Rethinking thresholds for serological evidence of influenza virus infection.

ABSTRACT:

Introduction

For pathogens such as influenza that cause many subclinical cases, serologic data can be used to estimate attack rates and the severity of an epidemic in near real time. Current methods for analysing serologic data tend to rely on use of a simple threshold or comparison of titres between pre- and post-epidemic, which may not accurately reflect actual infection rates.

Methods

We propose a method for quantifying infection rates using paired sera and bivariate probit models to evaluate the accuracy of thresholds currently used for influenza epidemics with low and high existing herd immunity levels, and a subsequent non-influenza period. Pre- and post-epidemic sera were taken from a cohort of adults in Singapore (n=838). Bivariate probit models with latent titre lev

SUBMITTER: Zhao X 

PROVIDER: S-EPMC5410725 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature