indicator was last updated in October 2025.
INDICATOR DESCRIPTION

Using Global Energy Monitor data, this indicator tracks the extent to which investments are changing the value of coal-fired power assets at risk of stranding, calculating the value of assets that are expected to be stranded in the year 2030, as a benchmark.

DATA DOWNLOAD

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INDICATOR AUTHORS

Prof Chi Zhang, Prof Wenjia Cai, Bo Li

HEADLINE FINDINGS

In 2024, the preparedness for a low-carbon transition decreased by 3.43% on average compared to the previous year. There is a strong correlation between countries’ transition preparedness and their level of human development measured by their HDI. Countries with a Very High HDI had an average preparedness score of 0.72, whereas those with High, Medium and Low HDI scored 0.45, 0.32 and 0.20 on average, respectively. There were decreases in preparedness across all HDI groups in 2024.
DATA SOURCES

Composite indicators are based on numerous input factors, including:
1. World Economic Forum indicators, World Economic Forum.

2. Human Development Reports, United Nations Development Programme.

3. World Development Indicators, World Bank.

4. Availability of finance for the energy transition. Bloomberg.

Full data sources can be found in the 2025 report appendix.
CAVEATS

The indicator in its current form does not reflect opportunities arising from the low-carbon transition, particularly those emerging from access to non-renewable resources vital to the transition, such as critical minerals. It also overlooks different aspects of access to renewable energy sources such as security, reliability, and flexibility. This omission is primarily attributed to the lack of reliable data.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator assesses countries’ transition risk through a complex index that incorporates 25 sub-indicators that monitor institutional performance (e.g., absence of political violence and terrorism, governmental effectiveness), economic situation (e.g.: macroeconomic stability, availability of finance for the transition, GNI per capita), societal (e.g.: proportion of wage income earned in highly exposed sectors, human capital), and technological factors (e.g., technology absorption, carbon intensity of manufacturing), weighted to derive a final preparedness score ranging from 0 and 1.

DATA DOWNLOAD

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INDICATOR AUTHORS

Dr Denitsa Angelova, Dr Pu Yang, Prof Nadia Ameli

4.2.5 Production-based and Consumption-based Attribution of CO2 and PM2.5 Emissions

The production of goods and services drives both greenhouse gas and PM2.5 emissions contributing to impacts on health and wellbeing. A comparison of production- and consumption-based emissions gives a better understanding of how emissions are embodied in global trade, with consumption-based emissions accounting allocating emissions to countries according to their consumption of goods and services even when the physical emissions occurred abroad. As the world works towards net-zero emissions, this indicator tracks the pollution burden from a country’s local production and final consumption.

HEADLINE FINDINGS

From 2019 to 2023, Very High HDI countries remained net importers of goods and services whose production caused net CO2 and PM2.5 emissions in lower HDI countries, accounting for 4.0% and 5.4% of global emissions in 2023, respectively.
DATA SOURCES

1. EXIOBASE 3: Developing a Time Series of Detailed Environmentally Extended Multi-Regional Input-Output Tables, 2018. stadler, K et al.
2. Global Carbon Project 2021, 2021. Friedlingstein, P et al.
3. World Bank Open Data database, 2022. World Bank Group.
4. Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS), 2021. International Institute for Applied Systems Analysis.
5. Emissions Database for Global Atmospheric Research (EDGAR) database, 2022. European Commission.
CAVEATS

GAINS process emissions are only distributed across MRIO sectors that can be clearly identified. Trucking-related emissions are distributed among all sectors based on diesel consumption. Simplifications and assumptions made during the emission inventory disaggregation stage may bring uncertainties into the results.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator useds an environmentally-extended multi-region input-output (EEMRIO) model to quantify countries consumption-based and production-based contribution to CO2 and PM2.5. The EEMRIO analysis reflects production and consumption structures and interdependencies between economic sectors across regions, estimating PM2.5 and CO2 emissions embodied in international trade, and calculating national PM2.5 and CO2 emissions from the consumption perspective.

DATA DOWNLOAD

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INDICATOR AUTHORS

Dr Kehan He, Prof Zhifu Mi, Dr Fabian Wagner, Prof Richard Wood

4.3.1 Clean Energy Investment

Protecting health from a changing climate and realising the health co-benefits of climate action requires a zero-carbon and just transition of the whole global economy, and must include a rapid decline in the production and use of health-harming fossil fuels. Investing in zero-carbon energy and energy efficiency is essential for both mitigating climate change and for reducing air pollution. Reaching net-zero emissions can lead to economic growth, which in turn can lead to further investment in clean energy. This indicator monitors trends in global investment in energy supply and energy efficiency.

