Leptospira infections among rodents and shrews trapped in public markets in Unguja Island, Zanzibar: Untold silent public health threat
Bibliographic record
Abstract
Leptospirosis is a zoonosis caused by spirochete bacteria belonging to the genus Leptospira. The disease is recognized as an occupational hazard where rodents and shrews are primary reservoirs of infection for animals and humans. A cross-sectional study was conducted from January to March 2022 to assess the seroprevalence of leptospira infection among rodents and shrews trapped in public markets namely Darajani, Mombasa, Jumbi, Mkokotoni, and Kwerekwe C. The study involved the capture of 210 live rodents and shrews for serum sample collection. The sera were then tested for antibodies against five leptospira serovars using the microscopic agglutination test (MAT). The findings of this study indicated that 16 out of 210 samples were seropositive for leptospira serovars. The overall seroprevalence of leptospira infection was 7.6% (95% CI =4.4-12.1), with a prevalence of 8.0 % (14/174) in rodents and 5.6 % (2/36) in shrews. The range of titers was between 1:20 and 1:160. Rattus rattus were shown to have the highest seroprevalence (5.2%), followed by Rattus norvegicus (1.7%) and Mus spp (1.1%). Samples of rodents and shrews captured from Darajani markets recorded a highest seroprevalence (4.2%). The most prevalent serovars were Sokoine 11 (5.2%), Lora 4 (1.9%), Pomona 2 (1.0%) and Grippotyphosa 1 (0.5%). These findings suggest that market workers, buyers, and sellers are at risk of being infected with leptospira pathogens when they come into contact with urine or contaminated water and soil. Hence, the findings of this study call for awareness creation about leptospiral infection and its association with rodents and shrews in market environments, and the need to control rodents and shrews in marketplaces by relevant government authorities.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".