Estimating The Costs Of Inaction And The Economic Benefits Of Addressing The Health Harms Of Climate Change

Recent national and international climate change assessments have expressed the harms of climate change in a new way, highlighting the economic threat they pose. These assessments represent progress in how the potential costs of climate change are estimated and communicated.¹ For example, in the US, the Fourth National Climate Assessment broke new ground by projecting hundreds of billions of dollars in climate change–related economic risks in the coming decades.² However, to date, most economic assessments of climate-sensitive harms have been limited to damage to property, infrastructure, and crops.³ There is a dearth of information about the health-related costs of failing to respond to the harms in the US and internationally, especially at local levels.^4,5

The physical and mental health–related harms caused or worsened by the climate crisis are active areas of investigation among researchers, but the costs of these harms are not well measured. This lack of economic estimation persists, despite a wealth of evidence linking climate change to exacerbation of many kinds of health-relevant exposures, including extreme heat and precipitation, wildfires, air pollution, drought, displacement, and certain infectious diseases.⁶

To accurately describe the health-related costs of climate change, it is important to distinguish between key terms. Climate-sensitive exposures (such as ozone smog air pollution, extreme heat, and extreme precipitation) and health outcomes include those with demonstrated responses to one or more meteorological variables or seasonal patterns.^6,7 In recent years, statistical analyses have enabled detection and attribution of the influence of human-caused climate change on extreme weather and other climate-related exposures.⁸ These climate change–related impacts on the environment include incremental contributions to the frequency and magnitude of extreme rainfall during hurricanes^8,9 and increased temperatures during heat waves,¹⁰ among others. It is not yet possible to apply analogous methods to directly quantify the attributable portion of climate-sensitive health outcomes to the incremental effects of climate change, as preexisting medical conditions, health vulnerabilities, and multiple exposures are among the many health determinants and causal factors involved. There is currently a knowledge gap that must be addressed for more complete understanding of climate change–related exposure-response relationships.

As the climate crisis accelerates and mitigation and adaptation take on increasing urgency, information on the costs of climate-sensitive health outcomes must be linked to the design and development of responsive public policy. To begin to fill the knowledge gap on health cost information, researchers have applied methods to consider the excess health harms observed from recent and projected climate-sensitive health outcomes.^11–13 Research on climate-sensitive health outcomes and health costs, the focus of this article, uses proxy metrics to improve understanding of the human toll of climate change until quantitative models are refined and validated to estimate the climate change–attributable fraction of a wider range of health outcomes.

This article identifies some approaches that could help surmount the challenges of current limitations and support broader implementation of a climate-health valuation approach. Studies have begun to quantify the economic harms of climate-sensitive health outcomes^14,15 and the benefits of adapting infrastructure to climate extremes.^16,17 Further research is needed that considers the variety, scope, and complexity of health-related costs and their importance for responsive public policy on the climate crisis.

Climate-Health Valuation And Its Applications

Climate-health valuation is a process for estimating the price tag of climate-sensitive health outcomes in terms of morbidity and mortality from climate-sensitive exposures. In our work, this includes the exposure-associated costs of hospital care, outpatient care, home health care visits, lost wages during hospital stays, and prescribed medications for physical and mental health harms (see online appendix exhibit A1).¹⁸ To also include the most extreme health harm—exposure-associated deaths—we apply the value of a statistical life to the estimated number of deaths. This is not an estimate of what a life is worth, but a means of assigning a dollar estimate to what a large group of people would be willing to pay to reduce their risks of dying from an exposure.¹⁹

Climate-health valuation information can inform a stronger public policy response to health problems linked to the climate crisis by providing decision makers with a better understanding of the relative costs and benefits of different courses of action. Estimation of health-related costs has been limited and simplified in climate impact models²⁰ that project the societal harms of the climate crisis for a number of reasons. Importantly, economic analyses of risks posed by the climate crisis are likely to underestimate health-sector costs and benefits because of a lack of underlying data to estimate climate damage functions. For example, the social cost of carbon and other international approaches that translate greenhouse gas concentrations into societal harms may vastly underestimate the economic risks of accelerating climate change because health-related costs are represented in only limited ways (for example, inclusion of costs from extreme heat–related mortality but not morbidity, exclusion of health costs from complex exposures such as wildfires and hurricanes, and no estimation of costs from mental health outcomes).²¹

