BMC Public Health (Feb 2024)
An experimental game to assess hunter’s participation in zoonotic diseases surveillance
Abstract
Abstract Background Strengthening the surveillance of zoonotic diseases emergence in the wild meat value chains is a critical component of the prevention of future health crises. Community hunters could act as first-line observers in zoonotic pathogens surveillance systems in wildlife, by reporting early signs of the possible presence of a disease in the game animals they observe and manipulate on a regular basis. Methods An experimental game was developed and implemented in a forested area of Gabon, in central Africa. Our objective was to improve our understanding of community hunters' decision-making when finding signs of zoonotic diseases in game animals: would they report or dissimulate these findings to a health agency? 88 hunters, divided into 9 groups of 5 to 13 participants, participated in the game, which was run over 21 rounds. In each round the players participated in a simulated hunting trip during which they had a chance of capturing a wild animal displaying clinical signs of a zoonotic disease. When signs were visible, players had to decide whether to sell/consume the animal or to report it. The last option implied a lowered revenue from the hunt but an increased probability of early detection of zoonotic diseases with benefits for the entire group of hunters. Results The results showed that false alerts—i.e. a suspect case not caused by a zoonotic disease—led to a decrease in the number of reports in the next round (Odds Ratio [OR]: 0.46, 95% Confidence Interval [CI]: 0.36–0.8, p < 0.01). Hunters who had an agricultural activity in addition to hunting reported suspect cases more often than others (OR: 2.05, 95% CI: 1.09–3.88, p < 0.03). The number of suspect case reports increased with the rank of the game round (Incremental OR: 1.11, CI: 1.06–1.17, p < 0.01) suggesting an increase in participants’ inclination to report throughout the game. Conclusion Using experimental games presents an added value for improving the understanding of people’s decisions to participate in health surveillance systems.
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