Forecast of Barmah Forest Virus (BFV) disease setting rainfall constant

We obtained data on notified 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 predictive model had good model accuracy, sensitivity and specificity. Maps on potential risk of future BFV disease indicated that disease would vary significantly across coastal regions in Queensland by 2100 due to marked differences in future rainfall and temperature projections.

The mao figures show (a) Geographical distribution of BFV disease under current climatic conditions for Queensland entire coastal regions, (b) forecast of potential probabilities of risk of BFV disease under climate change scenarios setting rainfall constant for 2025, (c) 2050 and (d) 2100.