Sequence-based prediction for vaccine strain selection and identification of antigenic variability in foot-and-mouth disease virus.

ABSTRACT: Identifying when past exposure to an infectious disease will protect against newly emerging strains is central to understanding the spread and the severity of epidemics, but the prediction of viral cross-protection remains an important unsolved problem. For foot-and-mouth disease virus (FMDV) research in particular, improved methods for predicting this cross-protection are critical for predicting the severity of outbreaks within endemic settings where multiple serotypes and subtypes commonly co-circulate, as well as for deciding whether appropriate vaccine(s) exist and how much they could mitigate the effects of any outbreak. To identify antigenic relationships and their predictors, we used linear mixed effects models to account for variation in pairwise cross-neutralization titres using o

SUBMITTER: Reeve R 

PROVIDER: S-EPMC3000348 | biostudies-literature | 2010 Dec

REPOSITORIES: biostudies-literature