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ORIGINAL RESEARCH article

Front. Epidemiol.
Sec. Infectious Disease Epidemiology
Volume 4 - 2024 | doi: 10.3389/fepid.2024.1467301
This article is part of the Research Topic Modelling the Impact of Human Behaviour on Infectious Disease Epidemiology View all articles

Using a Computational Cognitive Model to Simulate the Effects of Personal and Social Network Experiences on Seasonal Influenza Vaccination Decisions

Provisionally accepted
Matthew M. Walsh Matthew M. Walsh 1,2*Andrew M. Parker Andrew M. Parker 3Raffaele Vardavas Raffaele Vardavas 3Sarah Nowak Sarah Nowak 4David P. Kennedy David P. Kennedy 3Courtney A. Gidengil Courtney A. Gidengil 3
  • 1 Carnegie Institute of Technology, Carnegie Mellon University, Pittsburgh, United States
  • 2 Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
  • 3 RAND Corporation, Santa Monica, California, United States
  • 4 University of Vermont, Burlington, Vermont, United States

The final, formatted version of the article will be published soon.

    The substantial societal costs of seasonal influenza include illness, loss of lives, and loss of work productivity. Vaccination is the most effective means for averting the disease, yet fewer than half of adults in the United States are vaccinated annually. In this research, we focus on how personal experience and the experiences of close social contacts contribute to vaccination decisions. The results of a multi-year longitudinal survey study revealed the significant effects of personal and social network experiences on vaccination. We develop a memory-based model of vaccination decisions using the Adaptive Control of Thought -Rational (ACT-R) integrated cognitive architecture. The model accounts for the effects of personal and social experience on vaccination and suggests interventions that may be effective in increasing vaccination uptake.

    Keywords: Seasonal influenza, Vaccination, cognitive model, Public Health, ACT-R

    Received: 19 Jul 2024; Accepted: 18 Oct 2024.

    Copyright: © 2024 Walsh, Parker, Vardavas, Nowak, Kennedy and Gidengil. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Matthew M. Walsh, Carnegie Institute of Technology, Carnegie Mellon University, Pittsburgh, United States

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.