Wild Meat Consumption in the Wake of COVID-19: Shifts in Attitudes and Trade Dynamics in Ghana

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Framed within the Health Belief Model and utilizing a mixed-methods approach, the paper combines survey data from 255 consumers with insights from 10 in-depth interviews with traders operating across five major markets in Accra. Findings reveal that the wild meat value chain – comprising hunters, transporters, traders, and consumers – experienced significant disruption due to pandemic-related fears and mobility restrictions, leading to a marked decline in demand. This downturn had profound socio-economic consequences, particularly for women who dominate retail-level trading, resulting in income loss and business closures. In response, many traders adopted coping strategies such as relying on personal savings and psychological resilience. The paper underscores the urgent need for targeted government support, including financial assistance and investment in basic market infrastructure, to enable a more equitable and resilient recovery of the sector. These observations have broader implications for public health messaging, conservation policy, and gender-sensitive economic planning in post-pandemic contexts. Wildlife meat trade Health belief model COVID-19 pandemic Socio-economic dynamics Gender Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Wildlife meat–commonly referred to as bushmeat–refers to the hunting and consumption of wild animals for food. Across many African countries, including Ghana, it plays a critical role in local food security, cultural traditions, and informal economic livelihoods. Wildlife meat is not only consumed for subsistence but is also embedded in a broader commercial network that links rural producers with urban consumers. This value chain typically includes hunters, transporters, traders, market vendors, and final consumers (Vitekere et al., 2021 ). Driven by growing urban demand, the trade has become increasingly commercialized, particularly in fast-growing cities like Accra (Schulte-Herbruggen, 2012 ). However, the consumption and trade of wildlife meat also pose significant health risks due to the potential for zoonotic disease transmission–including viruses such as Ebola, HIV, and more recently, COVID-19 (Leroy et al., 2004; Van Heuverswyn & Peeters, 2007; Kamogne-Tagne et al., 2022). The COVID-19 pandemic, which emerged in late 2019, had profound socio-economic consequences and health vulnerabilities globally (Blay et al., 2023 ; Fagbamigbe et al., 2022). In Ghana, as in many countries, public health responses–including lockdowns and restrictions on movement–had severe repercussions on the informal sector, where a majority of the population, particularly women, earn their livelihoods (Anoko et al., 2020 ; Mosi et al., 2021). Informal traders involved in wildlife meat markets were among those most acutely impacted by these restrictions. In addition to logistical disruptions, traders also faced a sharp decline in consumer demand, driven by fears of zoonotic transmission (Nasution et al., 2021 ; Wenham et al., 2020 ). Such fears are not unprecedented. During the 2014 Ebola outbreak, similar declines in wildlife meat consumption were recorded in Ghana and other West African countries (Kuukyi et al., 2014 ; Sainge et al., 2023 ). These dynamics underscore how health crises can rapidly reshape consumption patterns. Consumer perceptions of safety often shift in response to public health messaging and perceived disease threats, as documented during earlier outbreaks (Liu et al., 2013 ). Despite this, most research on wildlife meat has historically focused on supply-side concerns–such as hunting practices, regulation, and biodiversity loss–while consumer behavior and the socio-economic vulnerabilities of traders during disease outbreaks have received limited scholarly attention (Damania et al., 2005 ; Ripple et al., 2016 ). The intersection of gender, informal livelihoods, and pandemic-induced consumption shifts remains particularly underexplored (Wenham et al., 2020 ). This study addresses that gap by examining how attitudes toward wildlife meat consumption changed before, during, and after the COVID-19 pandemic in Ghana, and how these shifts affected traders–especially women–in urban markets. By drawing on consumer insights and trader experiences, the paper offers a nuanced understanding of the socio-economic impacts of zoonotic risk perception and contributes to policy discussions around sustainable trade, gender equity, and public health preparedness. In doing so, it brings attention to the complex interplay between cultural practices, economic survival, and global health narratives in Africa’s urban spaces–reimagining how vulnerability and resilience are shaped in the digital and post-pandemic age. 2. Understanding Wildlife Meat Trade Dynamics Through the Health Belief Model 2.1. The Wildlife Meat Value Chain The wildlife meat trade, often locally referred to as bushmeat, operates through a multifaceted and dynamic value chain that includes several interconnected stages–namely hunting, processing, transportation, marketing, and consumption (Fig. 1 ). Each stage of this value chain is essential to its overall functionality and sustainability (Vitekere et al., 2021 ). Hunting, which marks the beginning of the chain, is largely undertaken by men, many of whom are relatives of rural women. These hunters supply wildlife meat to wholesalers who then facilitate its distribution to urban centers, including major markets in Accra (Mendelson et al., 2003 ). Women play a dominant role in the downstream segments of the chain–specifically in the processing, storage, preparation, and retailing of wildlife meat. Yet, despite their numerical dominance in these areas, women often have less control over the more profitable components such as hunting and transportation, which are largely male-dominated. This gendered division of labor contributes to economic disparities in earnings and influence within the trade (Wenham et al., 2020 ). The relatively low capital requirement for entry into wildlife meat trading makes it an accessible economic opportunity for many women, especially in urban informal markets. Women account for approximately 85% of retail sales, particularly through street vending and chop bars. However, despite this prominent role, women traders often earn significantly less than their male counterparts. Furthermore, women typically face higher startup costs–such as for purchasing cooking equipment or securing space in marketplaces–while men, particularly hunters, incur minimal costs but retain a greater share of profits (Mendelson et al., 2003 ). This economic asymmetry underscores the structural inequities within the trade, where women, though essential to its operation, remain economically marginalized. Geographic factors such as urban demand, seasonal availability, and transportation access further influence the profitability and livelihood security of actors within the wildlife meat trade (Vitekere et al., 2021 ). These dynamics call for targeted policy interventions to improve equity and sustainability within the sector, especially for women who are central yet under-rewarded contributors. Interventions could include access to microfinance, formal recognition of women’s roles in value chains, and support for safer processing environments. 2.2. The Health Belief Model and Consumer Attitudes To understand consumer attitudes toward wildlife meat consumption, especially during health crises such as the COVID-19 pandemic, the Health Belief Model (HBM) offers a valuable analytical framework. Originally developed in the 1950s to explain health-related behavior, HBM outlines six key constructs that influence individual decision-making: perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action, and self-efficacy (Champion & Skinner, 2008 ). These constructs are particularly relevant in the context of zoonotic outbreaks where food consumption behaviors shift in response to perceived disease risks. Perceived susceptibility reflects how vulnerable consumers feel to contracting diseases such as COVID-19 through the consumption of wildlife meat. In pandemics, higher perceived susceptibility typically correlates with reduced consumption, as shown in previous studies on the Ebola outbreak in Ghana and Sierra Leone (Kuukyi et al., 2014 ; Sainge et al., 2023 ). Perceived severity–concerns about the potential consequences of infection–further amplifies behavioral change. When consumers view zoonotic diseases as life-threatening, they are more likely to adjust their dietary habits. On the other hand, perceived benefits may include the nutritional, cultural, or economic value of wildlife meat. These perceived gains can outweigh health concerns, especially where alternative protein sources are scarce or unaffordable (Jun & Jaafar, 2011 ). Perceived barriers, such as the high cost or unavailability of substitutes, can limit consumers’ ability to shift behavior even when they are aware of risks (Kaptan & Kayısoglu, 2015 ). For instance, during COVID-19, many urban consumers reduced their wildlife meat intake due to fear of infection, but others continued consumption due to lack of options. Cues to action, such as public health messaging, community-level awareness, or visible illness, play a key role in triggering protective behaviors. Public advisories or media reports linking wildlife meat to COVID-19 likely influenced consumer decisions during the pandemic (Abukari & Kankam, 2023 ). Similarly, self-efficacy–an individual’s belief in their ability to take preventive action–is shaped by income, education, and access to information. Lower-income groups, who may rely more heavily on wildlife meat for subsistence, may feel less capable of adjusting their consumption, even when aware of health risks (Liu et al., 2013 ; see also Galibourg et al., 2024 ). Integrating the wildlife meat value chain with the Health Belief Model provides a nuanced understanding of how perceptions, risks, and structural constraints converge to shape consumption behavior during pandemics. While public health concerns often dominate narratives around zoonotic diseases, the continued reliance on wildlife meat for nutrition and income underscores the complexity of consumer attitudes and coping mechanisms. Importantly, health risks are not limited to zoonotic viruses. The wildlife meat trade is associated with other dangers, including poor hygiene practices, unsafe food handling, and the presence of contaminants such as heavy metals and lead introduced during hunting (Gbogbo et al., 2020 ; Oladayo et al., 2022 ). While some argue that the health risk from typical consumption levels in Ghana is low (Gbogbo et al., 2020 ), these concerns remain central to risk perception. Understanding how consumers weigh these risks against cultural and economic imperatives is crucial for designing effective, context-specific interventions. This study, therefore, seeks to examine how these health belief dimensions shaped consumer attitudes during COVID-19 and the downstream effects on traders–particularly women–who form the backbone of the wildlife meat economy in urban Ghana. 3. Methodology This study investigates consumer attitudes and the socio-economic impacts of wildlife meat (commonly referred to as bushmeat) trade in the wake of the COVID-19 pandemic. To capture the spatial and economic diversity of this trade in urban Ghana, five markets in the Greater Accra Metropolitan Area (GAMA) were purposively selected: Makola, Agbogbloshie, Dome, Madina, and Adabraka. These markets span four municipal and metropolitan assemblies–Accra Metropolitan Area, Ga East, Korle Klottey, and La Nkwantanang Madina–representing both central and peri-urban trading hubs with active smoked wildlife meat commerce (see Fig. 2 ). The selection of these locations was guided by their prominence in the wildlife meat trade and the presence of varied consumer and trader dynamics, providing a representative cross-section of market conditions in Accra. A concurrent mixed-methods design was adopted, integrating qualitative and quantitative approaches to ensure comprehensive analysis. Data were collected simultaneously between June and July 2023 through three instruments: (i) a structured survey for consumers, (ii) in-depth interviews with traders, and (iii) an observation checklist to document trade practices and environments. For the quantitative component, a total of 255 wildlife meat consumers were sampled using convenience and interval-based sampling techniques. Individuals were approached at every tenth count within the selected markets and screened for consumption of wildlife meat. Those who affirmed consumption were included, encompassing sellers, hawkers, and buyers. Face-to-face interviews were conducted in Twi, Ewe, or English, depending on respondent preference, with an average duration of 30 minutes. Data were digitally recorded using KoboCollect, a mobile-based data collection tool. To assess the reliability of the survey instrument, a Cronbach’s Alpha test was performed, yielding a score of 0.996. This high level of internal consistency indicates the robustness of the instrument in capturing reliable data on consumer perceptions and behaviours before, during, and after the pandemic. The qualitative strand comprised 10 in-depth interviews with female wildlife meat traders across the five markets. Participants were selected based on convenience and saturation principles (Hennink et al., 2020 ), ensuring that thematic saturation was reached. Interviews were conducted after obtaining verbal informed consent and lasted between 20 and 30 minutes. The interview guide explored themes such as changes in consumer demand, coping strategies during the pandemic, perceptions of zoonotic risk, and the socio-economic implications of COVID-19. Alongside the interviews, structured observations were carried out in each market, resulting in 10 observational records that provided context on trading environments, meat types, pricing, hygiene, and sourcing practices. Quantitative data were analyzed using SPSS and Microsoft Excel, applying both descriptive statistics (frequencies, percentages) and inferential analysis, particularly Chi-square tests, to identify significant patterns and associations in consumer behaviour. For the qualitative data, manual content analysis was employed. Interviews were transcribed verbatim into English, segmented by the study’s thematic objectives, and coded according to emergent themes. Responses were organized and frequency distributions were generated in Excel to identify dominant narratives. Verbatim quotes from participants were included to add depth and contextual richness to the findings. By combining consumer surveys, trader interviews, and observational insights, this methodological approach provided a holistic understanding of the wildlife meat trade and the interplay between public health concerns and livelihood realities in urban Ghana. 