Early stage COVID-19 disease dynamics in Germany: models and parameter identification.

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2020-01-01 Epub Date: 2020-07-10 DOI:10.1186/s13362-020-00088-y

Thomas Götz, Peter Heidrich

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引用次数: 0

Abstract

Since the end of 2019 an outbreak of a new strain of coronavirus, called SARS-CoV-2, is reported from China and later other parts of the world. Since January 21, World Health Organization (WHO) reports daily data on confirmed cases and deaths from both China and other countries (www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports). The Johns Hopkins University (github.com/CSSEGISandData/COVID-19/blob/master/csse_COVID_19_data/csse_COVID_19_time_series/time_series_COVID19_confirmed_global.csv) collects those data from various sources worldwide on a daily basis. For Germany, the Robert-Koch-Institute (RKI) also issues daily reports on the current number of infections and infection related fatal cases (www.rki.de/DE/Content/InfAZ/N/Neuartiges_Coronavirus/Situationsberichte/Gesamt.html). However, due to delays in the data collection, the data from RKI always lags behind those reported by Johns Hopkins. In this work we present an extended SEIRD-model to describe the disease dynamics in Germany. The parameter values are identified by matching the model output to the officially reported cases. An additional parameter to capture the influence of unidentified cases is also included in the model.

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德国早期 COVID-19 疾病动态：模型和参数识别。

自 2019 年底以来，中国和世界其他地区相继报告爆发了一种名为 SARS-CoV-2 的新型冠状病毒。自 1 月 21 日起，世界卫生组织（WHO）每天都报告来自中国和其他国家（www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports）的确诊病例和死亡数据。约翰霍普金斯大学（github.com/CSSEGISandData/COVID-19/blob/master/csse_COVID_19_data/csse_COVID_19_time_series/time_series_COVID_19_confirmed_global.csv）每天从全球不同来源收集这些数据。在德国，罗伯特-科赫研究所（RKI）也发布了关于当前感染人数和与感染相关的死亡病例数的每日报告 (www.rki.de/DE/Content/InfAZ/N/Neuartiges_Coronavirus/Situationsberichte/Gesamt.html)。然而，由于数据收集的延迟，RKI 的数据总是落后于约翰霍普金斯大学的报告。在这项工作中，我们提出了一个扩展的 SEIRD 模型来描述德国的疾病动态。通过将模型输出与官方报告的病例相匹配，确定了参数值。模型中还包含一个额外参数，用于捕捉未确定病例的影响。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.