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

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          Executive summary

          The Lancet Countdown is an international collaboration that independently monitors the health consequences of a changing climate. Publishing updated, new, and improved indicators each year, the Lancet Countdown represents the consensus of leading researchers from 43 academic institutions and UN agencies. The 44 indicators of this report expose an unabated rise in the health impacts of climate change and the current health consequences of the delayed and inconsistent response of countries around the globe—providing a clear imperative for accelerated action that puts the health of people and planet above all else.

          The 2021 report coincides with the UN Framework Convention on Climate Change 26th Conference of the Parties (COP26), at which countries are facing pressure to realise the ambition of the Paris Agreement to keep the global average temperature rise to 1·5°C and to mobilise the financial resources required for all countries to have an effective climate response. These negotiations unfold in the context of the COVID-19 pandemic—a global health crisis that has claimed millions of lives, affected livelihoods and communities around the globe, and exposed deep fissures and inequities in the world’s capacity to cope with, and respond to, health emergencies. Yet, in its response to both crises, the world is faced with an unprecedented opportunity to ensure a healthy future for all.

          Deepening inequities in a warming world

          Record temperatures in 2020 resulted in a new high of 3·1 billion more person-days of heatwave exposure among people older than 65 years and 626 million more person-days affecting children younger than 1 year, compared with the annual average for the 1986–2005 baseline ( indicator 1.1.2). Looking to 2021, people older than 65 years or younger than 1 year, along with people facing social disadvantages, were the most affected by the record-breaking temperatures of over 40°C in the Pacific Northwest areas of the USA and Canada in June, 2021—an event that would have been almost impossible without human-caused climate change. Although the exact number will not be known for several months, hundreds of people have died prematurely from the heat. Furthermore, populations in countries with low and medium levels of UN-defined human development index (HDI) have had the biggest increase in heat vulnerability during the past 30 years, with risks to their health further exacerbated by the low availability of cooling mechanisms and urban green space ( indicators 1.1.1, 2.3.2, and 2.3.3). Agricultural workers in countries with low and medium HDI were among the worst affected by exposure to extreme temperatures, bearing almost half of the 295 billion potential work hours lost due to heat in 2020 ( indicator 1.1.4). These lost work hours could have devastating economic consequences to these already vulnerable workers—data in this year’s report shows that the average potential earnings lost in countries in the low HDI group were equivalent to 4–8% of the national gross domestic product ( indicator 4.1.3).

          Through these effects, rising average temperatures, and altered rainfall patterns, climate change is beginning to reverse years of progress in tackling the food and water insecurity that still affects the most underserved populations around the world, denying them an essential aspect of good health. During any given month in 2020, up to 19% of the global land surface was affected by extreme drought; a value that had not exceeded 13% between 1950 and 1999 ( indicator 1.2.2). In parallel with drought, warm temperatures are affecting the yield potential of the world’s major staple crops—a 6·0% reduction for maize; 3·0% for winter wheat; 5·4% for soybean; and 1·8% for rice in 2020, relative to 1981–2010 ( indicator 1.4.1)—exposing the rising risk of food insecurity.

          Adding to these health hazards, the changing environmental conditions are also increasing the suitability for the transmission of many water-borne, air-borne, food-borne, and vector-borne pathogens. Although socioeconomic development, public health interventions, and advances in medicine have reduced the global burden of infectious disease transmission, climate change could undermine eradication efforts.

          The number of months with environmentally suitable conditions for the transmission of malaria ( Plasmodium falciparum) rose by 39% from 1950–59 to 2010–19 in densely populated highland areas in the low HDI group, threatening highly disadvantaged populations who were comparatively safer from this disease than those in the lowland areas ( indicator 1.3.1). The epidemic potential for dengue virus, Zika virus, and chikungunya virus, which currently primarily affect populations in central America, South America, the Caribbean, Africa, and south Asia, increased globally, with a basic reproductive rate increase of 13% for transmission by Aedes aegypti and 7% for transmission by Aedes albopictus compared with the 1950s. The biggest relative increase in basic reproductive rate of these arboviruses was seen in countries in the very high HDI group ( indicator 1.3.1); however, people in the low HDI group are confronted with the highest vulnerability to these arboviruses ( indicator 1.3.2).

