Systematic review of health risk assessment in Africa’s bushmeat trade: Are there any risks assessed?

Abstract

BACKGROUND: The bushmeat trade in tropical Africa represents a major route for zoonotic disease emergence. Yet, the extent to which health risks have been quantitatively assessed remains unclear. Therefore, our study aimed at systematically reviewing health risk assessments conducted in the African bushmeat trade, and identifying methodological patterns and research gaps. METHODOLOGY/PRINCIPAL FINDINGS: Following PRISMA guidelines, we searched Web of Science and Google Scholar (to November 2024) using multilingual Boolean queries. Eligible studies included any research assessing health, zoonotic, or food-borne risks in bushmeat value chains across Africa. Two co-authors independently cross-validated c. 23% of extracted data. Descriptive statistics and generalized linear models were used to explore publication patterns and predictors of research output. From 449 records finally identified, 129 met inclusion criteria. Ethnobiological and public health surveillance approaches dominated (41.1% each), while epidemiological studies were scarce. Most publications appeared after 2017, mainly from Cameroon, Nigeria, and the Democratic Republic of Congo, with epidemic occurrence significantly predicting national research output. Interviews were the most frequent method (44.8%), while pathogen detection occurred in 40.3% of studies, identifying 66 confirmed human pathogens (23 viruses, 19 bacteria, 24 parasites). More than 88% of studies did not report survey effort, and none implemented a formal quantitative health risk assessment. CONCLUSIONS/SIGNIFICANCE: Quantitative health risk assessment in the African bushmeat trade remains unattainable due to scarce data on pathogen prevalence, exposure, and host-pathogen interactions. Only formal recognition and state-regulated management of the trade-incorporating molecular surveillance, host-pathogen ecological data, and supply-chain mapping within a One Health framework-will enable reliable risk quantification.