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Evaluation of a heat warning system in Adelaide, South Australia, using case-series analysis

BACKGROUND: Heatwave warning systems aim to assist in reducing health effects during extreme heat. Evaluations of such systems have been limited. This study explored the effect of a heatwave warning programme on morbidity and mortality in Adelaide, South Australia, by comparing extreme events in 200...

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Autores principales: Nitschke, Monika, Tucker, Graeme, Hansen, Alana, Williams, Susan, Zhang, Ying, Bi, Peng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4964181/
https://www.ncbi.nlm.nih.gov/pubmed/27436672
http://dx.doi.org/10.1136/bmjopen-2016-012125
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author Nitschke, Monika
Tucker, Graeme
Hansen, Alana
Williams, Susan
Zhang, Ying
Bi, Peng
author_facet Nitschke, Monika
Tucker, Graeme
Hansen, Alana
Williams, Susan
Zhang, Ying
Bi, Peng
author_sort Nitschke, Monika
collection PubMed
description BACKGROUND: Heatwave warning systems aim to assist in reducing health effects during extreme heat. Evaluations of such systems have been limited. This study explored the effect of a heatwave warning programme on morbidity and mortality in Adelaide, South Australia, by comparing extreme events in 2009 and 2014, the latter with exposure to the preventive programme. METHODS: The health outcomes during the two heatwaves were compared using the incidence rate ratios (IRRs) of daily ambulance call-outs, emergency presentations and mortality data during the heatwaves compared with non-heatwave periods during the warm seasons. Excess or reduced numbers of cases were calculated and the differences in cases between the two heatwaves were estimated. RESULTS: IRRs for total ambulance call-outs and emergency presentations were lower during the 2014 heatwaves compared with the 2009 event. The estimated differences in health-specific outcomes between 2009 and 2014 were statistically significant with 207 (59%) for cardiac-related call-outs, 134 (30%) for renal and 145 (56%) for heat-related emergency presentations. Mortality was not reduced in 2014. There were an estimated 34.5 excess deaths in 2009 and 38.2 in 2014. CONCLUSIONS: Morbidity outcomes were reduced significantly during the 2014 event. The fact that cardiac, renal and heat-related diagnoses were significantly reduced is likely to be associated with the intervention in 2014, which comprised a public warning through media and intense preventive measures directed to individual populations at risk. Further analysis of risk factors of mortality during heatwaves should be explored.
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spelling pubmed-49641812016-08-03 Evaluation of a heat warning system in Adelaide, South Australia, using case-series analysis Nitschke, Monika Tucker, Graeme Hansen, Alana Williams, Susan Zhang, Ying Bi, Peng BMJ Open Epidemiology BACKGROUND: Heatwave warning systems aim to assist in reducing health effects during extreme heat. Evaluations of such systems have been limited. This study explored the effect of a heatwave warning programme on morbidity and mortality in Adelaide, South Australia, by comparing extreme events in 2009 and 2014, the latter with exposure to the preventive programme. METHODS: The health outcomes during the two heatwaves were compared using the incidence rate ratios (IRRs) of daily ambulance call-outs, emergency presentations and mortality data during the heatwaves compared with non-heatwave periods during the warm seasons. Excess or reduced numbers of cases were calculated and the differences in cases between the two heatwaves were estimated. RESULTS: IRRs for total ambulance call-outs and emergency presentations were lower during the 2014 heatwaves compared with the 2009 event. The estimated differences in health-specific outcomes between 2009 and 2014 were statistically significant with 207 (59%) for cardiac-related call-outs, 134 (30%) for renal and 145 (56%) for heat-related emergency presentations. Mortality was not reduced in 2014. There were an estimated 34.5 excess deaths in 2009 and 38.2 in 2014. CONCLUSIONS: Morbidity outcomes were reduced significantly during the 2014 event. The fact that cardiac, renal and heat-related diagnoses were significantly reduced is likely to be associated with the intervention in 2014, which comprised a public warning through media and intense preventive measures directed to individual populations at risk. Further analysis of risk factors of mortality during heatwaves should be explored. BMJ Publishing Group 2016-07-19 /pmc/articles/PMC4964181/ /pubmed/27436672 http://dx.doi.org/10.1136/bmjopen-2016-012125 Text en Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/ This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
spellingShingle Epidemiology
Nitschke, Monika
Tucker, Graeme
Hansen, Alana
Williams, Susan
Zhang, Ying
Bi, Peng
Evaluation of a heat warning system in Adelaide, South Australia, using case-series analysis
title Evaluation of a heat warning system in Adelaide, South Australia, using case-series analysis
title_full Evaluation of a heat warning system in Adelaide, South Australia, using case-series analysis
title_fullStr Evaluation of a heat warning system in Adelaide, South Australia, using case-series analysis
title_full_unstemmed Evaluation of a heat warning system in Adelaide, South Australia, using case-series analysis
title_short Evaluation of a heat warning system in Adelaide, South Australia, using case-series analysis
title_sort evaluation of a heat warning system in adelaide, south australia, using case-series analysis
topic Epidemiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4964181/
https://www.ncbi.nlm.nih.gov/pubmed/27436672
http://dx.doi.org/10.1136/bmjopen-2016-012125
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