In addition to their utility for health-related stakeholders concerned with health staffing and planning, climate-health cost estimates can inform decision making by industry, local municipalities, governors, legislators, regulators, financial industry professionals, and public and private governance at all levels (appendix exhibit A2).¹⁸ For government leaders, the cost burden of climate-sensitive exposures could motivate more ambitious investments in mitigation and adaptation. For health systems and insurance programs, the scale and range of climate-sensitive costs could help inform policies on staffing, resource allocation, and other climate-adaptive planning efforts.²² State and local public health departments can use valuation analyses to help demonstrate local harms in economic terms and shape response policies that compare health outcomes and financial burdens across broader geographies. Medical professionals can rely on this information to enhance their advocacy for climate action.²³ For individuals and communities, this information can make the damage of the climate crisis more local and tangible.

The Current Evidence Base For Estimating Climate-Sensitive Health Costs

Existing Evidence Base

Government regulators typically assess the costs of climate and energy policies by quantifying the health-related harms of air pollution produced from fossil fuel combustion (primarily fine particulate matter and ozone smog).²⁴ Because of strong and sustained investments in epidemiology and toxicology research, there is broad agreement on how to estimate health costs of air pollution–related morbidity and mortality. Researchers are now applying similar methods to estimate the range of health-related costs tied to other climate-sensitive exposures, including wildfires,²⁵ allergenic pollen,²⁶ and certain infectious diseases.²⁷ There is ongoing work in climate science to distinguish between natural climate variability and human-caused climate change,²⁸ in exposure science to characterize complex and at times coincident exposures, and in epidemiology to estimate the range of health risks that can result from different climate-sensitive exposures (for example, coastal flooding and resulting health impacts on affected communities). As a result, there is a high degree of uncertainty in existing climate-sensitive valuation estimates.

Moreover, this research still inconsistently captures the equity implications of climate-sensitive exposures, health outcomes, and costs. There is a lack of comprehensive demographic and socioeconomic data on people already suffering from climate-sensitive health effects and a lack of detailed information about expenses shouldered by populations to cope with these health problems. More fundamentally, researchers to date might not have prioritized the examination of equity implications in study design. Future climate-health valuation studies should capture equity implications of exposures and costs, to inform policies that help those most in need.

Although local studies in some cases can describe the health outcomes and costs of climate-sensitive exposures,²⁹ a lack of robust, timely, and publicly available health data nationally inhibits the synthesis of information to generate a more complete regional or national picture of the costs of the climate crisis on human health in the US and inform responsive policy solutions.

Case-Study Approach

A case-study approach to valuation relies on the existing body of evidence for climate-sensitive exposures that are anticipated to worsen in frequency, intensity, duration, or spatial extent in the future.⁶ The case-study method takes advantage of available data to combine exposure, health outcome, and cost information in a consistent manner to quantify illness-, injury-, and mortality-related health costs (including lost wages, hospital and emergency department care, and expenses associated with outpatient care and medications).

To advance understanding of the bigger picture, we have published work that uses US case studies as examples to demonstrate potential health risks in a changing climate. The first such approach¹⁵ captured a wide range of effects across the US for exposures spanning 2000–09 to explore health-related costs on the national-level burden of ozone air pollution, state-level costs of a West Nile virus outbreak, and localized costs from wildfires and a heat wave in Southern California, river flooding in North Dakota, and hurricanes in Florida.

