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Modeling the Spatiotemporal Epidemic Spreading of COVID-19 and the Impact of Mobility and Social Distancing Interventions

机译:建模Covid-19的时空流行蔓延和流动性和社会疏散干预的影响

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On 31 December, 2019, an outbreak of a novel coronavirus, SARS-CoV-2, that causes the COVID-19 disease, was first reported in Hubei, mainland China. This epidemics’ health threat is probably one of the biggest challenges faced by our interconnected modern societies. According to the epidemiological reports, the large basic reproduction number R0 ~ 3.0, together with a huge fraction of asymptomatic infections, paved the way for a major crisis of the national health capacity systems. Here, we develop an age-stratified mobility-based metapopulation model that encapsulates the main particularities of the spreading of COVID-19 regarding (i) its transmission among individuals, (ii) the specificities of certain demographic groups with respect to the impact of COVID-19, and (iii) the human mobility patterns inside and among regions. The full dynamics of the epidemic is formalized in terms of a microscopic Markov chain approach that incorporates the former elements and the possibility of implementing containment measures based on social distancing and confinement. With this model, we study the evolution of the effective reproduction number RetT, the key epidemiological parameter to track the evolution of the transmissibility and the effects of containment measures, as it quantifies the number of secondary infections generated by an infected individual. The suppression of the epidemic is directly related to this value and is attained when R 1. We find an analytical expression connecting R with nonpharmacological interventions, and its phase diagram is presented. We apply this model at the municipality level in Spain, successfully forecasting the observed incidence and the number of fatalities in the country at each of its regions. The expression for R should assist policymakers to evaluate the epidemics’ response to actions, such as enforcing or relaxing confinement and social distancing.
机译:2019年12月31日,在中国大陆湖北首次报告了冠心病,冠心病的新型冠状病毒,SARS-COV-2的爆发。这种流行病的健康威胁可能是我们互联的现代社会所面临的最大挑战之一。根据流行病学报告,大型基础繁殖数R0〜3.0,以及一部分巨大的无症状感染,为国家健康能力系统的主要危机铺平了道路。在这里,我们开发了一种基于年龄分层的流动性的比例模型,封装了Covid-19的传播的主要特性(i)其在个人之间的传播,(ii)某些人口统计团体的特异性关于Covid的影响-19,(iii)地区内部和地区的人类流动模式。疫情的完整动态是在纳入前部门的微观马尔可夫的链条方面正式化,并根据社会疏散和监禁实施遏制措施的可能性。通过这种模型,我们研究了有效再现数量Rett的演变,关键流行病学参数,以跟踪传导性的演变和遏制措施的影响,因为它量化了受感染的个体产生的次要感染的数量。抑制该流行病与该值直接相关,并且当R <1.我们发现连接r的分析表达与非药物干预率,并提出了其相图。我们在西班牙的市政级别应用了这一型号,成功地预测了观察到的发病率和在每个地区的国家的死亡人数。 R的表达应该协助政策制定者评估流行病对行动的反应,例如执行或放松监禁和社会疏散。

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