Mapping Global Bushmeat Activities to Improve Zoonotic Spillover Surveillance by Using Geospatial Modeling

Abstract

Human populations that hunt, butcher, and sell bushmeat (bushmeat activities) are at increased risk for zoonotic pathogen spillover. Despite associations with global epidemics of severe illnesses, such as Ebola and mpox, quantitative assessments of bushmeat activities are lacking. However, such assessments could help prioritize pandemic prevention and preparedness efforts. We used geospatial models that combined published data on bushmeat activities and ecologic and demographic drivers to map the distribution of bushmeat activities in rural regions globally. The resulting map had high predictive capacity for bushmeat activities (true skill statistic = 0.94). The model showed that mammal species richness and deforestation were principal drivers of the geographic distribution of bushmeat activities and that countries in West and Central Africa had the highest proportion of land area associated with bushmeat activities. These findings could help prioritize future surveillance of bushmeat activities and forecast emerging zoonoses at a global scale.

Keywords: Ebola; bushmeat; conservation; deforestation; disease outbreaks; hemorrhagic fever; mammals; mpox; pandemics; surveillance; viruses; wild meat; zoonoses.

Figure 1

Geographic distribution of articles from the literature used to model a map of global bushmeat activities (hunting, preparing, and selling bushmeat) to improve zoonotic spillover surveillance. We extracted data from 76 articles. Red dots indicate occurrences of bushmeat activities (n = 221) in 38 countries, and colored shading indicated the number of articles extracted per country.

Figure 2

Model prediction and uncertainty maps for model of global bushmeat activities (hunting, preparing, and selling bushmeat) to improve zoonotic spillover surveillance. A) Distribution of bushmeat activities in the tropical and subtropical regions from an ensemble of 3 model predictions using a hierarchical binomial model with spatial autocorrelation. B) Map illustrating the uncertainty of predicted bushmeat activities represented by the SD of each pixel. Each pixel represents a 5 × 5 km area.

Figure 3

Predicted priority regions for future survey efforts in urban areas as determined by a model of global bushmeat activities (hunting, preparing, and selling bushmeat) to improve zoonotic spillover surveillance. The 100 priority locations identified are indicated by the necessity for surveillance, a previously described measure (30). Color and size of dots indicate high to low priority of needed surveillance efforts.