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Cited by 1,603Climate Change and Health ImpactsAir Quality and Health ImpactsClimate Change and Environmental Impact

The DOI matches its Crossref record; 210 of the 218 references it cites were found in a registry or an index.

The 2021 report of the Lancet Countdown on health and climate change: code red for a healthy future

Open access
Romanello, Marina, McGushin, Alice, Di Napoli, Claudia, Drummond, Paul, Hughes, Nick, Jamart, Louis, Kennard, Harry, Lampard, Pete, Solano Rodriguez, Baltazar, Arnell, Nigel, Ayeb-Karlsson, Sonja, Belesova, Kristine, Cai, Wenjia, Campbell-Lendrum, Diarmid, Capstick, Stuart, Chambers, Jonathan, Chu, Lingzhi, Ciampi, Luisa, Dalin, Carole, Dasandi, Niheer, Dasgupta, Shouro, Davies, Michael, Dominguez-Salas, Paula, Dubrow, Robert, Ebi, Kristie L, Eckelman, Matthew, Ekins, Paul, Escobar, Luis E, Georgeson, Lucien, Grace, Delia, Graham, Hilary, Gunther, Samuel H, Hartinger, Stella, He, Kehan, Heaviside, Clare, Hess, Jeremy, Hsu, Shih-Che, Jankin, Slava, Jimenez, Marcia P, Kelman, Ilan, Kiesewetter, Gregor, Kinney, Patrick L, Kjellstrom, Tord, Kniveton, Dominic, Lee, Jason K W, Lemke, Bruno, Liu, Yang, Liu, Zhao, Lott, Melissa, Lowe, Rachel, Martinez-Urtaza, Jaime, Maslin, Mark, McAllister, Lucy, McMichael, Celia, Mi, Zhifu, Milner, James, Minor, Kelton, Mohajeri, Nahid, Moradi-Lakeh, Maziar, Morrissey, Karyn, Munzert, Simon, Murray, Kris A, Neville, Tara, Nilsson, Maria, Obradovich, Nick, Sewe, Maquins Odhiambo, Oreszczyn, Tadj, Otto, Matthias, Owfi, Fereidoon, Pearman, Olivia, Pencheon, David, Rabbaniha, Mahnaz, Robinson, Elizabeth, Rocklöv, Joacim, Salas, Renee N, Semenza, Jan C, Sherman, Jodi, Shi, Liuhua, Springmann, Marco, Tabatabaei, Meisam, Taylor, Jonathon, Trinanes, Joaquin, Shumake-Guillemot, Joy, Vu, Bryan, Wagner, Fabian, Wilkinson, Paul, Winning, Matthew, Yglesias, Marisol, Zhang, Shihui, Gong, Peng, Montgomery, Hugh, Costello, Anthony, Hamilton, Ian·2021·The Lancet
DOI 10.1016/s0140-6736(21)01787-6PMC PMC7616807
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Crossref · 10.1016/s0140-6736(21)01787-6

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210 of 210 references verified0 citation errors · 0 not checkable

