A systematic literature review of leptospirosis outbreaks worldwide, 1970–2012
Bibliographic record
Abstract
OBJECTIVE: This review describes the geographic and temporal distribution of, detection methods for, and other epidemiological features of published leptospirosis outbreaks, with the aim of informing efforts to standardize outbreak-reporting practices. METHODS: We conducted a systematic review of leptospirosis outbreaks reported in the scientific literature and ProMED during 1970-2012. Predefined criteria were used to identify and classify outbreaks and a standard form was used to extract information. RESULTS: During 1970-2012, we identified 318 outbreaks (average: 7 outbreaks/year; range: 1-19). Most outbreaks were reported in the Latin America and the Caribbean region (36%), followed by Southern Asia (13%), and North America (11%). Most outbreaks were located in tropical and subtropical ecoregions (55%). Quality classification showed that there was clear description of laboratory-confirmed cases in 40% of outbreaks. Among those, the average outbreak size was 82 cases overall (range: 2-2 259) but reached 253 cases in tropical/subtropical ecoregions. Common risk factors included outdoor work activities (25%), exposure to floodwaters (23%), and recreational exposure to water (22%). Epidemiologic investigation was conducted in 80% of outbreaks, mainly as case interviews. Case fatality was 5% overall (range: 0%-60%). CONCLUSIONS: Outbreak reporting increased over the study period with outbreaks covering tropical and non-tropical regions. Outbreaks varied by size, setting, and risk factors; however, data reviewed often had limited information regarding diagnosis and epidemiology. Guidelines are recommended to develop standardized procedures for diagnostic and epidemiological investigations during an outbreak and for reporting.
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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 | 0.008 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.033 | 0.030 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".