Linking multiple serological assays to infer dengue virus infections from paired samples using mixture models.

ABSTRACT: Dengue virus (DENV) is an increasingly important human pathogen, with already half of the globe's population living in environments with transmission potential. Since many cases are missed by direct detection methods (RT-PCR or antigen tests), serological assays play an important role in the diagnostic process. However, individual assays can suffer from low sensitivity and specificity and interpreting results from multiple assays remains challenging, particularly because interpretations from multiple assays may differ, creating uncertainty over how to generate finalized interpretations. We develop a Bayesian mixture model that can jointly model data from multiple paired serological assays, to infer infection events. We first test the performance of our model using simulated data. We then a

SUBMITTER: Hamins-Puertolas M 

PROVIDER: S-EPMC12646409 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature