Compound mortality impacts from extreme temperatures and the COVID-19 pandemic.

Extreme weather and coronavirus-type pandemics are both leading global health concerns. Until now, no study has quantified the compound health consequences of the co-occurrence of them. We estimate the mortality attributable to extreme heat and cold events, which dominate the UK health burden from weather hazards, in England and Wales in the period 2020-2022, during which the COVID-19 pandemic peaked in terms of mortality. We show that temperature-related mortality exceeded COVID-19 mortality by 8% in South West England. Combined, extreme temperatures and COVID-19 led to 19 (95% confidence interval: 16-22 in North West England) to 24 (95% confidence interval: 20-29 in Wales) excess deaths per 100,000 population during heatwaves, and 80 (95% confidence interval: 75-86 in Yorkshire and the Humber) to 127 (95% confidence interval: 123-132 in East of England) excess deaths per 100,000 population during cold snaps. These numbers are at least ~2 times higher than the previous decade. Society must increase preparedness for compound health crises such as extreme weather coinciding with pandemics.

Heatwave attribution based on reliable operational weather forecasts.

The 2021 Pacific Northwest heatwave was so extreme as to challenge conventional statistical and climate-model-based approaches to extreme weather attribution. However, state-of-the-art operational weather prediction systems are demonstrably able to simulate the detailed physics of the heatwave. Here, we leverage these systems to show that human influence on the climate made this event at least 8 [2-50] times more likely. At the current rate of global warming, the likelihood of such an event is doubling every 20 [10-50] years. Given the multi-decade lower-bound return-time implied by the length of the historical record, this rate of change in likelihood is highly relevant for decision makers. Further, forecast-based attribution can synthesise the conditional event-specific storyline and unconditional event-class probabilistic approaches to attribution. If developed as a routine service in forecasting centres, it could provide reliable estimates of human influence on extreme weather risk, which is critical to supporting effective adaptation planning.

Optimal heat stress metric for modelling heat-related mortality varies from country to country.

Combined heat and humidity is frequently described as the main driver of human heat-related mortality, more so than dry-bulb temperature alone. While based on physiological thinking, this assumption has not been robustly supported by epidemiological evidence. By performing the first systematic comparison of eight heat stress metrics (i.e., temperature combined with humidity and other climate variables) with warm-season mortality, in 604 locations over 39 countries, we find that the optimal metric for modelling mortality varies from country to country. Temperature metrics with no or little humidity modification associates best with mortality in ~40% of the studied countries. Apparent temperature (combined temperature, humidity and wind speed) dominates in another 40% of countries. There is no obvious climate grouping in these results. We recommend, where possible, that researchers use the optimal metric for each country. However, dry-bulb temperature performs similarly to humidity-based heat stress metrics in estimating heat-related mortality in present-day climate.

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

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.