Bushmeat consumption in Guinea: implications for public health and one health perspective
Bibliographic record
Abstract
Introduction: bushmeat is an important source of protein and income for many communities in developing countries, although bushmeat-related activities have been associated with many outbreaks of infectious diseases. In Guinea, its consumption attracted increasing attention since the Ebola epidemic from 2013 to 2016. However, estimates of its national scale consumption are lacking. This study explored the bushmeat consumption in urban areas of Guinea to guide public policies and interventions from a One Health perspective. Methods: the survey was conducted among 901 individuals aged 18 years and over from 458 households across the country's eight administrative regions. A two-stage random sampling method was used to select households. Data were collected through a questionnaire on socioeconomic status, sociodemographic characteristics, bushmeat consumption habits, consumed species, motivations, and sources of supply. A multilayer perceptron neural network analysis was used to identify the factors influencing bushmeat consumption. Results: the overall prevalence of bushmeat consumption was 24%, ranging from 15.9% in Conakry to 50% in N'zérékoré. Bushmeat consumption was 22.8% in poor households, 20.9% in middle-income households and 27.4% in rich households. Bushmeat consumption was mostly occasional (79.4%). The species of bushmeat consumed were mainly aulacodes (42.1%), antelopes (42.1%), primates (21.0%) and hare/rabbit (21.0%). Taste was the main reason for consumption (86.9%) and the main sources of supply were sellers (55.1%) and hunters (41.6%). The multilayer perceptron neural network analysis revealed that males, Christians, and individuals from the Forest ethnic group were the main factors influencing bushmeat consumption. Conclusion: the consumption of bushmeat remains a common practice in Guinea. Therefore, the implementation of effective policies and strategies for reducing the hunting of and dependence on bushmeat, which are based on the One Health approach, could make a major contribution to the conservation of the biodiversity of several species and improve health safety at both the local and global levels.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".