A multisectoral data integration framework and geospatial visualisation for last-mile heat-health decision making: A pilot deployment study in Rajasthan, India

Nymisha Herrera Nimmagadda , Saket Kumar , Dishani Gupta , Ruchit Nagar , Haya Khan , Narottam Sharma 

Adaptation for extreme heat depends on identifying and responding to populations most vulnerable to heat-related illnesses. Yet, in many low- and middle-income countries the data needed to assess vulnerability remains fragmented across disconnected information systems. As a result, frontline health officials plan their response strategies using limited, underreported, and retrospective surveillance data rather than prospective assessments of vulnerability. For India, a country at the center of multiple climate-sensitive illnesses, this study aimed to develop an interoperable data integration framework for the first time at the sub-district level; co-design a human-centered geospatial dashboard for heat-health planning; and evaluate its utility during statewide deployment through changes in officials' understanding of vulnerability and planning orientation.
The Heat-Health Vulnerability Index (HHVI) was designed by Khushi Baby through a five-stage human-centered process, in partnership with the State Government of Rajasthan's Department of Medical, Health, and Family Welfare. HHVI measures vulnerability through 21 indicators across data systems, with independent spatial identifiers and reporting cadences including ERA5 climate reanalysis, remote sensing, maternal and child health registries, non-communicable disease data, and demographic health survey data. All systems were resolved to an administrative block boundary, producing a choropleth dashboard and linking vulnerability grades to existing Heat Action Plan protocols. HHVI revealed non-obvious spatially heterogeneous patterns of vulnerability within districts. High-vulnerability blocks consistently appeared within largely moderate-risk districts, driven by multi-causal combinations that no single data source captured. 
Structured review sessions with district officials prior to deployment surfaced a gap in the HHVI dashboard between visualizing insights, and using the insights to plan, execute, and track responses. This informed the development of an action feature (Spark Action) to schedule existing heat actions from the dashboard insights page itself.   
The dashboard was deployed through structured full-day workshops across all administrative divisions of Rajasthan. The workshops brought together 129 government health officials across 44 districts, who are collectively responsible for health service delivery to over 80 million people. Officials navigated the dashboard using their district data and produced district-level heat season plans. Pre- and post-workshop assessments were administered to measure changes in vulnerability conceptualization and planning orientation.
Across 101 officials with matched pre- and post-assessments: correct conceptualization of vulnerability rose by 20.8 percentage points (p<0.001), and vulnerability-based planning prioritization increased by 17.8 percentage points (p<0.001), with case-count based planning declining from 23.8% to 14.9% , and correct identification of the first step in heat-season planning increased from 85.1% to 94.1% (+8.9 percentage points, p=0.027).
In summary, we demonstrated the feasibility of an integrated and actionable heat-health dashboard for Rajasthan’s sub-districts along with measurable shifts in health official knowledge and practices. Three design principles emerged for integrating and applying climate-health data for frontline government planners: geographic granularity must match the user's accountability level; confidence in integrated outputs is established through local knowledge validation; and for operational users, visualization alone does not guarantee response in the absence of clear decision aids.