Eco-epidemiological analysis of rickettsial seropositivity in rural areas of Colombia: A multilevel approach
Bibliographic record
Abstract
Rickettsiosis is a re-emergent infectious disease without epidemiological surveillance in Colombia. This disease is generally undiagnosed and several deadly outbreaks have been reported in the country in the last decade. The aim of this study is to analyze the eco-epidemiological aspects of rickettsial seropositivity in rural areas of Colombia where outbreaks of the disease were previously reported. A cross-sectional study, which included 597 people living in 246 households from nine hamlets in two municipalities of Colombia, was conducted from November 2015 to January 2016. The survey was conducted to collect sociodemographic and household characteristics (exposure) data. Blood samples were collected to determine the rickettsial seropositivity in humans, horses and dogs (IFA, cut-off = 1/128). In addition, infections by rickettsiae were detected in ticks from humans and animals by real-time PCR targeting gltA and ompA genes. Data was analyzed by weighted multilevel clog-log regression model using three levels (person, household and hamlets) and rickettsial seropositivity in humans was the main outcome. Overall prevalence of rickettsial seropositivity in humans was 25.62% (95%CI 22.11-29.12). Age in years (PR = 1.01 95%CI 1.01-1.02) and male sex (PR = 1.65 95%CI 1.43-1.90) were risk markers for rickettsial seropositivity. Working outdoors (PR = 1.20 95%CI 1.02-1.41), deforestation and forest fragmentation for agriculture use (PR = 1.75 95%CI 1.51-2.02), opossum in peridomiciliary area (PR = 1.56 95%CI 1.37-1.79) and a high proportion of seropositive domestic animals in the home (PR20-40% vs <20% = 2.28 95%CI 1.59-3.23 and PR>40% vs <20% = 3.14 95%CI 2.43-4.04) were associated with rickettsial seropositivity in humans. This study showed the presence of Rickettsia antibodies in human populations and domestic animals. In addition, different species of rickettsiae were detected in ticks collected from humans and animals. Our results highlighted the role of domestic animals as sentinels of rickettsial infection to identify areas at risk of transmission, and the importance of preventive measures aimed at curtailing deforestation and the fragmentation of forests as a way of reducing the risk of transmission of emergent and re-emergent pathogens.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".