Sherril Phyllis

Consumption of and trade in wild meat could result in infectious pathogen spillover into human populations. Such spillovers could propagate into sustained outbreaks in major cities where human aggregations potentially catalyze their spread. A better understanding of how urban wild meat value chains operate, the health hazards present and their risk assessment could assist in mitigating potential spillovers and outbreak events. We used key informant interviews and literature reviews to understand the structure and operations, actors, their practices, and health risk perceptions along a wild meat value chain supplying a rapidly urbanizing city in Africa, the Nairobi Metropolitan Area (NMA). I also analyzed 27 wild meat samples obtained from the Nairobi Metropolitan Area (NMA), Kenya, for the presence of selected zoonotic pathogens known to cause priority diseases namely E. coli, Brucella spp., Leptospira spp., Coxiella burnetii, Rift valley fever virus and Crimean Congo hemorrhagic fever virus. In addition, we conducted a quantitative microbial risk assessment to estimate the probability that handling and consumption of wild meat by hunters, traders and consumers could lead to exposure to Shiga toxin producing Escherichia coli (STEC) above the minimum infectious dose. Finally, I conducted a systematic literature review of peer-reviewed scientific articles and World Health Organization-Disease Outbreak News (WHO-DONs) to summarize response measures that have been implemented during suspected wild meat-borne outbreaks in Sub-Saharan Africa from 2004 to 2024 and provide an outbreak response framework tailored for the wild meat value chain.

Chapter 2 outlines the value chain structure, its governance, animals targeted, the spatial and temporal characteristics of the value chain as well as the value chain actors’ health risk practices and knowledge. The value chain operates via three main nodes: harvester, trader, and consumer nodes. We found wild meat to be harvested from peri-urban areas of the NMA, consumed or sold locally, or supplied to distant urban markets. Actors reported increased participation along the value chain during the dry season, and over the Christmas period. The value chain operated informally, creating a ‘rules in use’ framework focusing on sanction avoidance, while ignoring food safety concerns. Consequently, respondents reported slaughtering wild animals on the bare ground, handling wild meat with unwashed bare hands and uncleaned utensils. No value chain actors reported wearing personal protective equipment when handling wild meat. At the distant markets’ trader node where wild meat was sold disguised as livestock meat, meat vendors engaged in similar unsafe practices. Actors had limited awareness of the specific health hazards from wild meat.

Based on the reported health hazards faced by actors as outlined in Chapter 2, I report on two zoonotic pathogens in Chapter 3. The prevalence of E. coli ranged from 3.7%-40.7% with EHEC-stx2 (Shiga toxin producing E. coli-2 (STEC-2)) at 40.7% (95% CI: 24.5-59.3%) and EHEC-stx1(Shiga toxin producing E. coli-1 (STEC-1)) at 29.6% (95% CI: 15.9-48.5%). Enteroaggregative E. coli had a prevalence of 3.7% (95% CI: 0.7-18.3%) while ETEC-elt, ETEC-stl and C. burnetii had a prevalence of 7.4% (95% CI: 2.1-23.4 %). The presence of E. coli on the wild meat samples supports the data in Chapter 2 where actors reported enteric illnesses, including bloody diarrhea as some of the illnesses they have experienced in the past following their interaction with wild meat. None of the samples were positive for Brucella spp., Leptospira spp., and the viral pathogens Rift Valley Fever Virus and Crimean Congo Hemorrhagic Fever Virus.

Chapters 2 and 3 thus provided us with compelling evidence of the existence of E.coli as a health hazard along the wild meat value chain in the NMA, guiding our risk assessment. I estimated the probability of hunters and consumers exposure to STEC (both 1 and 2) above the minimum infectious dose at 0.43 (mean= 0.43; 95% CI= 0.24-0.63) and 0.27 (mean= 0.31; 95% CI= 0.08-0.60) respectively, suggesting that all actors risk exposure to wild meat-borne STEC. The probability of consumer exposure to STEC above the infectious dose was estimated at 0.03 (mean= 0.04; 95% CI= 0.009-0.08). Across all the value chain nodes assessed, the risk of exposure was strongly driven by the likelihood of wild meat being STEC positive for hunters, traders and consumers (Spearman’s rank-order correlation coefficient (ρ) = 0.95, 1.0 and 0.89, respectively), compared to other model inputs.

In Chapter 5, I focused on outbreak response as one of the contexts in which our data can be leveraged. We considered 84 disease outbreak events caused by four zoonotic viruses: Ebola (n=32), Marburg (n=11), Lassa (n=19), Mpox (n=20) and one bacterium: Bacillus anthracis (n=2). These events were observed across 24 countries, with the highest outbreaks reported in the Democratic Republic of the Congo (n=20). At the national level, responses involved human surveillance via contact tracing, case management and mitigation of the disease spread through vaccinations, public education on infection prevention and control, and bans on wild meat use, amongst others. National response was supported by the international community. At personal level, communities either adopted, or not, the proposed infection prevention and control measures. They either stopped, reduced or continued harvesting, sale and consumption of wild meat depending on their knowledge of the outbreak, and the directives issued by the health authorities. We proposed a framework for socially responsive response measures tailored to the needs and nature of wild meat value chains in Sub-Saharan Africa.

The main aim of this study was to estimate the risk of exposure of value chain actors to the health hazards along an urban wild meat value chain. We show that these actors indeed face health hazards as they harvest, process, sell and consume wild meat. These risks are further augmented by their unsafe and unhygienic practices while handling wild meat. These actors are thus a potential source of wild meat-borne pathogen spillovers and infectious disease outbreaks within the urban population. The data we provide from this study can be used as evidence against which health policies towards mitigating health risks, such as disease outbreaks, from wild meat can be designed and implemented. Our data is particularly important in preparing for, preventing, responding to and recovering from disease outbreaks from wild meat, a likely source of the next pandemic.