Spatial analysis of the bovine tuberculosis and animal movement network in the state of Espírito Santo, Brazil

• Ano de defesa: 2019
• Autor(a) principal: Galvis, Jason Onell Ardila
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
• Palavras-chave em Português: Análise de redes; Análise espacial; Dairy farms; Fazendas de leite; Livestock; Network analysis; Pecuária; Spatial analysis; Zoonoses; Zoonotic
• Link de acesso: https://www.teses.usp.br/teses/disponiveis/10/10134/tde-09012020-120114/

Brazil is one of the countries that has the strongest bovine production worldwide, with 2.5 thousand million farms and 178 thousand million bovines distributed in its national territory. The number of farms and animals in the country present a major challenge to animal disease control since have high surveillance coverage in this scenario is expensive and inefficient process. Therefore, it is necessary to identify and focus the resources on groups of farms with an increased risk of infection and which strongly contribute to disseminate a disease widely in the national territory. The main objective of the present study is to provide information and tools which may help decision makers to build efficient animal disease control programs. In general, in the present study we focused on the surveillance of bovine tuberculosis (bTB) and used the state of Espírito Santo (ES) in southeast Brazil to apply our methodologies. We divided this study into four sections: (1) provide information on the situation of bTB in ES and farms characteristics associated with this infectious disease; (2) complement the previous study with the identification of risk factors associated with the characteristic of animal transit and the distribution of cases of the disease that were reported in ES; (3) describe the characteristic of the cattle transit in ES and propose a methodology fir targeted surveillance of farms based on the structure of the trade network; (4) develop a methodology to predict farm locations based on the spatial information of trade partners. In conclusion, this study provided information and tools which can help to the decision makers to complement animal disease surveillance programs in ES and Brazil.