India is among the world’s most heat-exposed nations, with hundreds of millions of people facing dangerous temperatures each summer and a mortality burden that remains poorly understood at the district level. We estimate that a single day of extreme heat causes approximately 3,400 excess deaths nationally; a five-day heatwave causes nearly 30,000. Although global studies highlight surging heat-related mortality, granular spatial-temporal data on how heatwaves affect mortality at the district level in India remain inaccessible to common researchers. District-level estimates of heatwave-induced excess mortality covering all of India have not previously been reported in the peer-reviewed literature; this paper provides such estimates using publicly available data and a climate zone-based risk transfer methodology. We adapt findings from a multi-city epidemiological analysis of heat-related mortality across 10 Indian cities to estimate excess deaths across all Indian districts. We integrate district-level mortality rates from the Civil Registration System and population projections for 2024 with city-specific risk coefficients based on the Köppen–Geiger climate classification. We obtain district-level excess death estimates under one-day and five-day heatwave scenarios. Our results suggest that even a single day of extreme heat yields thousands of excess deaths, and a multi-day heatwave results in tens of thousands of excess deaths. By mapping heat-induced mortality risk to individual districts, this study finds that Uttar Pradesh alone accounts for approximately 8,100 excess deaths during a five-day heatwave, and districts such as Ahmedabad, Jaipur, and Surat each exceed 250 excess deaths in a single event. It underscores the need for more localized heat action plans, improved and heat-relevant healthcare infrastructure, and robust early-warning systems. These findings have implications not only for India but also for other countries in South Asia and Sub Saharan Africa facing similar heat vulnerabilities, highlighting the global urgency of heat adaptation measures. With respect to heatwave frequency and temperature thresholds, these estimates are conservative lower bounds. The direction of bias introduced by applying urban-derived risk coefficients to rural populations is uncertain and is discussed in the Limitations section.
Narang et al. (Tue,) studied this question.