We recently expanded on that analysis by examining a set of climate-sensitive case studies in the US from a single year (2012) that used a broader range of exposures and health outcomes.¹⁴ The updated analysis also identified expected payers of illness-related costs. We found that Medicaid and Medicare shouldered a disproportionate share of climate-sensitive health costs. This finding aligns with the prior scientific understanding that climate-sensitive health risks disproportionately harm low-income communities and the elderly.³⁰

This approach has important limitations. First, reliable cost estimates extrapolated from case studies rely on the collection of accurate data, but lack of systematic health data collection likely biases results toward exposures and health outcomes that are most immediate and visible, to the detriment of other long-term or less obvious health effects (for example, mental health harms). Moreover, health problems from chronic climate-sensitive exposures, such as the elevation of seasonal temperatures compared with previous summers,³¹ do not lend themselves to a discrete case-study analysis. Our experience reviewing climate-sensitive case studies for valuation required significant time (estimated at hundreds of person-hours) to identify and assemble the health outcome data, to translate those data into health costs and economic damages using consistent methods, and to interpret and contextualize the results.

Key Challenges And Potential Solutions

There is a need to improve the existing climate-health valuation evidence base, its dissemination, and its utility for policy makers. This can be done by expanding the scope and application of climate-health valuation analyses to consider health outcomes from complex climate-sensitive exposures such as wildfires and coastal storms; characterizing longer-term health burdens on patients, families, and caregivers;³² synthesizing valuation assessments using consistent methods; quantifying costs for both recent exposures and projected future exposures;¹¹ and ensuring that health-related economic findings are not confined to the peer-reviewed literature or large climate assessment reports but flow into the public dialogue and policy spheres to motivate more ambitious mitigation and adaptation actions.

Appendix exhibit A3¹⁸ describes major goals of valuation analyses, key challenges to achieving them, and some potential solutions to overcome these obstacles. The following sections describe in more detail some strategies to overcome the challenges.

Demonstrating Benefits Of Adaptation

Climate adaptation efforts have the potential to minimize climate-health harms and reduce associated economic damages.³³ Health-protective adaptation interventions address diverse climate-sensitive health threats in different ways, including developing early warning systems and health advisories; establishing public cooling centers and protocols to minimize extreme heat exposures; improving surveillance systems to monitor outbreaks of infectious disease that could increase because of climate change; and building climate-resilient physical infrastructure in homes, communities, and health care systems that can withstand more severe floods, storms, and wildfires. However, spending on adaptation projects is not yet occurring on a large scale, and investment in community preparedness remains sorely out of proportion with the scale of what is needed.³⁴ Furthermore, the effectiveness of climate-health adaptation interventions has seldom been evaluated in a systematic way. The evaluation of adaptation interventions is an emerging science,^16,17,35 and valuation of health benefits achieved by these programs, using context-appropriate methods,³⁶ should be prioritized to inform those investigations.

Climate-health valuation can support the case for expanded investments in adaptation and be used to identify successes or lessons learned.³⁷ Scientifically, to make that happen, a consistent framework to estimate health cost savings of different climate adaptation measures is needed to demonstrate their efficacy and help policy makers select from strategies.

Enhancing Staff Capacity And Application Of Valuation

Budgets and staff capacity to conduct climate-health valuation analyses are limited in state and local health departments.³⁸ Capacity building to conduct these analyses more widely is needed beyond the academic research community, including in training health economists to analyze climate-sensitive health risks.

In the US, the current Centers for Disease Control and Prevention (CDC) Building Resilience Against Climate Effects (BRACE) framework, which guides climate and health adaptation programs in one-third of US states, does not explicitly account for the economic implications of climate-sensitive health outcomes,³⁹ and there is not yet guidance from CDC or the Environmental Protection Agency on how to conduct such analyses.⁴⁰ However, CDC researchers have published analyses exploring the economic implications of the national asthma burden,⁴¹ a step that could facilitate future analyses of health-related costs from climate-sensitive exposures. Further application of that valuation approach to describe climate-sensitive health outcomes could give the CDC and its partners in state and local health departments a useful tool to make local knowledge of climate-health costs more broadly available.

