Climate Change Impacts, Exposure and Vulnerability

A changing climate has profound implications for human health, with more frequent heatwaves and extreme weather events, changing patterns of infectious disease, and the exacerbation of existing health challenges around the world. Indicators in this section track how these impact on human health.

View fullscreen:

1.1 Health and Heat

A changing climate has profound implications for human health, with more frequent heatwaves and extreme weather events, changing patterns of infectious disease, and the exacerbation of existing health challenges around the world. Indicators in this section track how these impact on human health.

View fullscreen:

1.1.1 Vulnerability to Extremes of Heat

People over 65 years of age, particularly those with chronic medical conditions (such as diabetes and heart, lung and kidney disease), are among the most vulnerable to the health effects of heatwaves. In a world that is increasingly warming due to climate change, this indicator measures the vulnerability to heat of populations around the world.

View fullscreen:

Headline findings

Although vulnerability to heat in the low and medium Human Development Index (HDI) country groups is 27–38% lower than in the very high HDI group, it is increasing in all groups and, since 1990, it has increased by 19% in the low HDI group and by 20% in the medium HDI group.

Data sources

1. Global Burden of Disease Study 2019. Institute for Health Metrics and Evaluation.

2. The United Nations Population Division’s World Urbanization Prospects.

Caveats

This indicator does not capture the existence or absence of effective adaptation measures, such as heat early warning systems, cooling devices, and green areas in cities.

 

This indicator was last updated in September 2021.

Indicator description

This indicator tracks a population’s vulnerability to heat using a composite index ranging from 0 to 100, which combines data on the proportion of the population older than 65 years; the prevalence of chronic respiratory disease, cardiovascular disease, and diabetes in this population, and the proportion of the total population living in urban areas.

 

1.1.2 Exposure of Vulnerable Populations to Heatwaves

Exposure to extremes of heat results in a range of health consequences, including heat stress and heat stroke, worsening heart disease, and acute kidney injury. Populations over 65, and newborns are particularly vulnerable to these effects, and are being exposed to heatwaves in increasing numbers. This indicator tracks the change in the number of heatwaves experienced by vulnerable populations around the world.

View fullscreen:

Headline findings

Children younger than 1 year were affected by 626 million more person-days of heatwave exposure and adults older than 65 years were affected by 3·1 billion more person-days of heatwave exposure in 2020 than in the 1986–2005 average.

 

Data Sources

1. ERA5 reanalysis, 2021. European Centre for Medium-Range Weather Forecasts.

2. Gridded Population of the World. 4 ed (GPWv4), 2021. NASA.

3. Histsoc dataset, 2021. Inter-Sectoral Impact Model Intercomparison Project – 2021 Revision of World Population Prospects, 2021. United Nations DESA/Population Division.

4. United Nation World Population Prospects.

Caveats

As two distinct sources were used for population data there may be some inconsistencies between the pre and post 2000 values.

 

This indicator was last updated in September 2021.

Indicator description

This indicator tracks the change in the number of heatwave exposure events (with one exposure event being one heatwave experienced by one person aged over 65 or child from birth to 1 year old) and days of heatwave exposure in these populations compared with the average number of events in the reference period (1986–2005). A heatwave was defined as a period of at least two days where both the daily minimum and maximum temperatures are above the 95th percentile of their respective climatologies.

1.1.3 Heat and Physical Activity

High temperatures can reduce the frequency and duration of physical activity, the desire to engage in exercise, and even low levels of physical activity can pose a risk to health under high temperatures. In a world that is increasingly warming due to climate change, this indicator measures hours of physical activity potentially lost due to heat.

View fullscreen:

Headline finding

The past four decades saw an increase in the number of hours in which temperatures were too high for safe outdoor exercise, with people in the low Human Development Index country group having an average loss of 3·7 h of safe exercise per day in 2020.

Data Sources

1. ERA5 reanalysis, 2021. European Centre for Medium-Range Weather Forecasts.

2. Grid cell-based population data, NASA’s Socioeconomic Data and Applications Center, hosted by the Center for International Earth Science Information Network at Columbia University. 2017.

Caveats

Setting 28ºC as the WBGT cutoff precluded robust analysis of regions where this threshold is not typically exceeded. Simple heat indices like WBGT do not fully capture the effect on exercise capacity of determinants such as age, physiology, and clothing.

 

This indicator was last updated in September 2021.

Indicator description

This indicator estimates the physical activity potentially lost per person by tracking the number of hours per day during which the wet bulb globe temperature (which measures ambient temperature, humidity, and radiant heat) exceeds 28°C, a threshold above which national sports medicine authorities recommend outdoor physical activities to be conducted with discretion.

1.1.4 Change in Labour Capacity

Our capacity to work is affected by temperature and humidity, particularly in highly active jobs in agriculture, industry, and manufacturing. Reduced work productivity can also result in flow on health and economic impacts for individuals and communities. As the world continues to warm, this indicator tracks the change in potential work hours lost due to high temperatures.

View fullscreen:

Headline findings

295 billion hours of potential work were lost due to extreme heat exposure in 2020, with 79% of all losses in countries with a low Human Development Index occurring in the agricultural sector.

Data Sources

1. ERA5 reanalysis, 2021. European Centre for Medium-Range Weather Forecasts.

2. Gridded Population of the World. 4 ed (GPWv4), 2021. NASA.

3. Sector employment data from ILOSTAT, 2021.

Caveats

These estimates are conservative, as they assume all work is undertaken in the shade, not accounting for the influence of solar radiation. The distribution of agricultural, construction manufacturing and service sector workers is only available at the country level, therefore country averages are applied evenly to each grid cell.

 

This indicator was last updated in September 2021

Indicator description

This indicator calculates hours of work lost by linking Wet Bulb Globe Temperature (including temperature, humidity, and solar radiation) with the amount of energy typically expended by workers in four sectors: agriculture, construction, service, and industry. It then combines this calculation with the proportion of people working (over 15 years old) in each of these four sectors within each country to estimate the potential work hours lost per year.

1.1.5 Heat and Sentiment

Climate change-related increases in heat extremes pose diverse risks to mental health globally, ranging from altered affective states to elevated mental health-related hospitalisations and suicidality. As the world continues to warm, this indicator tracks people’s sentiment, expressed on social media.

View fullscreen:

Headline findings

Exposure to heatwave events worsens expressed sentiment, with a 155% increase in negative expressions on Twitter during heatwaves in 2020 from the 2015–19 average.

Data Sources

1. ERA5 reanalysis, 2021. European Centre for Medium-Range Weather Forecasts.

2. Geolocated tweets collected via the Twitter Streaming API.

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 and the vast majority of the Twitter observations were posted in wealthy countries.

 

This indicator was last updated in September 2021

Indicator description

This indicator monitors expressed sentiment on Twitter, using over six billion geolocated tweets collected between 2015 and 2020. It deploys a multivariate ordinary least squares fixed effects model to estimate the annual effect of heatwaves on expressed sentiment. It compares sentiment expression during as-good-as-random heatwave days (as defined in indicator 1.1.2) with non-heatwave days in 40,000 unique localities.

1.1.6 Heat-Related Mortality

Exposure to extremes of heat results 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. People aged over 65 are particularly vulnerable to these effects. As the world continues to warm, this indicator tracks heat-related mortality in over 65 populations around the world.

View fullscreen:

Headline finding

Heat-related deaths in people older than 65 reached a record high of an estimated 345000 deaths in 2019; between 2018 and 2019, all WHO regions, except for Europe, saw an increase in heat-related deaths in this vulnerable age group.

