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P2-418 Weather variability and the incidence of influenza

Bayesian time series analysis

Bibliographic Data

ID11176883
AuthorsWenbiao Hu (0000-0001-6422-9240, The University of Queensland), Gail Williams (0000-0002-4822-5263, The University of Queensland), Sabine Tong (The University of Queensland)
Year2011
Volume65
IssueSuppl 1
PagesA337.2-A337
Publication date2011-08-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueJournal of Epidemiology and Community Health (JOURNAL)
Journal identifiersISSN: 0143-005X • E-ISSN: 1470-2738
PublisherBMJ (PUBLISHER • GB)
DOI10.1136/jech.2011.142976l.48
OpenAlexW2225561582
LanguageEN

Introduction Influenza is one of the most common infectious diseases in the world. Few studies have examined the quantitative relationship between weather conditions and influenza. This paper examined the potential impact of weather variability on the incidence of influenza in Brisbane, Australia. Methods Data on daily weather variables (minimum temperature and rainfall), notified influenza cases and population size in Brisbane were supplied by the Australian Bureau of Meteorology, Queensland Health, and Australian Bureau of Statistics for the period of 1 January 2002–31 December 2008, respectively. Bayesian time series Poisson regression model was performed to examine the potential impact of weather variability on the incidence of influenza. Results The weekly mean of number of influenza cases, minimum temperature and rainfall were 12.59, 15.41°C and 16.52 mm between January 2002 and December 2008, respectively. Bayesian time series Poisson regression model shows that the average number of weekly influenza cases increased by 8% (95% credible interval (CrI): 9 to 10%) and 6% (95% CrI: 2 to 10%), for a 1°C decrease in average weekly minimum temperature at a lag of one week and a 10 mm increase in average weekly rainfall at a lag of one week, respectively. An interactive effect between temperature and rainfall on influenza was also found. Conclusions The results of this study suggest that temperature and rainfall are among the main determinants of influenza transmission

Bayesian probability · Climatology · Coronavirus disease 2019 (COVID-19) · Disease · Distributed lag · Environmental health · Incidence (geometry) · Infectious disease (medical specialty) · Linear regression · Poisson distribution · Poisson regression · Population · Rate ratio · Regression analysis · Seasonal influenza · Statistics · Animal Disease Management and Epidemiology · COVID-19 epidemiological studies · Demography · Influenza Virus Research Studies · Internal Medicine · Mathematics · Medicine

Citation velocityhistorical
Highly citedNo

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