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Modeling the impact of mass influenza vaccination and public health interventions on COVID-19 epidemics with limited detection capability.
Mathematical Biosciences ( IF 4.3 ) Pub Date : 2020-05-16 , DOI: 10.1016/j.mbs.2020.108378
Qian Li 1 , Biao Tang 2 , Nicola Luigi Bragazzi 2 , Yanni Xiao 3 , Jianhong Wu 2
Affiliation  

The emerging coronavirus SARS-CoV-2 has caused a COVID-19 pandemic. SARS-CoV-2 causes a generally mild, but sometimes severe and even life-threatening infection, known as COVID-19. Currently, there exist no effective vaccines or drugs and, as such, global public authorities have so far relied upon non pharmaceutical interventions (NPIs). Since COVID-19 symptoms are aspecific and may resemble a common cold, if it should come back with a seasonal pattern and coincide with the influenza season, this would be particularly challenging, overwhelming and straining the healthcare systems, particularly in resource-limited contexts, and would increase the likelihood of nosocomial transmission. In the present study, we devised a mathematical model focusing on the treatment of people complaining of influenza-like-illness (ILI) symptoms, potentially at risk of contracting COVID-19 or other emerging/re-emerging respiratory infectious agents during their admission at the health-care setting, who will occupy the detection kits causing a severe shortage of testing resources. The model is used to assess the effect of mass influenza vaccination on the spread of COVID-19 and other respiratory pathogens in the case of a coincidence of the outbreak with the influenza season. Here, we show that increasing influenza vaccine uptake or enhancing the public health interventions would facilitate the management of respiratory outbreaks coinciding with the peak flu season, especially, compensate the shortage of the detection resources. However, how to increase influenza vaccination coverage rate remains challenging. Public health decision- and policy-makers should adopt evidence-informed strategies to improve influenza vaccine uptake.

中文翻译:

对检测能力有限的大规模流感疫苗接种和公共卫生干预措施对COVID-19流行病的影响进行建模。

新兴的冠状病毒SARS-CoV-2导致了COVID-19大流行。SARS-CoV-2引起一般性的轻度感染,但有时甚至是严重的甚至威胁生命的感染,称为COVID-19。当前,没有有效的疫苗或药物,因此,迄今为止,全球公共当局都依靠非药物干预措施(NPI)。由于COVID-19症状具有特殊性且可能类似于普通感冒,因此如果应以季节性模式出现并与流感季节相吻合,这将特别具有挑战性,使医疗保健系统不堪重负,特别是在资源有限的情况下,并会增加医院传播的可能性。在本研究中,我们设计了一个数学模型,着重于治疗抱怨类流感(ILI)症状的人,在医疗机构入院期间,可能有感染COVID-19或其他新兴/再出现的呼吸道传染病的风险,这些病菌将占用检测试剂盒,导致检测资源严重短缺。该模型用于评估在流感季节与流感暴发相吻合的情况下,大规模流感疫苗接种对COVID-19和其他呼吸道病原体传播的影响。在这里,我们表明,增加流感疫苗的摄入量或加强公共卫生干预措施将有助于管理与流感高峰期相符的呼吸道疾病,尤其是弥补检测资源的短缺。但是,如何提高流感疫苗接种率仍然具有挑战性。
更新日期:2020-05-16
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