Abstract
The transmission of African swine fever (ASF) could be influenced by temperature and rainfall, particularly through the transmission of wild boars. Australia's ASF risk assessment capabilities can be further enhanced by analyzing the impact of temperature and precipitation on ASF. As there are currently no cases of ASF in Australia, this study utilized Poland's ASF-wild boar cases between 2018 and 2021 to establish a risk assessment model for Australia. Two methods were adopted to model the risk by analyzing the correlation between the number of ASF-wild boar cases, and the temperature and rainfall. The two methods used were linear regression and fuzzy inference systems. The aim is to develop a risk assessment analysis that can estimate the seasonal risk of ASF in Australia. The results from the two models showed that there is a significant relationship between the number of cases and the changes in the temperature, but has shown no prominent association with the amount of rainfall. To the best of our knowledge, this is the first model that conducts a seasonal assessment of ASF risk in Australia. The proposed technique used in modelling the Australia’s risk assessment is leading and can handle the incompleteness of data, making this a novel approach that can be used to build models for other countries or regions and also for different infectious diseases.