          Similar findings are observed in the environmental suitability for Vibrio cholerae, a pathogen estimated to cause almost 100 000 deaths annually, particularly among populations with poor access to safe water and sanitation. Between 2003 and 2019, the coastal areas suitable for V cholerae transmission increased substantially across all HDI country groups—although, with 98% of their coastline suitable to the transmission of V cholerae in 2020, it is people in the low HDI country group that have the highest environmental suitability for this disease ( indicator 1.3.1).

          The concurrent and interconnecting risks posed by extreme weather events, infectious disease transmission, and food, water, and financial insecurity are over-burdening the most vulnerable populations. Through multiple simultaneous and interacting health risks, climate change is threatening to reverse years of progress in public health and sustainable development.

          Even with overwhelming evidence on the health impacts of climate change, countries are not delivering an adaptation response proportionate to the rising risks their populations face. In 2020, 104 (63%) of 166 countries did not have a high level of implementation of national health emergency frameworks, leaving them unprepared to respond to pandemics and climate-related health emergencies ( indicator 2.3.1). Importantly, only 18 (55%) of 33 countries with a low HDI had reported at least a medium level of implementation of national health emergency frameworks, compared with 47 (89%) of 53 countries with a very high HDI. In addition, only 47 (52%) of 91 countries reported having a national adaptation plan for health, with insufficient human and financial resources identified as the main barrier for their implementation ( indicator 2.1.1). With a world facing an unavoidable temperature rise, even with the most ambitious climate change mitigation, accelerated adaptation is essential to reduce the vulnerabilities of populations to climate change and protect the health of people around the world.

          An inequitable response fails everyone

          10 months into 2021, global and equitable access to the COVID-19 vaccine had not been delivered—more than 60% of people in high-income countries have received at least one dose of a COVID-19 vaccine compared with just 3·5% of people in low-income countries. Data in this report exposes similar inequities in the global climate change mitigation response.

          To meet the Paris Agreement goals and prevent catastrophic levels of global warming, global greenhouse gas emissions must reduce by half within a decade. However, at the current pace of reduction, it would take more than 150 years for the energy system to fully decarbonise ( indicator 3.1), and the unequal response between countries is resulting in an uneven realisation of the health benefits of a low-carbon transition.

          The use of public funds to subsidise fossil fuels is partly responsible for the slow decarbonisation rate. Of the 84 countries reviewed, 65 were still providing an overall subsidy to fossil fuels in 2018 and, in many cases, subsidies were equivalent to substantial proportions of the national health budget and could have been redirected to deliver net benefits to health and wellbeing. Furthermore, all the 19 countries whose carbon pricing policies outweighed the effect of any fossil fuels subsidies came from the very high HDI group ( indicator 4.2.4).

          Although countries in the very high HDI group have collectively made the most progress in the decarbonisation of the energy system, they are still the main contributors to CO 2 emissions through the local production of goods and services, accounting for 45% of the global total ( indicator 4.2.5). With a slower pace of decarbonisation and poorer air quality regulations than countries in the very high HDI group, the medium and high HDI country groups produce the most fine particle matter (PM 2·5) emissions and have the highest rates of air pollution-related deaths, which are about 50% higher than the total deaths in the very high HDI group ( indicator 3.3). The low HDI group, with comparatively lower amounts of industrial activity than in the other groups, has a local production that contributes to only 0·7% of global CO 2 emissions, and has the lowest mortality rate from ambient air pollution. However, with only 12% of its inhabitants relying on clean fuels and technologies for cooking, the health of these populations is still at risk from dangerously high concentrations of household air pollution ( indicator 3.2). Even in the most affluent countries, people in the most deprived areas over-whelmingly bear the burden of health effects from exposure to air pollution. These findings expose the health costs of the delayed and unequal mitigation response and underscore the millions of deaths to be prevented annually through a low-carbon transition that prioritises the health of all populations.

