Robust reconstruction and analysis of outbreak data: influenza A(H1N1)v transmission in a school-based population

Abstract

The rapid spread of the new influenza virus A(H1N1)v in young age groups in 2009 has been partly attributed to a high transmission intensity in schools. However, detailed characterization of the spread of influenza in school populations has been difficult to obtain, simply because it is very hard to identify who infected whom in a large outbreak. Data collected in large outbreak investigations typically miss many transmission events, and some reported transmission events will be incorrect. Here the authors present robust likelihood-based methods that can be used to analyze outbreak data while explicitly accounting for both missing data and erroneous data. They apply this method to a school-based outbreak of pandemic influenza A(H1N1)v that occurred in London, United Kingdom, in April 2009. The authors show that the generation interval in this school-based population was 2.20 days and that the reproduction number declined coincident with school closure, from 1.33 secondary cases per primary case to 0.43 secondary cases per primary case. These results provide quantitative evidence for the change in influenza transmission that is to be expected from school closure.