Modelagem de fatores de risco de febre aftosa através do sistema de notificações de doenças vesiculares no Brasil

Detalhes bibliográficos
Ano de defesa: 2019
Autor(a) principal: MIRANDA, Edyniesky Ferrer lattes
Orientador(a): SANTORO, Kleber Régis
Banca de defesa: CRISTINO, Cláudio Tadeu, DUARTE NETO, Paulo José, RAMOS, Rafael Antonio do Nascimento, CASTELLETTI, Carlos Henrique Madeiros
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal Rural de Pernambuco
Programa de Pós-Graduação: Programa de Pós-Graduação em Biometria e Estatística Aplicada
Departamento: Departamento de Estatística e Informática
País: Brasil
Palavras-chave em Português:
Área do conhecimento CNPq:
Link de acesso: http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/8156
Resumo: Foot-and-mouth disease (FMD) is the most contagious disease of mammals and has great potential to cause severe economic losses in split-hoofed animals. In disease management, decisions often must be made in a context of uncertainty. However, epidemiological models can be a powerful tool to aid the development of animal health policies and preventive disease control. The work aimed to find priority regions for vesicular disease surveillance in Brazil. The work was conducted using data from the Continental Information and Surveillance System (SivCont) for Brazil. The data refer to Vesicular Syndromes, collecting information on FMD and Vesicular Stomatitis (VS), as well as other diseases with symptoms compatible with vesicular syndromes of diverse infectious and noninfectious sources. It is also essential to consider the timeliness involved in surveillance programs, which can demonstrate the dynamics and interaction of the activities carried out. Also, the risk-based requirements of the FMD surveillance system were assessed. For the different analyses, various techniques were implemented such as GLM, data mining and Bayesian network analysis. On the other hand, the results of chapter 3 revealed delays in the timeliness of each state, the different classifications of diseases and especially in conditions with symptoms equal to FMD. Also, it even showed that there is a large variation in the timeliness of the FMD surveillance system when the Brazilian states were compared. It was also observed in chapter 4 that diseases with symptoms like FMD are the most notified events, and occur with more frequency in SC and PR. Besides this, the states of MG, PA, MS, RO and GO are identified as being more likely to have positive FMD diagnosis and more delayed in notifying. All results obtained in this research will allow decision-makers in the official veterinary services to strengthen surveillance measures in states with extreme timeliness values. Thus, reinforces the FMD surveillance system, which supports the surveillance programs.