Parasites and vectors of malaria on Rusinga Island, Western Kenya
Bibliographic record
Abstract
BACKGROUND: There is a dearth of information on malaria endemicity in the islands of Lake Victoria in western Kenya. In this study malaria prevalence and Plasmodium sporozoite rates on Rusinga Island were investigated. The contribution of different Anopheles species to indoor and outdoor transmission of malaria was also determined. METHODS: Active case detection through microscopy was used to diagnose malaria in a 10% random sample of the human population on Rusinga Island and a longitudinal entomological survey conducted in Gunda village in 2012. Nocturnally active host-seeking mosquitoes were captured indoors and outdoors using odour-baited traps. Anopheles species were tested for the presence of Plasmodium parasites using an enzyme linked immunosorbent assay. All data were analyzed using generalized linear models. RESULTS: Single infections of Plasmodium falciparum (88.1%), P. malariae (3.96%) and P. ovale (0.79%) as well as multiple infections (7.14%) of these parasites were found on Rusinga Island. The overall malaria prevalence was 10.9%. The risk of contracting malaria was higher among dwellers of Rusinga West than Rusinga East locations (Odds Ratio [OR] = 1.5, 95% Confidence Interval [CI] 1.14 - 1.97, P = 0.003). Parasite positivity was significantly associated with individuals who did not use malaria protective measures (OR = 2.65, 95% CI 1.76 - 3.91, p < 0.001). A total of 1,684 mosquitoes, including 74 anophelines, were captured. Unlike Culex species, more of which were collected indoors than outdoors (P < 0.001), the females of An. gambiae s.l. (P = 0.477), An. funestus s.l. (P = 0.153) and Mansonia species captured indoors versus outdoors were not different. The 46 An. gambiae s.l. collected were mainly An. arabiensis (92.3%). Of the 62 malaria mosquitoes tested, 4, including 2 indoor and 2 outdoor-collected individuals had Plasmodium. CONCLUSION: The rather significant and unexpected contribution of P. malariae and P. ovale to the overall malaria prevalence on Rusinga Island underscores the epidemiological importance of these species in the big push towards eliminating malaria. Although current entomological interventions mainly target indoor environments, additional strategies should be considered to prevent outdoor transmission of malaria.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".