Data Sources

1. ERA5 reanalysis, 2021. European Centre for Medium-Range Weather Forecast.

2. Gridded Population of the World. 4 ed (GPWv4), 2021. NASA. Histsoc dataset, 2020. Inter-Sectoral Impact Model Intercomparison Project – 2020.

3. Revision of World Population Prospects, 2021. United Nations DESA/Population Division.

4. Mortality rate and life expectancy data. Global Burden of Disease, 2021. Institute for Health Metrics and Evaluation.

Caveats

This analysis assumes exposure-response function is constant and fixed across locations. It does not capture changes in response to heat exposure that might happen over time or in different geographies, as a result of acclimation and adaptation. Not capturing these changes could result in an over-estimation of heat-related deaths.

 

This indicator was last updated in September 2021.

Indicator description

This indicator tracks global heat-related mortality in populations older than 65 years. It applies the exposure-response function and optimum temperature described by Honda and colleagues (2014) to the daily maximum temperature exposure of the population older than 65 years to estimate the attributable fraction and thus the deaths attributable to heat exposure.

1.2 Health and Extreme Weather Events

View fullscreen:

1.2.1 Wildfires

Wildfires cause a range of health impacts, ranging from direct thermal injuries through to exacerbation of acute and chronic lung disease from smoke and pollution. They will often cause substantial economic impacts, affecting vital infrastructure and emergency services. Climate change is creating hotter, drier conditions in many parts of the world, increasing the risk of wildfires. This indicator monitors the change in wildfire danger and the number of people exposed to wildfires globally.

View fullscreen:

Headline findings

Nearly 60% of countries had an increase in the number of days people were exposed to very high or extremely high fire danger in 2017–20 compared with 2001–04, and 72% of countries had increased human exposure to wildfires across the same period.

Data sources

1. Collection 6 active fire product, the Moderate Resolution Imaging Spectroradiometer, 2021. NASA EarthData.

2. Fire danger indices historical data from the Copernicus Emergency Management Service, 2021. Copernicus Climate Change Service.

3. Gridded Population of the World. 4 ed (GPWv4), 2021. NASA

Caveats

The fire danger index is calculated based on meteorological parameters. The actual fire events can be also influenced by anthropogenic factors, such as human-induced land use and land cover changes, industrial-scale fire suppression, and human induced ignition. The satellite data does not account for cloud cover or smoke and data is not collected at night. It also assumes that those affected by a wildfire are the population limited to a 10km radius of the fire grid point and does not track exposure to wildfire smoke.

 

This indicator was last updated in September 2021

Indicator description

This indicator uses both model-based wildfire danger and satellite-observed exposure. Climatological wildfire danger was 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) was tracked using satellite and population data.

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, and crop and livestock productivity, enhancing the risk of wildfires, and potentially leading to forced migration. As climate change alters rainfall patterns and increases temperatures, this indicator tracks the change in months of drought around the world.

View fullscreen:

Headline findings

In 2020, up to of 19% of the global land surface was affected by extreme drought in any given month.

Data sources

1. Global SPEI database, SPEIbase (Consejo Superior de Investigaciones Cientificas) 2021.

 

Caveats

This indicator only captures the impacts of climate change on meteorological drought, but does not capture the impacts of climate change on hydrological or agricultural drought. It also does not measure the direct relation between a drought and the population living in drought-affected areas.

 

This indicator was last updated in September 2021

Indicator description

This index measures significant increases in the number of months of meteorological drought, using the standardised precipitation evapotranspiration index, compared with an extended historical baseline (1950–2010), to account for periodic variations such as those generated by the El Niño Southern Oscillation.

1.3 Climate-Sensitive Infectious Diseases

View fullscreen:

1.3.1 Climate Suitability for Infectious Disease Transmission

The suitability for transmission of many infectious diseases is influenced by shifts in temperature and precipitation. 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.

View fullscreen:

Headline findings

The R0 for all arboviral diseases tracked has increased, and, in 2020, was 13% higher for transmission by A. aegypti and 7% higher for transmission by A. albopictus than in baseline years.

Data Sources

1. Precipitation and temperature data from CRU TS4.05, 2020. University of East Anglia Climatic Research Unit. 2020.

2. Earth Syst Sci Data, HYDE 3.2 gridded population data, 2017.

Caveats

These results are not based on case data. Control efforts, such as water, sanitation and hygiene programs, and vector control efforts, may help to mitigate these effects. National presented for vectorial capacity for the transmission of dengue only takes into account the most common aedes species in each country. Data are not presented for countries for which information on vector presence was not available.

 

This indicator was last updated in September 2021

Indicator description

This indicator tracks the environmental suitability for the transmission of arboviruses (dengue, chikungunya, and Zika) , malaria and Vibrio bacteria. For arboviruses it uses an improved model to capture the influence of temperature and rainfall on vectorial capacity and vector abundance, and overlaying it with human population density data to estimate the R0 (the expected number of secondary infections resulting from one infected person). The influence of the changing climate on the length of the transmission season for Plasmodium falciparum malaria is tracked with a threshold-based model that incorporates precipitation accumulation, average temperature, and relative humidity. The environmental suitability for infections from Vibrio species incorporates sea surface temperature and salinity, as well as chlorophyll-a for Vibrio cholerae.

1.3.2 Vulnerability to Mosquito-Borne Diseases

Vulnerability to dengue infections is affected by physiological, social, financial, and geographical factors, as well as a community’s capacity to adapt. Improvements in public health have seen a global reduction in vulnerability. As both the climate suitability for dengue, and populations’ adaptive capacity are changing, this indicator tracks both of these to gain an overall picture of population vulnerability to dengue fever.

View fullscreen:

Headline findings

While vulnerabilities to arboviruses transmitted by A. albopictus and A. aegypti have decreased across all countries since the year 2000, countries in the low Human Development Index group remain on average the most vulnerable.

Data sources

1. Version 4.03 of the CRU TS monthly high-resolution gridded multivariate climate dataset, 2020.

2. WHO/UNICEF Joint Monitoring Programme (JMP) for Water Supply, Sanitation and Hygiene, 2021.

3. Gross national income (GNI) per capita (constant 2017 PPP$) data are taken from the United Nations Development Programme, 2021.

4. Data on maternal, prenatal and nutrition conditions were taken from the 2019 Global Burden of Disease Study.

Caveats

The abundance models generate predictions and not observed frequencies in relation to climate conditions, and by so should be considered a potential abundance estimate.

 

This indicator was last updated in September 2021

Indicator description

This indicatordisplays vulnerabilities overlayed with the basic reproduction number (R0) for the transmission of dengue by Aedes aegypti and Aedes albopictus for each country, as described in Indicator 1.3.1. Values were aggregated by WHO region and HDI levels.

1.4 Food Security and Undernutrition

View fullscreen:

1.4.1 Terrestrial Food Security and Undernutrition

The global number of undernourished people worldwide has been steadily increasing worldwide since 2014. Undernutrition overwhelmingly affects children under five years old, being responsible for more than half of the deaths globally for this age group. This indicator uses changes in climate to track declines in crop yield potential due to warmer temperatures for the world’s major crops: maize, wheat, rice, and soybean.

View fullscreen:

Headline findings

Crop yield potential continues to follow a downward trend, with 6·0% reduction in the crop yield potential of maize, 3·0% for winter wheat, 5·4% for soybean, and 1·8% for rice, relative to the 1981–2010 average crop yield potential.

Data sources

1. ERA5 reanalysis, 2021. European Centre for Medium-Range Weather Forecasts and ERA5 Land hourly data. Copernicus Climate Change Service, 2019.

2. Portmann FT, Siebert S, Döll P. MIRCA2000—Global monthly irrigated and rainfed crop areas around the year 2000: A new high‐resolution data set for agricultural and hydrological modeling. Global biogeochemical cycles 2010; 24(1).

