Abstract
BackgroundDespite thousands of influenza cases annually recorded by surveillance systems around the globe, estimating the transmission patterns of seasonal influenza is challenging.MethodsWe 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.ResultsWe 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.ConclusionsThe 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.
Highlights
Annual influenza epidemics cause a marked excess of mortality and hospitalization as well as significant economic and healthcare burden [1]
We use mathematical modeling to estimate three key epidemiological indicators: i) the influenza infection attack rate, which corresponds to the proportion of individuals infected by influenza over the entire course of the season; ii) the effective reproductive number, Effective reproduction number (Reff) - i.e., the mean number of secondary infections caused by a typical infectious individual in a partially immune population; and iii) the age-specific susceptibility to infection by virus type/subtype
In each of the ten analyzed seasons, the incidence of influenza-like illness (ILI) cases reported to the Italian surveillance system shows an annual epidemic characterized by a peak occurring in February with the exception of the 2016–2017 season when the peak was recorded in December (Fig. 1A)
Summary
Annual influenza epidemics cause a marked excess of mortality and hospitalization as well as significant economic and healthcare burden [1]. Mathematical models of infectious disease transmission represent key tools to properly interpret the observed data and to provide quantitative estimates of quantities that hard to measure directly [6,7,8,9]. We use mathematical modeling to estimate three key epidemiological indicators: i) the influenza infection attack rate (overall and by age), which corresponds to the proportion of individuals infected by influenza over the entire course of the season; ii) the effective reproductive number, Reff - i.e., the mean number of secondary infections caused by a typical infectious individual in a partially immune population; and iii) the age-specific susceptibility to infection by virus type/subtype. Despite thousands of influenza cases annually recorded by surveillance systems around the globe, estimating the transmission patterns of seasonal influenza is challenging
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