4. Wildlife meat consumption: Shifts in attitudes and trade dynamics 4.1. Profile of participants The demographic composition of wildlife meat consumers in Accra reveals notable gender and age patterns. Females constituted a larger share of respondents (58.4%) compared to males (41.6%), suggesting that women are key actors in the wildlife meat consumption market. The data also indicate that younger demographics are highly involved in consumption, with 25.9% of consumers aged 18–24 and 30.6% aged 25–34. This reflects a generational continuity in wildlife meat consumption practices, countering assumptions that the practice is limited to older or rural populations. Ethnic composition shows that Akans represent the largest consumer group (40.8%), which is consistent with documented preferences and cultural attachment to wildlife meat among this group. Ewes follow at 31.4%, Ga-Adangbes at 12.5%, and Guans at 6.7%, with other groups collectively comprising 8.6%. This distribution supports existing literature indicating that wildlife meat consumption cuts across various ethnicities but is often shaped by cultural norms and culinary traditions. In terms of education, most consumers have attained at least basic education, though 18% reported no formal schooling. This educational variation may have implications for how consumers interpret and respond to health messaging about zoonotic diseases. Employment data show a significant proportion of self-employed individuals (39.2%), with a notable 27% classified as unemployed, including retirees. Income levels were generally modest, with 38% earning less than GHS 500 per month and another 31% earning between GHS 500–1,000, indicating that a considerable number of consumers operate within the lower-income bracket, which may influence purchasing decisions and risk perceptions. Among the wildlife meat traders interviewed, the majority (37.5%) were aged between 51–60, with 25% aged 30–40, and 12.5% aged above 61. The traders predominantly belonged to the Akan, Ewe, and Ga-Adangbe ethnic groups, mirroring the consumer base. Half of the respondents were married, while the rest were widowed (30%) or separated (20%). Importantly, 50% of traders identified as household heads, highlighting their role as primary income earners and the gendered economic significance of the trade. In terms of asset ownership, a relatively high proportion of traders possessed mobile phones (90%), TVs (70%), mobile money accounts (70%), and bank accounts (60%). Notably, 60% were subscribed to the national health insurance scheme–an encouraging sign of health-seeking behaviour amidst broader livelihood precarity. 4.2. Nature of the wildlife meat trade The wildlife meat trade in Accra is characterized by a regionally distributed supply network. In all five markets surveyed–Makola, Agbogbloshie, Dome, Madina, and Adabraka–the supply of wildlife meat originated from outside the Greater Accra Region. Traders reported sourcing their stock from distant regions such as Central, Eastern, and Ashanti, illustrating the spatial extent and inter-regional dependency of the trade. This wide-reaching network underscores the economic importance of wildlife meat not just within urban markets, but across regional rural-urban linkages. Transportation and logistics play a pivotal role in shaping trade dynamics. Transporters–typically men–function as intermediaries between rural hunters and urban traders, although in some cases hunters deliver the meat directly using public transportation. The trade relies heavily on commercial vehicles, making it vulnerable to fluctuations in fuel prices, road conditions, and market accessibility (see Fig. 3 ). These logistics introduce both time and cost pressures on traders, which in turn influence the pricing and type of wildlife meat sold. The concept of “friction of distance” is evident in the average travel distance between supply areas and markets. For example, the shortest route–from Mankessim (Central Region) to Accra–covers about 110 km and takes 2–3 hours by road. During fieldwork in June 2023, the average transport cost for this distance was approximately GHS 50 (USD 4.17). These costs, compounded by perishability risks, directly affect market dynamics and profit margins. Due to spoilage risks associated with transporting fresh meat over long distances, smoked wildlife meat has become the preferred product among both traders and consumers. As one trader from Madina Market explained: When you buy fresh wildlife meat, the meat will get bad by the time you travel and reach the market in a few days. This affects how much you sell it. Hence, it is better to deal with smoked ones because they last longer. (55-year-old female wildlife meat trader, Madina Market) This preference highlights the adaptive strategies employed by traders to manage perishability and maintain economic viability. The dominance of smoked wildlife meat also reflects consumer trust in its safety, taste, and storage convenience. However, it may also obscure visibility into hygiene and food safety issues during the processing stage–issues which became more significant during the COVID-19 pandemic, as health concerns reshaped consumption choices. In short, the wildlife meat trade in urban Ghana is shaped by a combination of gender roles, transport logistics, economic constraints, and consumer attitudes toward product quality and safety. These dynamics became more complex during and after the COVID-19 pandemic, as changing health beliefs and public perception influenced both consumption patterns and the livelihoods of those who depend on this informal trade. 4.3. Wildlife meat consumption pattern before, during and after COVID-19 The study revealed complex and evolving patterns in wildlife meat consumption across the three phases of the COVID-19 pandemic–before, during, and after–highlighting significant shifts in consumer attitudes and behaviours that directly affected the viability of the wildlife meat trade. Prior to the pandemic, wildlife meat consumption was widespread and culturally embedded, with 100% of respondents (N = 255) reporting regular consumption. It was widely regarded as a nutritious delicacy despite longstanding concerns about hygiene and zoonotic diseases, including Ebola (Gbogbo et al., 2020 ; Oladayo et al., 2022 ). At this time, the wildlife meat trade was thriving and served as a vital source of income, particularly for women traders. However, consumption declined sharply during the height of the pandemic. Only 27% of respondents continued to consume wildlife meat during COVID-19, with a slight recovery to 47% after the pandemic. These trends reflect widespread uncertainty, fear of disease transmission, and market disruptions. Awareness of the zoonotic origin of COVID-19 was nearly universal, with 98% of respondents acknowledging this link (Huang et al., 2020 ). Although 63.9% were skeptical that wildlife meat specifically contributed to the transmission of the virus, 36% associated its consumption with an increased risk of infection. These perceptions, combined with supply shortages and elevated prices, led to a dramatic drop in consumption and a corresponding decline in income for many traders. While health concerns drove some consumers away from bushmeat, others continued to eat it, citing benefits such as nutritional value, taste, and cultural significance–an outcome that aligns with the Health Belief Model’s emphasis on perceived benefits and risks (Champion & Skinner, 2008 ; Kuukyi et al., 2014 ). Consumption patterns also varied by location (see Fig. 4 ). To quantify these changes, percentage change analysis was conducted for each market using the formula: Percentage change = $$\:\left(\frac{Consumption\:during/after\:COVID-19-Consumption\:before\:COVID-19}{Consumption\:before\:COVID-19}\right)*100$$ The analysis revealed significant market-level variation. Overall, wildlife meat consumption decreased by approximately 73.3% during COVID-19 and 53% post-COVID. The Adabraka market showed the smallest decline–59% during and 34% after the pandemic–while Makola and Agbogbloshie markets saw the steepest declines, each reporting a 77% drop during COVID-19 (see Table 1 ). Table 1 Variations in wildlife meat consumption patterns based on market location Markets Wildlife meat consumption pattern frequency (%) Percentage change in consumption (%) Before COVID-19 During COVID-19 After COVID-19 Before-During Before-After Adabraka 32 13 21 -59 -34 Agbogbloshie 30 7 18 -77 -40 Dome 65 17 26 -74 -60 Madina 49 13 20 -73 -59 Makola 79 18 34 -77 -57 Total 255 (100) 68 (27) 119 (47) -73 -53 Source: Authors’ construct (2024). The decline in wildlife meat consumption during and after COVID-19 raises concerns about the sustainability of the wildlife meat trade. Recent trends show a decrease in the number of traders in markets, reflecting the impact of the pandemic on trade activities. For example, the Madina market, which recorded one of the highest consumption declines, has witnessed a significant reduction in the number of wildlife meat traders, as many have left the trade for other businesses. One trader recounted: We are not making money, so many have stopped... In this market, two other traders who sell wildlife meat don’t come regularly anymore because the market is bad. People are not buying. One came two weeks ago but hasn’t returned yet. Some of us are managing to continue (55-year-old female wildlife meat trader, Madina market). This testimony echoes the concerns raised by Ripple et al. ( 2016 ), who warned of an impending “wildlife meat crisis.” While overhunting had been seen as the primary threat, consumer perceptions of zoonotic disease risk–particularly in the wake of COVID-19–have emerged as a new and equally significant challenge to the trade’s survival. Gender differences in consumption patterns were also evident. Before the pandemic, 58.4% of wildlife meat consumers were female and 41.6% were male. However, during the pandemic, men were more likely to continue consumption (60%) compared to women (40%). This trend continued after the pandemic, with male consumption rising slightly to 61% and female consumption falling to 39%. This statistically significant difference (p = 0.007) suggests that women were more responsive to perceived health risks, consistent with the Health Belief Model, while men may have prioritized perceived benefits such as taste and protein value (Sainge et al., 2023 ; see Table 2 ). Table 2 Wildlife meat consumption pattern based on gender Wildlife meat consumption Variables Frequency (%) X 2 Value P-value Before COVID-19 Male 106 (41.6) Female 149 (58.4) 7.25 0.007 Total 255 (100) During COVID-19 Male 41 (60) 13.386 0.000 Female 27 (40) Total 68 (27) After COVID-19 Male 73 (61) 35.926 0.000 Female 46 (39) Total 119 (47) Source: Authors’ construct (2024). Thus, the wildlife meat consumption landscape during and after COVID-19 was shaped by intersecting factors including public health concerns, access and affordability, shifting attitudes, and gendered responses to risk. These dynamics underscore the vulnerability of informal food economies to global health crises and the need for context-sensitive policy interventions. The trajectory of wildlife meat consumption in Accra across the pre-COVID, peak pandemic, and post-COVID periods reveals a nuanced interplay of health concerns, economic shifts, and evolving consumer attitudes (see Fig. 5 ). While wildlife meat was widely consumed before the pandemic due to its affordability, cultural significance, and perceived nutritional value, the onset of COVID-19 dramatically altered consumption dynamics. During the pandemic, a sharp decline in wildlife meat consumption was reported, influenced by a combination of health-related fears and structural constraints. One of the most significant contributing factors was the scarcity of wildlife meat during lockdowns. With movement restrictions disrupting supply chains, hunters and transporters were unable to deliver meat regularly to urban markets. As availability declined, prices soared, reversing bushmeat’s status as an affordable protein source relative to options like cattle, goat, or fish (Kuukyi et al., 2014 ). As cost-of-living pressures intensified, many lower-income consumers shifted to cheaper alternatives such as eggs, plant-based proteins, and fish (Morris et al., 2020 ). One consumer captured this reality succinctly: “You buy what your money can buy, so I often bought eggs during COVID-19 because I couldn’t afford bushmeat” (44-year-old male wildlife meat consumer, Makola market). Beyond availability and cost, the fear of contracting COVID-19 from consuming wildlife meat played a major role in dampening demand. Influenced by public health campaigns and media messaging, many consumers associated wildlife meat with zoonotic transmission. These warnings, reminiscent of health advisories issued during previous Ebola outbreaks, acted as strong deterrents. As one respondent explained: Health practitioners and researchers told us that eating wildlife meat could lead to contracting COVID-19 and even other diseases like Ebola. I stopped eating wildlife meat during COVID-19 because of that (30-year-old female wildlife meat consumer, Agbogbloshie market). However, these fears were not