Integration of animal health and public health surveillance sources to exhaustively inform the risk of zoonosis: An application to echinococcosis in Rio Negro, Argentina.
PLoS Negl Trop Dis
; 14(8): e0008545, 2020 08.
Article
en En
| MEDLINE
| ID: mdl-32841252
ABSTRACT
The analysis of zoonotic disease risk requires the consideration of both human and animal geo-referenced disease incidence data. Here we show an application of joint Bayesian analyses to the study of echinococcosis granulosus (EG) in the province of Rio Negro, Argentina. We focus on merging passive and active surveillance data sources of animal and human EG cases using joint Bayesian spatial and spatio-temporal models. While similar spatial clustering and temporal trending was apparent, there appears to be limited lagged dependence between animal and human outcomes. Beyond the data quality issues relating to missingness at different times, we were able to identify relations between dog and human data and the highest 'at risk' areas for echinococcosis within the province.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Zoonosis
/
Enfermedades de los Perros
/
Equinococosis
/
Vigilancia en Salud Pública
Tipo de estudio:
Etiology_studies
/
Prognostic_studies
/
Risk_factors_studies
/
Screening_studies
Límite:
Adolescent
/
Animals
/
Child
/
Humans
País/Región como asunto:
America do sul
/
Argentina
Idioma:
En
Revista:
PLoS Negl Trop Dis
Asunto de la revista:
MEDICINA TROPICAL
Año:
2020
Tipo del documento:
Article
País de afiliación:
Estados Unidos