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Figures

Figure 1 Change in person-days of heatwave exposure relative to the 1986–2005 baseline (A) People younger than 1 year. (B) People older than 65 years. The dotted line at 0 represents the baseline.
Figure 1 Change in person-days of heatwave exposure relative to the 1986–2005 baseline (A) People younger than 1 year. (B) People older than 65 years. The dotted line at 0 represents the baseline.CC BY · PubMed Central
Figure 2 Average hours of safe physical activity lost per person due to high wet bulb globe temperatureby 2019 HDI country group (1980–2020) HDI=human development index.
Figure 2 Average hours of safe physical activity lost per person due to high wet bulb globe temperatureby 2019 HDI country group (1980–2020) HDI=human development index.CC BY · PubMed Central
Figure 3 Potential labour lost due to heat-related factors in each sector (1990–2000) Low HDI (A), medium HDI (B), high HDI (C), and very high HDI (D) groups (2019 HDI country group). HDI=human development index.
Figure 3 Potential labour lost due to heat-related factors in each sector (1990–2000) Low HDI (A), medium HDI (B), high HDI (C), and very high HDI (D) groups (2019 HDI country group). HDI=human development index.CC BY · PubMed Central
Figure 4 Heatwaves and sentiment on Twitter (A) Annual effect of heatwave exposure on the sentiment of Twitter users expressions from 2015–20. Boxes depict 95% CIs of the estimated average change in general sentiment expressions during days with heatwaves, relative to the median daily maximum temperature baseline range for each location and year. Sentiment was extracted from Twitter posts using a dictionary-based approach across multiple languages, see appendix 5 (p 16). Grey bars depict the geolocated Tweet count by year of observation. (A) Country-level count of total geolocated tweets for 2015–20.
Figure 4 Heatwaves and sentiment on Twitter (A) Annual effect of heatwave exposure on the sentiment of Twitter users expressions from 2015–20. Boxes depict 95% CIs of the estimated average change in general sentiment expressions during days with heatwaves, relative to the median daily maximum temperature baseline range for each location and year. Sentiment was extracted from Twitter posts using a dictionary-based approach across multiple languages, see appendix 5 (p 16). Grey bars depict the geolocated Tweet count by year of observation. (A) Country-level count of total geolocated tweets for 2015–20.CC BY · PubMed Central
Figure 5 Heat-related deaths of people older than 65 years in each country in 2019
Figure 5 Heat-related deaths of people older than 65 years in each country in 2019CC BY · PubMed Central
Figure 6 Annual population-weighted mean change in the number of days with very high and extremely high risk of wildfire from 2001–04 to 2017–20 for each country or territory Large urban areas with a population density ≥400 persons/km2 are excluded in the calculations of population-weighted mean values. Very high and extremely high risk is defined by the fire weather index.101
Figure 6 Annual population-weighted mean change in the number of days with very high and extremely high risk of wildfire from 2001–04 to 2017–20 for each country or territory Large urban areas with a population density ≥400 persons/km2 are excluded in the calculations of population-weighted mean values. Very high and extremely high risk is defined by the fire weather index.101CC BY · PubMed Central
Figure 7 Global land area affected by drought events per month Extreme drought is defined by a SPEI of ≤1·6 and exceptional drought is defined by a SPEI of ≤2. SPEI=standardised precipitation-evapotranspiration index.
Figure 7 Global land area affected by drought events per month Extreme drought is defined by a SPEI of ≤1·6 and exceptional drought is defined by a SPEI of ≤2. SPEI=standardised precipitation-evapotranspiration index.CC BY · PubMed Central
Figure 8 Change in climate suitability for infectious diseases Solid lines represent the annual change. Dashed lines represent the trend since 1950 (for dengue and malaria), 1982 (for Vibrio bacteria), and 2003 (for Vibrio cholerae). HDI=human development index.
Figure 8 Change in climate suitability for infectious diseases Solid lines represent the annual change. Dashed lines represent the trend since 1950 (for dengue and malaria), 1982 (for Vibrio bacteria), and 2003 (for Vibrio cholerae). HDI=human development index.CC BY · PubMed Central
Figure 9 Change in crop growth duration relative to the 1981–2010 global average The red line represents the annual global area-weighted change in crop growth duration. The blue line represents the running mean of change in crop growth duration over 11 years (5 years before and 5 years after).
Figure 9 Change in crop growth duration relative to the 1981–2010 global average The red line represents the annual global area-weighted change in crop growth duration. The blue line represents the running mean of change in crop growth duration over 11 years (5 years before and 5 years after).CC BY · PubMed Central
Figure 10 Global heat-related deaths of people aged 65 years and older and household air conditioning
Figure 10 Global heat-related deaths of people aged 65 years and older and household air conditioningCC BY · PubMed Central
Figure 11 Average urban population-weighted peak NDVI in each country or territory Average urban population-weighted peak NDVI for 2010 (A) and 2020 (B). Urban centres with >500000 inhabitants were included in the data. For countries without an urban centre of >500000 inhabitants, the most populated urban centre was used in the analysis. NDVI=normalised difference vegetation index.
Figure 11 Average urban population-weighted peak NDVI in each country or territory Average urban population-weighted peak NDVI for 2010 (A) and 2020 (B). Urban centres with >500000 inhabitants were included in the data. For countries without an urban centre of >500000 inhabitants, the most populated urban centre was used in the analysis. NDVI=normalised difference vegetation index.CC BY · PubMed Central
Figure 12 Spending per capita for potential adaptation to climate change for health Data for the health and health-care sector (A) and health-relevant sectors (B; see appendix 5 [p 109] for definition) in each 2019 HDI group. HDI=human development index.
