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Epidemics. 2019 Jul 22:100358. doi: 10.1016/j.epidem.2019.100358. [Epub ahead of print]

Analyzing influenza outbreaks in Russia using an age-structured dynamic transmission model.

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ITMO University, Saint Petersburg, Russian Federation. Electronic address:
RTI International, Research Triangle Park, NC, USA.


In this study, we addressed the ability of a minimalistic SEIR model to satisfactorily describe influenza outbreak dynamics in Russian settings. For that purpose, we calibrated an age-specific influenza dynamics model to Russian acute respiratory infection (ARI) incidence data over 2009-2016 and assessed the variability of proportion of non-immune individuals in the population depending on the regarded city, the non-epidemic indicence baseline, the contact structure considered and the used calibration method. The experiments demonstrated the importance of distinguishing characteristics of different age groups, such as contact intensities and background immunity levels. It was also found that the current model calibration process, which relies mostly on ARI incidence, demonstrates notable variation of output parameter values. Employing additional sources of data, such as strain-specific influenza incidence and external assessments on underreporting levels in different age groups, might enhance the plausibility of parameter values obtained by model calibration, along with reducing the assessment variation.


Background immunity; Incidence data; Mathematical modeling; Seasonal influenza

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