A new approach to characterising infectious disease transmission dynamics from sentinel surveillance: application to the Italian 2009-2010 A/H1N1 influenza pandemic.

ABSTRACT: Syndromic and virological data are routinely collected by many countries and are often the only information available in real time. The analysis of surveillance data poses many statistical challenges that have not yet been addressed. For instance, the fraction of cases that seek healthcare and are thus detected is often unknown. Here, we propose a general statistical framework that explicitly takes into account the way the surveillance data are generated. Our approach couples a deterministic mathematical model with a statistical description of the reporting process and is applied to surveillance data collected in Italy during the 2009-2010 A/H1N1 influenza pandemic. We estimate that the reproduction number R was initially into the range 1.2-1.4 and that case detection in children was signi

SUBMITTER: Dorigatti I 

PROVIDER: S-EPMC4088935 | biostudies-literature | 2012 Mar

REPOSITORIES: biostudies-literature