uniformly sustained. Over time, a portion of the population resumed consumption, citing personal experience and the absence of adverse health effects. This shift suggests that the “cues to action” necessary to maintain behavioural change were either weak or inconsistently reinforced. As another consumer reflected: When COVID-19 broke, we heard you could contract the pandemic when you consume meat. However, I have consumed different types of meat, including bushmeat, but I never contracted COVID-19 or any other diseases (26-year-old male, wildlife meat consumer, Dome Market). According to the Health Belief Model, this erosion of perceived susceptibility, due to the absence of reinforcing messages or observable negative consequences, contributed to a gradual reversion to pre-pandemic behaviours (Morris et al., 2020 ). Still, a notable subset of consumers continued to avoid wildlife meat out of caution. One woman emphasized her sustained abstinence: “Health practitioners said wildlife meat could cause diseases like COVID-19 or Ebola. I stopped eating it [bushmeat] during the pandemic and I still have not resumed because of those warnings”. Food safety concerns–particularly regarding the source and handling of bushmeat–also shaped consumption choices. Several respondents expressed distrust in hunting methods that involved firearms or poisons, which could contaminate meat with heavy metals like lead and zinc (Gbogbo et al., 2020 ). Others raised concerns about unhygienic processing and storage conditions, which increase the risk of contamination from bacteria, parasites, and viruses (Kamogne-Tagne et al., 2022; Oladayo et al., 2022 ). These anxieties, aligned with the HBM’s “perceived severity” and “perceived barriers” constructs, likely reinforced caution among health-conscious consumers. Despite these concerns, wildlife meat consumption did not disappear. Some consumers continued to eat it out of habit or for its perceived health and taste benefits. Prior to COVID-19, the main motivators for consumption included affordability, taste, availability in rural areas, and low fat content (Kuukyi et al., 2014 ). Post-pandemic, these factors remained relevant, but new considerations such as price volatility and food safety featured more prominently in decision-making. Notably, 18% of respondents could not specify a reason for their continued consumption, and 16% were unsure–highlighting the complexity of attitudes toward wildlife meat and the influence of deeply embedded social norms. Interestingly, this study challenges earlier assumptions about consistent wildlife meat availability. In contrast, traders and consumers alike reported marked shortages during and after COVID-19, compounding the effects of fear and rising prices on the viability of the trade. For many traders–particularly women who dominate the retail end of the chain–this decline in demand translated into lost income, reduced sales, and an uncertain future. In short, wildlife meat consumption patterns in Accra during and after COVID-19 were shaped by an intricate mix of perceived risk, economic strain, product availability, and behavioural adaptation. These findings not only affirm the relevance of the Health Belief Model in interpreting consumer decision-making during health crises but also underscore the importance of integrating public health messaging with livelihood considerations in future pandemic preparedness efforts. 5. Livelihood and socio-economic challenges of women in the wildlife meat trade Women’s engagement in the wildlife meat trade in Ghana is largely driven by its income-generating potential, echoing earlier findings by Wenham et al. ( 2020 ). This study confirms that wildlife meat trading provides a crucial source of livelihood, especially for women who serve as primary income earners in their households. Before the onset of COVID-19, the trade was highly profitable due to consistent consumer demand, low entry barriers, and relatively high profit margins. Women traders used income from the trade to cover essential living costs such as school fees, rent, and medical bills. Monthly earnings typically ranged between GHS 500 (USD 41.67) and GHS 2,000 (USD 166.67), depending on market volume and seasonal fluctuations. As noted by Fahad et al. ( 2023 ), income from this trade also allowed women to invest in assets like mobile phones, televisions, and radios, which not only enhanced their quality of life but also served as leverage in accessing informal credit, savings schemes, and loans. However, the COVID-19 pandemic significantly disrupted this economic stability. The sharp decline in wildlife meat consumption directly impacted women's earnings, pushing many into financial distress. One trader at the Agbogbloshie market remarked: “ I sell for money, and this is the only business I do. If not for the money I gain from selling, I would not be sitting here and suffering. My family’s survival depends on how much I earn” . The pandemic’s impact extended beyond income loss. Women traders faced mounting socio-economic pressures such as dwindling access to credit, collapsing supply chains, and heightened financial insecurity (Amankwaa, 2025 ). Market closures and lockdowns meant many traders were unable to work, leaving them without income for extended periods (Fahad et al., 2023 ). Those who relied solely on wildlife meat sales faced the greatest strain. A 55-year-old trader at Madina Market described the situation: My last born is in one of the colleges of education in the Volta region (Amedzofe Training College); the father does not care about her, so I sell to look after her. However, because of COVID-19, my sales have dropped, and there is no money in the system for people to buy again, so I am suffering in terms of money now. (55-year-old female wildlife meat trader, Madina Market) Traders struggled to maintain their businesses and provide for their families. Many lacked basic infrastructure, such as refrigeration or storage, and were unable to preserve unsold meat, resulting in significant losses. A 61-year-old trader from the Madina market recounted: “ During COVID-19, we were asked to stay home, so I had no money and food but managed till it was over.” Gender inequalities further exacerbated the crisis. Many women lacked collateral and formal assets to qualify for bank loans or government support, leaving them highly vulnerable to financial shocks (Wrigley-Asante, 2008 ; Amankwaa, 2025 ). Consequently, many relied on informal networks for survival–borrowing from friends, family, or social groups. As one trader shared: “ Because of COVID-19, most of the goods I bought got spoiled, and my business almost collapsed, so I borrowed money from a friend to start over. I'm still paying.” (55-year-old wildlife meat trader, Madina Market). The pandemic also disrupted transportation networks essential for sourcing wildlife meat. Travel restrictions made it difficult for hunters and transporters to move goods, leading to irregular supplies and inflated costs. Traders bore the brunt of these disruptions, with rising fuel prices further diminishing their already slim profit margins. One trader shared her experience: “ Acquiring wildlife meat from the hunters became difficult. Drivers charged high fees due to rising fuel prices, using up most of my profit” (55-year-old female wildlife meat trader, Madina Market). As economic pressures mounted, some women exited the trade entirely, while others struggled to stay afloat. The burden was particularly acute for women with fewer socio-economic resources, who lacked the buffers–such as savings, diversified income sources, or household support systems–that could help absorb financial shocks. The cumulative effect of income loss, increased costs, and limited institutional support has left many women in the wildlife meat trade in a precarious position, underlining the urgent need for targeted interventions to support post-pandemic recovery and economic resilience. 6. Coping mechanisms and support systems for wildlife meat traders under COVID-19 In response to the socio-economic disruptions brought about by the COVID-19 pandemic, women engaged in the wildlife meat trade in Accra adopted a range of coping strategies. Insights from in-depth interviews reveal how traders navigated financial hardship, supply chain disruptions, and declining consumer demand through both economic and psychological mechanisms. One of the most prominent strategies was the use of personal savings. Prior to the pandemic, many women had participated in informal savings schemes such as susu groups and microfinance programs, accumulating funds intended for business reinvestment or household needs. However, as lockdowns restricted trading activity and income streams dried up, these savings became essential lifelines. A wildlife meat trader explained: Our leaders used COVID-19 to spoil business for us market women. I spent the savings I planned to use for something better during COVID-19 (45-year-old female wildlife meat trader, Dome Market). In addition to depleting their savings, many traders diversified their income by engaging in alternative livelihood activities. High-demand products like face masks became temporary substitutes for lost revenue from wildlife meat sales. Others expanded their offerings to include dried fish, cow meat, pepper, and other staples. This form of livelihood diversification helped mitigate the financial shock of reduced wildlife meat consumption. As one trader explained: During COVID-19, I sold nose masks since that was what everybody was selling. I needed money to survive since my [bushmeat] business was not fetching again. (40-year-old female wildlife meat trader, Makola market). Another trader added: I sold many things in addition to the wildlife meat because people were not purchasing the bushmeat. You won't get anything if you want to depend on the wildlife meat alone. I sold dry and fried fish from Aboatoase, cow meat, pepper, etc” (45-year-old female wildlife meat trader, Adabraka market). Borrowing money from family and friends was another critical coping strategy. Despite the risks of personal indebtedness and strained relationships, many traders saw informal borrowing as a necessary survival tactic. These social networks became crucial buffers in the absence of formal support mechanisms. This behaviour is reflective of the Health Belief Model's construct of perceived benefits , where individuals make calculated decisions in times of crisis based on available options and expected outcomes (Hossain, 2005 ; Levine, 2014 ). Notably, external institutional support was largely absent. Many traders reported receiving no assistance from local authorities, despite continued obligations to pay daily tolls and levies. The lack of support reinforced a sense of abandonment and compelled traders to rely on their own resources. As one trader lamented: The district assembly comes daily to give us chits and take tolls, but they do not even care about renovating the shed we are selling under. We depend on ourselves because we don’t have anyone to depend on. I have decided to focus on my selling and pray that God helps me; I don’t care about COVID-19 or any politician (55-year-old female wildlife meat trader, Madina market). This mindset of self-reliance also signals a deeper form of psychological adaptation , as traders reoriented their outlooks to focus on personal resilience and self-efficacy. Drawing from the Health Belief Model (Champion & Skinner, 2008 ), this sense of agency empowered traders to take proactive steps to sustain their livelihoods. These psychological shifts became as vital as financial strategies, shaping how traders responded to ongoing uncertainties and setbacks. The coping strategies adopted by wildlife meat traders reflect broader patterns of resilience and adaptability documented in crisis literature (Nasution et al., 2021 ; Pahl-Wostl et al., 2023 ). These women not only managed short-term economic shocks but also demonstrated transformative learning–adjusting behaviours, expectations, and business models to meet new realities. Their responses offer valuable lessons for understanding informal sector resilience and the critical need for targeted institutional support in future public health and economic crises. 