3. Sacks WJ, Deryng D, Foley JA, Ramankutty N. Crop planting dates: an analysis of global patterns. Global Ecology and Biogeography 2010; 19(5): 607-20.

4. Saint Ville A, Po JYT, Sen A, Bui A, Melgar-Quiñonez H. Food security and the Food Insecurity Experience Scale (FIES): ensuring progress by 2030. Food Security 2019; 11(3): 483-91.

Caveats

The crop yield potential, as calculated here, does not take into account water shortage, and therefore characterises long-term change in yield potential rather than year to year variability.

 

This indicator was last updated in September 2021

Indicator description

This indicator tracks the change in crop growth duration (the time taken to reach a target sum of accumulated temperatures and a proxy for crop yield potential) for maize wheat, rice and soybean, using a 1981-2010 reference period. If this sum is reached early, then the crop matures too quickly, and yields are lower than average.

1.5 Migration, Displacement and Sea-Level Rise

Changes in water and soil quality and supply, livelihood security, flooding, and saltwater intrusion are just some of the health impacts of sea-level rise. The health consequences of these effects will depend on various factors, including the options of both in situ and migration adaptation. 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.

View fullscreen:

Headline findings

There are currently 569.6 million people settled below 5 metres above sea level, who could face risks from the direct and indirect hazards posed by the rising sea levels.

Data sources

1. Kopp RE, DeConto RM, Bader DA, et al. Evolving Understanding of Antarctic Ice-Sheet Physics and Ambiguity in Probabilistic Sea-Level Projections. Earth’s Future 2017; 5(12): 1217-33.

2. Kulp SA, Strauss BH. CoastalDEM: a global coastal digital elevation model improved from SRTM using a neural network. Remote sensing of environment 2018; 206: 231-9.

3. LandScan 2019, 2020. Oak Ridge National Lab.

4. Global Administrative Areas (GADM) version 3.6. 2021.

5. The Subnational Human Development Database. Smits J, Permanyer I. Sci Data 2019; 6: 190038.

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 about 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. Finally, this indicator only considers current population exposed to 1 metre or 5 metres of sea level rise, which are within the lowest and highest estimates projected by the end of the century.

 

This indicator was last updated in September 2021

Indicator description

This indicator uses a bathtub model, overlaying global mean sea level rise with coastal elevation and then uses 2019 gridded population data to estimate the current population at risk of exposure to 1m and 5m global mean sea level rise.

Adaptation, Planning, and Resilience for Health

Indicators in this section track how communities, health systems, and governments are understanding the health risks of climate change, the strategies and resources they are deploying, and how adaptation and resilience measures are being implemented globally.

View fullscreen:

2.1 Adaptation Planning and Assessment

Adaptation Planning and Assessment

View fullscreen:

2.1.1 National Adaptation Plans for Health/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, with vulnerability and adaptation assessments forming an essential first step in building local resilience. 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.

 

 

View fullscreen:

Headline findings

Countries are beginning to prepare for the health risks of climate change: In 2021, 47 (52%) of 91 countries reported having national health and climate change strategies or plans in place. Additionally, 45 (49%) of 91 countries in 2021 reported having done a climate change and health vulnerability and adaptation assessment.

Data sources

1. 2021 WHO Health and Climate Change Survey

Caveats

The survey sample is not a representative sample of all countries as this survey was voluntary. However, the inclusion of 91 countries despite a global pandemic demonstrates significant global coverage.

 

This indicator was last updated in September 2021

Indicator description

This indicator draws on the 2021 WHO Health and Climate Country Survey which was completed by 91 member states and non-member territories with representation from all 6 WHO regions. It tracks the development of national health and climate change strategies and plans and barriers to implementation.

2.1.3 City-Level Climate Change Risk Assessments

Cities and local communities are at the forefront of the health impacts of climate change and must be central to any adaptation response. This indicator tracks the proportion of global cities that have conducted climate change risk assessments and the climate-related health impacts/vulnerabilities that cities identified.

View fullscreen:

Headline findings

In 2020, 546 (81%) of 670 cities reported having completed or being in the process of doing climate change risk assessments; heat-related illness was the most common climate-related health concern, identified by 169 (55%) of 308 cities.

Data sources

1. 2020 CDP Annual Cities Survey

Caveats

This is a sample survey and cities are under no obligation to respond. The majority of responding cities are also from countries rated as high or very high HDI (94%). As such, the results are not representative of all cities.

 

This indicator was last updated in September 2021

Indicator description

This indicator draws on data from the CDP 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.

2.2 Climate Information Services for Health

Climate information from meteorological services is essential in monitoring disease outbreaks, extreme weather events, 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.

View fullscreen:

Headline findings

In 2020, national meteorological and hydrological services of 86 countries reported providing climate information to the health sector; only five of the 86 indicated that these climate services guide health sector policy and investment plans.

Data sources

1. Country Profile database, 2021. WMO

Caveats

This indicator only considers climate services provided by national member states, and not by academic, private, regional, or other providers. The data is self-reported by countries and may therefore include reporting bias.
The WMO survey is an open questionnaire that can be updated at any time by WMO members. Therefore figures reported here may change over the year.

 

This indicator was last updated in September 2021

Indicator description

This indicator takes data from the World Meteorological Organization Country Profile Database integrated questionnaire, which asks for information regarding which communities and sectors the National Member States provide products and information to and the extent to which these products are used to improve decisions.

2.3 Adaptation Delivery and Implementation

View fullscreen:

2.3.1 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. This indicator tracks countries’ emergency preparedness through their implementation of a national health emergency framework.

View fullscreen:

Headline findings

124 out of 166 countries (75%) reported medium-to-high implementation of a national health emergency framework in 2020; an increase of 14% compared to 2019.

Data sources

1. International Health Regulations monitoring framework, SPAR, 2020. WHO

Caveats

IHR monitoring questionnaires 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 September 2021

Indicator description

This indicator monitors the implementation of capacity “C8” (the existence of a national health emergency framework), as tracked by the International Health Regulations of the WHO. Due to changes in the reporting format, data is disaggregated in “preparedness” and “response” for 2005 to 2017 but reported as a single value for 2018-2020.

2.3.2 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 (AC) 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, and increased urban heat island effect. This indicator tracks the coverage of household AC use, the number of averted heat-related deaths by air conditioning in the 65-and-older population, and greenhouse gas emissions of air conditioning use.

View fullscreen:

Headline findings

Use of air conditioning, a widespread technology for indoor cooling in some regions of the world, averted an estimated 195 000 heat-related deaths among people 65 years or older in 2019; however, air conditioning also contributed to greenhouse gas emissions, air pollution, peak electricity demand, and urban heat islands.

Data sources

1. International Energy Agency data on household air conditioning use

2. ERA5 reanalysis, 2021. European Centre for Medium-Range Weather Forecast.

3. Gridded Population of the World. 4 ed (GPWv4), 2021. NASA.

4. Histsoc dataset, 2020. Inter-Sectoral Impact Model Intercomparison Project – 2020

5. Revision of World Population Prospects, 2021. United Nations DESA/Population Division

6. Mortality rate and life expectancy data. Global Burden of Disease, 2021. Institute for Health Metrics and Evaluation.

Caveats

Data is only available for a limited number of countries or country groups and the rest of the data is estimated as “rest of world”. In addition, the presence of air conditioning in a household does not guarantee the use of air conditioning in that household. A limited number of studies were available for the meta-analysis on the effect of air conditioning on RR of heat-related mortality and all studies were observational. Not all studies adjusted for confounding that having household air conditions may be associated with other characteristics that prevent heat-related mortality (good baseline health, not living alone). The estimate of a number of premature deaths (all ages) due to PM2.5 emissions from air conditioning assumes that the share of electricity use for AC is equally applied to powerplant emissions throughout a given country/region which may not be accurate especially for larger countries/regions.

