Real-time forecast of temperature-related excess mortality at small-area level: towards an operational framework.

The development of innovative tools for real-time monitoring and forecasting of environmental health impacts is central to effective public health interventions and resource allocation strategies. Though a need for such generic tools has been previously echoed by public health planners and regional authorities responsible for issuing anticipatory alerts, a comprehensive, robust and scalable real-time system for predicting temperature-related excess deaths at a local scale has not been developed yet. Filling this gap, we propose a flexible operational framework for coupling publicly available weather forecasts with temperature-mortality risk functions specific to small census-based zones, the latter derived using state-of-the-art environmental epidemiological models. Utilising high-resolution temperature data forecast by a leading European meteorological centre, we demonstrate a real-time application to forecast the excess mortality during the July 2022 heatwave over England and Wales. The output, consisting of expected temperature-related excess deaths at small geographic areas on different lead times, can be automated to generate maps at various spatio-temporal scales, thus facilitating preventive action and allocation of public health resources in advance. While the real-case example discussed here demonstrates an application for predicting (expected) heat-related excess deaths, the framework can also be adapted to other weather-related health risks and to different geographical areas, provided data on both meteorological exposure and the underlying health outcomes are available to calibrate the associated risk functions. The proposed framework addresses an urgent need for predicting the short-term environmental health burden on public health systems globally, especially in low- and middle-income regions, where rapid response to mitigate adverse exposures and impacts to extreme temperatures are often constrained by available resources.

SHARE-ENV: A Data Set to Advance Our Knowledge of the Environment-Wellbeing Relationship.

Climate change interacts with other environmental stressors and vulnerability factors. Some places and, owing to socioeconomic conditions, some people, are far more at risk. The data behind current assessments of the environment-wellbeing nexus is coarse and regionally aggregated, when considering multiple regions/groups; or, when granular, comes from ad hoc samples with few variables. To assess the impacts of climate change, we require data that are granular and comprehensive, both in the variables and population studied. We build a publicly accessible data set, the SHARE-ENV data set, which fulfills these criteria. We expand on EU representative, individual-level, longitudinal data (the SHARE survey), with environmental exposure information about temperature, radiation, precipitation, pollution, and flood events. We illustrate through four simplified multilevel linear regressions, cross-sectional and longitudinal, how full-fledged studies can use SHARE-ENV to contribute to the literature. Such studies would help assess climate impacts and estimate the effectiveness and fairness of several climate adaptation policies. Other surveys can be expanded with environmental information to unlock different research avenues.

A better integration of health and economic impact assessments of climate change.

Climate change could lead to high economic burden for individuals (i.e. low income and high prices). While economic conditions are important determinants of climate change vulnerability, environmental epidemiological studies focus primarily on the direct impact of temperature on morbidity and mortality without accounting for climate-induced impacts on the economy. More integrated approaches are needed to provide comprehensive assessments of climate-induced direct and indirect impacts on health. This paper provides some perspectives on how epidemiological and economic impact assessments could be better integrated. We argue that accounting for the economic repercussions of climate change on people's health and, vice versa, the consequences of health effects on the economy could provide more realistic scenario projections and could be more useful for adaptation policy.

Temperature-related mortality burden and projected change in 1368 European regions: a modelling study.

