Adapting everyday activities to summer heatwaves: a multi-country analysis of mobile phone location data

Abstract In the 21st century, record-breaking summer heatwaves have had devastating impacts on people’s health, well-being, and livelihoods. In light of this urgent threat, government institutions across the globe are developing guidelines and planned interventions to increase resilience to heatwaves. These measures require an understanding of how people adapt to extreme heat within the constraints of daily life. Existing studies have used large-scale mobility data to characterize heatwave adaptation at population levels, but skew towards cities and regions in high-income countries, have diverse methodologies that limit generalizability to other contexts, and focus on ‘activity level’ changes without discerning which activities are being altered. Addressing these gaps, this study combines climate reanalysis, mobile phone location, socio-demographic, and physical-geographical data across Brazil, France, India, Nigeria, Turkey, the USA, and China during 2022/2023 summer heatwaves. Google Community Mobility Reports data is used in multivariate multi-level modelling for the first six countries to examine daily activity changes during heatwaves (home, work, transit, grocery/pharmacy, retail/recreation, parks). In China, Baidu data on activity levels is analysed in a complementary multi-level model. The results show a widespread tendency to withdraw into homes but also highlight unequal substitutions of activities, and—under some circumstances—visits to potentially cooler locations away from home. This study highlights the global nature of heatwave adaptation and the value of considering adaptation within the context of people’s everyday lives.