Epidemiological analyses of cattle carcasses affected by cysticercosis and hydatidosis in the State of Rio Grande do Sul from 2014 to 2018

Autor: Arina Cauaneque, Eduardo De Freitas Costa, Daniela Lopes de Azevedo, Mauro Riegert Borba, Luis Gustavo Corbellini
Rok vydání: 2022
Předmět:
Zdroj: Pesquisa Veterinária Brasileira, Volume: 42, Article number: e06805, Published: 29 APR 2022
Pesquisa Veterinária Brasileira v.42 2022
Pesquisa Veterinária Brasileira
Colégio Brasileiro de Patologia Animal (CBPA)
instacron:EMBRAPA
Repositório Institucional da UFRGS
Universidade Federal do Rio Grande do Sul (UFRGS)
instacron:UFRGS
ISSN: 1678-5150
0100-736X
DOI: 10.1590/1678-5150-pvb-6805
Popis: Bovine cysticercosis and hydatidosis are frequently identified by inspectors in slaughterhouses from the state of Rio Grande do Sul. Slaughterhouse records can provide valuable information for animal-related diseases and public health surveillance. Analyzing these data can aid set priorities to regions or properties that need more attention. Slaughter condemnation data is collected daily and stored in the Agricultural Defense System (SDA) database of the State Veterinary Services. However, it needs to be turned into useful information in bovine cysticercosis and hydatidosis surveillance programs. This study aimed to discuss how the analysis of condemnation data in the context of epidemiology can be useful for a surveillance system of bovine cysticercosis and hydatidosis. For this purpose, slaughter data of 5,137,870 cattle from 480,000 animal movement permits (GTA) from 97,891 farms from 2014 to 2018 were obtained from the Secretary of Agriculture, Livestock and Rural Development of the State of Rio Grande do Sul (SEAPDR-RS). Differences in the occurrence rates of bovine cysticercosis and hydatidosis among mesoregions over time were assessed through generalized linear models. Cysticercosis was identified in 65,379 (1.27%) carcasses and hydatidosis in 323,395 (6.29%). The occurrence rates of both diseases varied distinctly over time between the regions (p
Databáze: OpenAIRE
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