HEADLINE FINDINGS

Global clean energy investment grew 8.7% to a record US$ 2.03 trillion in 2024, and exceeded fossil fuel investment by 69%
DATA SOURCES

1. World Energy Investment, 2025. International Energy Agency.
CAVEATS

Investment estimates are derived from International Energy Agency data for energy demand, supply and trade, and estimates of unit capacity costs. Other areas of expenditure, including operation and maintenance, research and development, financing costs, mergers and acquisitions or public markets transactions, are not included.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator draws on data from the annual International Energy Agency World Energy Investment to track energy supply investment. Clean energy invesment has three main components: clean supply (renewables, nuclear, clean fuels etc.); transmission (electricity networks and storage); and end-use (electrification and energy efficiency such as heat pumps, electric vehicles etc.). Fossil fuel investment includes coal, oil and gas electricity generation capacityand fuel supply without CCUs (carbon capture utilisation and storage).

DATA DOWNLOAD

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INDICATOR AUTHORS

Dr Daniel Scamman

4.3.2 Net Value of Fossil Fuel Subsidies and Carbon Prices

Carbon prices can help economies transistion away from high-carbon fuels and drive the transistion towards a low-carbon economy, working in contrast to fossil fuel subsidies that provide incentives for health-harming emissions and which slow down the low-carbon transition. As the world works to move away from health-harming fossil fuel use, this indicator compares carbon pricing and monetary fossil fuel sibsidies to calculate net economy-wide average carbon prices and revenues, covering 87 countries that emit 93% of gloabl CO2 emissions.

HEADLINE FINDINGS

83% of the 87 countries reviewed had a net-negative carbon price in 2023, generating a net subsidy to fossil fuels of US$ 956 billion. The value of the resulting net subsidies exceeded the entire national health budgets in 15 of these countries
DATA SOURCES

1. Fossil Fuel Subsidies Database, 2024. International Energy Agency.
2. OECD Inventory of Support Measures for Fossil Fuels, 2024. Organisation for Economic Co-operation and Development.
3. World Bank Carbon Pricing Dashboard, 2024. World Bank Group.
4. Greenhouse Gas Emissions from Energy, 2024. International Energy Agency.
5. Global Health Expenditure Database, 2024. World Health Organization.
6. World Economic Outlook Databases, 2024. International Monetary Fund.
CAVEATS

The economy-wide net carbon price was derived by dividing fossil fuel subsidies and carbon pricing revenues by total CO2 emissions. This fits well with the subsidies, as these are for fossil fuels, the principal source of CO2. However, some of the carbon pricing instruments from which the revenue was assessed are not only for fossil fuel combustion but apply to other sectors and non-CO2 gases.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator calculates net, economy-wide average carbon prices and associated net carbon revenue to the government. The calculations are based on the value of overall fossil fuel subsidies (taking into account both budgetary transfers and tax expenditures), the revenue from carbon pricing mechanisms, and the total CO2 emissions of the economy. Positive results indicate a net tax on CO2 emissions, while negative results indicate a net subsidy for fossil fuels.

DATA DOWNLOAD

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INDICATOR AUTHORS

Dr Daniel Scamman

4.3.3 Fossil Fuel and Green Bank Lending

Redirecting finance away from fossil fuels and towards clean renewable, energy efficiency, and carbon sinks is essential for a healthy, just transistion to net-zero emissions. The Net-Zero Banking Alliance (NZBA), now expected to be disbanded after several prominent Banks left the alliance, was convened by United Nations Environment Programme in 2021 to promote this financial shift. This indicator draws on Bloomberg data to monitor private banks’ lending to the fossil fuel sector and the green sector. A financial transformation will be essential to shift investments from fossil fuels to clean renewable energy sources; this will support countries’ response to energy crises, reduce air pollution, and secure a healthier, more equitable future.

