| Literature DB >> 32085721 |
Gabriel Augusto Marques Rossi1, Inge Van Damme2, Sarah Gabriël2.
Abstract
BACKGROUND: Taenia saginata taeniosis/cysticercosis has been well studied in several countries. Brazil is one of the most important beef exporting countries and has one of the highest cattle population size in the world. In this country, bovine cysticercosis (BCC) remains the most frequent reported zoonosis detected during post-mortem inspection, resulting in costs for the beef sector and public health. We performed a systematic literature review regarding data about BCC epidemiology in Brazil and meta-analyses for its prevalence in different administrative regions and the distribution over time, and based on this discussed possible control strategies.Entities:
Keywords: Beef inspection; Bovine cysticercosis; Brazil; Cattle; Spatial distribution; Taenia saginata
Year: 2020 PMID: 32085721 PMCID: PMC7035740 DOI: 10.1186/s13071-020-3971-0
Source DB: PubMed Journal: Parasit Vectors ISSN: 1756-3305 Impact factor: 3.876
Fig. 1Maps showing administrative regions, human and cattle populational characteristics according to the The Brazilian Institute of Geography and Statistics (IBGE) (https://www.ibge.gov.br/). a Brazil is divided into the following states: Acre (AC), Alagoas (AL), Amapá (AP), Amazonas (AM), Bahia (BA), Cerá (CE), Espírito Santo (ES), Goiás (GO), Maranhão (MA), Mato Grosso (MT), Mato Grosso do Sul (MS), Minas Gerais (MG), Pará (PA), Paraíba (PB), Paraná (PR), Pernambuco (PE), Piauí (PI), Rio de Janeiro (RJ), Rio Grande do Norte (RN), Rio Grande do Sul (RS), Rondônia (RO), Roraima (RR), Santa Catarina (SC), São Paulo (SP), Sergipe (SE) and Tocantins (TO), which are divided into five Brazilian regions (Midwest, Northeast, North, Southeast and South). b Human population size estimated for 2018 in 26 states. c Human population density estimated for 2018 in 26 states. d Cattle population size in 2017. The maps were created in Terraview® Software (INPE, São José dos Campos, Brazil, v.4.2.2) (http://www.dpi.inpe.br/terraview)
Fig. 2Prisma flowchart diagram of the record selection process
Bovine cysticercosis high-risk areas within nine Brazilian states
| State | Method | Areas with higher risk | |
|---|---|---|---|
| Bahia | PM inspection | 101 municipalities located at Itapetinga, Litoral Sul, Médio Rio de Contas, Vitória da Conquista and Extremo Sul territories | Bavia et al. [ |
| Espírito Santo | PM inspection | Counties: Ecoporanga, Linhares, Presidente Kennedy and Itapemirim | Avelar et al. [ |
| Goiás | PM inspection | The Central mesoregion was considered as the one with the highest prevalence and the microregions of Goiânia, Anápolis, Pires do Rio, Vale do Rio dos Bois, Meia Ponte e Anicuns (OR > 5) | Aquino et al. [ |
| São Paulo | PM inspection | Highest prevalence in regions Central, Ribeirão Preto and Presidente Prudente; higher probability of finding infected animals in regions of Araçatuba, Barretos, Bauru, Franca and Sorocaba | Ferreira et al. [ |
| PM inspection | Higher risk in the administrative regions São José do Rio Preto and Campinas | Rossi et al. [ | |
| Paraná | PM inspection | Municipalities of Campo Largo, Capanema, Rosário do Ivaí, Japira, Joaquim Távora, Laranjeiras do Sul, Rio Bonito do Iguaçu, Palmas, Saudades do Iguaçu and Antônio Olinto | Souza et al. [ |
| PM inspection | Higher prevalence in nucleus of Curitiba, Francisco Beltrão and Irati; higher OR in nucleus of União da Vitória, Francisco Beltrão and Irati | Guimarães-Peixoto et al. [ | |
| Mato Grosso | PM inspection | Highest OR in the administrative regions Sinop, Barra do Garças, Água Boa, Cáceres, Barra do Bugres, Cuiabá, Pontes Lacerda, Rondonópolis, Matupa, São Félix do Araguaia and Lucas do Rio Verde | Rossi et al. [ |