 

This indicator was last updated in September 2021

Indicator description

Using data from the International Energy Agency, this indicator calculates the global proportion of households using air conditioning. It also uses this IEA data to estimate the PM2.5; attributable premature mortality due to air conditioning use and the number of deaths averted by air conditioning use in the 65-and-older population. The 2021 report uses the results from Indicator 1.1.6, heat-related mortality, in combination with prevented fraction estimates to estimate the number of heat-related deaths prevented by air conditioning in the 65-and-older population for the world and for selected countries and regions.

2.3.3 Urban Green Space

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, benefiting both climate change mitigation and heat adaptation. This indicator tracks the availability of greenspace in urban areas around the world.

View fullscreen:

Headline findings

Globally in 2020, 27% of urban centres were classified as being moderately green or above, an increase from 14% in 2010; the percentage of cities under this classification varied from 17% of urban centres in the low HDI country groups to 39% of urban centres in the very high HDI country group.

Data sources

1. Global Human Settlement program, European Commission – Urban Centre Database GHS-UCDB R2019A.

2. NASA GPWv4 from Columbia University’s CIESIN for years 2010, 2015 and 2020.

3. Normalized Difference Vegetation Index (NDVI) was estimated from Landsat satellite images, a joint programme from the US Geological Survey and NASA.

Caveats

This indicator does not provide information on the quality or type of green space, nor on its accessibility. In tracking urban areas as defined by the Global Human Settlement (GHS) 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 generalizability of the findings.

 

This indicator was last updated in September 2021

Indicator description

This indicator quantifies exposure to urban green space for 2020 in the 1,029 urban centres across 168 countries that have more than 500,000 inhabitants or are the most populous centres in countries underrepresented 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 Normalised Difference Vegetation Index (NDVI).

2.4 Spending on Adaptation for Health and Health-Related Activities

Health is consistently identified as a key priority area for climate change adaptation, with countries increasingly allocating financial resources to deliver this. This indicator tracks total multilateral adaptation spending in the health sector and global financial transactions with the potential to deliver adaptation in the health and care sector and other sectors with potential secondary benefits for health.

View fullscreen:

Headline findings

Globally, adaptation funding that is directed at health systems represents a small proportion of total climate change adaptation funding (0.3%), and only 5.6% of all transactions with adaptation potential were relevant to health in 2019–20.

Data sources

1. Adaptation Funding Dataset from Climate Funds Update

2. Adaptation and Resilience to Climate Change dataset from kMatrix Ltd, in partnership with University College of London

3. IMF World Economic Outlook October 2020 update

Caveats

Due to limitations in data available, data on adaptation funding corresponds to the year that funds were approved, rather than the disbursement of funds. Consequently, it is anticipated that there can be several years of delay between approval and disbursement. The kMatrix dataset only includes economic transactions for which there is transactional/financial data available, and data only corresponds to the year that funds were approved rather than disbursed.

 

This indicator was last updated September 2021

Indicator description

This indicator monitors two elements of spending that could provide adaptation for health. The first element is the global funding approved for health-related adaptation projects through multilateral funds. The second element is global financial transactions with the potential to deliver adaptation in the health and care sector and other sectors that are relevant to the determinants of health (eg, waste and water management, built environment, or agricultural sectors).

THE HEALTH BENEFITS OF THE RESPONSE TO CLIMATE CHANGE

Tackling climate change could be the greatest global health opportunity of the 21st century. Many of the interventions required to mitigate and adapt bring enormous benefits for human health and wellbeing in the form of cleaner air, healthier diets, and more liveable cities. Indicators in this section track the world’s efforts to mitigate climate change, and the health benefits of this response.

View fullscreen:

3.1 Energy System and Health

Tackling climate change could be the greatest global health opportunity of the 21st century. Many of the interventions required to mitigate and adapt bring enormous benefits for human health and wellbeing in the form of cleaner air, healthier diets, and more liveable cities. Indicators in this section track the world’s efforts to mitigate climate change, and the health benefits of this response.

View fullscreen:

3.1.1 Carbon Intensity of the Energy System

The power generation sector is the largest contributor to global greenhouse gas emissions. Burning fossil fuels contributes to the majority of these emissions, and to toxic air pollution. This indicator monitors the carbon intensity of the energy system and greenhouse gas emissions from power generation.

View fullscreen:

Headline findings

From 2014 to 2018, despite strong growth in renewable energy in countries with a very high HDI, the carbon intensity of the global energy system has seen an annual average decline of just 0.6%, which is a rate incompatible with meeting the ambitions of the Paris Agreement.

Data sources

1. CO2 Emissions from Fuel Combustion Statistics, 2021. IEA

Caveats

The indicator does not provide information on the share of different fossil fuels, their use in different sectors, and the absolute levels of usage.

 

This indicator was last updated in September 2021

Indicator description

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.

3.1.2 Coal Phase-Out

Coal combustion continues to be the largest contributor to emissions from the energy sector and is a major contributor to premature mortality due to air pollution. The phase-out of coal-fired power is therefore an important first step in the mitigation of climate change. This indicator tracks progress towards coal phase-out.

View fullscreen:

Headline findings

In 2019, global coal use for all activities fell 1.2%. Global coal demand is expected to rise by 4.5% in 2021.

Data sources

1. World Extended Energy Balances, 2020. IEA

Caveats

This indicator is unavailable for select countries. Data reported to IEA can be impacted by changes in reporting country methodologies.

 

This indicator was last updated in September 2021

Indicator description

This indicator 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.

3.1.3 Zero-Carbon Emission Electricity

Continued growth in renewable energy, particularly wind and solar sources, is key to replacing fossil fuels. This indicator tracks electricity generation and the share of total electricity generation from all low-carbon sources.

View fullscreen:

Headline findings

While energy demand for coal, gas, oil and nuclear fell in 2020, renewables demand grew by a small amount, 0.9%.

Data sources

1. World Extended Energy Balances, 2020. IEA

Caveats

This indicator is unavailable for select countries. Data reported to IEA can be impacted by changes in reporting country methodologies.

 

This indicator was last updated in September 2021

Indicator description

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).

3.2 Clean Household Energy

The use of unhealthy and unsustainable fuels and technologies for cooking, heating, and lighting in the home contributes both to greenhouse gas emissions and to dangerous concentrations of household air pollution. This indicator tracks the proportion of the population who use clean fuels and technologies for cooking and tracks types of energy usage in the residential sector.

View fullscreen:

Headline findings

While progress has been made in the use of clean fuels in the home, in 2019, only 12% of households in the low Human Development Index (HDI) group primarily relied on clean fuels and technologies for cooking. In medium and high HDI group countries, the share of solid biofuel has fallen more rapidly and clean cooking fuel technology use has risen substantially.

Data sources

1. World Energy Balances, 2020. IEA

2. Household Energy Database, 2020. WHO – World Population Prospects: 2017 Revision.

3. United Nations DESA/Population Division – 2013 Global Burden of Disease Study

4. integrated exposure-response (IER) functions and mortality rates were taken from the 2019 GBD Project

Caveats

The data from the IEA on residential energy flows and energy access provide an indication of both the access to electricity and the proportion of the different types of energy used within the residential sector, providing a suggested picture on how access and use might be interacting.

 

This indicator was last updated in September 2021

Indicator description

This indicator draws on national surveys collected by WHO across 194 countries and tracks the proportion of the population who use clean fuels and technologies for cooking, defined as those that have emission rate targets meeting WHO’s 2005 guidelines for air quality. This indicator also tracks energy at point of use with data from the IEA.

