title: The Effects of Media Reports on Disease Spread and Important Public Health Measurements.
abstract: Controlling the spread of influenza to reduce the effects of infection on a population is an important mandate of public health. Mass media reports on an epidemic or pandemic can provide important information to the public, and in turn, can induce positive healthy behaviour practices (i.e., handwashing, social distancing) in the individuals, that will reduce the probability of contracting the disease. Mass media fatigue, however, can dampen these effects. Mathematical models can be used to study the effects of mass media reports on epidemic/pandemic outcomes. In this study we employ a stochastic agent based model to provide a quantification of mass media reports on the variability in important public health measurements. We also include mass media report data compiled by the Global Public Health Intelligence Network, to study the effects of mass media reports in the 2009 H1N1 pandemic. We find that the report rate and the rate at which individuals relax their healthy behaviours (media fatigue) greatly affect the variability in important public health measurements. When the mass media reporting data is included in the model, two peaks of infection result.
authors.affiliation: Modelling Infection and Immunity Lab, Centre for Disease Modelling, York University, Toronto, Canada; Mathematics & Statistics, York University, Toronto, Canada.
authors.forename: Shannon
authors.initials: S
authors.lastname: Collinson
authors.affiliation: Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Canada; Department of Medicine, Division of Infectious Diseases, University of Toronto, Toronto, Canada.
authors.forename: Kamran
authors.initials: K
authors.lastname: Khan
authors.affiliation: Modelling Infection and Immunity Lab, Centre for Disease Modelling, York University, Toronto, Canada; Mathematics & Statistics, York University, Toronto, Canada.
authors.forename: Jane M
authors.initials: JM
authors.lastname: Heffernan
mesh_terms: D006801:Humans; D053118:Influenza A Virus, H1N1 Subtype; D007251:Influenza, Human / Q000453:epidemiology*; D033181:Information Dissemination; D008962:Models, Theoretical; D058873:Pandemics; D061108:Social Media