          However, the world is not on track to realising the health gains of the transition to a low-carbon economy. Current global decarbonisation commitments are insufficient to meet Paris Agreement ambitions and would lead to a roughly 2·4°C average global temperature increase by the end of the century. The current direction of post-COVID-19 spending is threatening to make this situation worse, with just 18% of all the funds committed for economic recovery from the COVID-19 pandemic by the end of 2020 expected to lead to a reduction of greenhouse gas emissions. Indeed, the economic recovery from the pandemic is already predicted to lead to an unprecedented 5% increase in greenhouse gas emissions in 2021, which will bring global anthropogenic emissions back to their peak amounts.

          In addition, the current economic recession is threatening to undermine the target of mobilising US$100 billion per year from 2020 onwards to promote low-carbon shifts and adaptation responses in the most underserved countries, even though this quantity is minute compared with the trillions allocated to COVID-19 recovery. The high amounts of borrowing that countries have had to resort to during the pandemic could erase their ability to deliver a green recovery and maximise the health gains to their population of a low-carbon transition.

          An unprecedented opportunity to ensure a healthy future for all

          The overshoot in emissions resulting from a carbon-intensive COVID-19 recovery would irreversibly prevent the world from meeting climate commitments and the Sustainable Development Goals and lock humanity into an increasingly extreme and unpredictable environment. Data in this report expose the health impacts and health inequities of the current world at 1·2°C of warming above pre-industrial levels and supports that, on the current trajectory, climate change will become the defining narrative of human health.

          However, by directing the trillions of dollars that will be committed to COVID-19 recovery towards the WHO’s prescriptions for a healthy, green recovery, the world could meet the Paris Agreement goals, protect the natural systems that support wellbeing, and minimise inequities through reduced health effects and maximised co-benefits of a universal low-carbon transition. Promoting equitable climate change mitigation and universal access to clean energies could prevent millions of deaths annually from reduced exposure to air pollution, healthier diets, and more active lifestyles, and contribute to reducing health inequities globally. This pivotal moment of economic stimulus represents a historical opportunity to secure the health of present and future generations.

          There is a glimpse of positive change through several promising trends in this year’s data: electricity generation from renewable wind and solar energy increased by an annual average of 17% between 2013 and 2018 ( indicator 3.1); investment in new coal capacity decreased by 10% in 2020 ( indicator 4.2.1); and the global number of electric vehicles reached 7·2 million in 2019 ( indicator 3.4). Additionally, the global pandemic has driven increased engagement in health and climate change across multiple domains in society, with 91 heads of state making the connection in the 2020 UN General Debate and newly widespread engagement among countries in the very high HDI group ( indicator 5.4). Whether COVID-19 recovery supports, or reverses these trends, is yet to be seen.

          Neither COVID-19 nor climate change respect national borders. Without widespread, accessible vaccination across all countries and societies, SARS-CoV-2 and its new variants will continue to put the health of everybody at risk. Likewise, tackling climate change requires all countries to deliver an urgent and coordinated response, with COVID-19 recovery funds allocated to support and ensure a just transition to a low-carbon future and climate change adaptation across the globe. Leaders of the world have an unprecedented opportunity to deliver a future of improved health, reduced inequity, and economic and environmental sustainability. However, this will only be possible if the world acts together to ensure that no person is left behind.