BACKGROUND: Excessively high and low temperatures substantially affect human health. Climate change is expected to exacerbate heat-related morbidity and mortality, presenting unprecedented challenges to public health systems. Since localised assessments of temperature-related mortality risk are essential to formulate effective public health responses and adaptation strategies, we aimed to estimate the current and future temperature-related mortality risk under four climate change scenarios across all European regions. METHODS: We modelled current and future mortality due to non-optimal temperatures across 1368 European regions, considering age-specific characteristics and local socioeconomic vulnerabilities. Overseas territories were excluded from the analysis. We applied a three-stage method to estimate temperature-related risk continuously across age and spatial dimensions. Age and city-specific exposure-response functions were obtained for a comprehensive list of 854 European cities from the Urban Audit dataset of Eurostat. Regional aggregates were calculated using an aggregation and extrapolation method that incorporates the risk incidence in neighbouring cities. Mortality was projected for present conditions observed in 1991-2020 and for four different levels of global warming (1·5°C, 2°C, 3°C, and 4°C increase) by regions, and subregions using an ensemble of 11 climate models produced by the Coordinated Regional Climate Downscaling Experiment-CMIP5 over Europe, and population projection data from EUROPOP2019. FINDINGS: Our results highlight regional disparities in temperature-related mortality across Europe. Between 1991 and 2020, the number of cold-related deaths was 2·5 times higher in eastern Europe than western Europe, and heat-related deaths were 6 times higher in southern Europe than in northern Europe. During the same time period, there were a median of 363 809 cold-related deaths (empirical 95% CI 362 493-365 310) and 43 729 heat-related deaths (39 880-45 921), with a cold-to-heat-related death ratio of 8·3:1. Under current climate policies, aligned with 3°C increase in global warming, it is estimated that temperature-related deaths could increase by 54 974 additional deaths (24 112-80 676) by 2100, driven by rising heat-related deaths and an ageing population, resulting in a cold-to-heat-related death ratio of 2·6:1. Climate change is also expected to widen disparities in regional mortality, particularly impacting southern regions of Europe as a result of a marked increase in heat-related deaths. INTERPRETATION: This study shows that regional disparities in temperature-related mortality risk in Europe are substantial and will continue to increase due to the effects of climate change and an ageing population. The data presented can assist policy makers and health authorities in mitigating increasing health inequalities by prioritising the protection of more susceptible areas and older population groups. We identify the projected areas of heightened risk (southern Europe), where policy intervention aimed at building adaptation and enhancing resilience should be prioritised. FUNDING: European Commission.

High resolution mapping of nitrogen dioxide and particulate matter in Great Britain (2003-2021) with multi-stage data reconstruction and ensemble machine learning methods.

In this contribution, we applied a multi-stage machine learning (ML) framework to map daily values of nitrogen dioxide (NO2) and particulate matter (PM10 and PM2.5) at a 1 km2 resolution over Great Britain for the period 2003-2021. The process combined ground monitoring observations, satellite-derived products, climate reanalyses and chemical transport model datasets, and traffic and land-use data. Each feature was harmonized to 1 km resolution and extracted at monitoring sites. Models used single and ensemble-based algorithms featuring random forests (RF), extreme gradient boosting (XGB), light gradient boosting machine (LGBM), as well as lasso and ridge regression. The various stages focused on augmenting PM2.5 using co-occurring PM10 values, gap-filling aerosol optical depth and columnar NO2 data obtained from satellite instruments, and finally the training of an ensemble model and the prediction of daily values across the whole geographical domain (2003-2021). Results show a good ensemble model performance, calculated through a ten-fold monitor-based cross-validation procedure, with an average R2 of 0.690 (range 0.611-0.792) for NO2, 0.704 (0.609-0.786) for PM10, and 0.802 (0.746-0.888) for PM2.5. Reconstructed pollution levels decreased markedly within the study period, with a stronger reduction in the latter eight years. The pollutants exhibited different spatial patterns, while NO2 rose in close proximity to high-traffic areas, PM demonstrated variation at a larger scale. The resulting 1 km2 spatially resolved daily datasets allow for linkage with health data across Great Britain over nearly two decades, thus contributing to extensive, extended, and detailed research on the long-and short-term health effects of air pollution.

Reconstructing individual-level exposures in cohort analyses of environmental risks: an example with the UK Biobank.

