In this article, we present a comprehensive compilation of open access daily time-series datasets tailored to assess the temperature-mortality association. The data consists of daily mortality counts and average ambient temperature at various levels of geographic aggregation, including data from four cities, ten regions, and two counties, which have been utilised in previously published studies. These datasets are applicable for time-series regression analysis to estimate location-specific temperature-mortality associations. Additionally, the availability of data from multiple geographical locations enabled the exploration of geographical differences by pooling associations using meta-analysis. This compilation aims to serve as a valuable resource for researchers, educators, and students, facilitating their application of time-series regression modelling for research endeavours and training activities.

This compilation of time-series datasets has been used at the Asia Summer School on time-series regression for public health (https://asiasummerschool.weebly.com) for examples, exercises and working group activities. Aurelio Tobias was supported by the JSPS KAKENHI Grant Number 24K13527.

Compilation of open access daily time-series datasets for studying temperature-mortality association and other environmental stressors

Peer reviewed