Figure 12 Spending per capita for potential adaptation to climate change for health Data for the health and health-care sector (A) and health-relevant sectors (B; see appendix 5 [p 109] for definition) in each 2019 HDI group. HDI=human development index.CC BY · PubMed Central
Figure 13 Deaths attributable to exposure to PM2·5 in 2015, 2018, and 2019 by key sources of pollution and 2019 HDI groups HDI=human development index. PM2·5=fine particulate matter. *2015. †2018. ‡2019.
Figure 13 Deaths attributable to exposure to PM2·5 in 2015, 2018, and 2019 by key sources of pollution and 2019 HDI groups HDI=human development index. PM2·5=fine particulate matter. *2015. †2018. ‡2019.CC BY · PubMed Central
Figure 14 Deaths attributable to imbalanced diets and weight in 2018 by risk factor in each 2019 HDI group Each component in the stacked bar represents its individual contribution to attributable deaths. Since these contributions cannot be summed directly, the overall contribution by diet and weight components are represented by the dots as given in the key. HDI=human development index.
Figure 14 Deaths attributable to imbalanced diets and weight in 2018 by risk factor in each 2019 HDI group Each component in the stacked bar represents its individual contribution to attributable deaths. Since these contributions cannot be summed directly, the overall contribution by diet and weight components are represented by the dots as given in the key. HDI=human development index.CC BY · PubMed Central
Figure 15 Monetised cost of heat-related deaths by 2019 HDI group Monetised costs are expressed as the equivalent number of annual incomes of the average person lost. HDI=human development index.
Figure 15 Monetised cost of heat-related deaths by 2019 HDI group Monetised costs are expressed as the equivalent number of annual incomes of the average person lost. HDI=human development index.CC BY · PubMed Central
Figure 16 Average potential loss of earnings in the low HDI group as a result of potential labour loss due to heat exposure Losses are presented as a share of GDP by sector of employment. The agriculture and construction (sun additional) blocks represent the losses that would have been incurred in addition to those from agriculture and construction (shade) if all of the activities in these sectors had been carried out in direct sunlight. GDP=gross domestic product.
Figure 16 Average potential loss of earnings in the low HDI group as a result of potential labour loss due to heat exposure Losses are presented as a share of GDP by sector of employment. The agriculture and construction (sun additional) blocks represent the losses that would have been incurred in addition to those from agriculture and construction (shade) if all of the activities in these sectors had been carried out in direct sunlight. GDP=gross domestic product.CC BY · PubMed Central
Figure 17 Cost of year of life lost in 2015 and 2019 The equivalent number of annual incomes of the average person lost and total GDP in each 2019 HDI group. GDP=gross domestic product. HDI=human development index.
Figure 17 Cost of year of life lost in 2015 and 2019 The equivalent number of annual incomes of the average person lost and total GDP in each 2019 HDI group. GDP=gross domestic product. HDI=human development index.CC BY · PubMed Central
Figure 18 Annual investment in energy supply and energy efficiency globally
Figure 18 Annual investment in energy supply and energy efficiency globallyCC BY · PubMed Central
Figure 19 Net carbon prices, net carbon revenues, and net carbon revenue as a share of current national health expenditure across HDI groups (A) Net carbon prices. (B) Net carbon revenues. (C) Net carbon revenue as a share of current national health expenditure. Data from 84 countries in 2018, arranged by 2019 HDI group (low [n=1], medium [n=7], high [n=23], and very high [n=53]). Boxes represent IQR, horizontal lines inside the boxes represent the medians, and the brackets represent the range. HDI=human development index. tCO2=tonnes of carbon dioxide.
Figure 19 Net carbon prices, net carbon revenues, and net carbon revenue as a share of current national health expenditure across HDI groups (A) Net carbon prices. (B) Net carbon revenues. (C) Net carbon revenue as a share of current national health expenditure. Data from 84 countries in 2018, arranged by 2019 HDI group (low [n=1], medium [n=7], high [n=23], and very high [n=53]). Boxes represent IQR, horizontal lines inside the boxes represent the medians, and the brackets represent the range. HDI=human development index. tCO2=tonnes of carbon dioxide.CC BY · PubMed Central
Figure 20 The flows of embodied CO2 and PM2·5 emissions among HDI country groups in 2019 HDI=human development index.
Figure 20 The flows of embodied CO2 and PM2·5 emissions among HDI country groups in 2019 HDI=human development index.CC BY · PubMed Central
Figure 21 Aggregate monthly clicks between a health-related article and a climate-related article in Wikipedia, 2018—20
Figure 21 Aggregate monthly clicks between a health-related article and a climate-related article in Wikipedia, 2018—20CC BY · PubMed Central
Figure 22 Scientific journal articles relating to health and climate change by 2019 HDI group of the main country of affiliation of the first author, 2007–20
Figure 22 Scientific journal articles relating to health and climate change by 2019 HDI group of the main country of affiliation of the first author, 2007–20CC BY · PubMed Central
Figure 23 Proportion of countries referring to climate change, health, and the intersection between climate change and health in their UN General Debate statements, 1970–2020
Figure 23 Proportion of countries referring to climate change, health, and the intersection between climate change and health in their UN General Debate statements, 1970–2020CC BY · PubMed Central
Figure 24 Proportion of companies referring to climate change, health, and the intersection of climate change and health in their UN Global Compact Communication on Progress reports, 2011–20
Figure 24 Proportion of companies referring to climate change, health, and the intersection of climate change and health in their UN Global Compact Communication on Progress reports, 2011–20CC BY · PubMed Central

