Assessing the risk of bovine fasciolosis using linear regression analysis for the state of Rio Grande do Sul, Brazil

• The most important variable for the model was the Positivity Index for the previous year.
• The model demonstrated the importance of including other years (time-based effect).
• This model may be used to determine F. hepatica prevalence in other places and situations in the world.
• The generated data is important for epidemiological and parasite control studies.
• This multiple linear regression tool shall be used for governmental and animal health policies.

Fasciola hepatica is the causative agent of fasciolosis, a disease that triggers a chronic inflammatory process in the liver affecting mainly ruminants and other animals including humans. In Brazil, F. hepatica occurs in larger numbers in the most Southern state of Rio Grande do Sul. The objective of this study was to estimate areas at risk using an eight-year (2002–2010) time series of climatic and environmental variables that best relate to the disease using a linear regression method to municipalities in the state of Rio Grande do Sul. The positivity index of the disease, which is the rate of infected animal per slaughtered animal, was divided into three risk classes: low, medium and high. The accuracy of the known sample classification on the confusion matrix for the low, medium and high rates produced by the estimated model presented values between 39 and 88% depending of the year. The regression analysis showed the importance of the time-based data for the construction of the model, considering the two variables of the previous year of the event (positivity index and maximum temperature). The generated data is important for epidemiological and parasite control studies mainly because F. hepatica is an infection that can last from months to years.