National dialogues about reform of the US health care system and the country’s response to the climate crisis have continued on parallel but separate tracks. A climate-health valuation agenda could enable more direct integration of these two priorities, demonstrating the ways in which the major costs associated with climate-sensitive health problems pose significant risks to individuals, families, state and local health departments, medical care providers, and public and private health care and insurance systems. As the coronavirus disease 2019 (COVID-19) pandemic demonstrates, poor investment, inadequate planning, and deficient alignment of public health response efforts is damaging and costly to health and economic prosperity.

Valuation of expensive health harms linked to climate-sensitive exposures could help health systems anticipate and respond to financial challenges from climate change. For example, an analysis of emergency department visits during Hurricane Sandy identified specific vulnerabilities for geriatric patients requiring access to medical facilities, prescriptions, and dialysis care.⁴²

Improving Health Surveillance

There are several important barriers to a more complete and broader assessment of climate-sensitive health costs. First, many climate-sensitive health harms are difficult for researchers to quantify using available data, including those related to drought,⁴³ forced resettlement, and concurrent harms (for example, extreme heat and ozone air pollution).⁴⁴ As more evidence of the links between climate-sensitive exposures and health risks becomes available, including for mental health problems,⁴⁵ it should be rapidly integrated into valuation analyses.

Second, there are key subpopulations and equity issues to consider, including disproportionate health harms suffered by children, the elderly, women, people with preexisting conditions, low-income communities, communities of color, immigrant workers, and other marginalized populations.³⁰ With the existing evidence base, it can be difficult to identify the communities where disproportionate shares of climate-sensitive harms are experienced. The lack of specificity in existing data sets hinders a more complete understanding of inequitable health and cost burden on these groups.⁴⁶

Third, climate-health valuation analyses should venture beyond providing estimates of the burden of climate-sensitive health harms on insurance systems to also describe how those expenses burden populations that have limited access to medical care and health insurance. To help identify health inequities aggravated by climate-sensitive exposures, decision makers need to be able to evaluate climate-sensitive health outcomes and associated costs, disaggregated by income level, race, degree of access to medical care, presence of preexisting conditions,⁴⁷ gender,⁴⁸ and occupation. Steps could be taken to develop mortality and morbidity data tracking practices and systems that are more robust, reliable, and better able to rapidly share information.⁴⁹ Vital statistics, public health, and emergency management and response data systems could be integrated with other sources of health-relevant data on the indicators of social determinants of health. More standardized data collection (for example, consistent coding of the many types of heat-related illnesses) and dissemination processes across different levels of US health agencies, from local to state, tribal, and territorial, could help create more uniform frameworks for tracking the health effects of disasters and other climate-sensitive exposures.

Data transparency and sharing should be encouraged so that government agencies can make data available in a consistent way that allows for more direct comparisons between areas and facilitates longer-term investigations that capture additional health effects, including those identified in peer-reviewed epidemiologic analyses. Given the inequitable burden of climate-sensitive health outcomes on those who are least responsible for climate pollution, future work to better estimate inequitable harms and costs to human health could inform both more local and global climate policy deliberations.⁵⁰

Fourth, obstacles remain with regard to health surveillance and health care utilization databases to characterize climate-sensitive morbidity and its financial toll. In the US, the CDC’s response to the COVID-19 pandemic has highlighted the patchwork of inconsistent and slow health surveillance data reporting across the country and demonstrated the need for more comprehensive and integrated health data tracking systems that can help public health professionals better assess the scope of important population health risks in real-time.⁵¹ Although the CDC’s Environmental Public Health Tracking Network⁵² includes a subset of climate-sensitive exposures (including extreme heat), the data within this system cover only half of US states, and reporting to this system is incomplete and often lags by a year or more.⁵³ Similar data gaps and delays diminish the utility of the Agency for Healthcare Research and Quality’s Healthcare Cost and Utilization Project⁵⁴ and the Medical Expenditure Panel Survey.⁵⁵

A sustained approach to national climate-health tracking would allow for an understanding of how climate-sensitive health costs are trending over time, similar to the National Oceanic and Atmospheric Administration’s billion-dollar weather disasters data, which have tracked infrastructure and crop damage costs from the largest extreme weather events (inclusive of some climate-sensitive exposures and exposures unrelated to climate variability) since the 1980s, using a standardized valuation approach.⁵⁶

Conclusion

Expanded valuation analyses of the costs of climate-sensitive outcomes are urgently needed to inform public policy.

