Socio-environmental predictors of Barmah forest virus transmission in coastal areas, Queensland, Australia.
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 (beta = 0.139, P = 0.000), high tide (beta = 0.005, P = 0.000) and SEIFA index (beta = -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.
Naish
Suchithra
S
School of Public Health & Institute of Health and Biomedical Innovation, Queensland University of Technology, Qld, Australia. s.naish@qut.edu.au
Hu
Wenbiao
W
Nicholls
Neville
N
Mackenzie
John S
JS
Dale
Pat
P
McMichael
Anthony J
AJ
Tong
Shilu
S
D000524:Alphavirus; D018354:Alphavirus Infections / Q000453:epidemiology*; D002947:Cities; D002980:Climate; D006801:Humans; D006813:Humidity; D015994:Incidence; D016014:Linear Models; D011793:Queensland / Q000453:epidemiology; D011891:Rain; D012307:Risk Factors; D012623:Seawater; D012959:Socioeconomic Factors; D013696:Temperature