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          Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

          Summary Background In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and development investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding Bill & Melinda Gates Foundation.
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            Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

            Summary Background Rigorous analysis of levels and trends in exposure to leading risk factors and quantification of their effect on human health are important to identify where public health is making progress and in which cases current efforts are inadequate. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a standardised and comprehensive assessment of the magnitude of risk factor exposure, relative risk, and attributable burden of disease. Methods GBD 2019 estimated attributable mortality, years of life lost (YLLs), years of life lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 87 risk factors and combinations of risk factors, at the global level, regionally, and for 204 countries and territories. GBD uses a hierarchical list of risk factors so that specific risk factors (eg, sodium intake), and related aggregates (eg, diet quality), are both evaluated. This method has six analytical steps. (1) We included 560 risk–outcome pairs that met criteria for convincing or probable evidence on the basis of research studies. 12 risk–outcome pairs included in GBD 2017 no longer met inclusion criteria and 47 risk–outcome pairs for risks already included in GBD 2017 were added based on new evidence. (2) Relative risks were estimated as a function of exposure based on published systematic reviews, 81 systematic reviews done for GBD 2019, and meta-regression. (3) Levels of exposure in each age-sex-location-year included in the study were estimated based on all available data sources using spatiotemporal Gaussian process regression, DisMod-MR 2.1, a Bayesian meta-regression method, or alternative methods. (4) We determined, from published trials or cohort studies, the level of exposure associated with minimum risk, called the theoretical minimum risk exposure level. (5) Attributable deaths, YLLs, YLDs, and DALYs were computed by multiplying population attributable fractions (PAFs) by the relevant outcome quantity for each age-sex-location-year. (6) PAFs and attributable burden for combinations of risk factors were estimated taking into account mediation of different risk factors through other risk factors. Across all six analytical steps, 30 652 distinct data sources were used in the analysis. Uncertainty in each step of the analysis was propagated into the final estimates of attributable burden. Exposure levels for dichotomous, polytomous, and continuous risk factors were summarised with use of the summary exposure value to facilitate comparisons over time, across location, and across risks. Because the entire time series from 1990 to 2019 has been re-estimated with use of consistent data and methods, these results supersede previously published GBD estimates of attributable burden. Findings The largest declines in risk exposure from 2010 to 2019 were among a set of risks that are strongly linked to social and economic development, including household air pollution; unsafe water, sanitation, and handwashing; and child growth failure. Global declines also occurred for tobacco smoking and lead exposure. The largest increases in risk exposure were for ambient particulate matter pollution, drug use, high fasting plasma glucose, and high body-mass index. In 2019, the leading Level 2 risk factor globally for attributable deaths was high systolic blood pressure, which accounted for 10·8 million (95% uncertainty interval [UI] 9·51–12·1) deaths (19·2% [16·9–21·3] of all deaths in 2019), followed by tobacco (smoked, second-hand, and chewing), which accounted for 8·71 million (8·12–9·31) deaths (15·4% [14·6–16·2] of all deaths in 2019). The leading Level 2 risk factor for attributable DALYs globally in 2019 was child and maternal malnutrition, which largely affects health in the youngest age groups and accounted for 295 million (253–350) DALYs (11·6% [10·3–13·1] of all global DALYs that year). The risk factor burden varied considerably in 2019 between age groups and locations. Among children aged 0–9 years, the three leading detailed risk factors for attributable DALYs were all related to malnutrition. Iron deficiency was the leading risk factor for those aged 10–24 years, alcohol use for those aged 25–49 years, and high systolic blood pressure for those aged 50–74 years and 75 years and older. Interpretation Overall, the record for reducing exposure to harmful risks over the past three decades is poor. Success with reducing smoking and lead exposure through regulatory policy might point the way for a stronger role for public policy on other risks in addition to continued efforts to provide information on risk factor harm to the general public. Funding Bill & Melinda Gates Foundation.
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              The Socio-Economic Implications of the Coronavirus and COVID-19 Pandemic: A Review

              The COVID-19 pandemic has resulted in over 1.4 million confirmed cases and over 83,000 deaths globally. It has also sparked fears of an impending economic crisis and recession. Social distancing, self-isolation and travel restrictions forced a decrease in the workforce across all economic sectors and caused many jobs to be lost. Schools have closed down, and the need of commodities and manufactured products has decreased. In contrast, the need for medical supplies has significantly increased. The food sector has also seen a great demand due to panic-buying and stockpiling of food products. In response to this global outbreak, we summarise the socio-economic effects of COVID-19 on individual aspects of the world economy.