Recent developments in linkage procedures and exposure modelling offer great prospects for cohort analyses on the health risks of environmental factors. However, assigning individual-level exposures to large population-based cohorts poses methodological and practical problems. In this contribution, we illustrate a linkage framework to reconstruct environmental exposures for individual-level epidemiological analyses, discussing methodological and practical issues such as residential mobility and privacy concerns. The framework outlined here requires the availability of individual residential histories with related time periods, as well as high-resolution spatio-temporal maps of environmental exposures. The linkage process is carried out in three steps: (1) spatial alignment of the exposure maps and residential locations to extract address-specific exposure series; (2) reconstruction of individual-level exposure histories accounting for residential changes during the follow-up; (3) flexible definition of exposure summaries consistent with alternative research questions and epidemiological designs. The procedure is exemplified by the linkage and processing of daily averages of air pollution for the UK Biobank cohort using gridded spatio-temporal maps across Great Britain. This results in the extraction of exposure summaries suitable for epidemiological analyses of both short and long-term risk associations and, in general, for the investigation of temporal dependencies. The linkage framework presented here is generally applicable to multiple environmental stressors and can be extended beyond the reconstruction of residential exposures. IMPACT: This contribution describes a linkage framework to assign individual-level environmental exposures to population-based cohorts using high-resolution spatio-temporal exposure. The framework can be used to address current limitations of exposure assessment for the analysis of health risks associated with environmental stressors. The linkage of detailed exposure information at the individual level offers the opportunity to define flexible exposure summaries tailored to specific study designs and research questions. The application of the framework is exemplified by the linkage of fine particulate matter (PM2.5) exposures to the UK Biobank cohort.

Impact of population aging on future temperature-related mortality at different global warming levels.

Older adults are generally amongst the most vulnerable to heat and cold. While temperature-related health impacts are projected to increase with global warming, the influence of population aging on these trends remains unclear. Here we show that at 1.5 °C, 2 °C, and 3 °C of global warming, heat-related mortality in 800 locations across 50 countries/areas will increase by 0.5%, 1.0%, and 2.5%, respectively; among which 1 in 5 to 1 in 4 heat-related deaths can be attributed to population aging. Despite a projected decrease in cold-related mortality due to progressive warming alone, population aging will mostly counteract this trend, leading to a net increase in cold-related mortality by 0.1%-0.4% at 1.5-3 °C global warming. Our findings indicate that population aging constitutes a crucial driver for future heat- and cold-related deaths, with increasing mortality burden for both heat and cold due to the aging population.

Association between long-term exposure to low ambient PM2.5 and cardiovascular hospital admissions: A UK Biobank study.

INTRODUCTION: A causal link between air pollution exposure and cardiovascular events has been suggested. However fewer studies have investigated the shape of the associations at low levels of air pollution and identified the most important temporal window of exposure. Here we assessed long-term associations between particulate matter < 2.5 µm (PM2.5) at low concentrations and multiple cardiovascular endpoints using the UK Biobank cohort. METHODS: Using data on adults (aged > 40) from the UK Biobank cohort, we investigated the associations between 1-year, 3-year and 5-year time-varying averages of PM2.5 and incidence of major adverse cardiovascular events (MACE), myocardial infarction (MI), heart failure, atrial fibrillation and flutter and cardiac arrest. We also investigated outcome subtypes for MI and stroke. Events were defined as hospital inpatient admissions. We fitted Cox proportional hazard regression models applying extensive control for confounding at both individual and area level. Finally, we assessed the shape of the exposure-response functions to assess effects at low levels of exposure. RESULTS: We analysed data from 377,736 study participants after exclusion of prevalent subjects. The average follow-up (2006-2021) was 12.9 years. We detected 19,353 cases of MACE, 6,562 of acute MI, 6,278 of heart failure, 1,258 for atrial fibrillation and flutter, and 16,327 for cardiac arrest. Using a 5-year exposure window, we detected positive associations (for 5 µg/m3 increase in PM2.5) for 5-point MACE of [1.12 (95 %CI: 1.00-1.26)], heart failure [1.22 (1.00-1.50)] and cardiac arrest [1.16 (1.03-1.31)]. We did not find any association with acute MI, while non-ST-elevation MI was associated with the 1-year exposure window [1.52 (1.12-2.07)]. The assessment of the shape of the exposure-response relationships suggested that risk is approximately linear for most of the outcomes. CONCLUSIONS: We found positive associations between long-term exposure to PM2.5 and multiple cardiovascular outcomes for different exposure windows. The cardiovascular risk tends to rise even at exposure concentrations below 12-15 µg/m3, indicating high risk below UK national and international thresholds.

