Benjamin D Scalley1,2, Tony Spicer1, Le Jian1,3, Jianguo Xiao1, John Nairn4, Andrew Robertson1, Tarun Weeramanthri1. 1. Public Health Division, Department of Health, Government of Western Australia. 2. Western Australian Centre for Rural Health, University of Western Australia. 3. School of Public Health, Curtin University, Western Australia. 4. Australian Bureau of Meteorology, South Australia.
Abstract
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.
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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