Methods for Outbreaks Using Genomic Data

• Published in: Handbook of Infectious Disease Data Analysis pp. 245 - 262
• Main Authors: Klinkenberg, Don, Colijn, Caroline, Didelot, Xavier
• Format: Book Chapter
• Language: English
• Published: CRC Press 2020
• Edition: 1
• Subjects: Approximate Bayesian Computation; MCMC Algorithm; Outbreak Analysis; Transmission Tree; Posterior Distribution; Cumulative Distribution Function; Peak IgG; Transmission Events; Phylogenetic Tree; NGS Data; ABC Algorithm; Sampling Likelihood; Test Negative Design; Approximate Bayesian Computation Methods; NJ Tree; MCMC Chain; Beast Analysis; Beast Software; Accelerated Failure Time Model; Infection Times; Substitution Rate; FMD Outbreak; Wright Fisher Model; FMD
• ISBN: 9781138626713; 1138626716
• DOI: 10.1201/9781315222912-13

The assessment of the age-specific seroprevalence profile from serological data is often performed using current infection status data. This data is obtained by dichotomizing the optical density measurements on the basis of a fixed cut-off associated with the employed diagnostic assay. This means that the information embedded in the individual antibody optical density is lost, as it is replaced by a binary variable indicating only whether the subject is still susceptible or immune to the infection. Moreover, due to the nature of the assay's cut-off, this categorization is prone to misclassification and to the removal of those cases labeled as inconclusive. To overcome this issue, mixture models have been introduced for estimating the age-specific population seroprevalence, modeing directly the optical density measurements. In this chapter, we propose hierarchical Bayesian mixture models for the estimation of the age-specific seroprevalence for both pre- and post-vaccination epochs, using Markov chain Monte Carlo (MCMC) methods. For the former scenario, we discuss methods to estimate age-specific force on infection from the estimated seroprevalence. Data from varicella-zoster virus, parvovirus B19, and measles serological surveys in three European countries are employed to illustrate the proposed methodology.