Expanded valuation analyses of the costs of climate-sensitive health outcomes are urgently needed to inform public policy. The findings from such studies can be linked to provide a sense of the overall scope of health costs from climate change in communities, cities, states, regions, and countries.

At present, it is difficult to characterize the costs of health harms linked to climate-sensitive exposures in the US. Given the current inability to comprehensively track recent damage, there is limited understanding of the scope of projected future climate-sensitive health risks and costs. Moving forward, the US federal government should support more coordinated and forward-looking efforts to better track the health and economic costs of climate change and the health benefits and savings of climate response policies.

Expanded economic valuation of climate-sensitive health risks has the potential to motivate policies at multiple levels to slow climate change and to prioritize investments in health-protective climate adaptation efforts. The projected health and economic burden of climate change could be enormous if the problem continues unchecked and communities are not prepared for the growing health dangers of climate change.

NOTES

• 1 Neumann JE , Strzepek K . State of the literature on the economic impacts of climate change in the United States. J Benefit Cost Anal. 2014;5(3):411– 43. Crossref, Google Scholar
• 2 Reidmiller DR, Avery CW, Easterling DR, Kunkel KE, Lewis KLM, Maycock TK, Stewart BC editors. Fourth National Climate Assessment, volume II: impacts, risks, and adaptation in the United States [Internet]. Washington (DC): US Global Change Research Program; 2018 [cited 2020 Nov 2]. Available from: https://nca2018.globalchange.gov/ Google Scholar
• 3 Smith AB , Katz RW . US billion-dollar weather and climate disasters: data sources, trends, accuracy, and biases. Nat Hazards. 2013;67(2):387– 410. Crossref, Google Scholar
• 4 Hutton G , Menne B . Economic evidence on the health impacts of climate change in Europe. Environ Health Insights. 2014;8:43– 52. Crossref, Medline, Google Scholar
• 5 Hutton G . The economics of health and climate change: key evidence for decision making. Global Health. 2011;7:18. Crossref, Medline, Google Scholar
• 6 Balbus J , Crimmins A , Gamble JL , Easterling DR , Kunkel KE , Saha S et al. Introduction: climate change and human health. In: The impacts of climate change on human health in the United States: a scientific assessment [Internet]. Washington (DC): US Global Change Research Program; 2016 [cited 2020 Oct 16]. p. 25– 42. Available from: https://health2016.globalchange.gov/low/ClimateHealth2016_01_Introduction_small.pdf Google Scholar
• 7 US Global Change Research Program. Predicting climate-sensitive infectious diseases to protect public health and strengthen national security [Internet]. Washington (DC): US Global Change Research Program; 2019 Jun [cited 2020 Oct 16]. Available from: https://www.globalchange.gov/sites/globalchange/files/EID%20science%20plan.pdf Google Scholar
• 8 Reed KA , Stansfield AM , Wehner MF , Zarzycki CM . Forecasted attribution of the human influence on Hurricane Florence. Sci Adv. 2020;6(1):eaaw9253. Crossref, Medline, Google Scholar
• 9 Wang S-YS , Zhao L , Yoon J-H , Klotzbach P , Gillies RR . Quantitative attribution of climate effects on Hurricane Harvey’s extreme rainfall in Texas. Environ Res Lett. 2018;13(5):054014. Crossref, Google Scholar
• 10 Stott PA , Stone DA , Allen MR . Human contribution to the European heatwave of 2003. Nature. 2004;432(7017):610– 4. Crossref, Medline, Google Scholar
