Multihost/Multivector Community Network: Disentangling Sandfly Species and Host Interactions in Avian Habitats
Bibliographic record
Abstract
Ascertaining the feeding behavior of vectors is a key for understanding epidemiology of the infections they transmit. For some host–vector–parasite systems, this information is biased towards human and peridomestic habitats, frequently underestimating the likely role of wildlife. In addition, studies on vector interactions often focus on a one‐to‐one host–vector relationship, even though it is crucial to analyze how multiple vector species interact with multiple hosts. These biases particularly affect our knowledge of sandflies, the main vector of Leishmania spp. and various phleboviruses, that are rarely explored in non‐peridomestic habitats and in the context of multiple interactions with various hosts. To reveal the multihost/multivector network involving phlebotomine sandflies in a semiarid and poorly populated area of Spain, we sampled the sandfly community close to avian nests by means of two trapping methods (Centers for Disease Control (CDC) and sticky traps) during 3 years and identified the blood‐meal source of all engorged sandflies. We detected six phlebotomine species with Phlebotomus perniciosus , P. papatasi , and Sergentomyia minuta being the most abundant ones. We identified 13 blood source species, with humans being the most common one, followed by Coracias garrulus (European roller) and Sus scrofa (likely wild boar). Five of the six sandfly species fed largely on wild mammals, although, three also fed on wild birds. Phlebotomus sergenti only fed on birds based on this analysis. Phlebotomus papatasi and P. sergenti were common visitors of bird nests suggesting an endophagic behavior. A network analysis showed a highly‐connected and poorly‐specialized network wherein sandflies shared most of the blood source and showed an opportunistic feeding behavior with marked anthropophilia. Our results obtained close to avian nests show that sandfly populations are maintained by various wild animals, which will greatly complicate the management and control of the pathogens they transmit to humans and domestic animals.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".