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                Journal
                2985213R
                Lancet
                Lancet
                Lancet (London, England)
                0140-6736
                1474-547X
                11 November 2024
                30 October 2021
                20 October 2021
                15 November 2024
                : 398
                : 10311
                : 1619-1662
                Affiliations
                Institute for Global Health, University College London ( https://ror.org/02jx3x895) , London, UK
                Institute for Global Health, University College London ( https://ror.org/02jx3x895) , London, UK
                School of Agriculture, Policy and Development, University of Reading ( https://ror.org/05v62cm79) , Reading, UK
                Institute for Sustainable Resources, University College London ( https://ror.org/02jx3x895) , London, UK
                Institute for Sustainable Resources, University College London ( https://ror.org/02jx3x895) , London, UK
                Institute for Global Health, University College London ( https://ror.org/02jx3x895) , London, UK
                UCL Energy Institute, University College London ( https://ror.org/02jx3x895) , London, UK
                Department of Health Sciences, University of York ( https://ror.org/04m01e293) , York, UK
                UCL Energy Institute, University College London ( https://ror.org/02jx3x895) , London, UK
                Department of Meteorology, University of Reading ( https://ror.org/05v62cm79) , Reading, UK
                Institute for Environment and Human Security, United Nations University ( https://ror.org/01cdrde68) , Bonn, Germany
                Centre on Climate Change and Planetary Health, London School of Hygiene & Tropical Medicine ( https://ror.org/00a0jsq62) , London , UK
                Department of Earth System Science, Tsinghua University ( https://ror.org/03cve4549) , Beijing, China
                Department of Environment, Climate Change and Health, World Health Organization ( https://ror.org/01f80g185) , Geneva, Switzerland
                Centre for Climate Change and Social Transformations, School of Psychology, Cardiff University ( https://ror.org/03kk7td41) , Cardiff, UK
                Institute for Environmental Sciences, World Health Organization ( https://ror.org/01f80g185) , Geneva, Switzerland
                Yale Center on Climate Change and Health, Yale University ( https://ror.org/03v76x132) , New Haven, CT, USA
                The Walker Institute, University of Reading ( https://ror.org/05v62cm79) , Reading, UK
                Institute for Sustainable Resources, University College London ( https://ror.org/02jx3x895) , London, UK
                School of Government, University of Birmingham ( https://ror.org/03angcq70) , Birmingham, UK
                Economic analysis of Climate Impacts and Policy, Centro Euro-Mediterraneo sui Cambiamenti Climatici ( https://ror.org/01tf11a61) , Venice, Italy
                Institute for Environmental Design and Engineering, University College London ( https://ror.org/02jx3x895) , London, UK
                Natural Resources Institute, University of Greenwich ( https://ror.org/00bmj0a71) , London, UK
                Yale Center on Climate Change and Health, Yale University ( https://ror.org/03v76x132) , New Haven, CT, USA
                Department of Global Health, University of Washington ( https://ror.org/00cvxb145) , Seattle, WA, USA
                Department of Civil and Environmental Engineering, Northeastern University ( https://ror.org/04t5xt781) , Boston, MA, USA
                Institute for Sustainable Resources, University College London ( https://ror.org/02jx3x895) , London, UK
                Department of Fish and Wildlife Conservation, Virginia Polytechnic Institute and State University ( https://ror.org/02smfhw86) , Blacksburg, VA, USA
                Department of Geography, University College London ( https://ror.org/02jx3x895) , London, UK
                Animal and Human Health Program, International Livestock Research Institute ( https://ror.org/01jxjwb74) , Nairobi, Kenya
                Department of Health Sciences, University of York ( https://ror.org/04m01e293) , York, UK
