Effects of biological and environmental factors on orthoebolavirus serology in bats in Guinea
Bibliographic record
Abstract
Abstract Background Outbreaks of Ebola disease emerge regularly in human populations on the African continent. This highly virulent haemorrhagic fever can be caused by different orthoebolaviruses from the Filoviridae family. Several bat species are believed to carry and transmit some of these viruses to people or other animal species. However, clear evidence is still lacking. Natural circulation and zoonotic transmissions of viruses are generally complex as they often involve several host species and are influenced by biological, environmental and anthropogenic factors. A better understanding of the role of bats and other wildlife in the emergence of Ebola disease outbreaks is crucial for their prevention and early detection. Methods In this longitudinal study we searched for antibodies against orthoebolaviruses in fruit bats in order to explore some of the factors which might influence their natural circulation. We performed serological tests on populations of 4 bat species ( Eidolon helvum , Hypsignathus monstrosus , Myonycteris angolensis and Rousettus aegyptiacus ) sampled longitudinally for 18 months (2018-2020) in Guinea. The analysis of 1,427 bat samples for antibodies directed against different orthoebolavirus species allowed us to test the influence of biological and environmental variables on seropositivity by using GLMM. Results Results showed that the presence of antibodies against one of the orthoebolaviruses antigen is more frequent in the Eidolon helvum and Rousettus aegyptiacus species, in males, in sexually immature adults, and during the dry season. Conclusion Our results suggest that host species, sex, age, reproductive life-cycle and season may play an important role in the circulation of filoviruses. This information can be used to guide further sampling to specifically characterize the orthoebolavirus species underlying the production of these antibodies and to adjust surveillance protocols at the interface between bats, humans and other animals.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".