title: The development of predictive tools for pre-emptive dengue vector control: a study of Aedes aegypti abundance and meteorological variables in North Queensland, Australia.
abstract: OBJECTIVE
  To describe the meteorological influences on adult dengue vector abundance in Australia for the development of predictive models to trigger pre-emptive control operation.
  
  
  METHODS
  Multiple linear regression analyses were performed using meteorological data and female Aedes aegypti collection data from BG-Sentinel Mosquito traps placed at 11 monitoring sites in Cairns, north Queensland.
  
  
  RESULTS
  Considerable regression coefficients (R(2) = 0.64 and 0.61) for longer- and shorter-term factor models respectively were derived. Longer-term factors significantly associated with abundance of adult vectors were mean minimum temperature (lagged 6 month) and mean daily temperature (lagged 4 month), explaining the predictable increase in abundance during the wet season. Factors explaining fluctuation in abundance in the shorter term were mean relative humidity over the previous 2 weeks and current daily average temperature. Rainfall variables were not found to be strong predictors of A. aegypti abundance in either longer- or shorter-term models.
  
  
  CONCLUSIONS
  The implications of these findings for the development of useful predictive models for vector abundance risks are discussed. Such models can be used to guide the application of pre-emptive dengue vector control, and thereby enhance disease management.
authors.affiliation: Sansom Institute for Health Research, University of South Australia, Adelaide, SA, Australia.
authors.forename: Aishah H
authors.initials: AH
authors.lastname: Azil
authors.forename: Sharron A
authors.initials: SA
authors.lastname: Long
authors.forename: Scott A
authors.initials: SA
authors.lastname: Ritchie
authors.forename: Craig R
authors.initials: CR
authors.lastname: Williams
mesh_terms: D000330:Aedes; D000818:Animals; D003715:Dengue / Q000517:prevention & control*; D004199:Disease Vectors; D005260:Female; D006813:Humidity; D011156:Population Density; D011793:Queensland; D011891:Rain; D012044:Regression Analysis; D013696:Temperature