GH003-05
India-specific Heat stress Index and Its Impacts on Mortality in Mega-city Delhi

Wednesday, 9 December 2020: 07:12
Virtual
Rohit Kumar Choudhary1, Pallavi Joshi Lahari2, Sagnik Dey3, Santu Ghosh4 and Sushil Kumar Dash3, (1)Indian Institute of Technology Delhi, New Delhi, India, (2)Indian Institute of Technology Delhi, Centre for Atmospheric Sciences, New Delhi, India, (3)IIT Delhi, New Delhi, India, (4)St Johns Medical College, Department of Biostatistics, Bangalore, India
Abstract:
Climate change-induced extreme weather and heat waves have been associated with direct health impacts in terms of increased mortality and morbidity. Such health risks are likely to be spatially heterogeneous given the local climatic, demographic and social variations. The developing countries fare high on the risk scale with greater population exposure ratios and insufficient capacity to resist adverse impact. However, research evidence associating heat extremes and attributed mortality remain scarce for the developing countries.

India’s case is compelling in this regard, as heat stress/heat extremes make the second-highest cause of natural hazard-related deaths annually. Although there are past studies estimating heatwave attributed mortality for specific regions, studies on heat stress per se remain restricted to occupational/industrial health domain. We attempt to fill this gap in two ways by (1) developing India-specific heat stress thresholds, and (2) testing the impacts of customised heat stress thresholds on mortality in megacity Delhi as a case study.

We tune the four standard heat indices - WBGT, UTCI, Humidex and Heat Index as per the six Indian climatic zones based on 40-years of meteorological data from ERA-Interim to obtain climate zone-specific thresholds. Secondly, to understand the attribution of heat stress on short term mortality, we use daily all-cause natural mortality data and WBGT discomfort thresholds for Delhi over 2013-2016. The risk function is modelled using a semi-parametric quasi Poisson regression model, adjusted for non-linear confounding effects of time, relative humidity and PM2.5, stratified by season. Effect modification by age group and gender class is also explored. Such fine-scale heat stress-mortality risk functions can help strengthen climate change resilience policy and mitigate the adverse health impact of heat stress events at a local scale.