3.3 Mortality from Ambient Air Pollution by Sector

Air pollution is responsible for over several million premature deaths every year, with some 91% of deaths from ambient air pollution occurring in low-income and middle-income countries. The majority of this pollution originates from sectors that also produce greenhouse gas emissions, presenting an opportunity for win-win interventions. This indicator tracks global mortality attributable to ambient PM2.5 by sector.

View fullscreen:

Headline findings

3.3 million deaths were attributed to ambient PM2.5 pollution from human sources in 2019 – a third of which were directly related to fossil fuel combustion. The medium and high Human Development Index (HDI) groups suffered the highest mortality rates.

Data sources

1. World Energy Outlook, 2019 and 2020. IEA

2. WHO’s Urban Ambient Air Pollution Database (2018 update)

3. Global Burden of Disease 2019 study, MR-BRT curves. Institute for Health Metrics and Evaluation

Caveats

Different dose-response relationships are used for Europe (REVIHAAP, recommended by WHO-Europe) and Asia (WHO-Global). The non-linearity of the IERs used for non-European countries means that in highly polluted environments, the health benefits of a marginal reduction of emissions would be disproportionately smaller than the relative change in concentrations.

 

This indicator was last updated in September 2021

Indicator description

This indicator models the premature deaths caused by air pollution from individual economic sectors, combining bottom-up emission calculations with atmospheric chemistry and dispersion coefficients and then applying this to population data and PM2.5 exposure-response relationships. It also highlights the contribution to premature deaths from coal and biomass burning across all sectors.

3.4 Sustainable and Healthy 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. This indicator tracks fuel use for road transportation on a per capita basis, by fuel type.

View fullscreen:

Headline findings

Electricity use in transport rose by 15% from 2017 to 2018 and the global electric vehicle fleet topped 7.2 million cars in 2019; however, emissions from road transport also continued to increase.

Data sources

1. World Extended Energy Balances, 2020. IEA

2. UN Population estimates, 2019 edition

Caveats

This indicator 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.

 

This indicator was last updated in September 2021

Indicator description

This indicator captures change in total fuel use and type of fuel used for transport as well as electric vehicles on a per capita basis.

3.5 Food, Agriculture and Health

View fullscreen:

Headline Finding

Total emissions from livestock and crop production have increased by 14% and 10%, respectively, from 2000 to 2016, with 93% of livestock emissions attributed to ruminants.

Indicator Description

This indicator tracks emissions from livestock and crop production, providing the tonnes of CO2 equivalents emitted by animal or crop type, and by emission source.

Caveats

Data limitations – for example on grazing emissions from small island states – have been overcome with modelled outputs.

This indicator was last updated in July 2019

Data Sources

– Herrero M, Havlík P, Valin H, et al. Biomass use, production, feed efficiencies, and greenhouse gas emissions from global livestock systems. Proceedings of the National Academy of Sciences 2013; 110(52): 20888-93.

– FAOSTAT, 2019. FAO

– Chang J, Ciais P, Herrero M, et al. Combining livestock production information in a process-based vegetation model to reconstruct the history of grassland management. Biogeosciences 2016; 13(12): 3757-76.

– Carlson KM, Gerber JS, Mueller ND, et al. Greenhouse gas emissions intensity of global croplands. Nature Climate Change 2017; 7(1): 63

3.5.1 Emissions from Agricultural Production and Consumption

The food system is responsible for 20–30% of global greenhouse gas emissions, most of which originate from meat and dairy livestock. Although countries’ emissions are typically measured on a production basis, it is their consumption that generates the demand and results in diet-related health outcomes. This indicator tracks agricultural emissions from countries’ production and consumption.

View fullscreen:

Headline findings

Mostly caused by high quantities of red meat consumption, per-capita emissions from food consumption are considerably greater in the very high HDI country group than in other HDI country groups and are 61% higher than in the low HDI group in 2018.

Data sources

1. Herrero M, Havlík P, Valin H, et al. Biomass use, production, feed efficiencies, and greenhouse gas emissions from global livestock systems. Proceedings of the National Academy of Sciences 2013; 110(52): 20888-93.

2. 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.

3. Chang J, Ciais P, Herrero M, et al. Combining livestock production information in a process –
based vegetation model to reconstruct the history of grassland management. Biogeosciences 2016; 13 (12): 3757 – 76.

4. FAOSTAT, 2020. FAO

5. Carlson KM, Gerber JS, Mueller ND, et al. Greenhouse gas emissions intensity of global croplands. Nature Climate Change 2017; 7(1): 63

Caveats

Consumption refers to the net balance of food products entering a country within a given year, ie. national production and net imports together. It does not refer to the total GHG emissions attributable to food consumed by individuals. For livestock, some data is missing for some years, most notably Somalia (2000-2011) for non-dairy cattle, as well as data on grazing emissions from small islands are also missing. The emission factors differ from FAO numbers for livestock and for crops, due to the methodology used.

 

This indicator was last updated in September 2021

Indicator description

Agricultural emissions from countries’ production and consumption (adjusting for international trade) were tracked by use of data from the Food and Agriculture Organization of the United Nations.

3.5.2 Diet and Health Co-Benefits

Combined with a range of food system-wide interventions, achieving dietary change consistent with the Paris Agreement and the sustainable development goals is possible by reducing reliance on red meat consumption and prioritising healthier alternatives, with various diets and choices available depending on the region, individual, and cultural context. This indicator presents the change in deaths attributable to dietary risks by focusing on one particular area—the consumption of excess red meat.

View fullscreen:

Headline findings

Between 2017 and 2018 the estimated deaths due to excess red meat consumption rose by 1.8% to 842,000 deaths.

Data sources

1. FAO balance sheets, 2020

2. Miller V, Singh GM, Onopa J, et al. Global Dietary Database 2017: data availability and gaps on 54 major foods, beverages and nutrients among 5.6 million children and adults from 1220 surveys worldwide. BMJ Global Health 2021; 6 (2): e003585.

3. NCD. Risk Factor Collaboration. Trends in adult body-mass index in 200 countries from 1975 to 2014: a pooled analysis of 1698 population-based measurement studies with 19.2 million participants. The Lancet 2016; 387 (10026): 1377 – 96

4. Afshin A, Micha R, Khatibzadeh S, Mozaffarian D. Consumption of nuts and legumes and risk of incident ischemic heart disease, stroke, and diabetes: a systematic review and meta-analysis. The American Journal of Clinical Nutrition 2014; 100 (1): 278 – 88. 216.

5. Aune D, Keum N, Giovannucci E, et al. Nut consumption and risk of cardiovascular disease, total cancer, all-cause and cause-specific mortality: a systematic review and dose-response meta-analysis of prospective studies. BMC medicine 2016; 14 (1): 207.

6. Aune D, Giovannucci E, Boffetta P, et al. Fruit and vegetable intake and the risk of cardiovascular disease, total cancer and all-cause mortality —a systematic review and dose-response meta-analysis of prospective studies. International Journal of Epidemiology 2017; 46 (3): 1029 -56.

7. Bechthold A, Boeing H, Schwedhelm C, et al. Food groups and risk of coronary heart disease, stroke and heart failure: A systematic review and dose-response meta-analysis of prospective studies. Critical Reviews in Food Science and Nutrition 2019; 59 (7): 1071-90.

8. Schwingshackl L, Hoffmann G, Lampousi AM, et al. Food groups and risk of type 2 diabetes mellitus: a systematic review and meta-analysis of prospective studies. European Journal of Epidemiology 2017; 32 (5): 363 – 75.

9. Schwingshackl L, Schwedhelm C, Hoffmann G, et al. Food groups and risk of colorectal cancer. International Journal of Cancer 2018; 142 (9): 1748 – 58.

