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媒体报道对疾病传播及重要公共卫生措施的影响

The Effects of Media Reports on Disease Spread and Important Public Health Measurements.

作者信息

Collinson Shannon, Khan Kamran, Heffernan Jane M

机构信息

Modelling Infection and Immunity Lab, Centre for Disease Modelling, York University, Toronto, Canada; Mathematics & Statistics, York University, Toronto, Canada.

Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Canada; Department of Medicine, Division of Infectious Diseases, University of Toronto, Toronto, Canada.

出版信息

PLoS One. 2015 Nov 3;10(11):e0141423. doi: 10.1371/journal.pone.0141423. eCollection 2015.

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.

摘要

控制流感传播以减少感染对人群的影响是公共卫生的一项重要任务。大众媒体对流行病或大流行病的报道可以向公众提供重要信息,进而促使个体养成积极的健康行为习惯(如洗手、保持社交距离),这将降低感染疾病的概率。然而,大众媒体疲劳可能会削弱这些效果。数学模型可用于研究大众媒体报道对流行病/大流行病结果的影响。在本研究中,我们采用基于随机代理的模型来量化大众媒体报道对重要公共卫生指标变异性的影响。我们还纳入了全球公共卫生情报网络汇编的大众媒体报道数据,以研究大众媒体报道在2009年甲型H1N1流感大流行中的作用。我们发现,报道率以及个体放松健康行为的速率(媒体疲劳)对重要公共卫生指标的变异性有很大影响。当模型中纳入大众媒体报道数据时,会出现两个感染高峰。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a516/4631512/81276ebdb531/pone.0141423.g001.jpg

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