Ambient heat exposure and kidney function in patients with chronic kidney disease: a post-hoc analysis of the DAPA-CKD trial.

BACKGROUND: Higher temperatures are associated with higher rates of hospital admissions for nephrolithiasis and acute kidney injury. Occupational heat stress is also a risk factor for kidney dysfunction in resource-poor settings. It is unclear whether ambient heat exposure is associated with loss of kidney function in patients with established chronic kidney disease. We assessed the association between heat index and change in estimated glomerular filtration rate (eGFR) in participants from the DAPA-CKD trial in a post-hoc analysis. METHODS: DAPA-CKD was a randomised controlled trial of oral dapagliflozin 10 mg once daily or placebo that enrolled participants aged 18 years or older, with or without type 2 diabetes, with a urinary albumin-to-creatinine ratio of 200-5000 mg/g, and an eGFR of 25-75 mL/min per 1·73 m2. In this post-hoc analysis, we explored the association between time-varying daily centre-level heat index (ERA5 dataset) and individual-level change in eGFR in trial participants using linear mixed effect models and case-time series. The DAPA-CKD trial is registered with ClinicalTrials.gov, NCT03036150. FINDINGS: Climate and eGFR data were available for 4017 (93·3%) of 4304 participants in 21 countries (mean age: 61·9 years; mean eGFR: 43·3 mL per 1·73 m2; median 28 months follow-up). Across centres, a heat index of more than 30°C occurred on a median of 0·6% of days. In adjusted linear mixed effect models, within each 120-day window, each 30 days' heat index of more than 30°C was associated with a -0·6% (95% CI -0·9% to -0·3%) change in eGFR. Similar estimates were obtained using case-time series. Additional analyses over longer time-windows showed associations consistent with haemodynamic or seasonal variability, or both, but overall estimates corresponded to an additional 3·7 mL per 1·73 m2 (95% CI 0·1 to 7·0) loss of eGFR per year in a patient with an eGFR of 45 mL per 1·73 m2 located in a very hot versus a temperate environment. INTERPRETATION: Higher ambient heat exposure is associated with more rapid eGFR decline in those with established chronic kidney disease. Efforts to mitigate heat exposure should be tested as part of strategies to attenuate chronic kidney disease progression. FUNDING: None.

Regional variation in the role of humidity on city-level heat-related mortality.

The rising humid heat is regarded as a severe threat to human survivability, but the proper integration of humid heat into heat-health alerts is still being explored. Using state-of-the-art epidemiological and climatological datasets, we examined the association between multiple heat stress indicators (HSIs) and daily human mortality in 739 cities worldwide. Notable differences were observed in the long-term trends and timing of heat events detected by HSIs. Air temperature (Tair) predicts heat-related mortality well in cities with a robust negative Tair-relative humidity correlation (CT-RH). However, in cities with near-zero or weak positive CT-RH, HSIs considering humidity provide enhanced predictive power compared to Tair. Furthermore, the magnitude and timing of heat-related mortality measured by HSIs could differ largely from those associated with Tair in many cities. Our findings provide important insights into specific regions where humans are vulnerable to humid heat and can facilitate the further enhancement of heat-health alert systems.

Seasonality of mortality under climate change: a multicountry projection study.

