Forecast of Barmah Forest Virus disease in relation to variations of temperature and rainfall

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Data was obtained on notified Barmah Forest Virus (BFV) cases, climate (maximum and minimum temperature and rainfall), socio-economic and tidal conditions for current period 2000–2008 for coastal regions in Queensland. Grid-data on future climate projections for 2025, 2050 and 2100 were also obtained. Logistic regression models were built to forecast the potential risk of BFV disease distribution under existing climatic, socio-economic and tidal conditions. The model was applied to estimate the potential geographic distribution of BFV outbreaks under climate change scenarios. The figure shows: (a) Geographical distribution of BFV disease under current climatic conditions for Queensland's entire coastal regions, (b) forecast of potential probabilities of risk of BFV disease under climate change scenarios for 2025, (c) 2050 and (d) 2100.

Location of data collection

kmlPolyCoords

153.552920,-9.929730 137.994575,-9.929730 137.994575,-29.178588 153.552920,-29.178588 153.552920,-9.929730

Publications

Naish, Suchithra, Mengersen, Kerrie, Hu, Wenbiao, & Tong, Shilu (2013) Forecasting the future risk of Barmah Forest Virus disease under climate change scenarios in Queensland, Australia. PLoS ONE, 8(5), e62843. http://eprints.qut.edu.au/67158/

Research areas

Zoonoses

Population biology

Population modeling

rainfall

Barmah Forest Virus

Infectious disease epidemiology

Infectious disease modeling

Public health

Epidemiology

Infectious diseases

Ecology

Computational biology

BFV

Cite this collection

Naish, Suchithra; Mengersen, Kerrie; Hu, Wenbiao; Tong, Shilu (2013): Forecast of BFV disease setting minimum temperature and rainfall varies. Figure_3.tif. PLOS ONE.