                Human Potential Translational Research Programme, Yong Loo Lin School of Medicine, National University Singapore ( https://ror.org/01tgyzw49) , Singapore
                School of Public Health and Administration, Universidad Peruana Cayetano Heredia ( https://ror.org/03yczjf25) , Lima, Peru
                The Bartlett School of Sustainable Construction, University College London ( https://ror.org/02jx3x895) , London, UK
                Institute for Environmental Design and Engineering, University College London ( https://ror.org/02jx3x895) , London, UK
                Centre for Health and the Global Environment, University of Washington ( https://ror.org/00cvxb145) , Seattle, WA, USA
                UCL Energy Institute, University College London ( https://ror.org/02jx3x895) , London, UK
                Data Science Lab, Hertie School ( https://ror.org/0473a4773) , Berlin, Germany
                Department of Epidemiology, Harvard T H Chan School of Public Health, Boston, MA, USA
                Institute for Global Health, University College London ( https://ror.org/02jx3x895) , London, UK
                Air Quality and Greenhouse Gases Programme, International Institute for Applied Systems Analysis ( https://ror.org/02wfhk785) , Laxenburg, Austria
                Department of Environmental Health, School of Public Health, Boston University ( https://ror.org/05qwgg493) , Boston, MA, USA
                Health and Environment International Trust, Nelson, New Zealand
                School of Global Studies, University of Sussex ( https://ror.org/00ayhx656) , Falmer, UK
                Human Potential Translational Research Programme, Yong Loo Lin School of Medicine, National University Singapore ( https://ror.org/01tgyzw49) , Singapore
                School of Health, Nelson Marlborough Institute of Technology ( https://ror.org/00wykxp39) , Nelson, New Zealand
                Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University ( https://ror.org/03czfpz43) , Atlanta, GA, USA
                Department of Earth System Science, Tsinghua University ( https://ror.org/03cve4549) , Beijing, China
                Center on Global Energy Policy, Columbia University ( https://ror.org/00hj8s172) , New York, NY, USA
                Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine ( https://ror.org/00a0jsq62) , London, UK
                Department of Genetics and Microbiology, Universitat Autònoma de Barcelona ( https://ror.org/052g8jq94) , Barcelona, Spain
                Department of Geography, University College London ( https://ror.org/02jx3x895) , London, UK
                Center for Energy Markets, Technical University of Munich ( https://ror.org/02kkvpp62) , Munich, Germany
                School of Geography, Earth and Atmospheric Sciences, University of Melbourne ( https://ror.org/01ej9dk98) , Melbourne, VIC, Australia
                The Bartlett School of Sustainable Construction, University College London ( https://ror.org/02jx3x895) , London, UK
                Department of Public Health, Environments, and Society, London School of Hygiene & Tropical Medicine ( https://ror.org/00a0jsq62) , London, UK
                Copenhagen Center for Social Data Science, University of Copenhagen ( https://ror.org/035b05819) , Copenhagen, Denmark
                https://ror.org/00jma7w30 Institute for Environmental Design and Engineering, University College London ( https://ror.org/02jx3x895) , London, UK
                Preventive Medicine and Public Health Research Center, Psychosocial Health Research Institute, Iran University of Medical Sciences ( https://ror.org/03w04rv71) , Tehran, Iran
                Department of Technology, Management and Economics, Technical University of Denmark ( https://ror.org/04qtj9h94) , Copenhagen, Denmark
                Data Science Lab, Hertie School ( https://ror.org/0473a4773) , Berlin, Germany
                MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London ( https://ror.org/041kmwe10) , UK
                Department of Environment, Climate Change and Health, World Health Organization ( https://ror.org/01f80g185) , Geneva, Switzerland
                Department of Epidemiology and Global Health, Umeå University ( https://ror.org/05kb8h459) , Umeå, Sweden
