Brucellosis is an important zoonotic disease worldwide and it affects the health of animals, human and the livestock incomes negatively. Although it is an animal illness, it infects human by contact with infected animals or consuming contaminated milk or milk products. Modeling studies established to obtain seroprevalance of a disease is important in order to determine statistics and measuring strategies for this disease. Although fieldworks can represent data for a disease in a specific region, forming a model suits with associated fieldworks can offer a global strategy for it and this model can be used anywhere else. In this study, a model which is based on fuzzy logic and predicts seroprevalance of brucellosis in a specific localization is formed. In this model, fuzzy logic based prediction method for brucellosis seroprevalance is used for the first time. This model is used for determining brucellosis seroprevalance in sheep and goats in DiyarbakÄ±r and Van regions. Also, the results of the model show good fit with the data obtained in the regional studies, done in the same regions.
Key words: Brucellosis, seroprevalance, fuzzy logic.
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