Global Epidemiology and Spatial Distribution of Toxoplasma Gondii in Goats: Protocol for a Systematic Review and Bayesian Hierarchical Meta-Analysis Publisher Pubmed



Amouei A^{1, 2} ; Mizani A³ ; Hanafibojd AA⁴ ; Jafarikoshki T⁵ ; Sarvi S^{1, 6} ; Aghayan SA⁷ ; Amuei F⁸ ; Chegeni TN^{1, 6} ; Daryani A^{1, 6} Show Affiliations
Source: PLoS ONE Published:2023

Abstract

Background Toxoplasma gondii, a cosmopolitan protozoan parasite causes toxoplasmosis in humans and many species of domestic and wild animals. T. gondii instigates significant economic losses in sheep and goat farming industry and can lead to abortion, stillbirth, congenital malformations and neonatal losses. The objective of this protocol is to evaluate worldwide seroprevalence of T. gondii exposure in goats using Bayesian hierarchical meta-analysis and geographic information system (GIS). Methods A comprehensive literature search will be conducted using search engines, including Web of Science, ScienceDirect, Scopus, PubMed, ProQuest, EMBASE, PROSPERO Register and, Google Scholar without date and language restrictions. The authors search for cross-sectional studies that determine the seroprevalence of T. gondii in goats. Two reviewers will independently screen, selected studies; also, they will extract data, and assess the risk of bias. In case(s) of disagreement, a consensus will be reached with the help of a third author. The Bayesian hierarchical meta-analysis will use to estimate country and worldwide true seroprevalence of T. gondii, which is consist of the sensitivity and specificity of the applied serological assays. The obtained data will be used to identify country-level risk factors associated with T. gondii exposure using GIS in the ArcGIS software. Discussion The systematic review produced from this protocol will provide the true prevalence rate and spatial distribution T. gondii exposure in goats both regionally and globally using Bayesian hierarchical and GIS analysis. Copyright: © 2023 Amouei et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.