Nationwide variation of snakebite incidence in Kenya: Community surveys as an integrated NTD approach
Bibliographic record
Abstract
INTRODUCTION: Snakebite envenoming is a neglected tropical disease (NTD) of public health concern in Kenya. Its true burden remains elusive with an over-reliance on health facility-based data and geographically limited community surveys. This study aimed to generate data on snakebite burden in Kenyan communities and to capture the variation in incidence rate across the country by integrating snakebite incidence questions into nationwide Mass Drug Administration (MDA) campaigns for other NTDs. METHODS: A cross-sectional community survey was conducted, nested within MDA campaigns targeting trachoma, schistosomiasis and soil transmitted helminths. Data collection spanned from July 2022 to August 2023. Incidence rates per 100,000 person-years were calculated, and correlation between snakebite incidence and population density was assessed. Community survey data were compared to the reported snakebite cases in health facilities by the Kenya Health Information System (KHIS). RESULTS: A total of 13,117,754 individuals from 17 counties participated in the MDA surveys, representing 27.6% of Kenya's total population. Across these counties, 4,667 snakebite cases were reported over the previous year, with a slightly higher incidence rate among males (39.3 cases per 100,000 inhabitants) compared to females (32.2 cases per 100,000 inhabitants). County-level incidence rates varied, with Turkana County reporting the highest incidence rate (412.9 cases per 100,000 inhabitants) and Vihiga County recording the lowest (3.7 cases per 100,000 inhabitants). Discrepancies existed between health facility attendance reported by community members and numbers reported by KHIS. CONCLUSION: Integration of snakebite data collection with MDA campaigns allowed rapid and highly cost-effective data capture from a quarter of Kenya's population. The community data demonstrated considerable variation in incidence rates and discrepancies with hospital-based data. This informs resource allocation for treatment and prevention and emphasizes the need for robust integrated approaches to assess the burden of snakebite envenoming both in health facilities and communities.
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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 | 0.001 |
| 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".