10. Global Bmi Mortality Collaboration DE, Di Angelantonio E, Bhupathiraju S, et al. Body mass index and all-cause mortality: individual – participant data meta-analysis of 239 prospective studies in four continents. Lancet (London, England) 2016; 388 (10046): 776 – 86.

11. Wang H, Abbas KM, Abbasifard M, et al. Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950–2019: a comprehensive demographic analysis for the Global Burden of Disease Study 2019. The Lancet 2020; 396(10258): 1160-203.

12. Gustavsson J, Cederberg C, Sonesson U, Van Otterdijk R, Meybeck A. Global food losses and food waste: extent, causes and prevention. Rome, Italy: Food and Agriculture Organization of the United Nations, 2011.

Caveats

The relative risks used are all supported by statistically significant dose-response relationships in meta-analyses and the existence of plausible biological pathways, however, there are caveats related to nutritional epidemiological studies, such as potential measurement error of dietary exposure. Evidence quality was graded with NutriGrade as moderate or high-quality evidence and the Nutrition and Chronic Disease Expert Group and World Cancer Research Fund graded the evidence for a causal association of 10 of the 12 risk factors as probable or convincing.

 

This indicator was last updated in September 2021

Indicator description

This indicator involves a comparative risk assessment, linking food consumption data disaggregated by sex and age (adjusted for food waste to estimate exposure) from the food balance sheets of the Food and Agriculture Organization of the United Nations with dietary and weight-related risk factors.

3.6 Mitigation in the Healthcare Sector

Health care is among the most important sectors in managing the effects of climate change and, simultaneously, has an important role in reducing its own carbon emissions. This indicator measures healthcare emissions that come directly from the sector and indirectly through purchased goods and services.

View fullscreen:

Headline findings

The healthcare sector was responsible for 4.9% of global greenhouse gas emissions in 2018. Healthcare emissions are positively associated with Human Development Index levels, largely through health spending, but minimal association is seen after emissions of 400 kg CO2eq per capita.

Data sources

1. World Input-Output Database (WIOD) 2013 release with environmental accounts

2. EXIOBASE3

3. Global Health Expenditure Database: Indicators and data, 2018. World Health Organization

4. Population data, World Health Organization

5. Market exchange rates from UN statistics division

6. Consumer price index, 2020. World Bank Group

7. Human Development Index, 2021. UNDP

Caveats

Since only total health expenditure data is available from WHO, expenditures could not be separated as demand vs investment. MRIO models are built from aggregated top-down statistical data – as such results do not reflect individual healthcare systems’ power purchase agreements for renewable energy or offsetting activities. Results do not include direct emissions of waste anaesthetic gases from clinical operations or emissions from metered-dose inhalers since these are not currently reported consistently in national emissions inventories.

 

This indicator was last updated in September 2021

Indicator description

This indicator models emissions from the global healthcare sector by use of environmentally extended multi-region input-output (EE MRIO) models combined with data on healthcare expenditure from WHO. It also matches per-capita greenhouse gas emissions data with the Human Development Index (HDI), which is a composite calculated index published annually by UNDP.

Economics and Finance

The data here works to track the financial and economic dimensions of the effects of climate change, and of mitigation efforts required to respond to these changes. Indicators here monitor the economic costs of climate change and its drivers, as well as the investments and economic tools being deployed to transition to a low-carbon economy.

View fullscreen:

4.1 The Economic Impact of Climate Change and its Mitigation

The data here works to track the financial and economic dimensions of the effects of climate change, and of mitigation efforts required to respond to these changes. Indicators here monitor the economic costs of climate change and its drivers, as well as the investments and economic tools being deployed to transition to a low-carbon economy.

View fullscreen:

Headline Finding

In 2018, 831 climate-related extreme events resulted in US$166 billion in economic losses and no measurable losses in low-income countries were covered by insurance.

Indicator Description

This indicator tracks the total measurable annual economic losses (insured and uninsured) relative to GDP, resulting from climate-related extreme events.

Caveats

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 July 2019

Data Sources

– NatCatSERVICE, 2019. Munch Re

4.1.1 Economic Losses due to Climate-Related Extreme Events

Climate-related extreme events result in direct deaths and injury, the spread of water-borne illness, and the destruction of habitats and infrastructure. Compounding this, these events often result in large economic costs, exacerbating the direct health impacts they produce. This indicator tracks the insured and uninsured economic losses from extreme events.

View fullscreen:

Headline findings

When normalised by gross domestic product, economic losses from climate-related extreme events in 2020 were three times greater in the medium HDI country group than in the very high HDI country group.

Data sources

1. Swiss Re Institute: sigma catastrophe database, 2021

2. IMF World Economic Outlook

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 September 2021

Indicator description

This indicator tracks the total annual economic losses (insured and uninsured) relative to GDP, that result from climate-related extreme events.

4.1.2 Costs of Heat-Related Mortality

Exposure to extremes of heat results in an increase in all-cause mortality, particularly in the over 65 population. As exposures to extremes of heat and the resulting health outcomes continue to rise, this indicator places a monetary value on heat-related mortality for the population 65-and-over.

View fullscreen:

Headline findings

The monetised value of global heat-related mortality increased by 6.7%, from 0.27% of gross world product in 2018 to 0.28% in 2019; Europe continued to be the worst affected region, facing costs equivalent to the average income of 6.1 million of its citizens.

Data sources

1. ERA5 reanalysis, 2021. European Centre for Medium-Range Weather Forecast.

2. Gridded Population of the World. 4 ed (GPWv4), 2021. NASA. Histsoc dataset, 2020. Inter-Sectoral Impact Model Intercomparison Project – 2020

3. Revision of World Population Prospects, 2021. United Nations DESA/Population Division

4. Mortality rate and life expectancy data. Global Burden of Disease, 2021. Institute for Health Metrics and Evaluation.

5. Population data, World Bank Group, 2019.

6. GDP per capita for OECD countries. OECD statistics, 2021.

7. Mortality Risk Valuation in Environment, Health and Transport Policies, 2012. OECD

8. WHO methods and data sources for global burden of disease estimates 2000-2015, 2017.

Caveats

VSL values rely on estimates of ‘willingness to pay’ by individuals, which are influenced by the survey design and characteristics of individuals surveyed. As VSL estimates are not available for all countries and regions, the calculation method employed assumes that the average individual’s willingness to pay to reduce the risk of death is linked to the GDP per capita of the country in which they find themselves. VSLY is assumed to be constant at different ages while some studies argue that the distribution of VSLY to age is an Inverted-U shaped.

This indicator was last updated in September 2021.

Indicator description

This indicator combines estimates on heat-related mortality from indicator 1.1.6 and the value of statistical life-year (VSLY) estimated for the member countries of the Organisation for Economic Cooperation and Development (OECD) using a fixed ratio of the value of VSLY to gross domestic product (GDP) per capita. The value of mortality is presented as a proportion of total GDP and as number of peoples’ incomes the loss would be equivalent to in a given country and region.

4.1.3 Loss of Earnings from Heat-Related Labour Capacity Reduction

Higher temperatures, driven by climate change, are affecting people’s ability to work. This indicator considers the loss of earnings that could result from such reduced capacity, compounding the initial cause of ill health and impacting on wellbeing.

View fullscreen:

Headline findings

Working in conditions of extreme heat is a health risk; such conditions could reduce the capacity for paid labour, with an impact on workers’ earnings equivalent to 4–8% of GDP in the low HDI country group in 2020.

