Age-dependent seroprevalence of dengue and chikungunya: inference from a cross-sectional analysis in Esmeraldas Province in coastal Ecuador
Bibliographic record
Abstract
OBJECTIVES: There are few population-based estimates for prevalence of past exposure to dengue and chikungunya viruses despite common epidemiological features. Here, we have developed a novel statistical method to study patterns of age-dependent prevalence of immunity in a population following exposures to two viruses which share similar epidemiological features including mode of transmission and induction of long-lasting immunity. This statistical technique accounted for sociodemographic characteristics associated with individuals and households. SETTINGS: The data consist of a representative sample from an ongoing longitudinal birth cohort set-up in a tropical district in coastal Ecuador (Esmeraldas). PARTICIPANTS: We collected data and blood samples from 319 individuals belonging to 152 households following epidemics of the infections in 2015 in Latin America. PRIMARY OUTCOME: Plasma was tested for the presence of specific IgG antibodies to dengue and chikungunya viruses by commercial ELISA and defined a bivariate binary outcome indicating individuals' past exposure status to dengue and chikungunya (ie, presence/absence of IgG antibodies to dengue or chikungunya or both). RESULTS: Dengue seroprevalence increased rapidly with age reaching 97% (95% credible interval (CrI): 93%-99%) by 60 years. Chikungunya seroprevalence peaked at 42% (95% CrI: 18%-66%) around 9 years of age and averaged 27% (95% CrI: 8.7%-51.6%) for all ages. Rural areas were more likely to be associated with dengue-only exposure while urban areas and shorter distance to the nearest household were associated with exposures to both. Women living in urban settings were more likely to be chikungunya seropositive while rural men were more likely to be dengue seropositive. CONCLUSION: Dengue seroprevalence was strongly age dependent consistent with endemic exposure while that of chikungunya peaked in childhood consistent with the recent emergence of the virus in the study area. Our findings will inform control strategies for the two arboviruses in Ecuador including recommendations by the WHO on dengue vaccination.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".