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. 2025 Jul 1;20(7):e0327590.
doi: 10.1371/journal.pone.0327590. eCollection 2025.

Awareness campaigns and strengthened prevention as alternatives to banning: Preventing zoonotic diseases from wildlife in the Democratic Republic of Congo

Affiliations

Awareness campaigns and strengthened prevention as alternatives to banning: Preventing zoonotic diseases from wildlife in the Democratic Republic of Congo

Marc K Yambayamba et al. PLoS One. .

Abstract

Background: The Democratic Republic of Congo (DRC) faces a rising frequency of emerging infectious diseases outbreaks such as Ebola and Mpox. Wild meat consumption is considered a risk factor due to increased contact with wild animals. This study aimed to identify sociodemographic characteristics associated with wild meat consumption, assess the perceived risk of infectious diseases among consumers, and investigate attitudes towards selective measures to control disease spillover from wildlife.

Methods: A cross-sectional survey was conducted from June to August 2022 in four major cities: Kinshasa (Kinshasa), Kindu (Maniema), Lodja (Sankuru), and Boende (Tshuapa). Adults aged 18 years or older participated through a pre-tested questionnaire. Data included demographic characteristics, wild meat consumption behaviors, zoonotic disease risk perception, and potential human-wildlife disease prevention measures. The latter included measures such as law enforcement, education, and awareness campaigns, investing in disease prevention, strengthening response, and banning wild meat. Multivariable logistic regression was used to analyze associations between demographics, consumption, and risk perception.

Findings: Of 2,163 respondents, 59% were male, and 38% were aged 26-35. Wild meat consumption was reported by 86%. The main reason for consumption across cities was the meat taste (76%). Overall, only 36% of wild meat consumers perceived themselves to be at risk of a zoonotic disease. The highest risk perception was reported to be as high as 92% in Boende. Residents of Lodja had higher odds of wild meat consumption (OR: 11.4, CI: 6.35-21.40) compared to Kinshasa followed by those living in Kindu (1.61, 1.09-2.37), this association was also statistically significant in Boende. Risk perception was higher in Boende (OR: 5.26, CI: 1.72-15.0) and lower in Lodja (OR: 0.25, CI: 0.09-0.60) compared to Kinshasa. Knowing a family member or a relative infected with zoonotic disease increased risk perception (OR: 5.55, CI: 2.29-13.40). More than 70% of respondents supported measures such as awareness campaigns, increased disease prevention budgets, and law enforcement. Banning wild meat consumption was least supported across cities.

Conclusion: The findings highlight that wild meat consumption is quite homogenous with regards to sociodemographic characteristics, only the city of residence emerged as a significant factor. However, the risk perception is very low. Increased awareness campaigns and biosafety measures along the value chain would contribute to the prevention of zoonotic diseases originating from wildlife.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Map of the Democratic Republic of the Congo showing study provinces.
Provinces highlighted in blue—Kinshasa, Tshuapa, Sankuru, Maniema, and Tshopo—were targeted for data collection and analysis (Map created using in R software using open data).
Fig 2
Fig 2. Participants’ opinions on proposed control measures for preventing zoonotic disease transmission by city.
Stacked bar charts display the percentage of respondents in Boende, Kinshasa, Kindu, and Lodja who rated their level of agreement with five intervention strategies using a 5-point Likert scale (1 = strongly disagree to 5 = strongly agree). The proposed measures include awareness/education campaigns, investment in disease prevention, strengthening disease response, law enforcement, and banning wild meat. Sums may exceed one hundred because rounding.

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References

    1. Hilderink MH, de Winter II. No need to beat around the bushmeat-The role of wildlife trade and conservation initiatives in the emergence of zoonotic diseases. Heliyon. 2021;7(7):e07692. doi: 10.1016/j.heliyon.2021.e07692 - DOI - PMC - PubMed
    1. Peros CS, Dasgupta R, Kumar P, Johnson BA. Bushmeat, wet markets, and the risks of pandemics: Exploring the nexus through systematic review of scientific disclosures. Environ Sci Policy. 2021;124:1–11. doi: 10.1016/j.envsci.2021.05.025 - DOI - PMC - PubMed
    1. McNamara J, Robinson EJZ, Abernethy K, Midoko Iponga D, Sackey HNK, Wright JH, et al. COVID-19, Systemic Crisis, and Possible Implications for the Wild Meat Trade in Sub-Saharan Africa. Environ Resour Econ (Dordr). 2020;76(4):1045–66. doi: 10.1007/s10640-020-00474-5 - DOI - PMC - PubMed
    1. Jones KE, Patel NG, Levy MA, Storeygard A, Balk D, Gittleman JL, et al. Global trends in emerging infectious diseases. Nature. 2008;451(7181):990–3. doi: 10.1038/nature06536 - DOI - PMC - PubMed
    1. Wegner GI, Murray KA, Springmann M, Muller A, Sokolow SH, Saylors K, et al. Averting wildlife-borne infectious disease epidemics requires a focus on socio-ecological drivers and a redesign of the global food system. EClinicalMedicine. 2022;47:101386. doi: 10.1016/j.eclinm.2022.101386 - DOI - PMC - PubMed