2019-08-29T10:34:47 n5477

Forecast of Barmah Forest Virus (BFV) disease setting minimum temperature constant

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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 otential 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 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 minimum temperature constant for 2025, (c) 2050 and (d) 2100.

Geographical area of data collection

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


Naish S, Mengersen K, Hu W, Tong S (2013) Forecasting the Future Risk of Barmah Forest Virus Disease under Climate Change Scenarios in Queensland, Australia. PLoS ONE 8(5): e62843. http://dx.doi.org/doi:10.1371/journal.pone.0062843

Research areas

Computational biology
Public health
Infectious diseases
Population modelling
Infectious disease epidemiology
Population biology
Infectious disease modelling
Barmah Forest virus

Cite this collection

Naish, Sue; Mengersen, Kerrie; Tong, Shilu; Hu, Wenbiao (2015): Forecast of Barmah Forest Virus (BFV) disease setting minimum temperature constant. Queensland University of Technology. (Dataset) https://doi.org/10.4225/09/585c7f5a3a927

Data file types

.tif, figshare


Creative Commons Attribution 4.0 (CC-BY)


© 2013, Naish et al.

Dates of data collection

From 2000 to 2008


Has association with
Kerrie Mengersen  (Researcher)
Shilu Tong  (Researcher)
Sue Naish  (Researcher)
Wenbiao Hu  (Researcher)


Name: Dr Sue Naish


Date record created:
Date record modified:
Record status:
Published - Open Access