Dataset Information

Characterizing the transmission patterns of seasonal influenza in Italy: lessons from the last decade.

ABSTRACT:

Background

Despite thousands of influenza cases annually recorded by surveillance systems around the globe, estimating the transmission patterns of seasonal influenza is challenging.

Methods

We develop an age-structured mathematical model to influenza transmission to analyze ten consecutive seasons (from 2010 to 2011 to 2019-2020) of influenza epidemiological and virological data reported to the Italian surveillance system.

Results

We estimate that 18.4-29.3% of influenza infections are detected by the surveillance system. Influenza infection attack rate varied between 12.7 and 30.5% and is generally larger for seasons characterized by the circulation of A/H3N2 and/or B types/subtypes. Individuals aged 14 years or less are the most affected age-segment of the population, with A viruses especially affecting children aged 0-4 years. For all influenza types/subtypes, the mean effective reproduction number is estimated to be generally in the range 1.09-1.33 (9 out of 10 seasons) and never exceeding 1.41. The age-specific susceptibility to infection appears to be a type/subtype-specific feature.

Conclusions

The results presented in this study provide insights on type/subtype-specific transmission patterns of seasonal influenza that could be instrumental to fine-tune immunization strategies and non-pharmaceutical interventions aimed at limiting seasonal influenza spread and burden.

SUBMITTER: Trentini F

PROVIDER: S-EPMC8734132 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

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Publications

Characterizing the transmission patterns of seasonal influenza in Italy: lessons from the last decade.

Trentini Filippo F Pariani Elena E Bella Antonino A Diurno Giulio G Crottogini Lucia L Rizzo Caterina C Merler Stefano S Ajelli Marco M

BMC public health 20220106 1

<h4>Background</h4>Despite thousands of influenza cases annually recorded by surveillance systems around the globe, estimating the transmission patterns of seasonal influenza is challenging.<h4>Methods</h4>We develop an age-structured mathematical model to influenza transmission to analyze ten consecutive seasons (from 2010 to 2011 to 2019-2020) of influenza epidemiological and virological data reported to the Italian surveillance system.<h4>Results</h4>We estimate that 18.4-29.3% of influenza i ...[more]

PMID: 34991544

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Dataset Information

Characterizing the transmission patterns of seasonal influenza in Italy: lessons from the last decade.

Background

Methods

Results

Conclusions

Publications

Characterizing the transmission patterns of seasonal influenza in Italy: lessons from the last decade.

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