The implementation of heat alert warning systems, such as traditional weather forecasting services has not adequately reduced heat-related health mortalities or morbidities. This is because it operates without including a human health risk component. Additionally, heat warnings are issued for only extreme temperatures without considering the low, and medium heat intensities which could potentially affect the health of some populations. Therefore, there is a need to develop a heat vulnerability index (HVI) to help identify the vulnerable population so that future public health interventions are successful. This can be achived by considering the chronic health conditions, sociodemographic/socioeconomic factors, housing conditions, and green vegetation levels of the population. One important aspect that has remained uninvestigated is whether changes in the sociodemographic/socioeconomic, and health conditions of a population can lead to changes in their heat vulnerability index (HVI) levels. Previous studies have not studied all of these features but rather determined heat vulnerability index using one-time sociodemographic variables (one Census data only) or have relied on cumulative sociodemographic variables (two or more Census data combined). Furthermore, there is a dearth of knowledge about the levels of heat vulnerability index (HVI) under different extreme heat intensities (low, medium, and high). The overall aim of the study is to assess longitudinal spatial heat-health vulnerabilities at a Statistical Area 2 (SA2) level over time, and to investigate the accuracy of HVIs in predicting heat-related mortality and morbidity in Australia.
Increasing heat vulnerability is an important public health concern. The extent of short-term changes in heat vulnerability across Australia is yet unclear. First, we constructed a suburb-level heat vulnerability index (HVI) across Australia by using 5-year national census estimates in 2011, 2016, and 2021. Second, we assessed whether HVI is associated with all-cause heat-related deaths across all the suburbs in Australia. Third, we applied an interview-based study to understand the perception about the integration of HVI maps into Australian national heat action plans. We included demographic/socioeconomic data, temperature, landcover, and all-cause mortality data in this study. All analysis was conducted through multivariant statistics, geospatial modelling, and qualitative analysis. The current findings show that heat vulnerability is increasing and changing with time particularly across the suburbs in the greater capital cities. The northern territory and southeastern part of Australia showed high heat vulnerability. The vulnerability was driven among older people who lived alone during 2011, and individuals with chronic diabetes, low-income, and those with less than high school education in 2016-2021. Heat vulnerability showed weaker association with heat-related deaths in the capital cities but lacks association in Australia-wide.