7. Conclusion This study has examined shifting consumer attitudes toward wildlife meat consumption during and after the COVID-19 pandemic and assessed the socio-economic impact on women traders in Ghana’s urban markets. The findings show that while wildlife meat remains culturally significant and economically vital, the pandemic introduced a major rupture in consumption patterns and trade dynamics. The outbreak heightened public awareness of zoonotic disease risks, resulting in a notable decline in consumption, particularly among female consumers who exhibited higher perceived susceptibility and severity–key constructs of the Health Belief Model (HBM). The HBM provided a useful framework for understanding how individuals weighed risks and benefits during the crisis. Perceived barriers, such as price inflation and scarcity, further disincentivized consumption, while cues to action–such as media messaging and public health warnings–reinforced behavioural change. Conversely, a segment of the population, mostly men, continued consuming wildlife meat based on perceived benefits, such as taste and nutritional value, suggesting that behaviour during health crises is shaped by a complex balance of beliefs, economic conditions, and social norms. Women traders, who form the backbone of the wildlife meat trade, were disproportionately affected by reduced demand and mobility restrictions. In the absence of external support, they demonstrated considerable resilience through savings withdrawals, business diversification, and psychological adaptation (Amankwaa & Amponsah, 2024). Yet, their vulnerability was exacerbated by limited access to credit and inadequate market infrastructure. Policy interventions are urgently needed to support these traders and promote safer, more sustainable practices (Galibourg et al., 2024 ). Financial support from the Ministry of Trade and Industry and Metropolitan/Municipal Assemblies–such as interest-free loans, grants, and tax exemptions–would enable affected traders to rebuild their businesses. Moreover, promoting the domestication of wildlife through awards and national events could reduce dependence on wild populations while ensuring stable market supply. Health education initiatives led by the Ghana Health Service should also be expanded, targeting hunters, processors, and traders with training in food safety and zoonotic risk mitigation. Certification schemes tied to compliance can enhance public trust and accountability. Additionally, improved market infrastructure–including shaded stalls, cold storage, and reliable transportation–would alleviate supply chain bottlenecks and support hygienic trading practices. Finally, public awareness campaigns are crucial to dispel misinformation, reduce stigma, and encourage informed consumption. By integrating the behavioural insights of the Health Belief Model into policy design, stakeholders can more effectively influence public attitudes, improve resilience in informal trade sectors, and safeguard public health. Supporting women traders in this process is not only a matter of equity but also essential to sustaining a vital source of income for many urban households in Ghana and similar contexts across sub-Saharan Africa. Declarations Acknowledgements The authors are greatly indebted to all our participants who allowed us into their homes and workplaces to undertake this research. We are thankful to the two anonymous reviewers for their useful comments. Declaration of Interest Statement The authors declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Funding This research was funded by IDRC through the Women RISE initiative project. Ethical Approval Research ethics clearance was granted by the University of Ghana’s Ethics Committee for Humanities. The study was conducted in accordance with the ethical standards for research involving human participants, following the guidelines of the Ethics Committee for the Humanities, University of Ghana. Consent to Participate This study involved human participants. All participants were informed about the purpose of the study and they provided their voluntary, informed consent prior to participation and data collection. Clinical Trial Number Clinical trial number: not applicable References Abukari, H., & Kankam, B. (2023). Wild meat consumption in zoonotic pandemics in Ghana. Human Dimensions of Wildlife 29, 1–14. https://doi.org/10.1080/10871209.2023.2220004 Amankwaa, E. F. (2025). Floods and jolts impacting the livelihoods of market women in urban. Ghana In E. A. Ejiribe, S. Sodzi-Tettey & J. Ofori-Dankwa (Eds.), African Women Entrepreneurs in the Informal Economy . 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Scientific African, 15 (2022), e01083 https://doi.org/10.1016/j.sciaf.2021.e01083 Galibourg, D., Amankwaa, E. F., Gough, K. V., & Scott, R. (2024). Informal irrigated vegetable. value chains in urban Ghana: potential to improve food safety through changing stakeholder practices. International Development Planning Review , 46 (4), 391–414. https://doi.org/10.3828/idpr.2024.17 Gbogbo, F., Rainhill, J. E., Koranteng, S. S., Owusu, E. H., & Dorleku, W. P. (2020). Health risk. Assessment for human exposure to trace metals via wildlife meat in Ghana Biological Trace Element Research , 196 , 419–429. https://doi.org/10.1007/s12011-019-01953-7 Hennink, M., Hutter, I., & Bailey, A. (2020). Qualitative research methods . Sage. Hossain, S. (2005). Poverty, household strategies and coping with urban life . Examining. ‘livelihood framework’ in Dhaka City Bangladesh. Bangladesh e-journal of Sociology , 2 (1), 1–8. Huang, C., Wang, Y., Li, X., Ren, L., Zhao, J., Hu, Y., & Cao, B. (2020). Clinical features of patients. Infected with 2019 novel coronavirus in Wuhan, China. The Lancet , 395 (10223), 497–506, https://doi.prg/10.1016/S0140-6736(20)30183-5 Jun, G., & Jaafar, N. I. (2011). A study on consumers’ . attitudes toward online shopping in. China International Journal of Business and Social Science , 2(22), 122–132. Kamogne- Tagne, C. T., Brittain, S., Booker, F., Challender, D., & Maddison, N. Milner-Gulland. Coad, L. (2022). Impacts of the COVID-19 pandemic on livelihoods and wild meat use in communities surrounding the Dja Faunal Reserve, South‐East Cameroon. African Journal of Ecology , 60 (2), 135–145. https://doi.org/10.1111/aje.12995 Kaptan, B., & Kayısoglu, S. (2015). Consumers’ attitude towards food additives. American . Journal of Food Science and Nutrition Research , 2 (2), 21–25. Kuukyi, F. S., Amfo-Otu, R., & Wiafe, E. (2014). Consumer views of wildlife meat consumption. in Two Ghanaian markets Applied Research Journal , 1 (1), 20–27. Leroy, E. M., Telfer, P., Kumulungui, B., Yaba, P., Rouquet, P., Roques, P., Gonzalez, J. P. (2004a). A serological survey of Ebola virus infection in central African nonhuman primates. The Journal of Infectious Diseases , 190 (11), 1895–1899. https://doi.org/10.1086/425421 Levine, S. (2014). How to study livelihoods . Bringing a sustainable livelihoods framework to. life Secure Livelihoods Research Consortium: Researching livelihoods and services affected by conflict , 22 . Liu, R., Pieniak, Z., & Verbeke, W. (2013). Consumers' attitudes and behaviour toward safe. Food in China A review. Food Control , 33 (1), 93–104. https://doi.org/10.1016/j.foodcont.2013.01.051 Mendelson, S., Cowlishaw, G., & Rowcliffe, J. M. (2003). Anatomy of a wildlife meat. commodity Chain in Takoradi, Ghana. Journal of Peasant Studies , 31 (1), 73–100. https://doi.org/10.1080/030661503100016934 Morris, S. E., Moment, A., & Thomas, J. D. (2020). Caring for bereaved family members during. the COVID-19 pandemic: before and after the death of a patient. Journal of pain and symptom management , 60 (2), e70–e74. https://doi.org/10.1016/j.jpainsymman.2020.05.002 Mosi, L., Sylverken, A. A., Oyebola, K., Badu, K., Dukhi, N., Goonoo, N., & Mante P. K., Zahouli. Amankwaa, J., Tolba, E. F., Fagbamigbe, M. F., de Souza, A. F., D. K., & Matoke-Muhia, D. (2021). Correlating WHO COVID-19 interim guideline 2020.5 and testing capacity, accuracy, and logistical challenges in Africa. Pan African Medical Journal , 39 (1). https://doi.org/10.11604/pamj.2021.39.89.27522 Nasution, N., Sarmini, S., Warsono, W., Wasino, W., & Shintasiwi, F. (2021). Using Coping. Strategies of Informal Sector Traders amid COVID-19 in Indonesia for Social Studies. Teaching Materials on Realizing SDGs Journal of Social Studies Education . Research 12 (3), 144–174. Oladayo, T., Miteu, G., Addeh, I., Folayan, E., Olayinka, T., Adegboyega, J., & Benneth, E. (2022). Most prominent factors of food poisoning in Africa: Nigeria based perspective. IPS . Journal of Nutrition and Food Science , 1 (1), 11–17. https://doi.org/10.54117/ijnfs.v1i1.1 Pahl-Wostl, C., Odume, O. N., Scholz, G., De Villiers, A., & Amankwaa, E. F. (2023). The role. Of crises in transformative change towards sustainability Ecosystems and People , 19(1), 2188087. http://doi.org/10.1080/26395916.2023.2188087 Ripple, W. J., Abernethy, K., Betts, M. G., Chapron, G., Dirzo, R., Galetti, M., & Young, H. (2016). Wildlife meat hunting and extinction risk to the world's mammals. Royal Society Open Science , 3 (10), 160498. https://doi.org/10.1098/rsos.160498 Sainge, M. N., Wusha-Conteh, F., Fa, J. E., Sullivan, M. J., & Cuni-Sanchez, A. (2023). Wild. Meat consumption in urban Sierra Leone during the COVID-19 pandemic. Oryx , 1–5. https://doi.org/10.1017/s0030605322000990 Schulte-Herbruggen, B. (2012). The importance of wildlife meat in the livelihoods of cocoa . farmers living in a wildlife-depleted farm-forest landscape, SW Ghana (Doctoral dissertation, UCL (University College London). Van-Heuverswyn, F., & Peeters, M. (2007). The origins of HIV and implications for the global. Epidemic Current infectious disease reports , 9(4), 338–346. https://doi.org/10.1007/s11908-007-0052-x Vitekere, K., Kyamakya, C. K., Nyumu, J. K., & Hua, Y. (2021). Wildlife meat commercial. circuit in Kisangani region: first and second levels of the wildlife meat Supply chain, on Ituri Road, DRC. Open Access Library Journal , 8 (10), 1–20. https://doi.org/10.4236/oalib.1107988 Wenham, C., Smith, J., & Morgan, R. (2020). ‘COVID-19: the gendered impacts of the. outbreak’ The Lancet , 395(10227), pp. 846–848. https://doi.org/10.1016/s0140-6736(20)30526-2 Wrigley-Asante, C. (2008). Men are poor, but women are poorer . Gendered poverty and survival. strategies in the Dangme West District of Ghana Norsk Geografisk Tidsskrift-Norwegian Journal of Geography , 62 (3), 161–170. https://doi.org/10.1080/00291950802335541 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 25 Dec, 2025 Reviews received at journal 25 Dec, 2025 Reviewers agreed at journal 29 Nov, 2025 Reviews received at journal 08 Aug, 2025 Reviewers agreed at journal 05 Aug, 2025 Reviewers invited by journal 09 Jul, 2025 Editor assigned by journal 07 Jul, 2025 Submission checks completed at journal 07 Jul, 2025 First submitted to journal 01 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7024348","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":482951031,"identity":"f268bbc4-609d-4901-8b9e-ecc1a8b6609a","order_by":0,"name":"Hanson Kwakudua","email":"","orcid":"","institution":"University of Ghana","correspondingAuthor":false,"prefix":"","firstName":"Hanson","middleName":"","lastName":"Kwakudua","suffix":""},{"id":482951032,"identity":"775460e9-4ec2-4d92-b514-5dd90fbcd796","order_by":1,"name":"Ebenezer Forkuo Amankwaa","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7ElEQVRIiWNgGAWjYDAC5gMgMgHOYmxgYGDDr4UtAaYFwiJJC48BcVr42Zifbvi5Iy2xv/3MN8kvDDayGw6wX3uAT4tkG5vZzd4zOYkzzuRuk5ZhSDPecICn3ACfFoP7DWY3eNsqchsOALVIMBxOBGpJk8Cnxf4Y+7ebf4Fa5p9/8wyo5T9hLQZsPGa3edtycjfcyGGT/MBwAKiF/RheLRLHeMpuy7al1W+88czYmsEg2XjmYR42vFr429i33Xzblmwsdz754c0fFXayfcfbn+HVggKYwVEDIYkEjD/AFPsD4rWMglEwCkbBSAAAp9tQzBsUqcsAAAAASUVORK5CYII=","orcid":"","institution":"University of Ghana","correspondingAuthor":true,"prefix":"","firstName":"Ebenezer","middleName":"Forkuo","lastName":"Amankwaa","suffix":""},{"id":482951033,"identity":"90c4b75c-49c3-4cff-8b0f-f013f618034c","order_by":2,"name":"Fidelia Ohemeng","email":"","orcid":"","institution":"University of Ghana","correspondingAuthor":false,"prefix":"","firstName":"Fidelia","middleName":"","lastName":"Ohemeng","suffix":""},{"id":482951034,"identity":"aaa79955-3a43-48cb-99c4-93e7479fdb8e","order_by":3,"name":"Charlotte Wrigley-Asante","email":"","orcid":"","institution":"University of Ghana","correspondingAuthor":false,"prefix":"","firstName":"Charlotte","middleName":"","lastName":"Wrigley-Asante","suffix":""}],"badges":[],"createdAt":"2025-07-02 02:23:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7024348/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7024348/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86531074,"identity":"3ce0921f-18a1-47a6-b171-47c295543a5e","added_by":"auto","created_at":"2025-07-11 17:01:20","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":46106,"visible":true,"origin":"","legend":"\u003cp\u003eWildlife meat value chain\u003c/p\u003e\n\u003cp\u003eSource: Adapted from Vitekere et al. (2021).\u003c/p\u003e","description":"","filename":"groupimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7024348/v1/c9747714e954aae02b66483d.jpeg"},{"id":86532078,"identity":"038f9886-6270-4f15-956e-6ae3ec0b539a","added_by":"auto","created_at":"2025-07-11 17:17:20","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":836288,"visible":true,"origin":"","legend":"\u003cp\u003eMap of the Study Area\u003c/p\u003e\n\u003cp\u003eSource: Authors’ construct (2024)\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7024348/v1/0f4daa4abfc5005e24cd2bba.jpeg"},{"id":86531726,"identity":"aa6459f0-40d6-4b68-9024-772ccb4fa9e8","added_by":"auto","created_at":"2025-07-11 17:09:20","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":220305,"visible":true,"origin":"","legend":"\u003cp\u003eGeographical spread of women’s wildlife meat supply chain\u003c/p\u003e\n\u003cp\u003eSource: Authors’ construct (2024).\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7024348/v1/f08fd5e00a2ec6105268c694.jpeg"},{"id":86531082,"identity":"dd192c53-96a4-4cec-a84b-7eed1f23e75c","added_by":"auto","created_at":"2025-07-11 17:01:20","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":76173,"visible":true,"origin":"","legend":"\u003cp\u003eGeographic patterns of wildlife meat consumption before, during and after COVID-19\u003c/p\u003e\n\u003cp\u003eSource: Authors’ construct (2024).\u003c/p\u003e","description":"","filename":"groupimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7024348/v1/7c880095dd47cfc2c03b6188.jpeg"},{"id":86531724,"identity":"5dfce8da-e3db-4807-914b-5a5637b9ee01","added_by":"auto","created_at":"2025-07-11 17:09:20","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":12492,"visible":true,"origin":"","legend":"\u003cp\u003eFactors influencing wildlife meat consumption during and after COVID-19\u003c/p\u003e\n\u003cp\u003eSource: Authors’ construct (2024)\u003c/p\u003e","description":"","filename":"image05.png","url":"https://assets-eu.researchsquare.com/files/rs-7024348/v1/2cc7059d414d17986d68b685.png"},{"id":86532566,"identity":"2b38a9d9-b138-493a-8733-155911e8ef31","added_by":"auto","created_at":"2025-07-11 17:25:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2103695,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7024348/v1/25a916ed-0160-4d32-8179-3bff832576ed.