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美国得克萨斯州的数学建模与新冠疫情预测:一个预测模型分析及疾病爆发概率

Mathematical Modeling and COVID-19 Forecast in Texas, USA: A Prediction Model Analysis and the Probability of Disease Outbreak.

作者信息

Hassan Md Nazmul, Mahmud Md Shahriar, Nipa Kaniz Fatema, Kamrujjaman Md

机构信息

Department of Mathematics and Statistics, Texas Tech University, Lubbock, Texas, USA.

Department of Sciences and Mathematics, Schreiner University, Kerrville, Texas, USA.

出版信息

Disaster Med Public Health Prep. 2021 May 19;17:e19. doi: 10.1017/dmp.2021.151.

Abstract

BACKGROUND

Response to the unprecedented coronavirus disease 2019 (COVID-19) outbreak needs to be augmented in Texas, United States, where the first 5 cases were reported on March 6, 2020, and were rapidly followed by an exponential rise within the next few weeks. This study aimed to determine the ongoing trend and upcoming infection status of COVID-19 in county levels of Texas.

METHODS

Data were extracted from the following sources: published literature, surveillance, unpublished reports, and websites of Texas Department of State Health Services (DSHS), Natality report of Texas, and WHO Coronavirus Disease (COVID-19) Dashboard. The 4-compartment Susceptible-Exposed-Infectious-Removal (SEIR) mathematical model was used to estimate the current trend and future prediction of basic reproduction number and infection cases in Texas. Because the basic reproduction number is not sufficient to predict the outbreak, we applied the Continuous-Time Markov Chain (CTMC) model to calculate the probability of the COVID-19 outbreak.

RESULTS

The estimated mean basic reproduction number of COVID-19 in Texas is predicted to be 2.65 by January 31, 2021. Our model indicated that the third wave might occur at the beginning of May 2021, which will peak at the end of June 2021. This prediction may come true if the current spreading situation/level persists, i.e., no clinically effective vaccine is available, or this vaccination program fails for some reason in this area.

CONCLUSION

Our analysis indicates an alarming ongoing and upcoming infection rate of COVID-19 at county levels in Texas, thereby emphasizing the promotion of more coordinated and disciplined actions by policy-makers and the population to contain its devastating impact.

摘要

背景

美国得克萨斯州需要加强对2019年新型冠状病毒病(COVID-19)这一前所未有的疫情的应对。该州于2020年3月6日报告了首批5例病例,随后在接下来的几周内迅速呈指数级增长。本研究旨在确定得克萨斯州县一级COVID-19的当前趋势和未来感染状况。

方法

数据来自以下来源:已发表的文献、监测数据、未发表的报告以及得克萨斯州卫生服务部(DSHS)的网站、得克萨斯州出生报告和世界卫生组织冠状病毒病(COVID-19)仪表板。采用四分区易感-暴露-感染-清除(SEIR)数学模型来估计得克萨斯州基本再生数和感染病例的当前趋势及未来预测。由于基本再生数不足以预测疫情爆发,我们应用连续时间马尔可夫链(CTMC)模型来计算COVID-19爆发的概率。

结果

预计到2021年1月31日,得克萨斯州COVID-19的估计平均基本再生数为2.65。我们的模型表明,第三波疫情可能在2021年5月初出现,并将于2021年6月底达到峰值。如果当前的传播情况/水平持续,即没有临床有效的疫苗可用,或者该地区的疫苗接种计划因某种原因失败,这一预测可能会成为现实。

结论

我们的分析表明,得克萨斯州县一级COVID-19当前和未来的感染率令人担忧,从而强调政策制定者和民众应采取更协调、更自律的行动,以遏制其毁灭性影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/88df/8314068/3b0fc78d2e4a/S1935789321001518_fig1.jpg

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