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Research works printed but not linked: 5

  1. Sanga, 2008, Addressing gender issues through the production and use of gender-sensitive information, Afr Stat J, 7, 116
  2. Shupler, 2020, COVID-19 lockdown in a Kenyan informal settlement: impacts on household energy and food security, medRxiv
  3. Ranger, 2013, Unburnable carbon 2013: wasted capital and stranded assets about the Grantham Research Institute on, Manag Environ Qual, 24, 1
  4. Hendryx, 2020, Impacts of coal use on health, Annu Rev Public Health, 41, 397, 10.1146/annurev-publhealth-040119-094104 · DOI
  5. Yoshida, 2015, Wikipedia page view reflects web search trend. Proceedings of the ACM Web Science Conference, Commun ACM, 65, 1

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Authors
Romanello, M., McGushin, A., Di Napoli, C., Drummond, P., Hughes, N., Jamart, L., Kennard, H., Lampard, P., Solano Rodriguez, B., Arnell, N., Ayeb-Karlsson, S., Belesova, K., Cai, W., Campbell-Lendrum, D., Capstick, S., Chambers, J., Chu, L., Ciampi, L., Dalin, C., Dasandi, N., Dasgupta, S., Davies, M., Dominguez-Salas, P., Dubrow, R., Ebi, K. L., Eckelman, M., Ekins, P., Escobar, L. E., Georgeson, L., Grace, D., Graham, H., Gunther, S. H., Hartinger, S., He, K., Heaviside, C., Hess, J., Hsu, S.-C., Jankin, S., Jimenez, M. P., Kelman, I., Kiesewetter, G., Kinney, P. L., Kjellstrom, T., Kniveton, D., Lee, J. K. W., Lemke, B., Liu, Y., Liu, Z., Lott, M., Lowe, R., Martinez-Urtaza, J., Maslin, M., McAllister, L., McMichael, C., Mi, Z., Milner, J., Minor, K., Mohajeri, N., Moradi-Lakeh, M., Morrissey, K., Munzert, S., Murray, K. A., Neville, T., Nilsson, M., Obradovich, N., Sewe, M. O., Oreszczyn, T., Otto, M., Owfi, F., Pearman, O., Pencheon, D., Rabbaniha, M., Robinson, E., Rocklöv, J., Salas, R. N., Semenza, J. C., Sherman, J., Shi, L., Springmann, M., Tabatabaei, M., Taylor, J., Trinanes, J., Shumake-Guillemot, J., Vu, B., Wagner, F., Wilkinson, P., Winning, M., Yglesias, M., Zhang, S., Gong, P., Montgomery, H., Costello, A., & Hamilton, I.
Affiliations
  • University College London (GB)
  • University of York (GB)
  • University of Reading (GB)
  • London School of Hygiene & Tropical Medicine (GB)
  • Tsinghua University (CN)
  • World Health Organization (CH)
  • Cardiff University (GB)
  • Yale University (US)
  • University of Birmingham (GB)
  • CMCC Foundation - Euro-Mediterranean Center on Climate Change (IT)
  • University of Washington (US)
  • Northeastern University (US)
  • Virginia Tech (US)
  • International Livestock Research Institute (KE)
  • National University of Singapore (SG)
  • Universidad Peruana Cayetano Heredia (PE)
  • Harvard University (US)
  • International Institute for Applied Systems Analysis (AT)
  • Boston University (US)
  • University of Sussex (GB)
  • Nelson Marlborough Institute of Technology (NZ)
  • Emory University (US)
  • Center on Global Energy Policy (US)
  • Technical University of Munich (DE)
  • The University of Melbourne (AU)
  • University of Copenhagen (DK)
  • Technical University of Denmark (DK)
  • Hertie School (DE)
  • Umeå University (SE)
  • Max Planck Institute for Human Development (DE)
  • Agricultural Research & Education Organization (IR)
  • Cooperative Institute for Research in Environmental Sciences (US)
  • University of Exeter (GB)
  • University of Oxford (GB)
  • Universiti Malaysia Terengganu (MY)
  • Tampere University (FI)
  • Universidade de Santiago de Compostela (ES)
