An agent-based model about the effects of fake news on a norovirus outbreak

J. Brainard*, P. R. Hunter, Ian Hall

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

Background: Concern about health misinformation is longstanding, especially on the Internet. Methods: Using agent-based models, we considered the effects of such misinformation on a norovirus outbreak, and some methods for countering the possible impacts of “good” and “bad” health advice. The work explicitly models spread of physical disease and information (both online and offline) as two separate but interacting processes. The models have multiple stochastic elements; repeat model runs were made to identify parameter values that most consistently produced the desired target baseline scenario. Next, parameters were found that most consistently led to a scenario when outbreak severity was clearly made worse by circulating poor quality disease prevention advice. Strategies to counter “fake” health news were tested. Results: Reducing bad advice to 30% of total information or making at least 30% of people fully resistant to believing in and sharing bad health advice were effective thresholds to counteract the negative impacts of bad advice during a norovirus outbreak. Conclusion: How feasible it is to achieve these targets within communication networks (online and offline) should be explored.

Translated title of the contributionAn agent-based model about the effects of fake news on a norovirus outbreak
Original languageFrench
Pages (from-to)99-107
Number of pages9
JournalRevue d'Epidemiologie et de Sante Publique
Volume68
Issue number2
DOIs
Publication statusPublished - Apr 2020

Bibliographical note

Funding Information:
Adrian Pratt, Tom Finnie and Steve Leach of Public Health England (PHE) gave many helpful comments. Thanks to Soroush Vosoughi, Shannon Fast and Anil Doshi for answering questions about their research. Our study was funded by the National Institute for Health Research (NIHR) Health Protection Research Units in Emergency Preparedness and Response and Gastrointestinal infections in partnership with PHE. The views expressed are those of the authors and not necessarily those of the National Health Service, the NIHR, the Department of Health or PHE. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript and associated documents.

Funding Information:
Adrian Pratt, Tom Finnie and Steve Leach of Public Health England (PHE) gave many helpful comments. Thanks to Soroush Vosoughi, Shannon Fast and Anil Doshi for answering questions about their research. Our study was funded by the National Institute for Health Research (NIHR) Health Protection Research Units in Emergency Preparedness and Response and Gastrointestinal infections in partnership with PHE . The views expressed are those of the authors and not necessarily those of the National Health Service, the NIHR, the Department of Health or PHE. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript and associated documents.

Publisher Copyright:
© 2020 Elsevier Masson SAS

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

Keywords

  • Agent-based-models
  • Fake news
  • Filter bubbles
  • Norovirus
  • Outbreak

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