Closing Heat Data Gaps in Climate Disease Frontline Communities (2024-2025)
This project set out to investigate the relationship between heat exposure and kidney health in Sri Lanka, where farmers in tropical regions face a growing burden of chronic kidney disease of unknown etiology (CKDu). Previous studies have suggested that strenuous labor in high heat conditions may contribute to kidney injury, but high-resolution, individualized heat exposure data have been lacking. In collaboration with the University of Ruhuna, the team sought to fill this gap by installing a network of weather monitoring stations in CKDu-impacted and unimpacted communities to collect temperature, humidity and globe temperature data.
Over the course of the year, the team successfully deployed monitoring stations in Padawiya, Matara and Jaffna, generating high-quality hourly datasets for analysis. These data will help clarify how chronic heat stress may correlate with CKDu prevalence in agricultural communities, with Padawiya serving as a high-prevalence site and Matara as a control. Beyond technical implementation, the project advanced team members’ skills in data science tools such as R and MATLAB and fostered cross-disciplinary collaboration among students and medical professionals.
The team’s findings were presented at the Bass Connections Showcase and in other academic settings with a manuscript now in preparation. Looking ahead, the group plans to expand its community engagement efforts in Sri Lanka while continuing to refine its analyses. By generating urgently needed high-resolution heat exposure data, the project contributes both to the scientific understanding of heat-related kidney risks and to building capacity for addressing global environmental health challenges.
Timing
Summer 2024 – Summer 2025
Crediting
Atmospheric Heat Exposure Variability and Knowledge Gap Analysis for Sri Lanka (Poster presentation at the Fortin Foundation Bass Connections Showcase, April 16, 2025)
Manuscript in progress
Image: Rice farming in Sri Lanka, by Sanjini de Silva/IWMI, licensed under CC BY-NC-ND 2.0