UN Brown-bag seminar: Climate change and mortality

On Monday, 15 April, at 12:00pm, in person at the Population Council (1 Dag Hammarskjold Plaza, New York, NY 10017) and virtually on MS Teams

Prof. Raya Muttarak, together with Ms. Sirinya Kaikeaw, Mr. William Kemp, Mr. Vinod Joseph K J, Ms. Rosanna Gualdi, will present the results of our research on climate change and mortality. 

Abstract: Environmental extremes such as heatwaves, droughts, floods, and storms are projected to increase in both frequency and intensity over the course of the 21st century; climate change poses a significant, pressing public health concern, affecting population mental and physical health. These effects are heterogeneous across population subgroups, differing by various sociodemographic and spatial characteristics, including age, sex, socio-economic status, pre-existing health conditions and place of residence. Currently, there is a lack of scientific consensus on how extreme climatic events and temperatures differentially affect mortality patterns. If climate change only leads to mortality displacement, its long-run effect on population dynamics is likely to be negligible. It is however plausible that climate change-induced extreme events contribute to substantial increase in mortality. 

During this seminar the EU-funded POPCLIMA project will share global and local insights from its ongoing research. The seminar will begin with a global systematic literature review assessing the climate extreme-mortality relationship (1), followed by two in-depth studies, firstly focusing on geographic and sex-differences in mortality across European countries (2), and concluding with a case study investigating a potential harvesting effect of extreme temperatures-related mortality in the Italian context (3). The evidence on climate-related mortality across climatic hazards, geographic regions, and sociodemographic characteristics will be examined. These findings contribute to the understanding of the effect of climate change on mortality rates and aim to inform assumptions about future population dynamics.