Email updates

Keep up to date with the latest news and content from BMC Infectious Diseases and BioMed Central.

Open Access Research article

Planning for the next influenza H1N1 season: a modelling study

Fabrice Carrat1235*, Camille Pelat12, Daniel Levy-Bruhl4, Isabelle Bonmarin4 and Nathanael Lapidus12

Author Affiliations

1 Université Pierre et Marie Curie - Paris 6, UMR-S 707, Paris, F-75012, France

2 Inserm U707, Paris, F-75012, France

3 Assistance Publique Hôpitaux de Paris, Hôpital Saint Antoine, Paris, F-75012, France

4 Département des maladies infectieuses, Institut de Veille Sanitaire, Saint-Maurice; 94415, France

5 F Carrat, UMR-S 707, Faculté de médecine Saint Antoine, 27 rue Chaligny, 75571 PARIS CEDEX 12, France

For all author emails, please log on.

BMC Infectious Diseases 2010, 10:301  doi:10.1186/1471-2334-10-301

Published: 21 October 2010

Abstract

Background

The level of herd immunity before and after the first 2009 pandemic season is not precisely known, and predicting the shape of the next pandemic H1N1 season is a difficult challenge.

Methods

This was a modelling study based on data on medical visits for influenza-like illness collected by the French General Practitioner Sentinel network, as well as pandemic H1N1 vaccination coverage rates, and an individual-centred model devoted to influenza. We estimated infection attack rates during the first 2009 pandemic H1N1 season in France, and the rates of pre- and post-exposure immunity. We then simulated various scenarios in which a pandemic influenza H1N1 virus would be reintroduced into a population with varying levels of protective cross-immunity, and considered the impact of extending influenza vaccination.

Results

During the first pandemic season in France, the proportion of infected persons was 18.1% overall, 38.3% among children, 14.8% among younger adults and 1.6% among the elderly. The rates of pre-exposure immunity required to fit data collected during the first pandemic season were 36% in younger adults and 85% in the elderly. We estimated that the rate of post-exposure immunity was 57.3% (95% Confidence Interval (95%CI) 49.6%-65.0%) overall, 44.6% (95%CI 35.5%-53.6%) in children, 53.8% (95%CI 44.5%-63.1%) in younger adults, and 87.4% (95%CI 82.0%-92.8%) in the elderly.

The shape of a second season would depend on the degree of persistent protective cross-immunity to descendants of the 2009 H1N1 viruses. A cross-protection rate of 70% would imply that only a small proportion of the population would be affected. With a cross-protection rate of 50%, the second season would have a disease burden similar to the first, while vaccination of 50% of the entire population, in addition to the population vaccinated during the first pandemic season, would halve this burden. With a cross-protection rate of 30%, the second season could be more substantial, and vaccination would not provide a significant benefit.

Conclusions

These model-based findings should help to prepare for a second pandemic season, and highlight the need for studies of the different components of immune protection.