Dengue virus serological prevalence and seroconversion rates in children and adults in Medellin, Colombia: implications for vaccine introduction
Bibliographic record
Abstract
BACKGROUND: Dengue is an important public health problem worldwide. A vaccine has recently been licensed in some countries of Latin America and Asia. Recommendations for dengue vaccine introduction include endemicity and a high serological prevalence of dengue in the territories considering its introduction. METHODS: A community-based survey was conducted to estimate dengue seroprevalence and age-specific seroconversion rates in a community in Medellin, Colombia, using a dengue serological test (IgG indirect ELISA). Residents were selected at random and were first screened for dengue infection; they were then followed over 2.5 years. RESULTS: A total of 3684 individuals aged between 1 and 65 years participated in at least one survey. The overall dengue seroprevalence was 61%, and only 3.3% of seropositive subjects self-reported a past history of dengue. Among dengue virus (DENV)-naïve subjects with more than two visits (n=1002), the overall seroconversion rate was 8.7% (95% confidence interval 7.3-10.4) per 1000 person-months, over the study period. Overall, the mean age of DENV prevalent subjects was significantly higher than the mean age of seroconverted subjects. Specifically, DENV seropositivity over 70% was observed in participants over 21 years old. Serotype-specific plaque-reduction neutralization tests (PRNT) revealed that all four dengue serotypes were circulating, with DENV4 being most prevalent. CONCLUSIONS: These laboratory-based findings could inform dengue vaccine decisions, as they provide age-specific seroprevalence and seroconversion data, evidencing permanent and ongoing dengue transmission in the study area. This study provides evidence for the existing rates of secondary and heterotypic responses, presenting a challenge that must be addressed adequately by the new vaccine candidates.
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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".