2022
DOI: 10.1186/s12889-021-12426-9
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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. … Show more

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Cited by 18 publications
(23 citation statements)
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References 47 publications
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“…Contacts among age classes followed a published contact matrix for Spain, part of a larger study that analyzed 26 European countries [21]. The latent period was set to 1.5 days and the infectious period to 1.2 days; hence, the influenza generation time was 2.7 days [22].…”
Section: Populationmentioning
confidence: 99%
See 1 more Smart Citation
“…Contacts among age classes followed a published contact matrix for Spain, part of a larger study that analyzed 26 European countries [21]. The latent period was set to 1.5 days and the infectious period to 1.2 days; hence, the influenza generation time was 2.7 days [22].…”
Section: Populationmentioning
confidence: 99%
“…The distribution of contact rates was chosen on the basis of the dominant (or codominant) strains in Spain in the years 2010-2019 [22,23]. In the absence of transmission rates for Spain, Italian transmission rates for the overall population were used as a proxy, using data for the same years in which matching strains were observed in the two markets (Table 1).…”
Section: Populationmentioning
confidence: 99%
“…A deterministic transmission model was already published [ 13 ] and used to simulate the population-level dynamics of influenza infection ( Box 1 ).…”
Section: Methodsmentioning
confidence: 99%
“…8,36.8,37.5,44.2,41.7,36.7,35.2,32.7,25.9,26.6,29.0,25.4,23.3,28.2,31.0,38.2,56.5,73.3,80.2,80.4,64. 6,76.1,99.1,100.0,85.3,71.7,48.3,31.3,21.6,16.5,11.7,9.9,8.0,6.6,4.6,4.2) y2 <c (32,30,28,32,31,42,46,50,50,51,67,48,51,48,50,38,66,53,50,35,26,40,27,26,23,17,11,18,11,7,7,12,8,7,15,23,26,23,31,26,39,36,42,25,19,15,5,6,2,5,4,3,1,2,2) z2 <c(29, 21,27,31,36,45,44,52,49,55,78,100,5...…”
Section: X2mentioning
confidence: 99%
“…COVID-19 pandemic in Italy [7-9], infodemiology and infoveillance [10], seasonal flu in Italy [11, 12].…”
Section: Introductionmentioning
confidence: 99%