Literature DB >> 23756508

Using the Excess Heat Factor (EHF) to predict the risk of heat related deaths.

Neil Langlois1, Jonathon Herbst, Kerryn Mason, John Nairn, Roger W Byard.   

Abstract

Extremes of climate are not uncommon in Australia and heatwaves are not infrequent. Periods of high ambient temperature may result in clusters of heat related deaths, which may place strain on forensic facilities. This paper describes the formulation of the Excess Heat Factor using meteorological data to provide a means of predicting death resulting from periods of extreme heat stress. The 2009 South Australian heatwave had the highest ranked Excess Heat Factor in Adelaide's records. There were 58 heat related deaths, with the bulk of the heat related deaths following the peak Excess Heat Factor value (144 °C(2)). The 2008 heatwave had a lower peak Excess Heat Factor value (36 °C(2)); there was only one heat related death, which followed the peak in the Excess Heat Factor. It is proposed that calculation of the Excess Heat Factor from meteorological data could provide a means to predict and identify heat related deaths resulting from extreme weather conditions.
Copyright © 2013 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

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Year:  2013        PMID: 23756508     DOI: 10.1016/j.jflm.2012.12.005

Source DB:  PubMed          Journal:  J Forensic Leg Med        ISSN: 1752-928X            Impact factor:   1.614


  6 in total

1.  Can the Excess Heat Factor Indicate Heatwave-Related Morbidity? A Case Study in Adelaide, South Australia.

Authors:  Gertrud Hatvani-Kovacs; Martin Belusko; John Pockett; John Boland
Journal:  Ecohealth       Date:  2015-12-22       Impact factor: 3.184

2.  Heat-related deaths.

Authors:  Roger W Byard
Journal:  Forensic Sci Med Pathol       Date:  2013-03-16       Impact factor: 2.007

3.  Using the excess heat factor to indicate heatwave-related urinary disease: a case study in Adelaide, South Australia.

Authors:  Matthew Borg; Monika Nitschke; Susan Williams; Stephen McDonald; John Nairn; Peng Bi
Journal:  Int J Biometeorol       Date:  2019-01-28       Impact factor: 3.787

4.  The excess heat factor: a metric for heatwave intensity and its use in classifying heatwave severity.

Authors:  John R Nairn; Robert J B Fawcett
Journal:  Int J Environ Res Public Health       Date:  2014-12-23       Impact factor: 3.390

5.  Performance of Excess Heat Factor Severity as a Global Heatwave Health Impact Index.

Authors:  John Nairn; Bertram Ostendorf; Peng Bi
Journal:  Int J Environ Res Public Health       Date:  2018-11-08       Impact factor: 3.390

6.  Mining Social Media to Identify Heat Waves.

Authors:  Francesca Cecinati; Tom Matthews; Sukumar Natarajan; Nick McCullen; David Coley
Journal:  Int J Environ Res Public Health       Date:  2019-03-02       Impact factor: 3.390

  6 in total

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