TY - JOUR
T1 - Socio-environmental predictors of Barmah forest virus transmission in coastal areas, Queensland, Australia
AU - Naish, Suchithra
AU - Hu, Wenbiao
AU - Nicholls, Neville
AU - MacKenzie, John S.
AU - Dale, Pat
AU - McMichael, Anthony J.
AU - Tong, Shilu
PY - 2009/2
Y1 - 2009/2
N2 - 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 (β = 0.139, P = 0.000), high tide (β = 0.005, P = 0.000) and SEIFA index (β = -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.
AB - 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 (β = 0.139, P = 0.000), high tide (β = 0.005, P = 0.000) and SEIFA index (β = -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.
KW - Barmah forest virus
KW - Control
KW - Outbreak
KW - Queensland
KW - Risk factors
UR - http://www.scopus.com/inward/record.url?scp=60349101683&partnerID=8YFLogxK
U2 - 10.1111/j.1365-3156.2008.02217.x
DO - 10.1111/j.1365-3156.2008.02217.x
M3 - Article
SN - 1360-2276
VL - 14
SP - 247
EP - 256
JO - Tropical Medicine and International Health
JF - Tropical Medicine and International Health
IS - 2
ER -