Geographical and Occupational Aspects of Leptospirosis in the Coffee-Triangle Region of Colombia, 2007-2011
Bibliographic record
Abstract
BACKGROUND: There are few studies occupationally profiling as well as using Geographic information system (GIS) to map human leptospirosis. There are no detailed, municipality-level, epidemiological maps in Colombia neither in South America. We developed such maps for the Coffee-triangle region, Colombia and assess some occupational issues. METHODS: surveillance cases data (2007-2011) were used to estimate the annual incidence rates (cases/100,000 population) of leptospirosis to develop the first maps of disease in the 53 municipalities of the Coffee-triangle region of Colombia. GIS used was Kosmo(®) 3.1. Five thematic maps were developed according to municipalities and years. Using labor official information, analyses between agriculture (harvested areas) with disease occurrence was done (linear regression). RESULTS: Between 2007 and 2011, 786 cases were reported (77.8% from one department, Risaralda), for a cumulated rate of 32.18 cases/100,000 population. The highest rate was reported in the less developed municipality of one department (Pueblo Rico, Risaralda) with 1535.05 cases/100,000 population (187 cases, 2009). Armenia (Quindio department capital city), reported 23.41 cases/100,000pop (2011). In those patients with identified occupations, 33.3% were agriculture workers, finding a significant relationship between the number of cases in 2008 and the harvested area by municipality (r(2)=0.48; p=0.0083). CONCLUSION: one of the 53 municipalities contributed with almost a quarter of the cases. Agriculture was significantly associated with the incidence. Use of GIS-based epidemiological maps allow to focus actions in prevention and control for risk zones for leptospirosis which still represents a significant issue in the region and Colombia, particularly in agriculture workers.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".