Data sources

1. ERA5 reanalysis, 2021. European Centre for Medium-Range Weather Forecasts

2. Gridded Population of the World. 4 ed (GPWv4), 2021. NASA

3. Sector employment and earnings data from ILOSTAT, 2021.

4. World Economic Outlook database, 2021. IMF

5. International Finance Statistics, 2021. IMF

Caveats

There are data gaps in the ILO 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 account for time off work was actually taken. Results reflect potential loss of earnings in formal paid sectors, rather than actual loss, and do not include informal and unpaid labor that is significant in many countries. These estimates are conservative, as they assume all work is undertaken in the shade, not accounting for the influence of solar radiation.

 

This indicator was last updated in September 2021

Indicator description

The indicator combines heat-related potential work hours lost in agriculture, construction, service, and industry as estimated in Indicator 1.1.4 with data on average earnings by country and sectors.

 

4.1.4 Costs of the Health Impacts of Air Pollution

Air pollution is responsible for over seven million deaths each year, resulting in profound economic costs. Efforts to mitigate climate change often reduce air pollution, resulting in significant cost-savings and a cost-effective intervention. This indicator tracks the costs of life lost from exposure to anthropogenic air pollution.

View fullscreen:

Headline findings

Equivalent to the annual income of 78.1 million and 99.1 million people, the greatest economic costs of mortality due to air pollution fall on countries in the medium and high HDI country groups; costs relative to GDP decreased between 2015 and 2019 globally, with the exception of costs in southeast Asia.

Data sources

1. World Energy Outlook, 2019 and 2020. IEA

2. WHO’s Urban Ambient Air Pollution Database (2018 update)

3. UN World Prospects (2017 update)

4. Global Burden of Disease 2019 study, MR-BRT curves. Institute for Health Metrics and Evaluation

5. Population data, World Bank Group, 2019.

6. GDP per capita for OECD countries. OECD statistics, 2021.

7. Mortality Risk Valuation in Environment, Health and Transport Policies, 2012. OECD

8. WHO methods and data sources for global burden of disease estimates 2000-2015, 2017.

9. IMF World Economic Outlook, April 2021

10. UN World population prospects, 2019

Caveats

VSL values rely on estimates of ‘willingness to pay’ by individuals, which are influenced by the survey design and characteristics of individuals surveyed. As VSL estimates are not available for all countries and regions, the calculation method employed assumes that the average individual’s willingness to pay to reduce the risk of death is linked to the GDP per capita of the country in which they find themselves. VSLY is assumed to be constant at different ages while some studies argue that the distribution of VSLY to age is an Inverted-U shaped.

 

This indicator was last updated in September 2021

Indicator description

This indicator estimates the change in Years of Life Lost (YLLs) due to anthropogenic PM2.5 for 137 countries in years 2015 and 2019. It combines data from Indicator 3.3 and the value of statistical life-year (VSLY) estimated for the member countries of the Organisation for Economic Cooperation and Development (OECD) using a fixed ratio of the value of VSLY to gross domestic product (GDP) per capita. The value of mortality is presented as a proportion of total GDP and as number of people’s income the loss would be equivalent to in a given country and region.

4.2 The Economics of the Transition to Zero-Carbon Economies

View fullscreen:

Headline Finding

In Europe, improvements in particulate air pollution from human activity were seen from 2015 to 2016. If the levels of pollution for these two years remained the same over a person’s lifetime, this would lead to an annual average reduction in Years of Life Lost worth €5.2 billion.

Indicator Description

This indicator estimates the change in Years of Life Lost due to PM2.5 in European Union countries from 2015 to 2016, applied across 100 years to the 2015 population. A Value of a Life Year (€50,000) is then assigned to the Years of Life Lost to give an estimation of the annual average economic reduction of this change in PM2.5.

Caveats

Data is only available for EU countries and will be expanded in subsequent years. A Value of a Life Year of €50,000 is the lower bound estimate as suggested by the EU Impact Assessment Guidelines. This value does not take into account the health economic costs of healthcare delivery or societal economic costs such as workforce losses, thus representing an underestimation of real economic losses.

This indicator was last updated in July 2019

Data Sources

– Amann M, Bertok I, Borken-Kleefeld J, et al. Cost-effective control of air quality and greenhouse gases in Europe: Modeling and policy applications. Environmental Modelling & Software 2011; 26(12): 1489-501

– World Energy Outlook, 2017. IEA

4.2.1 Coal and Clean Energy Investment

Coal phase-out is both an essential first step in the response to climate change, and an important intervention to reduce morbidity and mortality from air pollution. Investment in zero-carbon energy and energy efficiency must continue to displace investment in fossil fuels if the world is to meet its commitments under the Paris Agreement. This indicator monitors investments in new coal-fired capacity and in renewable energy supply and energy efficiency.

View fullscreen:

Headline findings

Global investment in energy supply and energy efficiency reduced by 13% between 2019 and 2020; investment in renewable energy and energy efficiency increased by 3% and investment in new coal capacity reduced by 13%.

Data sources

1. World Energy Investment, 2021. IEA

Caveats

Investment estimates are derived from IEA 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 September 2021

Indicator description

This indicator draws on data from the annual International Energy Agency World Energy Investment to track global coal investment, as a percentage of a 2006 baseline. It also uses the IEA data to assess 7 categories of investment: hydropower, bioenergy, other renewables (include solar and wind), nuclear power, energy efficiency, electricity networks and storage and fossil fuels.

4.2.2 Employment in Low-Carbon and High-Carbon Industries

Evidence suggests that employees in some fossil fuel extraction industries and their local communities, suffer a greater incidence of cardiovascular and cerebrovascular disease, respiratory disease and cancers. Investments in renewable energies and energy efficiency are estimated to create almost three times more jobs per unit of spending than those in fossil fuel industries. Along with strong labour and environmental standards, investment and employment in renewables present an opportunity to improve health and livelihoods. This indicator tracks global direct employment in fossil fuel extraction industries and direct and indirect (supply chain) employment in renewable energy.

View fullscreen:

Headline findings

Direct employment in fossil fuel extraction declined by 14% from 13.1 million in 2019 to 12.7 million in 2020.

Data sources

1. Employment in renewables, 2018, IRENA.

2. IBISWorld: oil and gas exploration and production; coal mining, 2021. IBISWorld

Caveats

Fossil fuel extraction values include direct employment, whereas renewable energy jobs include direct and indirect employment.

At the time of writing, 2020 data on employment in the renewables sector was unavailable.

 

This indicator was last updated in September 2021

Indicator description

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

4.2.3 Funds Divested from Fossil Fuels

Public health institutions have a long history of divesting from products that harm the health of their patients – whether they be tobacco, alcohol, or arms. Increasingly, they are choosing not to invest in the fossil fuel industry because of its impact on public health and on climate change. This indicator tracks the global value of fossil fuel divestment and the value of funds divested by health and medical institutions.

View fullscreen:

Headline findings

The global value of funds committing to fossil fuel divestment between 2008 and 2020 was US$14.52 trillion, with health institutions accounting for US$42 billion.

Data sources

1. Divestment Commitments dataset, 2021. 350.org

Caveats

Due to confidentiality issues, the value of funds divested by each organization is not available. The year of divestment reflects the year when the commitment was recorded in 350.org.

 

This indicator was last updated in September 2021

Indicator description

This indicator tracks the total global value of funds divested from fossil fuels, and the value of divested funds coming from health institutions, using self-reported data from 350.org. The following organisations classified as non-health institutions by 350.org have been considered as health institutions for the purpose of this indicator: HESTA Super Fund; Doctors for the Environment Australia; London School of Hygiene & Tropical Medicine; Berliner Ärzteversorgung / Berlin Doctor’s Pensionfund; HCF; The Royal College of General Practitioners; New Zealand Nurses Organisation; the Royal College of Emergency Physicians. Divestment commitments by the American Medical Association, which divested in 2018, were added separately.

