Literature DB >> 19187524

Socio-environmental predictors of Barmah forest virus transmission in coastal areas, Queensland, Australia.

Suchithra Naish1, Wenbiao Hu, Neville Nicholls, John S Mackenzie, Pat Dale, Anthony J McMichael, Shilu Tong.   

Abstract

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.

Entities:  

Mesh:

Year:  2009        PMID: 19187524     DOI: 10.1111/j.1365-3156.2008.02217.x

Source DB:  PubMed          Journal:  Trop Med Int Health        ISSN: 1360-2276            Impact factor:   2.622


  5 in total

1.  Spatio-temporal patterns of Barmah Forest virus disease in Queensland, Australia.

Authors:  Suchithra Naish; Wenbiao Hu; Kerrie Mengersen; Shilu Tong
Journal:  PLoS One       Date:  2011-10-13       Impact factor: 3.240

2.  A comparative analysis of three vector-borne diseases across Australia using seasonal and meteorological models.

Authors:  Margaret D Stratton; Hanna Y Ehrlich; Siobhan M Mor; Elena N Naumova
Journal:  Sci Rep       Date:  2017-01-10       Impact factor: 4.379

Review 3.  The Role of Temperature in Transmission of Zoonotic Arboviruses.

Authors:  Alexander T Ciota; Alexander C Keyel
Journal:  Viruses       Date:  2019-11-01       Impact factor: 5.048

4.  Mayaro virus infection in amazonia: a multimodel inference approach to risk factor assessment.

Authors:  Fernando Abad-Franch; Gustavo H Grimmer; Vanessa S de Paula; Luiz T M Figueiredo; Wornei S M Braga; Sérgio L B Luz
Journal:  PLoS Negl Trop Dis       Date:  2012-10-11

5.  Forecasting the future risk of Barmah Forest virus disease under climate change scenarios in Queensland, Australia.

Authors:  Suchithra Naish; Kerrie Mengersen; Wenbiao Hu; Shilu Tong
Journal:  PLoS One       Date:  2013-05-15       Impact factor: 3.240

  5 in total

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