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Wild Meat Consumption in the Wake of COVID-19: Shifts in Attitudes and Trade Dynamics in Ghana","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eWildlife meat\u0026ndash;commonly referred to as bushmeat\u0026ndash;refers to the hunting and consumption of wild animals for food. Across many African countries, including Ghana, it plays a critical role in local food security, cultural traditions, and informal economic livelihoods. Wildlife meat is not only consumed for subsistence but is also embedded in a broader commercial network that links rural producers with urban consumers. This value chain typically includes hunters, transporters, traders, market vendors, and final consumers (Vitekere et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Driven by growing urban demand, the trade has become increasingly commercialized, particularly in fast-growing cities like Accra (Schulte-Herbruggen, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). However, the consumption and trade of wildlife meat also pose significant health risks due to the potential for zoonotic disease transmission\u0026ndash;including viruses such as Ebola, HIV, and more recently, COVID-19 (Leroy et al., 2004; Van Heuverswyn \u0026amp; Peeters, 2007; Kamogne-Tagne et al., 2022).\u003c/p\u003e\u003cp\u003eThe COVID-19 pandemic, which emerged in late 2019, had profound socio-economic consequences and health vulnerabilities globally (Blay et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Fagbamigbe et al., 2022). In Ghana, as in many countries, public health responses\u0026ndash;including lockdowns and restrictions on movement\u0026ndash;had severe repercussions on the informal sector, where a majority of the population, particularly women, earn their livelihoods (Anoko et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Mosi et al., 2021). Informal traders involved in wildlife meat markets were among those most acutely impacted by these restrictions. In addition to logistical disruptions, traders also faced a sharp decline in consumer demand, driven by fears of zoonotic transmission (Nasution et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Wenham et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Such fears are not unprecedented. During the 2014 Ebola outbreak, similar declines in wildlife meat consumption were recorded in Ghana and other West African countries (Kuukyi et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Sainge et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThese dynamics underscore how health crises can rapidly reshape consumption patterns. Consumer perceptions of safety often shift in response to public health messaging and perceived disease threats, as documented during earlier outbreaks (Liu et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Despite this, most research on wildlife meat has historically focused on supply-side concerns\u0026ndash;such as hunting practices, regulation, and biodiversity loss\u0026ndash;while consumer behavior and the socio-economic vulnerabilities of traders during disease outbreaks have received limited scholarly attention (Damania et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Ripple et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The intersection of gender, informal livelihoods, and pandemic-induced consumption shifts remains particularly underexplored (Wenham et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThis study addresses that gap by examining how attitudes toward wildlife meat consumption changed before, during, and after the COVID-19 pandemic in Ghana, and how these shifts affected traders\u0026ndash;especially women\u0026ndash;in urban markets. By drawing on consumer insights and trader experiences, the paper offers a nuanced understanding of the socio-economic impacts of zoonotic risk perception and contributes to policy discussions around sustainable trade, gender equity, and public health preparedness. In doing so, it brings attention to the complex interplay between cultural practices, economic survival, and global health narratives in Africa\u0026rsquo;s urban spaces\u0026ndash;reimagining how vulnerability and resilience are shaped in the digital and post-pandemic age.\u003c/p\u003e"},{"header":"2. Understanding Wildlife Meat Trade Dynamics Through the Health Belief Model","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1. The Wildlife Meat Value Chain\u003c/h2\u003e\n \u003cp\u003eThe wildlife meat trade, often locally referred to as bushmeat, operates through a multifaceted and dynamic value chain that includes several interconnected stages\u0026ndash;namely hunting, processing, transportation, marketing, and consumption (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Each stage of this value chain is essential to its overall functionality and sustainability (Vitekere et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). Hunting, which marks the beginning of the chain, is largely undertaken by men, many of whom are relatives of rural women. These hunters supply wildlife meat to wholesalers who then facilitate its distribution to urban centers, including major markets in Accra (Mendelson et al., \u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eWomen play a dominant role in the downstream segments of the chain\u0026ndash;specifically in the processing, storage, preparation, and retailing of wildlife meat. Yet, despite their numerical dominance in these areas, women often have less control over the more profitable components such as hunting and transportation, which are largely male-dominated. This gendered division of labor contributes to economic disparities in earnings and influence within the trade (Wenham et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eThe relatively low capital requirement for entry into wildlife meat trading makes it an accessible economic opportunity for many women, especially in urban informal markets. Women account for approximately 85% of retail sales, particularly through street vending and chop bars. However, despite this prominent role, women traders often earn significantly less than their male counterparts. Furthermore, women typically face higher startup costs\u0026ndash;such as for purchasing cooking equipment or securing space in marketplaces\u0026ndash;while men, particularly hunters, incur minimal costs but retain a greater share of profits (Mendelson et al., \u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e). This economic asymmetry underscores the structural inequities within the trade, where women, though essential to its operation, remain economically marginalized.\u003c/p\u003e\n \u003cp\u003eGeographic factors such as urban demand, seasonal availability, and transportation access further influence the profitability and livelihood security of actors within the wildlife meat trade (Vitekere et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). These dynamics call for targeted policy interventions to improve equity and sustainability within the sector, especially for women who are central yet under-rewarded contributors. Interventions could include access to microfinance, formal recognition of women\u0026rsquo;s roles in value chains, and support for safer processing environments.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2. The Health Belief Model and Consumer Attitudes\u003c/h2\u003e\n \u003cp\u003eTo understand consumer attitudes toward wildlife meat consumption, especially during health crises such as the COVID-19 pandemic, the Health Belief Model (HBM) offers a valuable analytical framework. Originally developed in the 1950s to explain health-related behavior, HBM outlines six key constructs that influence individual decision-making: perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action, and self-efficacy (Champion \u0026amp; Skinner, \u003cspan class=\"CitationRef\"\u003e2008\u003c/span\u003e). These constructs are particularly relevant in the context of zoonotic outbreaks where food consumption behaviors shift in response to perceived disease risks.\u003c/p\u003e\n \u003cp\u003ePerceived susceptibility reflects how vulnerable consumers feel to contracting diseases such as COVID-19 through the consumption of wildlife meat. In pandemics, higher perceived susceptibility typically correlates with reduced consumption, as shown in previous studies on the Ebola outbreak in Ghana and Sierra Leone (Kuukyi et al., \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e; Sainge et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). Perceived severity\u0026ndash;concerns about the potential consequences of infection\u0026ndash;further amplifies behavioral change. When consumers view zoonotic diseases as life-threatening, they are more likely to adjust their dietary habits.\u003c/p\u003e\n \u003cp\u003eOn the other hand, perceived benefits may include the nutritional, cultural, or economic value of wildlife meat. These perceived gains can outweigh health concerns, especially where alternative protein sources are scarce or unaffordable (Jun \u0026amp; Jaafar, \u003cspan class=\"CitationRef\"\u003e2011\u003c/span\u003e). Perceived barriers, such as the high cost or unavailability of substitutes, can limit consumers\u0026rsquo; ability to shift behavior even when they are aware of risks (Kaptan \u0026amp; Kayısoglu, \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e). For instance, during COVID-19, many urban consumers reduced their wildlife meat intake due to fear of infection, but others continued consumption due to lack of options.\u003c/p\u003e\n \u003cp\u003eCues to action, such as public health messaging, community-level awareness, or visible illness, play a key role in triggering protective behaviors. Public advisories or media reports linking wildlife meat to COVID-19 likely influenced consumer decisions during the pandemic (Abukari \u0026amp; Kankam, \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). Similarly, self-efficacy\u0026ndash;an individual\u0026rsquo;s belief in their ability to take preventive action\u0026ndash;is shaped by income, education, and access to information. Lower-income groups, who may rely more heavily on wildlife meat for subsistence, may feel less capable of adjusting their consumption, even when aware of health risks (Liu et al., \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e; see also Galibourg et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eIntegrating the wildlife meat value chain with the Health Belief Model provides a nuanced understanding of how perceptions, risks, and structural constraints converge to shape consumption behavior during pandemics. While public health concerns often dominate narratives around zoonotic diseases, the continued reliance on wildlife meat for nutrition and income underscores the complexity of consumer attitudes and coping mechanisms.\u003c/p\u003e\n \u003cp\u003eImportantly, health risks are not limited to zoonotic viruses. The wildlife meat trade is associated with other dangers, including poor hygiene practices, unsafe food handling, and the presence of contaminants such as heavy metals and lead introduced during hunting (Gbogbo et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e; Oladayo et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). While some argue that the health risk from typical consumption levels in Ghana is low (Gbogbo et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e), these concerns remain central to risk perception. Understanding how consumers weigh these risks against cultural and economic imperatives is crucial for designing effective, context-specific interventions.\u003c/p\u003e\n \u003cp\u003eThis study, therefore, seeks to examine how these health belief dimensions shaped consumer attitudes during COVID-19 and the downstream effects on traders\u0026ndash;particularly women\u0026ndash;who form the backbone of the wildlife meat economy in urban Ghana.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3. Methodology","content":"\u003cp\u003eThis study investigates consumer attitudes and the socio-economic impacts of wildlife meat (commonly referred to as bushmeat) trade in the wake of the COVID-19 pandemic. To capture the spatial and economic diversity of this trade in urban Ghana, five markets in the Greater Accra Metropolitan Area (GAMA) were purposively selected: Makola, Agbogbloshie, Dome, Madina, and Adabraka. These markets span four municipal and metropolitan assemblies\u0026ndash;Accra Metropolitan Area, Ga East, Korle Klottey, and La Nkwantanang Madina\u0026ndash;representing both central and peri-urban trading hubs with active smoked wildlife meat commerce (see Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). The selection of these locations was guided by their prominence in the wildlife meat trade and the presence of varied consumer and trader dynamics, providing a representative cross-section of market conditions in Accra.\u003c/p\u003e\n\u003cp\u003eA concurrent mixed-methods design was adopted, integrating qualitative and quantitative approaches to ensure comprehensive analysis. Data were collected simultaneously between June and July 2023 through three instruments: (i) a structured survey for consumers, (ii) in-depth interviews with traders, and (iii) an observation checklist to document trade practices and environments.\u003c/p\u003e\n\u003cp\u003eFor the quantitative component, a total of 255 wildlife meat consumers were sampled using convenience and interval-based sampling techniques. Individuals were approached at every tenth count within the selected markets and screened for consumption of wildlife meat. Those who affirmed consumption were included, encompassing sellers, hawkers, and buyers. Face-to-face interviews were conducted in Twi, Ewe, or English, depending on respondent preference, with an average duration of 30 minutes. Data were digitally recorded using KoboCollect, a mobile-based data collection tool. To assess the reliability of the survey instrument, a Cronbach\u0026rsquo;s Alpha test was performed, yielding a score of 0.996. This high level of internal consistency indicates the robustness of the instrument in capturing reliable data on consumer perceptions and behaviours before, during, and after the pandemic.\u003c/p\u003e\n\u003cp\u003eThe qualitative strand comprised 10 in-depth interviews with female wildlife meat traders across the five markets. Participants were selected based on convenience and saturation principles (Hennink et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e), ensuring that thematic saturation was reached. Interviews were conducted after obtaining verbal informed consent and lasted between 20 and 30 minutes. The interview guide explored themes such as changes in consumer demand, coping strategies during the pandemic, perceptions of zoonotic risk, and the socio-economic implications of COVID-19. Alongside the interviews, structured observations were carried out in each market, resulting in 10 observational records that provided context on trading environments, meat types, pricing, hygiene, and sourcing practices.