HEADLINE FINDINGS

Headline finding: Private bank lending to the green sector increased 13% from 2023 to 2024, reaching US$ 532 billion— meanwhile, fossil fuel lending surged 29% to US$ 611 billion.
DATA SOURCES

1. Fossil fuel and green fixed income data. 2024. Bloomberg.
2. Net Zero Banking Alliance. 2024
CAVEATS

This data only represents a subset of investments provided by the financial sector – equity investments are not covered by the data, nor are contributions from other financial actors such as institutional investors. In addition, the labelling of a debt as ‘green’ is reliant on the classification by the issuer, which makes it susceptible to green-washing as there is no independent verification of the classification.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

Data for bank lending to the fossil fuel and green sectors was taken from a proprietary Bloomberg dataset covering the global debt market. Fossil fuel lending is defined as being directed towards exploration, production, operation and marketing activities in oil and gas. Green lending is self-identitfied by the issuer as funding for a project or activity with an environmenal or sustainability-oriented goal.
INDICATOR AUTHORS

Prof. Nadia Ameli, Dr. Papa Orgen

HEADLINE FINDINGS

Headline finding: between 2020–2022, the Green Climate Fund (GCF) provided US$ 166 million for health adaptation, while the World Bank’s financing for climate change and health adaptation reached US$ 1.12 billion in 2024; 69% more than in 2023. On the other hand, 28 countries that explicitly cost health adaptation finance needs in NAP and NDC submissions estimate US$ 7 billion annual needs from 2025 – 2030.
DATA SOURCES

1. UNFCCC: Adaptation registry and NDCs database for National Adaptation Plans and Nationally Determined Contributions
2. OECD CFRD Database
3. Green Climate Fund (GCF)
4. The World Bank
CAVEATS

Limited coverage: Only 28 countries reported quantifiable health needs; others embed health within broader priorities.
Timeframe gaps: Reported needs often lack clear periods; estimates centred on 2025–2030.
Reporting bias: Many countries under- or over-state costs due to data or capacity limits.
Document timing: Based on latest NAPs/NDCs available as of March 2025.
Classification mismatch: Health definitions differ across datasets; better harmonisation needed for comparability.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This composite indicator combines quantitative data on health-tagged adaptation finance from the OECD Climate-Related Development Finance Dataset (2020–2022), the Green Climate Fund, and World Bank climate finance reports (2020–2024). Projects are classified as having a principal or significant adaptation objective using OECD Rio Markers. Reported flows are then compared with health adaptation needs extracted from countries’ NAPs and NDCs (2025–2030), identified through text-mining and human-in-loop validation of UNFCCC submissions. All values are standardised to 2022 USD and grouped by UNFCCC country status to assess the alignment between financing delivered and financing required for health adaptation.

DATA DOWNLOAD

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INDICATOR AUTHORS

Dr Papa Orgen, Professor Nadia Ameli, Dr Sabah Abdulla, Professor Anil Markandya, Dr Cat Pinho-Gomes

Media Coverage of Health and Climate Change

Traditional media outlets (newspaper, radio, and television) continue to provide a major platform for public engagement, and play an important role in agenda-setting within today's multi-media landscape. Newspapers can shape public understanding of climate change, both through their influence on their readers and the wider political agenda. This indicator tracks coverage of health and climate change in 56 newspapers in 33 countries, including China’s People’s Daily.

HEADLINE FINDINGS

In 2024, 24.8% of climate change articles mentioned health, up from 23.5% in 2023. However, average coverage of health and climate change across sources fell by 15%, from 204 to 173 articles per news source
DATA SOURCES

1. Nexis Uni® database.
2. Factiva© database.
3. ProQuest LLC database.
4. People’s Daily official website.
CAVEATS

The selected newspapers cannot be taken to be representative of all media reporting in their countries, and the content analysis does not reflect the ways in which climate change and/or health is reported in the media, nor the general messaging. The search terms used are likely to have influenced the types of articles obtained, and databases might return hits of duplicate articles.

In developing the search strategy for the 2020 and 2021 Lancet Countdown report, it was found that a significant portion of articles may mention both climate change and health but do not engage with them as integrated issues. Including this coverage remains important as it brings both sets of issues – health and climate change – onto the public agenda and into public awareness.
INDICATOR DESCRIPTION

Articles from 2007 to 2024 in 56 newspapers across 33 countries, written in English, German, Portuguese and Spanish were analysed using key word searches within three databases. Additionally, articles in Chinese in China’s People’s Daily were assessed through a process of first trawling through all articles and then searching for keywords in article text.

