Heat waves (HWs) have killed more people in Australia than all other natural hazards combined. Climate change is expected to increase the frequency, duration, and intensity of HWs and leads to a doubling of heat-related deaths over the next 40 years. Despite being a significant public health issue, HWs do not attract the same level of attention from researchers, policy makers, and emergency management agencies compared to other natural hazards. The purpose of the study was to identify risk factors that might lead to population vulnerability to HW in Western Australia (WA). HW vulnerability and resilience among the population of the state of WA were investigated by using time series analysis. The health impacts of HWs were assessed by comparing the associations between hospital emergency department (ED) presentations, hospital admissions and mortality data, and intensities of HW. Risk factors including age, gender, socioeconomic status (SES), remoteness, and geographical locations were examined to determine whether certain population groups were more at risk of adverse health impacts due to extreme heat. We found that hospital admissions due to heat-related conditions and kidney diseases, and overall ED attendances, were sensitive indicators of HW. Children aged 14 years or less and those aged 60 years or over were identified as the most vulnerable populations to HWs as shown in ED attendance data. Females had more ED attendances and hospital admissions due to kidney diseases; while males had more heat-related hospital admissions than females. There were significant dose–response relationships between HW intensity and SES, remoteness, and health service usage. The more disadvantaged and remotely located the population, the higher the health service usage during HWs. Our study also found that some population groups and locations were resilient to extreme heat. We produced a mapping tool, which indicated geographic areas throughout WA with various vulnerability and resilience levels to HW. The findings from this study will allow local government, community service organizations, and agencies in health, housing, and education to better identify and understand the degree of vulnerability to HW throughout the state, better target preparatory strategies, and allocate limited resources to those most in need.

Objective: To determine which measures of heatwave have the greatest predictive power for increases in health service utilisation in Perth, Western Australia. Methods:Three heatwave formulas were compared, using Poisson or zero-inflated Poisson regression, against the number of presentations to emergency departments from all causes, and the number of inpatient admissions from heat-related causes. The period from July 2006 to June 2013 was included. A series of standardised thresholds were calculated to allow comparison between formulas, in the absence of a gold standard definition of heatwaves.Results: Of the three heatwave formulas, Excess Heat Factor (EHF) produced the most clear dose-response relationship with Emergency Department presentations. The EHF generally predicted periods that resulted in a similar or higher rate of health service utilisation, as compared to the two other formulas, for the thresholds examined. Conclusions:The EHF formula, which considers a period of acclimatisation as well as the maximum and minimum temperature, best predicted periods of greatest health service demand. The strength of the dose-response relationship reinforces the validity of the measure as a predictor of hazardous heatwave intensity. Implications:The findings suggest that the EHF formula is well suited for use as a means of activating heatwave plans and identifies the required level of response to extreme heatwave events as well as moderate heatwave events that produce excess health service demand.

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