Fasciola hepatica infection in cattle and the use of simulation models for endemic areas.

Fasciolosis is a food-borne disease that causes great distress to a range of hosts, including humans. The objectives of this study were to (1) evaluate the liver damage and carcass weight of cattle naturally infected with Fasciola hepatica from the state of Rio Grande do Sul (RS), Brazil, and to (2) determine the distribution of adult flukes in 12,236 cattle liver from RS. The data from these experiments were used to calculate the overall economic loss due to F. hepatica infection. Eighteen adult Polled Hereford cows were divided into a triclabendazole (TbG) and a F. hepatica-positive group (FhG). For Experiment 1, a generalized linear mixed model revealed a statistical difference in carcass weight (49.8 kg) between TbG and FhG. The Monte Carlo analysis also revealed that the animals' weight differences were due to the disease. For Experiment 2, the prevalence of infected livers was above 16% (1904/12,236), mostly (20.1%) from the south-west region of RS. The Susceptible-infected-recovered (SIR) epidemic model revealed the evolution of the infection using a high infectivity and low recovery rate. Other distinctive scenarios that occur in RS were also established with different rates of infectivity. The economic assessment showed a potential loss of US$45 million to the beef cattle industry of RS, with an overall State cost of US$90.3 million. These novel findings reveal the importance of fasciolosis infection, which can cause a significant health condition and poor animal welfare.

Modelling the spatial distribution of Fasciola hepatica in bovines using decision tree, logistic regression and GIS query approaches for Brazil.

Fascioliasis is a condition caused by the trematode Fasciola hepatica. In this paper, the spatial distribution of F. hepatica in bovines in Brazil was modelled using a decision tree approach and a logistic regression, combined with a geographic information system (GIS) query. In the decision tree and the logistic model, isothermality had the strongest influence on disease prevalence. Also, the 50-year average precipitation in the warmest quarter of the year was included as a risk factor, having a negative influence on the parasite prevalence. The risk maps developed using both techniques, showed a predicted higher prevalence mainly in the South of Brazil. The prediction performance seemed to be high, but both techniques failed to reach a high accuracy in predicting the medium and high prevalence classes to the entire country. The GIS query map, based on the range of isothermality, minimum temperature of coldest month, precipitation of warmest quarter of the year, altitude and the average dailyland surface temperature, showed a possibility of presence of F. hepatica in a very large area. The risk maps produced using these methods can be used to focus activities of animal and public health programmes, even on non-evaluated F. hepatica areas.