Philippe Gaubert

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 supply 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.

Pangolins have become emblematic of the global wildlife trade crisis due to intense trafficking for consumption and traditional medicine. Coupled with habitat loss, the illicit trade in pangolins has severely threatened wild populations. Genetic identification of distinct pangolin populations is an imperative step toward guiding effective and informed conservation management. These populations can serve as a reference for assigning seized individuals to their geographic origins, and thus tracing trafficking networks. However, pangolin population genetics studies have been hindered by limited sampling of geo-referenced individuals, largely due to the species’ elusive nature. To address this, we developed a tailored gene-capture approach targeting 671 loci totaling 627 kb with high evolutionary and adaptive value across all eight pangolin species. We optimized the approach for low-quality DNA, including samples from museum collections and wildlife trade, such as bushmeat and scale seizures. We reassessed range-wide population delineations for the three most traded species, the white-bellied ( Phataginus tricuspis ), Sunda ( Manis javanica ), and Chinese ( M. pentadactyla ) pangolins, highlighting the need for biogeographically consistent lineage nomenclature and spatially aware analyses to support coherent conservation planning. The unprecedented geo-referenced DNA database for the three species yielded snapshot insights into pangolin trafficking hotspots and trade dynamics of both domestic markets and global trade seizures, the former providing novel insights into bushmeat trade. Domestic trade reflects local and occasional cross-border sourcing, averaging 454 km across the three species, while international trafficking seizures in mostly scales point to broader, regional procurement. However, common sourcing regions between the two trade market types indicate their interconnectivity, suggesting that local trade may contribute to international trade supply. Our study identified significant international trade hotspots for the white-bellied, Sunda, and Chinese pangolins, centered around southwestern Cameroon, southwestern Borneo Island, and Myanmar, respectively. Addressing geo-referenced sampling gaps and increasing local-to-global seizure data over time may offer deeper spatiotemporal insights into pangolin trade dynamics. Our study design may serve as a replicable model for enabling authorities and practitioners to implement intelligence-driven, geographically targeted interventions, by identifying the key regions most implicated in pangolin trafficking.

The giant forest hog (GFH, Hylochoerus meinertzhageni ), the largest and most elusive wild pig, is found in a disjunct range across equatorial Africa, primarily inhabiting forests and woodlands. It is the only remaining African suid species without whole-genome data. The GFH is currently classified into three subspecies, differing in skull morphology and size. Here, we present the first whole-genome data of nine GFHs; one from Guinea and eight Uganda, representing the two geographically most distant subspecies. This genomic evidence allowed us to resolve the previously uncertain placement of the GFH among African suids as a sister group to the warthogs ( Phacochoerus spp.). Also, we found a deep evolutionary split between the two GFH populations resulting in a level of genetic differentiation ( F _ST > 0.75), which is similar to or higher than values observed among species of African wild pigs. The GFH likely diverged from warthogs around 4.6 Mya while the two study populations of GFH diverged at least 0.5 Mya and, subsequently, experienced very dissimilar demographic trajectories. The individual from Guinea had half of the heterozygosity level of the Uganda population, and lower value compared to all the African suids, probably as a result of the long term low N _e and isolation. Due to the close affinity of GFH with the African rainforest biotic zone, our findings have implications for understanding the history of habitat change in Africa. They also indicate a very deep and previously underappreciated evolutionary divergence within the GFH that may have implications for its conservation.

The bushmeat trade in Africa is a largely unregulated activity that drives the unsustainable exploitation of wild terrestrial vertebrates—an issue often coined the bushmeat crisis. We build on a four-gene mitochondrial DNA-typing approach to develop an unprecedented reference database framework for effectively tracing the bushmeat trade in tropical Africa. Our dataset comprises over 2,500 samples collected over a 13-yr period across 10 African countries and two European airports. Relying on an expert analytical pipeline and ∼8,700 nucleotide sequences, we identified 96% of samples to the species-level. In contrast, we estimated that conventional two-gene approaches would have yielded 18–26% erroneous or inconclusive taxonomic assignments. DNA-typing refined > 50% of field identifications, with refinement reaching 92-95% for highly processed carcasses seized in Europe. Leveraging expanded taxonomic representation, we empirically refined the genetic species thresholds applied to bushmeat and provide a reproducible pipeline for using our expert reference database from NCBI. Overall, we identified 133 species—mostly mammals—with one-third listed as of conservation concern, and uncovered cryptic diversity evidence within several taxa. Our results also demonstrated the value of community ecology indexes for large-scale monitoring of the bushmeat trade. While national markets generally mirrored regional biodiversity patterns across tropical Africa, Benin emerged as a notable outlier and a key wildlife trade hotspot. We advocate for the integration of community ecology frameworks into surveillance efforts to guide more effective, regionally tailored mitigation strategies. Continued, standardized sampling is essential to broaden taxonomic coverage and enhance detection of cryptic biodiversity in genetic bushmeat monitoring.