DATA DOWNLOAD

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INDICATOR AUTHORS

Dr Lucy McAllister, Prof Wenjia Cai, Dr Pete Lampard, Olivia Pearman

Individual Engagement in Health and Climate Change

Online activity is increasingly being used to understand and drive public and individual engagement, transforming individual access to global knowledge and debates. This indicator tracks individuals’ information-seeking behaviour on English Wikipedia and Google in English, Spanish and French in relation to the link between climate change and health. With content on Wikipedia created and edited by users, it can influence the agenda of other media sources. Google is the most visted website in the world and captures a vast majority of the global search engine market.

HEADLINE FINDINGS

Individuals’ proactive engagement with health and climate change is increasing, with the average global Google search index increasing from 49.4 in 2023 to 59.9 in 2024, with the world’s most affected countries dominating the trend.
DATA SOURCES

1. Wikimedia Dumps, 2022. Wikimedia Foundation
2. Google Trends data
CAVEATS

The Wikipedia data is not geo-referenced, so it is not possible to infer the location of page visits. Only English Wikipedia pages were considered in the analysis (approximately 50% of total Wikipedia pages), and while they are accessed globally, it is biased towards English-speaking countries. Google does not make the raw search volumnes publicly available, only a normalized search index. To prevent skewed trends, Google Trends excludes searches generated by a very small number of users.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

The first part of this indicator measures the number of clicks from health-related Wikipedia articles that lead to visits to climate change-related Wikipedia articles, and the number of visits to climate change-related articles that result in clicks to health-related pages from 2019-2024. This ‘clickstream data’ is used as a proxy for the degree to which individuals engage with health and climate change as related issues. The second part tracks normalised Google Trends data on the search term “health climate change” and data on the “climate change” topic within the public health and the health category between 2014-2024.

DATA DOWNLOAD

Click here to download Google Trends data.

Click here to download Wikipedia data.
INDICATOR AUTHORS

Prof Simon Munzert, Dafni Kalatzi Pantera, Prof Niheer Dasandi

HEADLINE FINDINGS

The number of scientific articles on health and climate change published in 2024 declined by 2.2% compared to 2023 – but remained higher than for every other year.
DATA SOURCES

1. OpenAlex database, 2025.
2. UN world population prospects data.
CAVEATS

There exists no ‘complete’ repository of all scientific literature, open databases cover a large number or indexed records, however far from all entries includes abstracts which limits the automated processing. Abstracts were added manually when possible to a local copy of the OpenAlex database, but some records might be missed. Only entries with an abstract in English were annotated.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator identifies original research articles and research-related articles published from 1990 to 2024 that cover health and climate change topics using a machine-learning approach. This allowed for a more granular picture of the research landscape, including developments across major domains of research (mitigation, adaptation, impacts), the health impacts covered, locations studied, as well as patterns of authorship.

DATA DOWNLOAD

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INDICATOR AUTHORS

Dr Tim Repke, Prof Jan C. Minx

5.3.2 Scientific Engagement on the Health Impacts of Climate Change

This subindicator is building on indicator 5.3.1, that captures health impacts that can tentatively be attributed to climate change, using different methods to estimate these climate-related health impacts. This indicator maps the volume of studies published between January 1990 and December 2024 referring to health impacts related to climate variables, where changes in the climate driver can be attributed to human influence.

HEADLINE FINDINGS

56% (26,158) of the 46,810 scientific publications covering the health impacts of climate change since 1990 focus on events in which changes in climate variables can be attributed to human influence. However, the number of such studies fell 14.7% between 2023 and 2024 .
DATA SOURCES

1. OpenAlex database, 2025
CAVEATS

The method cannot fully attribute the health outcomes identified in each study to human influence on the climate. Rather, it shows where the health outcomes of changes in climate variables coincide geographically with changes in those variables that can be attributed to human influence. This indicator is only based on English-language literature, which might bias which regions are well represented.

This indicator was updated in October 2025
INDICATOR DESCRIPTION

Attributable effects are identified by linking studies on climate impacts with data from climate models and observational record. Attribution is based on human-attributable changes in temperature and precipitation, and the identified health impacts co-referenced co-referenced with gographical locations in the title or abstract.

DATA DOWNLOAD

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INDICATOR AUTHORS

Dr Tim Repke, Dr Max Callaghan, Prof Jan C. Minx

5.4.1 Government Engagement

Engagement by political leaders is central to accelerated and ambitions climate interventions that protect human health. This indicator monitors political engagement through national leaders’ statements at the UN General Debate (UNGA), the cornerstone of the annual UNGA, and Nationally Determined Controbutions (NDCs), the key policy instrument to protect people and the planet from climate change. As the world warms and the impacts of climate change are being felt gloablly, it is essential these issues are being recognised as important areas of concern and prompts for change.