  • World Meteorological Organization (CH)
  • University of Hong Kong (HK)
  • Energy Institute (GB)
Corresponding author
Hamilton, Ian
ORCID
Venue
The Lancet
Publisher
Elsevier BV
Published
2021-10
Volume
398
Issue
10311
Pages
1619-1662
ISSN
  • 0099-5355 (ISSN-L)
  • 0140-6736
DOI
10.1016/s0140-6736(21)01787-6
PMC
PMC7616807
OpenAlex
W3211328827
Cited by
1,603
References
218
Citations by year
2026: 200 · 2025: 251 · 2024: 289 · 2023: 523 · 2022: 318 · 2021: 20
FWCI
27.37
Type
journal article
Language
en
Update notices
erratum (2021-12-11)
Open access
Licence
Locations
  • The Lancet (acceptedVersion)
  • PubMed (publishedVersion)
  • Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, cc-by-nc-nd)
  • Greenwich Academic Literature Archive (University of Greenwich) (acceptedVersion)
  • PubMed Central (acceptedVersion, cc-by)
  • London School of Economics and Political Science Research Online (London School of Economics and Political Science) (acceptedVersion)
  • CentAUR (University of Reading) (submittedVersion)
  • White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (submittedVersion)
  • London School of Economics and Political Science Theses Online (London School of Economics and Political Science) (submittedVersion)
  • Sussex Research Online (University of Sussex) (submittedVersion)
  • UNU Collections (United Nations University) (submittedVersion)
  • National University of Singapore (submittedVersion)
  • CGSPace A Repository of Agricultural Research Outputs (Consultative Group for International Agricultural Research) (submittedVersion, other-oa)
  • UCL Discovery (University College London) (submittedVersion)
  • Figshare (submittedVersion)
  • Hispana (submittedVersion, other-oa)
  • ORCA Online Research @Cardiff (Cardiff University) (submittedVersion)
  • ARCA (Università Ca' Foscari Venezia) (submittedVersion, cc-by-nc-nd)
  • Minerva Access (University of Melbourne) (submittedVersion, cc-by)
  • OPUS 4 (Zuse Institute Berlin) (submittedVersion)
  • University of Birmingham Research Portal (University of Birmingham) (submittedVersion, other-oa)
  • Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU) (submittedVersion)
  • IIASA PURE (International Institute of Applied Systems Analysis) (submittedVersion)
  • Tampere University Institutional Repository (Tampere University) (submittedVersion, cc-by-nc-nd)
Funders
  • Wellcome Trust (209734/Z/17/Z)
  • Northeastern University
  • Royal Society
  • National Research Foundation
  • UK Energy Research Centre
  • International Energy Agency
  • National Research Foundation Singapore
  • National University of Singapore
  • National Aeronautics and Space Administration (80NSSC21K0507)
  • Svenska Forskningsrådet Formas (2018\u201301754, 2017\u201301300)
  • Harvard University
  • Natural Environment Research Council (NE/N01524X/1, 205200/Z/16/Z, NE/R01440X/1, 216035/Z/19/Z)
Topics
  • Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Climate Change and Health Impacts
  • Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Air Quality and Health Impacts
  • Physical Sciences › Environmental Science › Global and Planetary Change › Climate Change and Environmental Impact
Keywords
health and climate change, COVID-19 pandemic, health equity, low-carbon transition, climate change adaptation, global health indicators, sustainable development, just transition
MeSH terms
Forecasting, Health Planning, Humans, Global Health, Climate Change, Renewable Energy

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