Ecological drivers of malaria vector habitat and transmission over 1 year of long-lasting insecticidal net intervention in Côte d’Ivoire
Bibliographic record
Abstract
BACKGROUND: Malaria is a mosquito-borne parasitic disease that causes significant morbidity and mortality in at-risk populations, especially in children in sub-Saharan Africa. Despite reductions in malaria burden owing to the scale-up of effective interventions, there are concerns that long-lasting insecticidal net (LLIN) effects may not be sustained owing to widespread insecticide resistance and differential impacts of LLIN on vector species. In this study, we aimed to test the effect of different LLIN products and other environmental factors on the ecological niche of three mosquito vector species using state-of-the-art ecological niche modelling approaches. METHODS: This study used data from a cluster randomized control trial that took place in Tiébissou, in Central Côte d'Ivoire. Anopheles mosquito density and Plasmodium falciparum vector infection data were available across 33 clusters. We used satellite remote sensing related to land cover, climate, topography and population density across the study area alongside vector species occurrence data to construct ecological niche models for An. coluzzi, An. gambiae s.s. and An. funestus s.s., and for P. falciparum-infected vectors, at baseline and 1-year post-LLIN intervention. We compared the projected habitat and habitat determinants for each species, and assessed the respective contributions of each intervention arm and environmental factors on the probability of species occurrence. RESULTS: Minimal to considerable overall reductions in suitable habitat across the study area were observed for the three mosquito vector species (less than 1% to more than 60%), and considerable overall reduction was observed for P. falciparum-infected vectors (more than 50%). We did not detect an effect of intervention arm on the probability of occurrence of any vector species, while we found strong significant effects of a combination of land cover, climate, topography and/or population density variables on each of the three mosquito vector species and malaria-infected vectors. Our results suggest environmental factors may have facilitated or restricted changes in the probability of occurrence of vector species and infected vectors in the context of vector control interventions. CONCLUSIONS: Our study highlights wide ecological differences across malaria vector species and supports the need to consider malaria vector species composition when deploying malaria vector control interventions in endemic settings.
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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 | 0.000 | 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) | 0.000 | 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".