\u003c/p\u003e\n\u003cp\u003eQuantitative data were analyzed using SPSS and Microsoft Excel, applying both descriptive statistics (frequencies, percentages) and inferential analysis, particularly Chi-square tests, to identify significant patterns and associations in consumer behaviour. For the qualitative data, manual content analysis was employed. Interviews were transcribed verbatim into English, segmented by the study\u0026rsquo;s thematic objectives, and coded according to emergent themes. Responses were organized and frequency distributions were generated in Excel to identify dominant narratives. Verbatim quotes from participants were included to add depth and contextual richness to the findings.\u003c/p\u003e\n\u003cp\u003eBy combining consumer surveys, trader interviews, and observational insights, this methodological approach provided a holistic understanding of the wildlife meat trade and the interplay between public health concerns and livelihood realities in urban Ghana.\u003c/p\u003e"},{"header":"4. Wildlife meat consumption: Shifts in attitudes and trade dynamics","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003e4.1. Profile of participants\u003c/h2\u003e\n \u003cp\u003eThe demographic composition of wildlife meat consumers in Accra reveals notable gender and age patterns. Females constituted a larger share of respondents (58.4%) compared to males (41.6%), suggesting that women are key actors in the wildlife meat consumption market. The data also indicate that younger demographics are highly involved in consumption, with 25.9% of consumers aged 18\u0026ndash;24 and 30.6% aged 25\u0026ndash;34. This reflects a generational continuity in wildlife meat consumption practices, countering assumptions that the practice is limited to older or rural populations.\u003c/p\u003e\n \u003cp\u003eEthnic composition shows that Akans represent the largest consumer group (40.8%), which is consistent with documented preferences and cultural attachment to wildlife meat among this group. Ewes follow at 31.4%, Ga-Adangbes at 12.5%, and Guans at 6.7%, with other groups collectively comprising 8.6%. This distribution supports existing literature indicating that wildlife meat consumption cuts across various ethnicities but is often shaped by cultural norms and culinary traditions.\u003c/p\u003e\n \u003cp\u003eIn terms of education, most consumers have attained at least basic education, though 18% reported no formal schooling. This educational variation may have implications for how consumers interpret and respond to health messaging about zoonotic diseases. Employment data show a significant proportion of self-employed individuals (39.2%), with a notable 27% classified as unemployed, including retirees. Income levels were generally modest, with 38% earning less than GHS 500 per month and another 31% earning between GHS 500\u0026ndash;1,000, indicating that a considerable number of consumers operate within the lower-income bracket, which may influence purchasing decisions and risk perceptions.\u003c/p\u003e\n \u003cp\u003eAmong the wildlife meat traders interviewed, the majority (37.5%) were aged between 51\u0026ndash;60, with 25% aged 30\u0026ndash;40, and 12.5% aged above 61. The traders predominantly belonged to the Akan, Ewe, and Ga-Adangbe ethnic groups, mirroring the consumer base. Half of the respondents were married, while the rest were widowed (30%) or separated (20%). Importantly, 50% of traders identified as household heads, highlighting their role as primary income earners and the gendered economic significance of the trade. In terms of asset ownership, a relatively high proportion of traders possessed mobile phones (90%), TVs (70%), mobile money accounts (70%), and bank accounts (60%). Notably, 60% were subscribed to the national health insurance scheme\u0026ndash;an encouraging sign of health-seeking behaviour amidst broader livelihood precarity.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003e4.2. Nature of the wildlife meat trade\u003c/h2\u003e\n \u003cp\u003eThe wildlife meat trade in Accra is characterized by a regionally distributed supply network. In all five markets surveyed\u0026ndash;Makola, Agbogbloshie, Dome, Madina, and Adabraka\u0026ndash;the supply of wildlife meat originated from outside the Greater Accra Region. Traders reported sourcing their stock from distant regions such as Central, Eastern, and Ashanti, illustrating the spatial extent and inter-regional dependency of the trade. This wide-reaching network underscores the economic importance of wildlife meat not just within urban markets, but across regional rural-urban linkages.\u003c/p\u003e\n \u003cp\u003eTransportation and logistics play a pivotal role in shaping trade dynamics. Transporters\u0026ndash;typically men\u0026ndash;function as intermediaries between rural hunters and urban traders, although in some cases hunters deliver the meat directly using public transportation. The trade relies heavily on commercial vehicles, making it vulnerable to fluctuations in fuel prices, road conditions, and market accessibility (see Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). These logistics introduce both time and cost pressures on traders, which in turn influence the pricing and type of wildlife meat sold.\u003c/p\u003e\n \u003cp\u003eThe concept of \u0026ldquo;friction of distance\u0026rdquo; is evident in the average travel distance between supply areas and markets. For example, the shortest route\u0026ndash;from Mankessim (Central Region) to Accra\u0026ndash;covers about 110 km and takes 2\u0026ndash;3 hours by road. During fieldwork in June 2023, the average transport cost for this distance was approximately GHS 50 (USD 4.17). These costs, compounded by perishability risks, directly affect market dynamics and profit margins.\u003c/p\u003e\n \u003cp\u003eDue to spoilage risks associated with transporting fresh meat over long distances, smoked wildlife meat has become the preferred product among both traders and consumers. As one trader from Madina Market explained:\u003c/p\u003e\n \u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003e\u003cem\u003eWhen you buy fresh wildlife meat, the meat will get bad by the time you travel and reach the market in a few days. This affects how much you sell it. Hence, it is better to deal with smoked ones because they last longer.\u003c/em\u003e (55-year-old female wildlife meat trader, Madina Market)\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003eThis preference highlights the adaptive strategies employed by traders to manage perishability and maintain economic viability. The dominance of smoked wildlife meat also reflects consumer trust in its safety, taste, and storage convenience. However, it may also obscure visibility into hygiene and food safety issues during the processing stage\u0026ndash;issues which became more significant during the COVID-19 pandemic, as health concerns reshaped consumption choices.\u003c/p\u003e\n \u003cp\u003eIn short, the wildlife meat trade in urban Ghana is shaped by a combination of gender roles, transport logistics, economic constraints, and consumer attitudes toward product quality and safety. These dynamics became more complex during and after the COVID-19 pandemic, as changing health beliefs and public perception influenced both consumption patterns and the livelihoods of those who depend on this informal trade.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e4.3. Wildlife meat consumption pattern before, during and after COVID-19\u003c/h2\u003e\n \u003cp\u003eThe study revealed complex and evolving patterns in wildlife meat consumption across the three phases of the COVID-19 pandemic\u0026ndash;before, during, and after\u0026ndash;highlighting significant shifts in consumer attitudes and behaviours that directly affected the viability of the wildlife meat trade. Prior to the pandemic, wildlife meat consumption was widespread and culturally embedded, with 100% of respondents (N\u0026thinsp;=\u0026thinsp;255) reporting regular consumption. It was widely regarded as a nutritious delicacy despite longstanding concerns about hygiene and zoonotic diseases, including Ebola (Gbogbo et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e; Oladayo et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). At this time, the wildlife meat trade was thriving and served as a vital source of income, particularly for women traders.\u003c/p\u003e\n \u003cp\u003eHowever, consumption declined sharply during the height of the pandemic. Only 27% of respondents continued to consume wildlife meat during COVID-19, with a slight recovery to 47% after the pandemic. These trends reflect widespread uncertainty, fear of disease transmission, and market disruptions. Awareness of the zoonotic origin of COVID-19 was nearly universal, with 98% of respondents acknowledging this link (Huang et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). Although 63.9% were skeptical that wildlife meat specifically contributed to the transmission of the virus, 36% associated its consumption with an increased risk of infection. These perceptions, combined with supply shortages and elevated prices, led to a dramatic drop in consumption and a corresponding decline in income for many traders.\u003c/p\u003e\n \u003cp\u003eWhile health concerns drove some consumers away from bushmeat, others continued to eat it, citing benefits such as nutritional value, taste, and cultural significance\u0026ndash;an outcome that aligns with the Health Belief Model\u0026rsquo;s emphasis on perceived benefits and risks (Champion \u0026amp; Skinner, \u003cspan class=\"CitationRef\"\u003e2008\u003c/span\u003e; Kuukyi et al., \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e). Consumption patterns also varied by location (see Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). To quantify these changes, percentage change analysis was conducted for each market using the formula:\u003c/p\u003e\n \u003cp\u003ePercentage change =\u003c/p\u003e\n \u003cdiv id=\"Equa\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e$$\\:\\left(\\frac{Consumption\\:during/after\\:COVID-19-Consumption\\:before\\:COVID-19}{Consumption\\:before\\:COVID-19}\\right)*100$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003eThe analysis revealed significant market-level variation. Overall, wildlife meat consumption decreased by approximately 73.3% during COVID-19 and 53% post-COVID. The Adabraka market showed the smallest decline\u0026ndash;59% during and 34% after the pandemic\u0026ndash;while Makola and Agbogbloshie markets saw the steepest declines, each reporting a 77% drop during COVID-19 (see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eVariations in wildlife meat consumption patterns based on market location\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eMarkets\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eWildlife meat consumption pattern \u003cem\u003efrequency (%)\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003ePercentage change in consumption\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e(%)\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBefore COVID-19\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDuring COVID-19\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAfter COVID-19\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBefore-During\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBefore-After\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdabraka\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAgbogbloshie\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDome\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMadina\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMakola\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e255 (100)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e68 (27)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e119 (47)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e-73\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e-53\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eSource: Authors\u0026rsquo; construct (2024).\u003c/p\u003e\n \u003cp\u003eThe decline in wildlife meat consumption during and after COVID-19 raises concerns about the sustainability of the wildlife meat trade. Recent trends show a decrease in the number of traders in markets, reflecting the impact of the pandemic on trade activities. For example, the Madina market, which recorded one of the highest consumption declines, has witnessed a significant reduction in the number of wildlife meat traders, as many have left the trade for other businesses. One trader recounted:\u003c/p\u003e\n \u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003e\u003cem\u003eWe are not making money, so many have stopped... In this market, two other traders who sell wildlife meat don\u0026rsquo;t come regularly anymore because the market is bad. People are not buying. One came two weeks ago but hasn\u0026rsquo;t returned yet. Some of us are managing to continue (55-year-old female wildlife meat trader, Madina market).\u003c/em\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003eThis testimony echoes the concerns raised by Ripple et al. (\u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e), who warned of an impending \u0026ldquo;wildlife meat crisis.\u0026rdquo; While overhunting had been seen as the primary threat, consumer perceptions of zoonotic disease risk\u0026ndash;particularly in the wake of COVID-19\u0026ndash;have emerged as a new and equally significant challenge to the trade\u0026rsquo;s survival.