4.2.4 Net Value of Fossil Fuel Subsidies and Carbon Prices

Placing a price on greenhouse gas emissions provides an incentive to drive the transition towards a low-carbon economy. This strategy also allows for a close reflection of the true cost of emissions-intensive practices, particularly fossil fuel use, capturing some of the negative externalities resulting from their impact on health. However, not all countries have explicitly set carbon prices, and, in some cases, the strength of any carbon price might be undermined by the opposing influence of subsidies on fossil fuel production and consumption. As the world works to move away from fossil fuel use, this indicator tracks both carbon pricing mechanisms and fossil fuel subsidies to estimate net carbon prices and revenues.

View fullscreen:

Headline findings

65 (77%) of the 84 countries reviewed had a net-negative carbon price in 2018; the resulting net loss of revenue was, in many cases, equivalent to substantial proportions of the national health budget.

Data sources

1. Energy Subsidies, 2021. IEA.

2. OECD Inventory of support measures for fossil fuels, 2021. OECD

3. Carbon Pricing Dashboard, 2021. World Bank

4. Carbon dioxide Emissions from Fuel Combustion, 2020. IEA

5. Global Health Expenditure Database, 2021. WHO

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 September 2021

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 carbon dioxide emissions, while negative results indicate a net subsidy for fossil fuels.

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

The production of goods and services drives both greenhouse gas and PM2.5 emissions, thus 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, which is essential to enable better international policy formulation that protects human health in all geographies. As the world works towards net-zero emissions, this indicator tracks the pollution burden from a country’s local production and final consumption.

View fullscreen:

Headline Finding

In 2019, 18% of CO2 and 17% of PM2.5 global emissions were embodied in trade between countries of different Human Development Index levels.

Headline Finding

1. EXIOBASE3, 2019.

2. Global Carbon Budget 2020.

3. GAINS model

4. EDGAR database

Caveats

GAINS process emissions are only distributed across MRIO sectors that can be clearly identified. Truck-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 September 2021

Indicator description

This indicator estimates the embodied flows of CO2 and PM2.5 in international trade and then calculates national CO2 and PM2.5 emissions from the consumption perspective using environmentally extended multi-regional input-output (EEMRIO) analysis.

Public and Political Engagement

Public and political engagement underpins the foundations of the world’s collective response to climate change, with reductions in global emissions at the speed required by the Paris Agreement depending on engagement from all sectors of society. The indicators in this section track the links between health and climate change in the media, national governments, the corporate sector, and the broader public.

View fullscreen:

5.1 Media Coverage of Health and Climate Change

Newspapers provide an important forum for public engagement. They 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 leading newspapers in 36 countries.

View fullscreen:

Headline findings

In 2020, the upward trend in coverage of health and climate change continued but did not match the increase seen in 2019; in 2020, most of the coverage of health and climate change referred to COVID-19.

Data sources

1. Nexis Uni® database

2. Factiva© database

3. ProQuest LLC database

4. People’s Daily Mandarin edition

5. Hindustan Times

6. Times of India

7. New York Times

8. Washington Post

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. Also, 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 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. However, including this coverage remains important as it brings both sets of issues – health and climate change – onto the public agenda and into public awareness.

 

This indicator was last updated in September 2021

Indicator description

This indicator has both a quantitative and qualitative component to its tracking of health and climate change in the media. Articles from 2007 to 2020 in 66 newspapers across 36 countries, written in English, German, Portuguese and Spanish were analysed using keyword 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. For the qualitative content analysis, this indicator assesses the content of health and climate change in elite press in the USA and India across two key periods in 2020.

5.2 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 Wikipedia in relation to the link between climate change and health.

View fullscreen:

Headline findings

Individual information seeking about health and climate change decreased overall by 15% from 2019 to 2020; spikes in engagement in mid-2020 were almost exclusively due to interest in pandemic-related content.

Data sources

1. Wikimedia Dumps, 2021. https://dumps.wikimedia.org/other/clickstream/

Caveats

The data is not geo-referenced, so it is not possible to infer the location page visits came from. Only English Wikipedia pages were considered in the analysis (approximately 50% of total Wikipedia pages), and while they are accessed globally, it is somewhat biased towards English-speaking countries.

 

This indicator was last updated in September 2021

Indicator description

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 2018-2020. This “clickstream data” is used as a proxy for the degree to which individuals engage with health and climate change as related issues.

5.3 Coverage of Health and Climate Change in Scientific Journals

Peer-reviewed scientific journals are the premier source of high-quality research that provides evidence used by the media, the government, and the public. This indicator tracks scientific engagement with health and climate change in peer-reviewed journals.

View fullscreen:

Headline findings

Original research on health and climate change increased 11-fold between 2007 and 2020, driven primarily by scientists in countries in the very high HDI group; the number of articles on health and climate change that addressed gender remained low; and in 2020, 7% of health and climate change articles referred to COVID-19.

Data sources

1. OVID MEDLINE

2. OVID Embase

Caveats

The methodology provided here enables a quantitative appraisal of the research question. The quality of the data and the specifics of its content are not assessed. However, with the outputs all published in peer-reviewed journals, there is a de facto quality check. For this reason, the indicator does not cover grey literature.

 

This indicator was last updated in September 2021

Indicator description

This indicator identifies original research articles and research-related articles published from 2007 to 2020 that cover health and climate change topics, using keyword searches for health and climate change in OVID MEDLINE and OVID Embase. It used the comprehensive indexing systems and thesaurus of Medical Subject Headings for MEDLINE and Emtree for Embase and the search strategy was refined for a >90% sensitivity and >50% precision for each database. Articles were geographically organised based on the institution of the first author.

5.4 Government Engagement in Health and Climate Change

Meeting the commitments under the Paris Agreement require accelerated and ambitious interventions from governments across the world. Ensuring these efforts maximise human health and wellbeing begins with these issues being recognised as important areas of concern, and as reasons for change. This indicator tracks references to health and climate change in the speeches of global leaders at the United Nations General Debate (UNGD), the key event for Member States to speak about their nations’ priorities and concerns.

View fullscreen:

Headline findings

In 2020, 47% of government leaders engaged with the health dimensions of climate change in their statements at the UN General Debate, which is more than double the proportion in 2019; this increase was linked to engagement with the COVID-19 pandemic.

Data sources

1. UNFCCC NDC Registry (interim)

2. UN General Debate statements (official English versions)

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 UNGD 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 indirect links between climate change and health.

This indicator was last updated in September 2021

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 (up until 31st March 2020) first 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 UN General Debate, which is part of the annual UN General Assembly, as a proxy of high-level political engagement on these two topics as separate and related issues.

5.5 Corporate Sector Engagement in Health and Climate Change

The corporate sector is central to the transition to a low-carbon economy, both through its own behaviour and greenhouse gas emissions and its wider political influence. This indicator tracks engagement with health and climate change in healthcare companies within the UN Global Compact, the world’s biggest corporate sustainability framework.

View fullscreen:

Headline findings

In 2020, engagement in health and climate change increased to its highest level among companies in the UN Global Compact. Over a third (38%) of companies referred to the health dimensions of climate change in their 2020 progress reports.

Data sources

1. UN Global Compact Communication on Progress reports.

Caveats

Only reports that were submitted in English have been considered. This means a little under half of all available reports have been analysed. This analysis is based on a narrow range of search terms, which excludes reference to many indirect links between climate change and health, meaning indirect connections, such as the effect of climate change on agriculture, are not captured.

 

This indicator was last updated in September 2021

Indicator description

UN Global Compact Communication on Progress reports from health and healthcare companies from 2011 to 2020, written in English and publicly available, were assessed for references to health and climate change using key search terms.