• 11 Hsiang S , Kopp R , Jina A , Rising J , Delgado M , Mohan S et al. Estimating economic damage from climate change in the United States. Science. 2017;356(6345):1362– 9. Crossref, Medline, Google Scholar
• 12 Xiao J , Huang M , Zhang W , Rosenblum A , Ma W , Meng X et al. The immediate and lasting impact of Hurricane Sandy on pregnancy complications in eight affected counties of New York State. Sci Total Environ. 2019;678:755– 60. Crossref, Medline, Google Scholar
• 13 Liu Y , Saha S , Hoppe BO , Convertino M . Degrees and dollars—health costs associated with suboptimal ambient temperature exposure. Sci Total Environ. 2019;678:702– 11. Crossref, Medline, Google Scholar
• 14 Limaye VS , Max W , Constible J , Knowlton K . Estimating the health-related costs of 10 climate-sensitive U.S. events during 2012. Geohealth. 2019;3(9):245– 65. Crossref, Medline, Google Scholar
• 15 Knowlton K , Rotkin-Ellman M , Geballe L , Max W , Solomon GM . Six climate change–related events in the United States accounted for about $14 billion in lost lives and health costs. Health Aff (Millwood). 2011;30(11):2167– 76. Go to the article, Google Scholar
• 16 Hess JJ , Lm S , Knowlton K , Saha S , Dutta P , Ganguly P et al. Building resilience to climate change: pilot evaluation of the impact of India’s first heat action plan on all-cause mortality. J Environ Public Health. 2018;2018:7973519. Crossref, Medline, Google Scholar
• 17 Rappold AG , Fann NL , Crooks J , Huang J , Cascio WE , Devlin RB et al. Forecast-based interventions can reduce the health and economic burden of wildfires. Environ Sci Technol. 2014;48(18):10571– 9. Crossref, Medline, Google Scholar
• 18 To access the appendix, click on the Details tab of the article online.
• 19 Environmental Protection Agency. Guidelines for preparing economic analyses [Internet]. Washington (DC): EPA; 2010 Dec. Appendix B, Mortality risk valuation estimates; [cited 2020 Oct 16]. Available from: https://www.epa.gov/sites/production/files/2017-09/documents/ee-0568-22.pdf Google Scholar
• 20 Ackerman F , Munitz C . Climate damages in the FUND model: a disaggregated analysis. Ecol Econ. 2012;77:219– 24. Crossref, Google Scholar
• 21 Diaz D , Moore F . Quantifying the economic risks of climate change. Nat Clim Chang. 2017;7(11):774– 82. Crossref, Google Scholar
• 22 Richardson J , Grose J , Jackson B , Gill J-L , Sadeghian HB , Hertel J et al. Effect of climate change and resource scarcity on health care. Nurs Stand. 2014;28(45):44– 9. Crossref, Medline, Google Scholar
• 23 Patz JA , Stull VJ , Limaye VS . A low-carbon future could improve global health and achieve economic benefits. JAMA. 2020;323(13):1247– 8. Crossref, Medline, Google Scholar
• 24 Fann N , Fulcher CM , Baker K . The recent and future health burden of air pollution apportioned across U.S. sectors. Environ Sci Technol. 2013;47(8):3580– 9. Crossref, Medline, Google Scholar
• 25 Fann N , Alman B , Broome RA , Morgan GG , Johnston FH , Pouliot G et al. The health impacts and economic value of wildland fire episodes in the U.S.: 2008–2012. Sci Total Environ. 2018;610-611:802– 9. Crossref, Medline, Google Scholar
• 26 Anenberg SC , Weinberger KR , Roman H , Neumann JE , Crimmins A , Fann N et al. Impacts of oak pollen on allergic asthma in the United States and potential influence of future climate change. Geohealth. 2017;1(3):80– 92. Crossref, Medline, Google Scholar
• 27 Mac S , da Silva SR , Sander B . The economic burden of Lyme disease and the cost-effectiveness of Lyme disease interventions: a scoping review. PLoS One. 2019;14(1):e0210280. Crossref, Medline, Google Scholar
