Tracking the impacts of climate change on human health via indicators: lessons from the Lancet Countdown.

BACKGROUND: In the past decades, climate change has been impacting human lives and health via extreme weather and climate events and alterations in labour capacity, food security, and the prevalence and geographical distribution of infectious diseases across the globe. Climate change and health indicators (CCHIs) are workable tools designed to capture the complex set of interdependent interactions through which climate change is affecting human health. Since 2015, a novel sub-set of CCHIs, focusing on climate change impacts, exposures, and vulnerability indicators (CCIEVIs) has been developed, refined, and integrated by Working Group 1 of the "Lancet Countdown: Tracking Progress on Health and Climate Change", an international collaboration across disciplines that include climate, geography, epidemiology, occupation health, and economics. DISCUSSION: This research in practice article is a reflective narrative documenting how we have developed CCIEVIs as a discrete set of quantifiable indicators that are updated annually to provide the most recent picture of climate change's impacts on human health. In our experience, the main challenge was to define globally relevant indicators that also have local relevance and as such can support decision making across multiple spatial scales. We found a hazard, exposure, and vulnerability framework to be effective in this regard. We here describe how we used such a framework to define CCIEVIs based on both data availability and the indicators' relevance to climate change and human health. We also report on how CCIEVIs have been improved and added to, detailing the underlying data and methods, and in doing so provide the defining quality criteria for Lancet Countdown CCIEVIs. CONCLUSIONS: Our experience shows that CCIEVIs can effectively contribute to a world-wide monitoring system that aims to track, communicate, and harness evidence on climate-induced health impacts towards effective intervention strategies. An ongoing challenge is how to improve CCIEVIs so that the description of the linkages between climate change and human health can become more and more comprehensive.

Effects of ambient heat exposure on risk of all-cause mortality in children younger than 5 years in Africa: a pooled time-series analysis.

BACKGROUND: Reducing child mortality is a Sustainable Development Goal, and climate change constitutes numerous challenges for Africa. Previous research has shown an association between leading causes of child mortality and climate change. However, few studies have examined these effects in detail. We aimed to explore the effects of ambient heat on neonate, post-neonate, and child mortality rates. METHODS: For this pooled time-series analysis, health data were obtained from the International Network for the Demographic Evaluation of Populations and Their Health (INDEPTH) Health and Demographic Surveillance System. We included data from 29 settlements from 13 countries across Africa, collected via monthly surveys from Jan 1, 1993, to Dec 31, 2016. Climate data were obtained from ERA5, collected from Jan 1, 1991, to Dec 31, 2019. We pooled these data for monthly mean daily maximum wet bulb globe temperature (WBGT) and downscaled to geolocations. Due to data heaping, we pooled our health data on a monthly temporal scale and a spatial scale into six different climate regions (ie, Sahel [ie, Burkina Faso and northern Ghana], Guinea [ie, southern Ghana, Côte d'Ivoire, and Nigeria], Senegal and The Gambia, eastern Africa [ie, Kenya, Malawi, Tanzania, Mozambique, and Uganda], South Africa, and Ethiopia). Our outcomes were neonate (ie, younger than 28 days), post-neonate (ie, aged 28 days to 1 year), and child (ie, older than 1 year and younger than 5 years) mortality. To assess the association between WBGT and monthly all-cause mortality, we used a time-series regression with a quasi-Poisson, polynomial-distributed lag model. FINDINGS: Between Jan 1, 1993, and Dec 31, 2016, there were 44 909 deaths in children younger than 5 years across the 29 sites in the 13 African countries: 10 078 neonates, 14 141 post-neonates, and 20 690 children. We observed differences in the association of heat with neonate, post-neonate, and child mortality by study region. For example, for Ethiopia, the relative risk ratio of mortality at the 95th percentile compared with median heat exposure during the study period was 1·14 (95% CI 1·06-1·23) for neonates, 0·99 (0·90-1·07) for post-neonates, and 0·79 (0·73-0·87) for children. Across the whole year, there was a significant increase in the relative risk of increased mortality for children in eastern Africa (relative risk 1·27, 95% CI 1·19-1·36) and Senegal and The Gambia (1·11, 1·04-1·18). INTERPRETATION: Our results show that the influence of extreme heat on mortality risk in children younger than 5 years varies by age group, region, and season. Future research should explore potentially informative ways to measure subtleties of heat stress and the factors contributing to vulnerability. FUNDING: EU Horizons as part of the Heat Indicators for Global Health (HIGH) Horizons project.

Wet Bulb Globe Temperature: Indicating Extreme Heat Risk on a Global Grid.

The Wet Bulb Globe Temperature (WBGT) is an international standard heat index used by the health, industrial, sports, and climate sectors to assess thermal comfort during heat extremes. Observations of its components, the globe and the wet bulb temperature (WBT), are however sparse. Therefore WBGT is difficult to derive, making it common to rely on approximations, such as the ones developed by Liljegren et al. (2008, https://doi.org/10.1080/15459620802310770, W B G T L i l j e g r e n ) and by the American College of Sports Medicine ( W B G T A C S M 87 ). In this study, a global data set is created by implementing an updated WBGT method using ECMWF ERA5 gridded meteorological variables and is evaluated against existing WBGT methods. The new method, W B G T B r i m i c o m b e , uses globe temperature calculated using mean radiant temperature and is found to be accurate in comparison to W B G T L i l j e g r e n across three heatwave case studies. In addition, it is found that W B G T A C S M 87 is not an adequate approximation of WBGT. Our new method is a candidate for a global forecasting early warning system.