| Mato Grosso do Sul | PM inspection | Higher risk in the administrative regions Amambai, Navirai, Nova Andradina, Dourados, Três Lagoas, Campo Grande, Ponta Porã, Costa Rica, Aquidauana and Coxim | Pereira et al. [ |
| PM inspection | Municipalities of Dourados and Santa Rita do Rio Pardo | Concenço et al. [ | |
| Paraíba | ELISA and immunoblot | Higher prevalence in animals in Borborema, Agreste/Zona da Mata and Sertão | Maia et al. [ |
| Rondônia | PM inspection | Higher risk in the administrative regions Porto Velho, Guajará-Mirim, Colorado D’Oeste, Cacoal, Ji-Paraná | Alves et al. [ |
Variables associated with risk factors for bovine cysticercosis according to 13 studies performed in Brazil
| Variable | Area | Methodology | Reference |
|---|---|---|---|
| Raising animals in regions where coffee, orange and sugarcane are harvested | São Paulo State | Cluster analysis of selected variables and prevalence in municipalities based on | Rossi et al. [ |
| Access of cattle to non-controlled water sources and sport fishing activities near the farms | States of São Paulo, Minas Gerais, Mato Grosso and Mato Grosso do Sul | Case–control study in farms based on | Rossi et al. [ |
| Animal purchasing and presence of flooded pastures | Paraíba State | Logistic regression of results obtained for herd-level using serological analyses | Maia et al. [ |
| Raising animals in regions with large human population | Mato Grosso State | Logistic regression of selected variables and prevalence in municipalities based on | Rossi et al. [ |
| Ingestion of undercooked beef by humans and occurrence bovine cysticercosis in animals | São João do Evangelista, Minas Gerais | Association analysis between results from cattle serological analyses and questionnaire completed by humans in sampled farms | Garro et al. [ |
| Salinas, Minas Gerais | Magalhães et al. [ | ||
| Expertise of those responsible for the farm, the family income and water quality | Triangulo Mineiro, Minas Gerais | Logistic regression of results from cattle serological analyses and questionnaire completed by humans in sampled farms | Duarte et al. [ |
| Raising animals in areas with high educational human development index or where sugarcane and coffee are harvested | São Paulo State | Maps | Ferreira et al. [ |
| Raising animals in regions with large human population and rainfall index (positive correlation) and large size of cattle population in municipalities (negative correlation) | Mato Grosso do Sul State | Correlation analysis of selected variables and prevalence in municipalities based on | Pereira et al. [ |
| Bovine meat for human consumption acquired in the city and farm | Viçosa country, Minas Gerais | Logistic regression of results from cattle serological analyses and questionnaire completed by humans in sampled farms | Santos et al. [ |
| Farm size greater than 301 hectares | Colatina, Espírito Santo | Case–control study in farms | Acevedo-Nieto et al. [ |
| Interference of the rivers and their tributaries that fed the municipalities | Triangulo Mineiro, Minas Gerais, | Risk analysis along with mapping and spatial analysis of data | Duarte et al. [ |
| Raising animals in regions with large human population, percentage or urban houses and rural areas with inappropriate sewage system | Rondônia | Correlation analysis of selected variables and prevalence in municipalities based on | Alves et al. [ |
Fig. 3Forest tree of 40 studies reporting BCC prevalence in Brazil, grouped per administrative region (North, Northeast, Central-Western, Southeast and South)
Fig. 4Time distribution of BCC prevalence in five Brazilian states where most data regarding BCC were available (Goiás, Mato Grosso, Mato Grosso do Sul, Minas Gerais and São Paulo) from 2007 to 2015. The points represent the observed data and the lines are the predicted probabilities. Data are from Dutra et al. [26] and Rossi et al. [11]
Fig. 5Recommended measures for T. saginata cysticercosis/taeniosis control