Accounting for the spread of vaccination behavior to optimize influenza vaccination programs

PLoS One. 2021 Jun 4;16(6):e0252510. doi: 10.1371/journal.pone.0252510. eCollection 2021.

Abstract

Vaccination is the most efficient means of preventing influenza infection and its complications. While previous studies have considered the externalities of vaccination that arise from indirect protection against influenza infection, they have often neglected another key factor-the spread of vaccination behavior among social contacts. We modeled influenza vaccination as a socially contagious process. Our model uses a contact network that we developed based on aggregated and anonymized mobility data from the cellphone devices of ~1.8 million users in Israel. We calibrated the model to high-quality longitudinal data of weekly influenza vaccination uptake and influenza diagnoses over seven years. We demonstrate how a simple coupled-transmission model accurately captures the spatiotemporal patterns of both influenza vaccination uptake and influenza incidence. Taking the identified complex underlying dynamics of these two processes into account, our model determined the optimal timing of influenza vaccination programs. Our simulation shows that in regions where high vaccination coverage is anticipated, vaccination uptake would be more rapid. Thus, our model suggests that vaccination programs should be initiated later in the season, to mitigate the effect of waning immunity from the vaccine. Our simulations further show that optimally timed vaccination programs can substantially reduce disease transmission without increasing vaccination uptake.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Disease Transmission, Infectious / statistics & numerical data
  • Humans
  • Influenza, Human / epidemiology
  • Influenza, Human / prevention & control*
  • Influenza, Human / transmission
  • Mass Vaccination / psychology
  • Mass Vaccination / standards
  • Mass Vaccination / statistics & numerical data*
  • Models, Statistical
  • Vaccination Refusal / statistics & numerical data*

Grants and funding

This work was supported by the Zimin Institute for Engineering Solutions Advancing Better Lives, the Israeli National Institute for Health Policy Research (NIHP) as part of project number 164-16, and the Koret Foundation grant for Smart Cities and Digital Living. The funders had no role in study design, data collection, analysis, decision to publish, or manuscript preparation.