Estimating heat-related mortality in near real time for national heatwave plans

Y. T. Eunice Lo*, Daniel M. Mitchell, Ross Thompson, Emer O'Connell, Antonio Gasparrini

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

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Heatwaves are a serious threat to human life. Public health agencies that are responsible for delivering heat-health action plans need to assess and reduce the mortality impacts of heat. Statistical models developed in epidemiology have previously been used to attribute past observed deaths to high temperatures and project future heat-related deaths. Here, we investigate the novel use of summer temperature-mortality associations established by these models for monitoring heat-related deaths in regions in England in near real time. For four summers in the period 2011--2020, we find that coupling these associations with observed daily mean temperatures results in England-wide heatwave mortality estimates that are consistent with the excess deaths estimated by UK Health Security Agency. However, our results for 2013, 2018 and 2020 highlight that the lagged effects of heat and characteristics of individual summers contribute to disagreement between the two methods. We suggest that our method can be used for heatwave mortality monitoring in England because it has the advantages of including lagged effects and controlling for other risk factors. It could also be employed by health agencies elsewhere for reliably estimating the health burden of heat in near real time and near-term forecasts.
Original languageEnglish
Article number024017
Number of pages13
JournalEnvironmental Research Letters
Issue number2
Publication statusPublished - 3 Feb 2022

Bibliographical note

Funding Information:
We thank the Extreme Events and Health Protection Team at the UK Health Security Agency for providing a record of historical Level 3 Heat Health Alerts, and Mark McCarthy at the Met Office for providing the 2020 HadUK-Grid data before they became publicly available. Y T E Lo was funded under the NERC project, HAPPI-Health (Grant ID: NE/R009554/1). D M Mitchell was funded by a NERC fellowship (Grant ID: NE/N014057/1). A Gasparrini was funded by the Medical Research Council-UK (Grant ID: MR/M022625/1), NERC (Grant ID: NE/R009384/1), and the European Union’s Horizon 2020 Project Exhaustion (Grant ID: 820655).

Publisher Copyright:
© 2022 Crown copyright. Reproduced with the permission of the Controller of Her Majesty's Stationery Office.


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