• 28 World Meteorological Organization. Commission for Climatology: frequently asked questions (FAQs) [Internet]. Geneva: WMO; 2019 [cited 2020 Oct 16]. Available from: https://www.wmo.int/pages/prog/wcp/ccl/faqs.php Google Scholar
• 29 Murray KO , Ruktanonchai D , Hesalroad D , Fonken E , Nolan MS . West Nile virus, Texas, USA, 2012. Emerg Infect Dis. 2013;19(11):1836– 8. Crossref, Medline, Google Scholar
• 30 Gamble J , Balbus J , Berger M , Bouye K , Campbell V , Chief K et al. Populations of concern. In: Crimmins A, Balbus J, Gamble JL, Beard CB, Bell JE, Dodgen Det al. editors. The impacts of climate change on human health in the United States: a scientific assessment [Internet]. Washington (DC): US Global Change Research Program; 2016 [cited 2020 Nov 2]. p. 247– 85. Available from: https://health2016.globalchange.gov/populations-concern Google Scholar
• 31 Limaye VS , Vargo J , Harkey M , Holloway T , Patz JA . Climate change and heat-related excess mortality in the Eastern USA. Ecohealth. 2018;15(3):485– 96. Crossref, Medline, Google Scholar
• 32 Bosello F , Roson R , Tol RSJ . Economy-wide estimates of the implications of climate change: human health. Ecol Econ. 2006;58(3):579– 91. Crossref, Google Scholar
• 33 Bierbaum R , Smith JB , Lee A , Blair M , Carter L , Chapin FS et al. A comprehensive review of climate adaptation in the United States: more than before, but less than needed. Mitig Adapt Strategies Glob Change. 2013;18(3):361– 406. Crossref, Google Scholar
• 34 United Nations Environment Programme. Adaptation gap report [Internet]. Nairobi: UNEP; 2018 Dec 6 [cited 2020 Nov 2]. Available from: https://www.unenvironment.org/resources/adaptation-gap-report Google Scholar
• 35 Benmarhnia T , Bailey Z , Kaiser D , Auger N , King N , Kaufman JS . A difference-in-differences approach to assess the effect of a heat action plan on heat-related mortality, and differences in effectiveness according to sex, age, and socioeconomic status (Montreal, Quebec). Environ Health Perspect. 2016;124(11):1694– 9. Crossref, Medline, Google Scholar
• 36 Watkiss P , Hunt A , Blyth W , Dyszynski J . The use of new economic decision support tools for adaptation assessment: a review of methods and applications, towards guidance on applicability. Clim Change. 2015;132(3):401– 16. Crossref, Google Scholar
• 37 Carleton T , Delgado M , Greenstone M , Houser T , Hsiang S , Hultgren A et al. Valuing the global mortality consequences of climate change accounting for adaptation costs and benefits [Internet]. Chicago (IL): University of Chicago, Becker Friedman Institute for Economics; 2018 July [cited 2020 Nov 2]. (Working Paper No. 2018-51). Available from: https://bfi.uchicago.edu/wp-content/uploads/BFI_WP_201851.pdf Google Scholar
• 38 Gilmore EA , St. Clair T . Budgeting for climate change: obstacles and opportunities at the US state level. Clim Policy. 2018;18(6):729– 41. Crossref, Google Scholar
• 39 Centers for Disease Control and Prevention. CDC’s Building Resilience Against Climate Effects (BRACE) framework [Internet]. Atlanta (GA): CDC; 2019 Sep 9 [cited 2020 Oct 16]. Available from: https://www.cdc.gov/climateandhealth/BRACE.htm Google Scholar
• 40 Environmental Protection Agency. Climate change in the United States: benefits of global action [Internet]. Washington (DC): EPA; 2015 [cited 2020 Oct 16]. Available from: https://www.epa.gov/cira Google Scholar
• 41 Centers for Disease Control and Prevention. Asthma in the US [Internet]. Atlanta (GA): CDC; 2011 May [cited 2020 Oct 16]. Available from: https://www.cdc.gov/vitalsigns/asthma/index.html Google Scholar
