Zhou Wei Ke, Wang Ai Li, Xia Fan, Xiao Yan Ni, Tang San Yi
College of Mathematics and Information Science, Shaanxi Normal University, Xi'an 710062, China.
School of Mathematics and Information Science, Baoji University of Arts and Sciences, Baoji 721013, China.
Math Biosci Eng. 2020 Mar 10;17(3):2693-2707. doi: 10.3934/mbe.2020147.
The 2019 novel coronavirus disease (COVID-19) is running rampantly in China and is swiftly spreading to other countries in the world, which causes a great concern on the global public health. The absence of specific therapeutic treatment or effective vaccine against COVID-19 call for other avenues of the prevention and control measures. Media reporting is thought to be effective to curb the spreading of an emergency disease in the early stage. Cross-correlation analysis based on our collected data demonstrated a strong correlation between media data and the infection case data. Thus we proposed a deterministic dynamical model to examine the interaction of the disease progression and the media reports and to investigate the effectiveness of media reporting on mitigating the spread of COVID-19. The basic reproduction number was estimated as 5.3167 through parameterization of the model with the number of cumulative confirmed cases, the number of cumulative deaths and the daily number of media items. Sensitivity analysis suggested that, during the early phase of the COVID-19 outbreak, enhancing the response rate of the media reporting to the severity of COVID-19, and enhancing the response rate of the public awareness to the media reports, both can bring forward the peak time and reduce the peak size of the infection significantly. These findings suggested that besides improving the medical levels, media coverage can be considered as an effective way to mitigate the disease spreading during the initial stage of an outbreak.
2019年新型冠状病毒病（COVID-19）在中国肆虐，并迅速蔓延至世界其他国家，引起了全球公共卫生的高度关注。由于缺乏针对COVID-19的特效治疗方法或有效疫苗，需要采取其他防控措施。媒体报道被认为在早期阶段对遏制紧急疾病的传播有效。基于我们收集的数据进行的交叉相关分析表明，媒体数据与感染病例数据之间存在很强的相关性。因此，我们提出了一个确定性动力学模型，以研究疾病进展与媒体报道之间的相互作用，并探讨媒体报道对减轻COVID-19传播的有效性。通过用累计确诊病例数、累计死亡数和每日媒体报道数量对模型进行参数化，基本再生数估计为5.3167。敏感性分析表明，在COVID-19疫情爆发的早期阶段，提高媒体报道对COVID-19严重程度的反应率，以及提高公众对媒体报道的认知反应率，都可以提前峰值时间并显著降低感染的峰值规模。这些发现表明，除了提高医疗水平外，媒体报道可被视为在疫情爆发初期减轻疾病传播的有效方法。
