Angkana Huang (University of Cambridge)

Speaker: Angkana Huang (University of Cambridge)

Title: Reconciling heterogeneous dengue virus infection risk estimates from different study designs and the extended insights

Abstract: Accurate estimation of the force of infection (FOI) is crucial for understanding dengue transmission and population immunity. FOI can be inferred from longitudinal serology (tracking seroconversion), cross-sectional serology (age-specific seroprevalence), and reported case data, though discrepancies between these methods are understudied. Using 26 years of cohort and case data from Thailand, we observed significantly higher FOI estimates from seroincidence compared to reported cases, with moderate correlation between seroprevalence and case-based estimates. Simulations and theoretical analysis pointed to factors like antibody kinetics, assay variability, and age-related FOI heterogeneity as drivers of these differences. Extending inference models to incorporate these factors reconciled FOI and susceptibility estimates, validating previous findings on the demographic influence on infection risk and revealing age-specific dengue susceptibility, often overlooked in mosquito-borne disease studies.
DOI of the papers:
https://doi.org/10.1101/2024.09.09.24313375
https://doi.org/10.1073/pnas.2115790119