| Summary: | Objective : To assess the socio-environmental predictors of Barmah forest virus (BFV) transmission in coastal areas, Queensland, Australia. Methods : Data on BFV notified cases, climate, tidal levels and socioeconomic index for area (SEIFA) in six coastal cities, Queensland, for the period 1992-2001 were obtained from the relevant government agencies. Negative binomial regression models were used to assess the socio-environmental predictors of BFV transmission. Results : The results show that maximum and minimum temperature, rainfall, relative humidity, high and low tide were statistically significantly associated with BFV incidence at lags 0-2 months. The fitted negative binomial regression models indicate a significant independent association of each of maximum temperature (ß = 0.139, P = 0.000), high tide (ß = 0.005, P = 0.000) and SEIFA index (ß = -0.010, P = 0.000) with BFV transmission after adjustment for confounding variables. Conclusions : The transmission of BFV disease in Queensland coastal areas seemed to be determined by a combination of local social and environmental factors. The model developed in this study may have applications in the control and prevention of BFV disease in these areas. © 2009 Blackwell Publishing Ltd.
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