                Umeå University ( https://ror.org/05kb8h459) , Umeå, Sweden; Centre for Humans and Machines, Max Planck Institute for Human Development ( https://ror.org/02pp7px91) , Berlin, Germany
                Section of Sustainable Health, Department of Public Health and Clinical Medicine, Umeå University ( https://ror.org/05kb8h459) , Umeå, Sweden
                https://ror.org/02jx3x895 UCL Energy Institute, University College London ( https://ror.org/02jx3x895) , London, UK
                Department of Arts, Media & Digital Technologies, Nelson Marlborough Institute of Technology ( https://ror.org/00wykxp39) , Nelson, New Zealand
                Iranian Fisheries Science Research Institute, Agricultural Research, Education, and Extension Organisation, Tehran, Iran
                Cooperative Institute of Research in Environmental Sciences, University of Colorado ( https://ror.org/02ttsq026) , Boulder, CO, USA
                College of Medicine and Health, Exeter University ( https://ror.org/03yghzc09) , Exeter, UK
                Iranian Fisheries Science Research Institute, Agricultural Research, Education, and Extension Organisation, Tehran, Iran
                School of Agriculture, Policy and Development, University of Reading ( https://ror.org/05v62cm79) , Reading, UK
                Section of Sustainable Health, Department of Public Health and Clinical Medicine, Umeå University ( https://ror.org/05kb8h459) , Umeå, Sweden
                Harvard Medical School, Harvard University ( https://ror.org/03vek6s52) , Boston, MA, USA
                Lateral Public Health Consulting, Stockholm, Sweden
                Department of Anesthesiology, Yale University ( https://ror.org/03v76x132) , New Haven, CT, USA
                Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University ( https://ror.org/03czfpz43) , Atlanta, GA, USA
                Oxford Martin School, University of Oxford ( https://ror.org/052gg0110) , Oxford, UK
                Higher Institution Centre of Excellence, Institute of Tropical Aquaculture and Fisheries, Universiti Malaysia Terengganu ( https://ror.org/02474f074) , Kuala Terengganu, Malaysia
                Department of Civil Engineering, Tampere University ( https://ror.org/033003e23) , Tampere, Finland
                Department of Electronics and Computer Science, Universidade de Santiago de Compostela ( https://ror.org/030eybx10) , Santiago, Spain
                WHOWMO Joint Climate and Health Office, Geneva, Switzerland
                Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University ( https://ror.org/03czfpz43) , Atlanta, GA, USA
                Air Quality and Greenhouse Gases Programme, International Institute for Applied Systems Analysis ( https://ror.org/02wfhk785) , Laxenburg, Austria
                Department of Public Health, Environments, and Society, London School of Hygiene & Tropical Medicine ( https://ror.org/00a0jsq62) , London, UK
                Institute for Sustainable Resources, University College London ( https://ror.org/02jx3x895) , London, UK
                School of Public Health and Administration, Universidad Peruana Cayetano Heredia ( https://ror.org/03yczjf25) , Lima, Peru
                Department of Earth System Science, Tsinghua University ( https://ror.org/03cve4549) , Beijing, China
                Department of Geography, University of Hong Kong ( https://ror.org/02zhqgq86) , Hong Kong Special Administrative Region, China
                Centre for Human Health and Performance, University College London ( https://ror.org/02jx3x895) , London, UK
                Institute for Global Health, University College London ( https://ror.org/02jx3x895) , London, UK
                UCL Energy Institute, University College London ( https://ror.org/02jx3x895) , London, UK
                Author notes
                Correspondence to: Prof Ian Hamilton, Energy Institute, University College London, London WC1H 0NN, UK i.hamilton@ 123456ucl.ac.uk
                Article
                EMS200003
                10.1016/S0140-6736(21)01787-6
                7616807
                34687662
                2c4324d6-002e-4452-9d14-c60893f8ca01

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