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The model assesses the probabilities of two kinds of events which must take place before an outbreak can occur: (1) introduction of the virus and mosquito vectors to places where human population densities are high; and (2) vector population growth rates as influenced by climatic factors. The results showed that if either<jats:italic>Aedes aegypti<\/jats:italic>or<jats:italic>Ae. albopictus<\/jats:italic>were to become established in WA, three centres in the northern part of the State (Kununurra, Fitzroy Crossing, Broome) would be at particular risk of experiencing an outbreak. The model can also be readily extended to predict the risk of introduction of other viruses carried by<jats:italic>Aedes<\/jats:italic>mosquitoes, such as yellow fever, chikungunya and Zika viruses.<\/jats:p>","DOI":"10.1017\/s0950268816002090","type":"journal-article","created":{"date-parts":[[2016,9,13]],"date-time":"2016-09-13T09:30:10Z","timestamp":1473759010000},"page":"54-66","update-policy":"http:\/\/dx.doi.org\/10.1017\/policypage","source":"Crossref","is-referenced-by-count":10,"title":["Predicting arboviral disease emergence using Bayesian networks: a case study of dengue virus in Western Australia"],"prefix":"10.1017","volume":"145","author":[{"given":"S. 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