Predictive Modeling of Covid-19 Data in the US: Adaptive Phase-Space Approach.
Predictive Modeling of Covid-19 Data in the US: Adaptive Phase-Space Approach.
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DOI：
10.1109/ojemb.2020.3008313
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发表时间：
2020
影响因子：
5.8
通讯作者：
Marmarelis VZ
中科院分区：
文献类型：
--
作者：
Marmarelis VZ
目前，全球科学界正加紧努力，分析新型冠状病毒疫情的动态，以预测主要流行病学影响，并协助制定适当的临床管理计划，以及指导有关适当缓解措施的社会政治决策。大多数努力遵循的变体建立SIR方法框架，将人口分为“易感”，“传染性”和“消除/删除”分数，并定义其动态的相互关系与一阶微分方程。目标：本文提出了一种新的方法，基于数据引导的检测和级联的感染波-他们中的每一个描述的Riccati方程自适应估计参数。研究方法：这种方法被应用于美国确诊病例的Covid-19每日时间序列数据，从而将流行时间过程分解为五个代表迄今为止（6月18日）主要感染波的“Riccati模块”。结果：目前已过了4波感染高峰，预计7月20日为第5波感染高峰。所获得的参数估计值表明感染率逐渐降低，尽管预计最新一波是最大的。结论：这一分析表明，如果没有新的感染浪潮出现，到9月26日，美国的COVID-19疫情将得到控制（每日新增病例<5000例），确诊病例最高将达到416万例。重要的是，这种方法可用于检测（通过严格的统计方法）未来可能出现的新一波感染。对来自各个州或国家的数据进行分析可以量化不同缓解措施的不同效果。
There are currently intensified efforts by the scientific community world-wide to analyze the dynamics of the Covid-19 pandemic in order to predict key epidemiological effects and assist the proper planning for its clinical management, as well as guide sociopolitical decision-making regarding proper mitigation measures. Most efforts follow variants of the established SIR methodological framework that divides a population into “Susceptible”, “Infectious” and “Recovered/Removed” fractions and defines their dynamic inter-relationships with first-order differential equations. Goal: This paper proposes a novel approach based on data-guided detection and concatenation of infection waves – each of them described by a Riccati equation with adaptively estimated parameters. Methods: This approach was applied to Covid-19 daily time-series data of US confirmed cases, resulting in the decomposition of the epidemic time-course into five “Riccati modules” representing major infection waves to date (June 18th). Results: Four waves have passed the time-point of peak infection rate, with the fifth expected to peak on July 20th. The obtained parameter estimates indicate gradual reduction of infectivity rate, although the latest wave is expected to be the largest. Conclusions: This analysis suggests that, if no new waves of infection emerge, the Covid-19 epidemic will be controlled in the US (<5000 new daily cases) by September 26th, and the maximum of confirmed cases will reach 4,160,000. Importantly, this approach can be used to detect (via rigorous statistical methods) the emergence of possible new waves of infections in the future. Analysis of data from individual states or countries may quantify the distinct effects of different mitigation measures.
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影响因子：
4.3
作者：
Kegan, B;West, RW
通讯作者：
West, RW
DOI：
10.1098/rspa.1927.0118
发表时间：
1927-08-01
期刊：
PROCEEDINGS OF THE ROYAL SOCIETY OF LONDON SERIES A-CONTAINING PAPERS OF A MATHEMATICAL AND PHYSICAL CHARACTER
影响因子：
--
作者：
Kermack, WO;McKendrick, AG
通讯作者：
McKendrick, AG
影响因子：
4
作者：
Harko, Tiberiu;Lobo, Francisco S. N.;Mak, M. K.
通讯作者：
Mak, M. K.
影响因子：
5.2
作者：
Carcione, Jose M.;Santos, Juan E.;Ba, Jing
通讯作者：
Ba, Jing
影响因子：
1.2
作者：
Benvenuto, Domenico;Giovanetti, Marta;Ciccozzi, Massimo
通讯作者：
Ciccozzi, Massimo