• 42 Malik S , Lee DC , Doran KM , Grudzen CR , Worthing J , Portelli I et al. Vulnerability of older adults in disasters: emergency department utilization by geriatric patients after Hurricane Sandy. Disaster Med Public Health Prep. 2018;12(2):184– 93. Crossref, Medline, Google Scholar
• 43 Achakulwisut P , Mickley LJ , Anenberg SC . Drought-sensitivity of fine dust in the US Southwest: implications for air quality and public health under future climate change. Environ Res Lett. 2018;13(5):054025. Crossref, Google Scholar
• 44 Krug A , Fenner D , Holtmann A , Scherer D . Occurrence and coupling of heat and ozone events and their relation to mortality rates in Berlin, Germany, between 2000 and 2014. Atmosphere. 2019;10(6):348. Crossref, Google Scholar
• 45 Obradovich N , Migliorini R , Paulus MP , Rahwan I . Empirical evidence of mental health risks posed by climate change. Proc Natl Acad Sci U S A. 2018;115(43):10953– 8. Crossref, Medline, Google Scholar
• 46 Constible J , Morganelli C . On the frontlines: climate change threatens the health of America’s workers [Internet]. New York (NY): Natural Resources Defense Council; 2020 Jul 28 [cited 2020 Oct 16]. (Report No. R: 20-05-B). Available from: https://www.nrdc.org/sites/default/files/front-lines-climate-change-threatens-workers-report.pdf Google Scholar
• 47 Nerbass FB , Pecoits-Filho R , Clark WF , Sontrop JM , McIntyre CW , Moist L . Occupational heat stress and kidney health: from farms to factories. Kidney Int Rep. 2017;11(2):998– 1008. Crossref, Google Scholar
• 48 Rao N , Lawson ET , Raditloaneng WN , Solomon D , Angula MN . Gendered vulnerabilities to climate change: insights from the semi-arid regions of Africa and Asia. Clim Dev. 2019;11(1):14– 26. Crossref, Google Scholar
• 49 MacKenzie EJ, Wollek SH, Yost OC, Cork DL editors. A framework for assessing mortality and morbidity after large-scale disasters [Internet]. Washington (DC): National Academies Press; 2020 [cited 2020 Oct 16]. Available from: https://www.nap.edu/read/25863/chapter/1 Google Scholar
• 50 Patz JA , Gibbs HK , Foley JA , Rogers JV , Smith KR . Climate change and global health: quantifying a growing ethical crisis. EcoHealth. 2007;4(4):397– 405. Crossref, Google Scholar
• 51 Shah RU , Curtis LH . Data quarantine in the time of the COVID-19 pandemic. Circ Cardiovasc Qual Outcomes. 2020;13(6):e006908. Crossref, Medline, Google Scholar
• 52 Centers for Disease Control and Prevention. National Environmental Public Health Tracking [Internet]. Atlanta (GA): CDC; 2019 [2020 Oct 16]. Available from: https://www.cdc.gov/nceh/tracking/default.htm Google Scholar
• 53 Centers for Disease Control and Prevention. National Environmental Public Health Tracking: state and local tracking programs [Internet]. Atlanta (GA): CDC; 2020 [2020 Oct 16]. Available from: https://www.cdc.gov/nceh/tracking/grants.htm Google Scholar
• 54 Agency for Healthcare Research and Quality. HCUPnet: Healthcare Cost and Utilization Project [Internet]. Rockville (MD): AHRQ; [cited 2020 Oct 16]. Available from: https://hcupnet.ahrq.gov/ Google Scholar
• 55 Agency for Healthcare Research and Quality. Medical Expenditure Panel Survey–Household Component [Internet]. Rockville (MD): AHRQ; [cited 2020 Oct 16]. Available from: https://meps.ahrq.gov/mepsweb/survey_comp/household.jsp Google Scholar
• 56 Smith AB . 2010–2019: a landmark decade of U.S. billion-dollar weather and climate disasters. Beyond the Data [blog on the Internet]. 2020 Jan 8 [cited 2020 Oct 16]. Available from: https://www.climate.gov/news-features/blogs/beyond-data/2010-2019-landmark-decade-us-billion-dollar-weather-and-climate Google Scholar