冠状病毒病-2019 (COVID-19)大流行中心的数学建模

Q3 Mathematics Epidemiologic Methods Pub Date : 2020-05-01 DOI:10.1515/em-2020-0009
B. Jamshidi, M. Rezaei, S. Jamshidi Zargaran, F. Najafi
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引用次数: 6

摘要

在流行病学中,震中的建模在概念上和数学上都很重要。本文试图用数学方法模拟震中。我们提出了一种寻找新震中的算法。将我们的模型应用于COVID-19大流行相关数据,我们分别在第1、35、42、42、49、50、50、50和56天获得了中国、韩国、伊朗、意大利、法国、德国、西班牙、美国和瑞士的震中。虽然这些中心的数量不到全球所有受污染国家的5%,但截至2020年3月22日,它们占新病例的74%,占确诊病例总数的80%以上。最后,我们得出结论,预计在2020年3月22日至4月1日期间,我们将面临三个新的震中。
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Mathematical modeling the epicenters of coronavirus disease-2019 (COVID-19) pandemic
Abstract In epidemiology, the modeling of epicenters is important both conceptually and mathematically. This paper is an attempt to model epicenters mathematically. We present an algorithm to find new epicenters. Applying our model for the data related to COVID-19 pandemic, we obtain epicenters in China, South Korea, Iran, Italy, France, Germany, Spain, the USA, and Switzerland, on the days 1, 35, 42, 42, 49, 50, 50, 50, and 56, respectively. Although the number of these epicenters is less than 5% of all contaminated countries across the globe, as of March 22, 2020, they make up 74% of new cases and over 80% of total confirmed cases. Finally, we conclude that we expect to face three new epicenters between March 22 and April 1, 2020.
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来源期刊
Epidemiologic Methods
Epidemiologic Methods Mathematics-Applied Mathematics
CiteScore
2.10
自引率
0.00%
发文量
7
期刊介绍: Epidemiologic Methods (EM) seeks contributions comparable to those of the leading epidemiologic journals, but also invites papers that may be more technical or of greater length than what has traditionally been allowed by journals in epidemiology. Applications and examples with real data to illustrate methodology are strongly encouraged but not required. Topics. genetic epidemiology, infectious disease, pharmaco-epidemiology, ecologic studies, environmental exposures, screening, surveillance, social networks, comparative effectiveness, statistical modeling, causal inference, measurement error, study design, meta-analysis
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