Understanding the dynamics of seasonal influenza in Italy: incidence, transmissibility and population susceptibility in a 9-year period
Version of Record online: 14 JUN 2012
© 2012 Blackwell Publishing Ltd
Influenza and Other Respiratory Viruses
Volume 7, Issue 3, pages 286–295, May 2013
How to Cite
Lunelli, A., Rizzo, C., Puzelli, S., Bella, A., Montomoli, E., Rota, M. C., Donatelli, I. and Pugliese, A. (2013), Understanding the dynamics of seasonal influenza in Italy: incidence, transmissibility and population susceptibility in a 9-year period. Influenza and Other Respiratory Viruses, 7: 286–295. doi: 10.1111/j.1750-2659.2012.00388.x
- Issue online: 17 APR 2013
- Version of Record online: 14 JUN 2012
- Accepted 3 May 2012. Published Online 14 June 2012.
- Mathematical modelling;
- parameter estimation;
- seasonal influenza;
- sentinel surveillance system;
- virological and serological data
Objectives: Influenza surveillance systems have been established in many countries in the world, yielding timely information about the intensity and features of seasonal outbreaks. Such data have also been used to estimate epidemiological parameters and to evaluate the effect of factors on infection dynamics. However, little is known about the extent of under-reporting in surveillance data, and thus of the true influenza incidence in the population.
Design: Through mathematical and statistical modelling, we analysed Italian epidemiological and virological surveillance data collected together with serological data derived from influenza vaccine clinical trials performed in Italy.
Results: Depending on the season, the reporting rate estimates ranged between 20% and 33% of the total incidence with higher reporting rates in seasons dominated by A/H3N2 virus. Despite a generally higher number of individuals immune against A/H3N2 viruses, effective reproduction ratios were quite similar in all seasons varying between 1·2 and 1·4. We observed an age-dependent transmissibility for different subtypes: susceptible children were more likely than susceptible adults and elderly to get infected when A/H1N1 or B strains were circulating, while no clear age-dependence was found for A/H3N2. We also perform sensitivity analysis under different assumptions for vaccine effectiveness, generation time (GT) and model variants; we found that the overall results in predicted patterns were extremely similar, with a slightly better fit obtained with shorter GTs.
Conclusions: Our results provide relevant information on the influenza dynamics to fine-tune intervention strategies and for data collection improvement.