Yan Wang1, Francesco Nordio2, John Nairn3, Antonella Zanobetti1, Joel D Schwartz4. 1. Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA. 2. Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA. 3. Australian Bureau of Meteorology, Adelaide, South Australia, Australia; University of Adelaide, Adelaide, South Australia, Australia. 4. Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA. Electronic address: joel@hsph.harvard.edu.
Abstract
BACKGROUND: How adaptation and intensity of heat waves affect heat wave-related mortality is unclear, making health projections difficult. METHODS: We estimated the effect of heat waves, the effect of the intensity of heat waves, and adaptation on mortality in 209 U.S. cities with 168 million people during 1962-2006. We improved the standard time-series models by incorporating the intensity of heat waves using excess heat factor (EHF) and estimating adaptation empirically using interactions with yearly mean summer temperature (MST). We combined the epidemiological estimates for heat wave, intensity, and adaptation with the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model dataset to project heat wave-related mortality by 2050. RESULTS: The effect of heat waves increased with its intensity. Adaptation to heat waves occurred, which was shown by the decreasing effect of heat waves with MST. However, adaptation was lessened as MST increased. Ignoring adaptation in projections would result in a substantial overestimate of the projected heat wave-related mortality (by 277-747% in 2050). Incorporating the empirically estimated adaptation into projections would result in little change in the projected heat wave-related mortality between 2006 and 2050. This differs regionally, however, with increasing mortality over time for cities in the southern and western U.S. but decreasing mortality over time for the north. CONCLUSIONS: Accounting for adaptation is important to reduce bias in the projections of heat wave-related mortality. The finding that the southern and western U.S. are the areas that face increasing heat-related deaths is novel, and indicates that more regional adaptation strategies are needed.
BACKGROUND: How adaptation and intensity of heat waves affect heat wave-related mortality is unclear, making health projections difficult. METHODS: We estimated the effect of heat waves, the effect of the intensity of heat waves, and adaptation on mortality in 209 U.S. cities with 168 million people during 1962-2006. We improved the standard time-series models by incorporating the intensity of heat waves using excess heat factor (EHF) and estimating adaptation empirically using interactions with yearly mean summer temperature (MST). We combined the epidemiological estimates for heat wave, intensity, and adaptation with the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model dataset to project heat wave-related mortality by 2050. RESULTS: The effect of heat waves increased with its intensity. Adaptation to heat waves occurred, which was shown by the decreasing effect of heat waves with MST. However, adaptation was lessened as MST increased. Ignoring adaptation in projections would result in a substantial overestimate of the projected heat wave-related mortality (by 277-747% in 2050). Incorporating the empirically estimated adaptation into projections would result in little change in the projected heat wave-related mortality between 2006 and 2050. This differs regionally, however, with increasing mortality over time for cities in the southern and western U.S. but decreasing mortality over time for the north. CONCLUSIONS: Accounting for adaptation is important to reduce bias in the projections of heat wave-related mortality. The finding that the southern and western U.S. are the areas that face increasing heat-related deaths is novel, and indicates that more regional adaptation strategies are needed.
Authors: Matthew Borg; Monika Nitschke; Susan Williams; Stephen McDonald; John Nairn; Peng Bi Journal: Int J Biometeorol Date: 2019-01-28 Impact factor: 3.787
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