A systematic review of the use of gridded population datasets in the assessment of climate-health risks

The global climate crisis poses a growing and multifaceted threat to human health. Assessing and mitigating these climate-related health risks requires spatially explicit understanding of where populations are exposed and vulnerable to climate hazards. Advances in geospatial technologies and the increasing availability of satellite and remote sensing data have enabled the development of high-resolution global gridded population datasets, which have become critical infrastructure for climate-health research. These datasets support the analysis of population exposure and vulnerability across regions and scales, and are increasingly important for scenario-based assessments aligned with future climate and socioeconomic pathways.

This study systematically reviews academic literature published since 2015 to assess how gridded population data are being used in climate change and health research. Specifically, we examine who is using gridded population datasets, in which geographical regions, and for what types of climate-related health analyses. We assess the types of gridded population products used, including their spatial resolution and levels of demographic disaggregation, and how population data are integrated with climate and health information. Where reported, we also evaluate how study results are interpreted and applied to inform policy or decision-making.

The review of 222 academic peer-reviewed studies demonstrates that i) gridded population data have become foundational infrastructure for climate–health research, with a marked increase in publications since 2015; ii) applications span multiple health domains; iii) there is a substantial geographical imbalance; iv) gridded population data enable assessments of population exposure and vulnerability; v) use of age- and sex-disaggregated data is limited.

Overall, the review highlights gridded population data as a crucial bridge between climate science and public health action, emphasising the need for continued dataset development, interdisciplinary collaboration, and integration with future climate and socio-economic scenarios.