BACKGROUND: Climate change can directly impact temperature-related excess deaths and might subsequently change the seasonal variation in mortality. In this study, we aimed to provide a systematic and comprehensive assessment of potential future changes in the seasonal variation, or seasonality, of mortality across different climate zones. METHODS: In this modelling study, we collected daily time series of mean temperature and mortality (all causes or non-external causes only) via the Multi-Country Multi-City Collaborative (MCC) Research Network. These data were collected during overlapping periods, spanning from Jan 1, 1969 to Dec 31, 2020. We projected daily mortality from Jan 1, 2000 to Dec 31, 2099, under four climate change scenarios corresponding to increasing emissions (Shared Socioeconomic Pathways [SSP] scenarios SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). We compared the seasonality in projected mortality between decades by its shape, timings (the day-of-year) of minimum (trough) and maximum (peak) mortality, and sizes (peak-to-trough ratio and attributable fraction). Attributable fraction was used to measure the burden of seasonality of mortality. The results were summarised by climate zones. FINDINGS: The MCC dataset included 126 809 537 deaths from 707 locations within 43 countries or areas. After excluding the only two polar locations (both high-altitude locations in Peru) from climatic zone assessments, we analysed 126 766 164 deaths in 705 locations aggregated in four climate zones (tropical, arid, temperate, and continental). From the 2000s to the 2090s, our projections showed an increase in mortality during the warm seasons and a decrease in mortality during the cold seasons, albeit with mortality remaining high during the cold seasons, under all four SSP scenarios in the arid, temperate, and continental zones. The magnitude of this changing pattern was more pronounced under the high-emission scenarios (SSP3-7.0 and SSP5-8.5), substantially altering the shape of seasonality of mortality and, under the highest emission scenario (SSP5-8.5), shifting the mortality peak from cold seasons to warm seasons in arid, temperate, and continental zones, and increasing the size of seasonality in all zones except the arid zone by the end of the century. In the 2090s compared with the 2000s, the change in peak-to-trough ratio (relative scale) ranged from 0·96 to 1·11, and the change in attributable fraction ranged from 0·002% to 0·06% under the SSP5-8.5 (highest emission) scenario. INTERPRETATION: A warming climate can substantially change the seasonality of mortality in the future. Our projections suggest that health-care systems should consider preparing for a potentially increased demand during warm seasons and sustained high demand during cold seasons, particularly in regions characterised by arid, temperate, and continental climates. FUNDING: The Environment Research and Technology Development Fund of the Environmental Restoration and Conservation Agency, provided by the Ministry of the Environment of Japan.

Importance of humidity for characterization and communication of dangerous heatwave conditions.

Heatwaves are one of the leading causes of climate-induced mortality. Using the examples of recent heatwaves in Europe, the United States and Asia, we illustrate how the communication of dangerous conditions based on temperature maps alone can lead to insufficient societal perception of health risks. Comparison of maximum daily values of temperature with physiological heat stress indices accounting for impacts of both temperature and humidity, illustrates substantial differences in geographical extent and timing of their respective peak values during these recent events. This signals the need to revisit how meteorological heatwaves and their expected impacts are communicated. Close collaboration between climate and medical communities is needed to select the best heat stress indicators, establish them operationally, and introduce them to the public. npj Climate and Atmospheric Science (2023) 6:33.

Neglected implications of land-use and land-cover changes on the climate-health nexus.

Climate change can substantially affect temperature-related mortality and morbidity, especially under high green-house gas emission pathways. Achieving the Paris Agreement goals require not only drastic reductions in fossil fuel-based emissions but also land-use and land-cover changes (LULCC), such as reforestation and afforestation. LULCC has been mainly analysed in the context of land-based mitigation and food security. However, growing scientific evidence shows that LULCC can also substantially alter climate through biogeophysical effects. Little is known about the consequential impacts on human health. LULCC-related impact research should broaden its scope by including the human health impacts. LULCC are relevant to several global agendas (i.e. Sustainable Development Goals). Thus, collaboration across research communities and stronger stakeholder engagement are required to address this knowledge gap.

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.

Increased energy use for adaptation significantly impacts mitigation pathways.