HEADLINE FINDINGS

Government engagement with health and climate change continued to decrease in 2024, with only 30% of countries mentioning health and climate change in their UN General Debate (UNGD) statement, down from 62% in 2021.
DATA SOURCES

1. Understanding State Preferences With Text As Data: Introducing the UN General Debate Corpus, 2017. Batuor, A et al.

2. Nationally Determined Contributions Registry, 2025. United Nations Framework Convention on Climate Change.
CAVEATS

The results present a somewhat conservative estimate of high-level political engagement with the intersection of climate change and health. There may be examples of governments referring to climate change and health but not the direct linkages between the two and there may be examples of governments discussing the health impacts of climate change in their United Nations General Debate speeches but the distance between the climate change term and the health term exceeds 25 words. The analyses are based on a narrow range of search terms, which excludes reference to many of indirect links between climate change and health.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator tracks government engagement in health and climate change in two key forums. It assesses reference to health and climate change as well as their prominence in the text of all available (as of March 1st 2025) Nationally Determined Contributions by Parties to the Paris Agreement. It also tracks mentions of climate change and health in statements made by national leaders at the United Nations General Debate, which is part of the annual United Nations General Assembly, as proxy of high-level political engagement on these two topics as separate and related issues.

DATA DOWNLOAD

Click here to download NDC data.

Click here to download UNGA data.
INDICATOR AUTHORS

Prof Slava Jankin, Dr Pete Lampard, Prof Niheer Dasandi

HEADLINE FINDINGS

The proportion of tweets by international organisations referencing health co-benefits of climate mitigation continued to increase in 2024, reaching a record-high of 25% of X posts in November 2024.
DATA SOURCES

1. Extracted posts on X. Accessed in 2025.
CAVEATS

This indicator works with a limited predefined set of international organisations, and search terms could be missing parts of co-benefits discussions. The organisations may strategically choose what to share on the platofrm, which could bias the analysis.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

Natural language processing (a subfield of machine learning) is used here to track the uptake and engagement of health co-benefits in policy discourse on social media of major international organisations (IOs) involved in climate change adaptation and mitigation work. With the dataset of IO’s posts, a search through the text of each post was performed to identify if they discuss co-benefits. An indicator of engagement intensity was developed as a monthly proportion of posts containing at least one term from the search term list in relation to the total number of posts by that IO.

DATA DOWNLOAD

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INDICATOR AUTHORS

Dr Olga Gasparyan, Prof Slava Jankin, Prof Cathryn Tonne

HEADLINE FINDINGS

In 2024, only 51% of companies referred to the health dimensions of climate change in their UN Global Compact Reports, down from 63% in 2023.
DATA SOURCES

1. Communication on Progress (CoP) portal, 2022. United Nations Global Compact.
CAVEATS

This analysis is based on a narrow range of search terms, which excludes reference to many of indirect links between climate change and health, such as the effect of climate change on agriculture. Therefore, the results present a somewhat conservative estimate of high corporate engagement with the intersection of climate change and health.

This indicator was last updated in October 2025
INDICATOR DESCRIPTION

This indicator monitors engagement on health and climate change from the over 25,000 companies from 167 countries who signed up to the UNGC by tracking mentions of health and climate change in their annual Global Compact Communication of Progress (GCCOP) reports. A total of 44,449 reports between 2011 to 2024 for companies based in 123 countries were downloaded for the analysis.

DATA DOWNLOAD

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INDICATOR AUTHORS

Paulina Garcia Corral, Dr Hannah Becharai, Prof Slava Jankin

Climate change impacts, exposure and vulnerability

1.1.1 Exposure of Vulnerable Populations to Heatwaves

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1.1.2 Heat and Physical Activity

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1.1.3 Change in Labour Capacity

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1.1.4 Rising Nighttime Temperatures and Sleep Loss

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1.1.5 Heat-Related Mortality

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1.2.1 Wildfires

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1.2.2 Drought

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1.2.3 Extreme Precipitation

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1.2.4 Sand and Dust Storms

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1.2.5 Extreme Weather and Sentiment

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1.3.1 Dengue, chikungunya, Zika

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1.3.2 Malaria

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