This community innovation has been accepted at the 2026 DHIS2 Annual Conference as a digital poster.
Heat–Health Monitoring Using Routine DHIS2 Data
As climate change accelerates, heatwaves are becoming more frequent and severe, posing significant public health risks, particularly in climate-vulnerable countries such as Bangladesh. This study leverages routine clinical data captured through the DHIS2 Individual Event Capture module, standardized using ICD-10 codes (including L55 for sunburn and T67 for heatstroke and sunstroke), to monitor heat-related illnesses across government healthcare facilities. These data are integrated with meteorological indicators—daily temperature and humidity—to examine associations between extreme heat events and hospital admissions. Between January 2023 and November 2025, a total of 8,538 heat-related illness cases were reported, showing a gradual decline over time: 3,592 cases in 2023, 2,868 in 2024, and 2,077 in 2025. Beyond temperature-only analysis, the study emphasizes the application of a heat index that better reflects human heat stress by combining air temperature and humidity. Daily apparent temperature was calculated using Humidex and the NOAA Rothfusz regression algorithm to capture the compounded physiological burden of heat and moisture, which is particularly relevant in Bangladesh’s humid tropical climate. Temporal analysis reveals clear seasonal peaks during the pre-monsoon and summer months, with April, May, and June consistently recording higher case numbers in 2023 and 2024. These peaks align more closely with extreme heat index values than with temperature alone. Spatial analysis identifies persistent hotspots, including Chandpur, Cumilla, Kustia, and Patuakhali, where high humidity amplifies heat stress risks. Building on over a decade of DHIS2 investment, the DHIS2–Open-Meteo integration transforms routine service data into near–real-time climate-health intelligence. Embedded within existing national systems, this scalable model supports continuous surveillance, early warning, and targeted public health action without creating parallel platforms.
Author: Muhammad Masud Parvez, Dewan Md Emdadul Hoque, Chandrasegarar Soloman, Priscilla Wobil, Hasnain Ahmed
Keywords:
Climate change; Heatwaves; Heat–health surveillance; DHIS2; Individual Event Capture; Heat-related illness; ICD-10; Heat index; Humidex; Rothfusz regression; Open-Meteo; Climate–health integration; Early warning systems; Bangladesh; Health information systems
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