Application of Climate Envelope Model in the Control of Fasciola gigantica Prevalence in Nigeria

Abstract

: Mapping the potential areas for pathogen prevalence is a repetitive process and this research is an initial attempt to model the nation-wide prevalence of Fasciola gigantica in Nigeria. Data on Fasciola gigantica occurrence localities were obtained from published literature together with bioclimatic variables, the climate envelope model (MaxEnt) was utilized to analyze and predict its spatial range and to create suitable areas for Fasciola gigantica prevalence in Nigeria. The results show that the predicted areas of high risk included parts of northwestern Nigeria in Sokoto, Kebbi, Katsina, and some patches of Kano State. Likewise, Bauchi, Gombe, Borno, and large portions of Plateau State. Other areas of high risk as indicated by the model included Ekiti, Ogun, and Lagos State in the southwest. Similarly, infection risks covered the southeastern Nigeria in some parts of Rivers, Akwa Ibom and Cross rivers. The three most important variables with the highest training gain as revealed by the model are isothermality, minimum temperature of the coldest month, and precipitation seasonality. The performance of the MaxEnt model was better than a random prediction with training AUC scores of 0.891. This shows that MaxEnt is a suitable modelling technique for predicting the spatial range of fascioliasis prevalence in Nigeria based on its very good predictive accuracy.