Responding to heatwave intensity: Excess Heat Factor is a superior predictor of health service utilisation and a trigger for heatwave plans

Aust N Z J Public Health. 2015 Dec;39(6):582-7. doi: 10.1111/1753-6405.12421. Epub 2015 Aug 10.

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.

Keywords: excess heat factor; heatwave; heatwave planning.

Publication types

  • Comparative Study

MeSH terms

  • Australia
  • Disasters*
  • Emergency Service, Hospital / statistics & numerical data*
  • Extreme Heat*
  • Heat Exhaustion / epidemiology
  • Heat Stress Disorders / epidemiology
  • Hospitalization / statistics & numerical data*
  • Hot Temperature / adverse effects*
  • Humans
  • Models, Theoretical
  • Western Australia / epidemiology