Climate adaptation actions can be energy-intensive, but how adaptation feeds back into the energy system and the environment is absent in nearly all up-to-date energy scenarios. Here we quantify the impacts of adaptation actions entailing direct changes in final energy use on energy investments and costs, greenhouse gas emissions, and air pollution. We find that energy needs for adaptation increase considerably over time and with warming. The resulting addition in capacity for power generation leads to higher greenhouse gas emissions, local air pollutants, and energy system costs. In the short to medium term, much of the added capacity for power generation is fossil-fuel based. We show that mitigation pathways accounting for the adaptation-energy feedback would require a higher global carbon price, between 5% and 30% higher. Because of the benefits in terms of reduced adaptation needs, energy system costs in ambitious mitigation scenarios would be lower than previous estimates, and they would turn negative in well-below-2-degree scenarios, pointing at net gains in terms of power system costs.

Small-area assessment of temperature-related mortality risks in England and Wales: a case time series analysis.

BACKGROUND: Epidemiological literature on the health risks associated with non-optimal temperature has mostly reported average estimates across large areas or specific population groups. However, the heterogeneous distribution of drivers of vulnerability can result in local differences in health risks associated with heat and cold. We aimed to analyse the association between ambient air temperature and all-cause mortality across England and Wales and characterise small scale patterns in temperature-related mortality risks and impacts. METHODS: We performed a country-wide small-area analysis using data on all-cause mortality and air temperature for 34 753 lower super output areas (LSOAs) within 348 local authority districts (LADs) across England and Wales between Jan 1, 2000, and Dec 31, 2019. We first performed a case time series analysis of LSOA-specific and age-specific mortality series matched with 1 × 1 km gridded temperature data using distributed lag non-linear models, and then a repeated-measure multivariate meta-regression to pool LAD-specific estimates using area-level climatological, socioeconomic, and topographical predictors. FINDINGS: The final analysis included 10 716 879 deaths from all causes. The small-area assessment estimated that each year in England and Wales, there was on average 791 excess deaths (empirical 95% CI 611-957) attributable to heat and 60 573 (55 796-65 145) attributable to cold, corresponding to standardised excess mortality rates of 1·57 deaths (empirical 95% CI 1·21-1·90) per 100 000 person-years for heat and 122·34 deaths (112·90-131·52) per 100 000 person-years for cold. The risks increased with age and were highly heterogeneous geographically, with the minimum mortality temperature ranging from 14·9°C to 22·6°C. Heat-related mortality was higher in urban areas, whereas cold-related mortality showed a more nuanced geographical pattern and increased risk in areas with greater socioeconomic deprivation. INTERPRETATION: This study provides a comprehensive assessment of excess mortality related to non-optimal outdoor temperature, with several risk indicators reported by age and multiple geographical levels. The analysis provides detailed risk maps that are useful for designing effective public health and climate policies at both local and national levels. FUNDING: Medical Research Council, Natural Environment Research Council, EU Horizon 2020 Programme, National Institute of Health Research.

Comparison of weather station and climate reanalysis data for modelling temperature-related mortality.

Epidemiological analyses of health risks associated with non-optimal temperature are traditionally based on ground observations from weather stations that offer limited spatial and temporal coverage. Climate reanalysis represents an alternative option that provide complete spatio-temporal exposure coverage, and yet are to be systematically explored for their suitability in assessing temperature-related health risks at a global scale. Here we provide the first comprehensive analysis over multiple regions to assess the suitability of the most recent generation of reanalysis datasets for health impact assessments and evaluate their comparative performance against traditional station-based data. Our findings show that reanalysis temperature from the last ERA5 products generally compare well to station observations, with similar non-optimal temperature-related risk estimates. However, the analysis offers some indication of lower performance in tropical regions, with a likely underestimation of heat-related excess mortality. Reanalysis data represent a valid alternative source of exposure variables in epidemiological analyses of temperature-related risk.