\u003c/p\u003e\n \u003cp\u003eGender differences in consumption patterns were also evident. Before the pandemic, 58.4% of wildlife meat consumers were female and 41.6% were male. However, during the pandemic, men were more likely to continue consumption (60%) compared to women (40%). This trend continued after the pandemic, with male consumption rising slightly to 61% and female consumption falling to 39%. This statistically significant difference (p\u0026thinsp;=\u0026thinsp;0.007) suggests that women were more responsive to perceived health risks, consistent with the Health Belief Model, while men may have prioritized perceived benefits such as taste and protein value (Sainge et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e; see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eWildlife meat consumption pattern based on gender\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eWildlife meat consumption\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFrequency (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e Value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eBefore COVID-19\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e106 (41.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e149 (58.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e255 (100)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eDuring COVID-19\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41 (60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e13.386\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27 (40)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e68 (27)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eAfter COVID-19\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e73 (61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e35.926\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46 (39)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e119 (47)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eSource: Authors\u0026rsquo; construct (2024).\u003c/p\u003e\n \u003cp\u003eThus, the wildlife meat consumption landscape during and after COVID-19 was shaped by intersecting factors including public health concerns, access and affordability, shifting attitudes, and gendered responses to risk. These dynamics underscore the vulnerability of informal food economies to global health crises and the need for context-sensitive policy interventions.\u003c/p\u003e\n \u003cp\u003eThe trajectory of wildlife meat consumption in Accra across the pre-COVID, peak pandemic, and post-COVID periods reveals a nuanced interplay of health concerns, economic shifts, and evolving consumer attitudes (see Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e). While wildlife meat was widely consumed before the pandemic due to its affordability, cultural significance, and perceived nutritional value, the onset of COVID-19 dramatically altered consumption dynamics.\u003c/p\u003e\n \u003cp\u003eDuring the pandemic, a sharp decline in wildlife meat consumption was reported, influenced by a combination of health-related fears and structural constraints. One of the most significant contributing factors was the scarcity of wildlife meat during lockdowns. With movement restrictions disrupting supply chains, hunters and transporters were unable to deliver meat regularly to urban markets. As availability declined, prices soared, reversing bushmeat\u0026rsquo;s status as an affordable protein source relative to options like cattle, goat, or fish (Kuukyi et al., \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e). As cost-of-living pressures intensified, many lower-income consumers shifted to cheaper alternatives such as eggs, plant-based proteins, and fish (Morris et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). One consumer captured this reality succinctly: \u003cem\u003e\u0026ldquo;You buy what your money can buy, so I often bought eggs during COVID-19 because I couldn\u0026rsquo;t afford bushmeat\u0026rdquo; (44-year-old male wildlife meat consumer, Makola market).\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eBeyond availability and cost, the fear of contracting COVID-19 from consuming wildlife meat played a major role in dampening demand. Influenced by public health campaigns and media messaging, many consumers associated wildlife meat with zoonotic transmission. These warnings, reminiscent of health advisories issued during previous Ebola outbreaks, acted as strong deterrents. As one respondent explained:\u003c/p\u003e\n \u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003e\u003cem\u003eHealth practitioners and researchers told us that eating wildlife meat could lead to contracting COVID-19 and even other diseases like Ebola. I stopped eating wildlife meat during COVID-19 because of that (30-year-old female wildlife meat consumer, Agbogbloshie market).\u003c/em\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003eHowever, these fears were not uniformly sustained. Over time, a portion of the population resumed consumption, citing personal experience and the absence of adverse health effects. This shift suggests that the \u0026ldquo;cues to action\u0026rdquo; necessary to maintain behavioural change were either weak or inconsistently reinforced. As another consumer reflected:\u003c/p\u003e\n \u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003e\u003cem\u003eWhen COVID-19 broke, we heard you could contract the pandemic when you consume meat. However, I have consumed different types of meat, including bushmeat, but I never contracted COVID-19 or any other diseases (26-year-old male, wildlife meat consumer, Dome Market).\u003c/em\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003eAccording to the Health Belief Model, this erosion of perceived susceptibility, due to the absence of reinforcing messages or observable negative consequences, contributed to a gradual reversion to pre-pandemic behaviours (Morris et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). Still, a notable subset of consumers continued to avoid wildlife meat out of caution. One woman emphasized her sustained abstinence: \u003cem\u003e\u0026ldquo;Health practitioners said wildlife meat could cause diseases like COVID-19 or Ebola. I stopped eating it [bushmeat] during the pandemic and I still have not resumed because of those warnings\u0026rdquo;.\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eFood safety concerns\u0026ndash;particularly regarding the source and handling of bushmeat\u0026ndash;also shaped consumption choices. Several respondents expressed distrust in hunting methods that involved firearms or poisons, which could contaminate meat with heavy metals like lead and zinc (Gbogbo et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). Others raised concerns about unhygienic processing and storage conditions, which increase the risk of contamination from bacteria, parasites, and viruses (Kamogne-Tagne et al., 2022; Oladayo et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). These anxieties, aligned with the HBM\u0026rsquo;s \u0026ldquo;perceived severity\u0026rdquo; and \u0026ldquo;perceived barriers\u0026rdquo; constructs, likely reinforced caution among health-conscious consumers.\u003c/p\u003e\n \u003cp\u003eDespite these concerns, wildlife meat consumption did not disappear. Some consumers continued to eat it out of habit or for its perceived health and taste benefits. Prior to COVID-19, the main motivators for consumption included affordability, taste, availability in rural areas, and low fat content (Kuukyi et al., \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e). Post-pandemic, these factors remained relevant, but new considerations such as price volatility and food safety featured more prominently in decision-making. Notably, 18% of respondents could not specify a reason for their continued consumption, and 16% were unsure\u0026ndash;highlighting the complexity of attitudes toward wildlife meat and the influence of deeply embedded social norms.\u003c/p\u003e\n \u003cp\u003eInterestingly, this study challenges earlier assumptions about consistent wildlife meat availability. In contrast, traders and consumers alike reported marked shortages during and after COVID-19, compounding the effects of fear and rising prices on the viability of the trade. For many traders\u0026ndash;particularly women who dominate the retail end of the chain\u0026ndash;this decline in demand translated into lost income, reduced sales, and an uncertain future.\u003c/p\u003e\n \u003cp\u003eIn short, wildlife meat consumption patterns in Accra during and after COVID-19 were shaped by an intricate mix of perceived risk, economic strain, product availability, and behavioural adaptation. These findings not only affirm the relevance of the Health Belief Model in interpreting consumer decision-making during health crises but also underscore the importance of integrating public health messaging with livelihood considerations in future pandemic preparedness efforts.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"5. Livelihood and socio-economic challenges of women in the wildlife meat trade","content":"\u003cp\u003eWomen\u0026rsquo;s engagement in the wildlife meat trade in Ghana is largely driven by its income-generating potential, echoing earlier findings by Wenham et al. (\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This study confirms that wildlife meat trading provides a crucial source of livelihood, especially for women who serve as primary income earners in their households. Before the onset of COVID-19, the trade was highly profitable due to consistent consumer demand, low entry barriers, and relatively high profit margins. Women traders used income from the trade to cover essential living costs such as school fees, rent, and medical bills. Monthly earnings typically ranged between GHS 500 (USD 41.67) and GHS 2,000 (USD 166.67), depending on market volume and seasonal fluctuations. As noted by Fahad et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), income from this trade also allowed women to invest in assets like mobile phones, televisions, and radios, which not only enhanced their quality of life but also served as leverage in accessing informal credit, savings schemes, and loans.\u003c/p\u003e\u003cp\u003eHowever, the COVID-19 pandemic significantly disrupted this economic stability. The sharp decline in wildlife meat consumption directly impacted women's earnings, pushing many into financial distress. One trader at the Agbogbloshie market remarked: \u0026ldquo;\u003cem\u003eI sell for money, and this is the only business I do. If not for the money I gain from selling, I would not be sitting here and suffering. My family\u0026rsquo;s survival depends on how much I earn\u0026rdquo;\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eThe pandemic\u0026rsquo;s impact extended beyond income loss. Women traders faced mounting socio-economic pressures such as dwindling access to credit, collapsing supply chains, and heightened financial insecurity (Amankwaa, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Market closures and lockdowns meant many traders were unable to work, leaving them without income for extended periods (Fahad et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Those who relied solely on wildlife meat sales faced the greatest strain. A 55-year-old trader at Madina Market described the situation:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e\u003cem\u003eMy last born is in one of the colleges of education in the Volta region (Amedzofe Training College); the father does not care about her, so I sell to look after her. However, because of COVID-19, my sales have dropped, and there is no money in the system for people to buy again, so I am suffering in terms of money now. (55-year-old female wildlife meat trader, Madina Market)\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTraders struggled to maintain their businesses and provide for their families. Many lacked basic infrastructure, such as refrigeration or storage, and were unable to preserve unsold meat, resulting in significant losses. A 61-year-old trader from the Madina market recounted: \u0026ldquo;\u003cem\u003eDuring COVID-19, we were asked to stay home, so I had no money and food but managed till it was over.\u0026rdquo;\u003c/em\u003e\u003c/p\u003e\u003cp\u003eGender inequalities further exacerbated the crisis. Many women lacked collateral and formal assets to qualify for bank loans or government support, leaving them highly vulnerable to financial shocks (Wrigley-Asante, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Amankwaa, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Consequently, many relied on informal networks for survival\u0026ndash;borrowing from friends, family, or social groups. As one trader shared: \u0026ldquo;\u003cem\u003eBecause of COVID-19, most of the goods I bought got spoiled, and my business almost collapsed, so I borrowed money from a friend to start over. I'm still paying.\u0026rdquo; (55-year-old wildlife meat trader, Madina Market).\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe pandemic also disrupted transportation networks essential for sourcing wildlife meat. Travel restrictions made it difficult for hunters and transporters to move goods, leading to irregular supplies and inflated costs. Traders bore the brunt of these disruptions, with rising fuel prices further diminishing their already slim profit margins. One trader shared her experience: \u0026ldquo;\u003cem\u003eAcquiring wildlife meat from the hunters became difficult. Drivers charged high fees due to rising fuel prices, using up most of my profit\u0026rdquo; (55-year-old female wildlife meat trader, Madina Market).\u003c/em\u003e\u003c/p\u003e\u003cp\u003eAs economic pressures mounted, some women exited the trade entirely, while others struggled to stay afloat. The burden was particularly acute for women with fewer socio-economic resources, who lacked the buffers\u0026ndash;such as savings, diversified income sources, or household support systems\u0026ndash;that could help absorb financial shocks. The cumulative effect of income loss, increased costs, and limited institutional support has left many women in the wildlife meat trade in a precarious position, underlining the urgent need for targeted interventions to support post-pandemic recovery and economic resilience.