Article Text

PDF

Global problems
P2-418 Weather variability and the incidence of influenza: Bayesian time series analysis
  1. W Hu1,
  2. G Williams1,
  3. S Tong1
  1. 1The University of Queensland, Brisbane, Australia
  2. 2Queensland University of Technology, Brisbane, Australia

Abstract

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.

Statistics from Altmetric.com

Request permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.