Climate change and human health: estimating district-level health vulnerabilities in the Indian context

Divya Chaudhry () and Indranil Mukhopadhyay
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Divya Chaudhry: O.P. Jindal Global University
Indranil Mukhopadhyay: O.P. Jindal Global University

Climatic Change, 2023, vol. 176, issue 11, No 10, 20 pages

Abstract: Abstract Evidence of the health impact of climate change has been extensively documented in recent scholarly literature. In order to mitigate the adverse health effects induced by climate change, the need for conducting vulnerability assessments (VAs) has been emphasised. A higher vulnerability to climate change is often linked with substantial risks to human lives and built environment. Despite the potential of VAs in alleviating risks posed by climate change, only a limited amount of scholarly work in this domain has been conducted in the Indian context. The present research addresses this lacuna and contributes to the limited scholarship on climate change and health VAs in India. Drawing on the VA framework introduced by the fourth assessment report (AR4) of the Intergovernmental Panel on Climate Change (IPCC), this paper estimates district-level health vulnerabilities caused by climate change using multi-dimensional indices. The indices are multi-dimensional since they integrate 50 district-level indicators from 8 data sources for all 640 Census 2011 districts. The statistical technique of Principal Component Analysis (PCA) has been used for integrating the indicators. The findings of this paper indicate that nearly 56% of India’s population in 344 districts is highly vulnerable to the health impact of climate change. The results show that high vulnerability in certain districts is mediated by high adaptive capacity (AC). Since climate exposure varies across districts, the paper highlights the need for local-level responses and Complex Adaptive System (CAS) thinking to understand the implications of climate change and human health.

Keywords: Human health; Vulnerability; Climate change; Vulnerability assessments; Districts; Complex Adaptive Systems (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10584-023-03630-0

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