\u003c/p\u003e"},{"header":"6. Coping mechanisms and support systems for wildlife meat traders under COVID-19","content":"\u003cp\u003eIn response to the socio-economic disruptions brought about by the COVID-19 pandemic, women engaged in the wildlife meat trade in Accra adopted a range of coping strategies. Insights from in-depth interviews reveal how traders navigated financial hardship, supply chain disruptions, and declining consumer demand through both economic and psychological mechanisms.\u003c/p\u003e\u003cp\u003eOne of the most prominent strategies was the use of personal savings. Prior to the pandemic, many women had participated in informal savings schemes such as \u003cem\u003esusu\u003c/em\u003e groups and microfinance programs, accumulating funds intended for business reinvestment or household needs. However, as lockdowns restricted trading activity and income streams dried up, these savings became essential lifelines. A wildlife meat trader explained: \u003cem\u003eOur leaders used COVID-19 to spoil business for us market women. I spent the savings I planned to use for something better during COVID-19 (45-year-old female wildlife meat trader, Dome Market).\u003c/em\u003e\u003c/p\u003e\u003cp\u003eIn addition to depleting their savings, many traders diversified their income by engaging in alternative livelihood activities. High-demand products like face masks became temporary substitutes for lost revenue from wildlife meat sales. Others expanded their offerings to include dried fish, cow meat, pepper, and other staples. This form of livelihood diversification helped mitigate the financial shock of reduced wildlife meat consumption. As one trader explained:\u003c/p\u003e\u003cp\u003e\u003cem\u003eDuring COVID-19, I sold nose masks since that was what everybody was selling. I needed money to survive since my [bushmeat] business was not fetching again. (40-year-old female wildlife meat trader, Makola market).\u003c/em\u003e\u003c/p\u003e\u003cp\u003eAnother trader added:\u003c/p\u003e\u003cp\u003e\u003cem\u003eI sold many things in addition to the wildlife meat because people were not purchasing the bushmeat. You won't get anything if you want to depend on the wildlife meat alone. I sold dry and fried fish from Aboatoase, cow meat, pepper, etc\u0026rdquo; (45-year-old female wildlife meat trader, Adabraka market).\u003c/em\u003e\u003c/p\u003e\u003cp\u003eBorrowing money from family and friends was another critical coping strategy. Despite the risks of personal indebtedness and strained relationships, many traders saw informal borrowing as a necessary survival tactic. These social networks became crucial buffers in the absence of formal support mechanisms. This behaviour is reflective of the Health Belief Model's construct of \u003cem\u003eperceived benefits\u003c/em\u003e, where individuals make calculated decisions in times of crisis based on available options and expected outcomes (Hossain, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Levine, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eNotably, external institutional support was largely absent. Many traders reported receiving no assistance from local authorities, despite continued obligations to pay daily tolls and levies. The lack of support reinforced a sense of abandonment and compelled traders to rely on their own resources. As one trader lamented:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e\u003cem\u003eThe district assembly comes daily to give us chits and take tolls, but they do not even care about renovating the shed we are selling under. We depend on ourselves because we don\u0026rsquo;t have anyone to depend on. I have decided to focus on my selling and pray that God helps me; I don\u0026rsquo;t care about COVID-19 or any politician (55-year-old female wildlife meat trader, Madina market).\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThis mindset of self-reliance also signals a deeper form of \u003cem\u003epsychological adaptation\u003c/em\u003e, as traders reoriented their outlooks to focus on personal resilience and self-efficacy. Drawing from the Health Belief Model (Champion \u0026amp; Skinner, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), this sense of agency empowered traders to take proactive steps to sustain their livelihoods. These psychological shifts became as vital as financial strategies, shaping how traders responded to ongoing uncertainties and setbacks.\u003c/p\u003e\u003cp\u003eThe coping strategies adopted by wildlife meat traders reflect broader patterns of resilience and adaptability documented in crisis literature (Nasution et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Pahl-Wostl et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These women not only managed short-term economic shocks but also demonstrated transformative learning\u0026ndash;adjusting behaviours, expectations, and business models to meet new realities. Their responses offer valuable lessons for understanding informal sector resilience and the critical need for targeted institutional support in future public health and economic crises.\u003c/p\u003e"},{"header":"7. Conclusion","content":"\u003cp\u003eThis study has examined shifting consumer attitudes toward wildlife meat consumption during and after the COVID-19 pandemic and assessed the socio-economic impact on women traders in Ghana\u0026rsquo;s urban markets. The findings show that while wildlife meat remains culturally significant and economically vital, the pandemic introduced a major rupture in consumption patterns and trade dynamics. The outbreak heightened public awareness of zoonotic disease risks, resulting in a notable decline in consumption, particularly among female consumers who exhibited higher perceived susceptibility and severity\u0026ndash;key constructs of the Health Belief Model (HBM).\u003c/p\u003e\u003cp\u003eThe HBM provided a useful framework for understanding how individuals weighed risks and benefits during the crisis. Perceived barriers, such as price inflation and scarcity, further disincentivized consumption, while cues to action\u0026ndash;such as media messaging and public health warnings\u0026ndash;reinforced behavioural change. Conversely, a segment of the population, mostly men, continued consuming wildlife meat based on perceived benefits, such as taste and nutritional value, suggesting that behaviour during health crises is shaped by a complex balance of beliefs, economic conditions, and social norms.\u003c/p\u003e\u003cp\u003eWomen traders, who form the backbone of the wildlife meat trade, were disproportionately affected by reduced demand and mobility restrictions. In the absence of external support, they demonstrated considerable resilience through savings withdrawals, business diversification, and psychological adaptation (Amankwaa \u0026amp; Amponsah, 2024). Yet, their vulnerability was exacerbated by limited access to credit and inadequate market infrastructure.\u003c/p\u003e\u003cp\u003ePolicy interventions are urgently needed to support these traders and promote safer, more sustainable practices (Galibourg et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Financial support from the Ministry of Trade and Industry and Metropolitan/Municipal Assemblies\u0026ndash;such as interest-free loans, grants, and tax exemptions\u0026ndash;would enable affected traders to rebuild their businesses. Moreover, promoting the domestication of wildlife through awards and national events could reduce dependence on wild populations while ensuring stable market supply.\u003c/p\u003e\u003cp\u003eHealth education initiatives led by the Ghana Health Service should also be expanded, targeting hunters, processors, and traders with training in food safety and zoonotic risk mitigation. Certification schemes tied to compliance can enhance public trust and accountability. Additionally, improved market infrastructure\u0026ndash;including shaded stalls, cold storage, and reliable transportation\u0026ndash;would alleviate supply chain bottlenecks and support hygienic trading practices.\u003c/p\u003e\u003cp\u003eFinally, public awareness campaigns are crucial to dispel misinformation, reduce stigma, and encourage informed consumption. By integrating the behavioural insights of the Health Belief Model into policy design, stakeholders can more effectively influence public attitudes, improve resilience in informal trade sectors, and safeguard public health. Supporting women traders in this process is not only a matter of equity but also essential to sustaining a vital source of income for many urban households in Ghana and similar contexts across sub-Saharan Africa.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are greatly indebted to all our participants who allowed us into their homes and workplaces to undertake this research. We are thankful to the two anonymous reviewers for their useful comments.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Interest Statement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by IDRC through the Women RISE initiative project.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eResearch ethics clearance was granted by the University of Ghana\u0026rsquo;s Ethics Committee for Humanities. The study was conducted in accordance with the ethical standards for research involving human participants, following the guidelines of the Ethics Committee for the Humanities, University of Ghana.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study involved human participants. All participants were informed about the purpose of the study and they provided their voluntary, informed consent prior to participation and data collection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trial Number\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eClinical trial number: not applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003e\u003cspan\u003eAbukari, H., \u0026amp; Kankam, B. (2023). 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(2008). \u003cem\u003eMen are poor, but women are poorer\u003c/em\u003e. Gendered poverty and survival.\u0026nbsp;\u003c/span\u003e\u003cspan\u003estrategies in the Dangme West District of Ghana \u003cem\u003eNorsk Geografisk Tidsskrift-Norwegian Journal of Geography\u003c/em\u003e, \u003cem\u003e62\u003c/em\u003e(3), 161\u0026ndash;170. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/00291950802335541\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"human-ecology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"huec","sideBox":"Learn more about [Human Ecology](http://link.springer.com/journal/10745)","snPcode":"10745","submissionUrl":"https://submission.nature.com/new-submission/10745/3","title":"Human Ecology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Wildlife meat trade, Health belief model, COVID-19 pandemic, Socio-economic dynamics, Gender","lastPublishedDoi":"10.21203/rs.3.rs-7024348/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7024348/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis paper explores how consumer attitudes toward wild game meat consumption shifted during and after the COVID-19 pandemic and examines the resulting effects on the wildlife trade in Ghana. Framed within the Health Belief Model and utilizing a mixed-methods approach, the paper combines survey data from 255 consumers with insights from 10 in-depth interviews with traders operating across five major markets in Accra. Findings reveal that the wild meat value chain \u0026ndash; comprising hunters, transporters, traders, and consumers \u0026ndash; experienced significant disruption due to pandemic-related fears and mobility restrictions, leading to a marked decline in demand. This downturn had profound socio-economic consequences, particularly for women who dominate retail-level trading, resulting in income loss and business closures. In response, many traders adopted coping strategies such as relying on personal savings and psychological resilience. The paper underscores the urgent need for targeted government support, including financial assistance and investment in basic market infrastructure, to enable a more equitable and resilient recovery of the sector. These observations have broader implications for public health messaging, conservation policy, and gender-sensitive economic planning in post-pandemic contexts.\u003c/p\u003e","manuscriptTitle":"Wild Meat Consumption in the Wake of COVID-19: Shifts in Attitudes and Trade Dynamics in Ghana","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-11 17:01:15","doi":"10.21203/rs.3.rs-7024348/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-25T22:34:02+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-25T19:02:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"280376841223138923340901412359630952423","date":"2025-11-29T16:48:38+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-08T15:07:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"136050470756734118075761998394853746121","date":"2025-08-05T16:02:17+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-09T12:13:45+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-07T12:05:24+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-07T12:04:26+00:00","index":"","fulltext":""},{"type":"submitted","content":"Human Ecology","date":"2025-07-02T02:19:41+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"human-ecology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"huec","sideBox":"Learn more about [Human Ecology](http://link.springer.com/journal/10745)","snPcode":"10745","submissionUrl":"https://submission.nature.com/new-submission/10745/3","title":"Human Ecology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"e4e1ad59-2f46-4f4d-8dd8-0cb8803f0c16","owner":[],"postedDate":"July 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-02T02:38:11+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-11 17:01:15","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7024348","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7024348","identity":"rs-7024348","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}