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Toxoplasma gondii in domiciled dogs and cats in urban areas of Brazil: risk factors and spatial distribution.

Igor Falco ArrudaPatricia Riddell MillarAlynne da Silva BarbosaLuiz Claudio de Souza AbboudIzabel Cristina Dos ReisAlex Sander da Cruz MoreiraMariana Pedrosa de Paula GuimarãesMaria Regina Reis Amendoeira
Published in: Parasite (Paris, France) (2021)
Toxoplasma gondii is a highly prevalent zoonotic parasite in Brazil capable of infecting mammals and birds. The increase in the urban populations of pets and the narrowing of the human-animal relationship can facilitate the transmission of important public health zoonoses, such as toxoplasmosis. This study aimed to evaluate the frequency and spatial distribution of T. gondii infection and its risk factors in domiciled dogs and cats attended at the Jorge Vaitsman Institute, Rio de Janeiro. Serum samples from 400 dogs and 272 cats were evaluated by an indirect fluorescent antibody test (IFAT) for IgG anti-T. gondii antibodies. Epidemiological questionnaires were used to interview the animals' owners to identify risk factors for infection. Of the total, 34% (136/400) of dogs and 8.1% (22/272) of cats had anti-T. gondii antibodies. Breed (OR: 2.10-95%, CI 1.27-3.46) was a risk factor for dogs, while sex (OR: 3.40-95%, CI 1.10-10.52) and homemade food consumption (OR: 8.49-95%, CI 2.48-29.05) were risk factors for cats. Offal consumption was considered a risk factor for both species evaluated (OR: 2.74-95%, CI 1.38-5.43 for dogs; OR: 7.66-95%, CI 1.24-47.29 for cats). The spatial analysis showed that T. gondii seropositive animals were widely distributed in the metropolitan region of Rio de Janeiro state, with a concentration observed mainly in the west and north zones of Rio de Janeiro city. The results emphasize the importance of adopting prophylactic measures to control T. gondii transmission in domiciled dogs and cats in Rio de Janeiro, contributing positively to public health.
Keyphrases
  • toxoplasma gondii
  • public health
  • risk factors
  • endothelial cells
  • genetic diversity
  • neural network