泊松过程在新疆新型冠状肺炎分析中的应用
Application of Poisson Process in Covid-19 Analysis of Xinjiang
摘要: 本文利用具有恒定速率λ的泊松过程,以2020年7月16日至2020年8月17日新疆新型冠状肺炎阳性患者的每日病例数为例,对新疆冠状肺炎病例数进行统计分析。结果表明,在此期间新疆没有新疆新型冠状肺炎阳性患者的概率极小,利用复合泊松过程建立了新疆新型冠状肺炎阳性患者相关花费的数学模型,所得结果可为新疆各级部门对新疆新型冠状病毒的管控和预防提供一定的参考价值。
Abstract:
In this paper, the Poisson process with constant rate λ was used to statistically analyze the number of coronavirus cases in Xinjiang by taking the number of daily cases of Xinjiang COVID-19 positive patients on July 16, 2020 solstice and August 17, 2020 as an example. The results showed that the probability of no COVID-19 positive patients in Xinjiang was very small during this period. The mathematical model of COVID-19 positive patients in Xinjiang was established by using the com-pound Poisson process. The results can provide certain reference value for Xinjiang departments at all levels to control and prevent novel coronavirus in Xinjiang.
参考文献
|
[1]
|
Munandar, D., Supian, S. and Subiyanto, S. (2020) Probability Distributions of COVID-19 Tweet Posted Trends Uses a Nonhomoge-neous Poisson Process. International Journal of Quantitative Research and Modeling, 1, 229-238. [Google Scholar] [CrossRef]
|
|
[2]
|
Zhang, X., Ma, R. and Wang, L. (2020) Predicting Turning Point, Duration and At-tack Rate of COVID-19 Outbreaks in Major Western Countries. Chaos Solitons & Fractals, 135, Article ID: 109829. [Google Scholar] [CrossRef] [PubMed]
|
|
[3]
|
Ma, Y., Liu, X., Tao, W., et al. (2020) Estimation of the Outbreak Severity and Evaluation of Epidemic Prevention Ability of COVID-19 by Province in China. American Journal of Public Health, 110, 1837-1843. [Google Scholar] [CrossRef]
|
|
[4]
|
S.M.劳斯. 随机过程[M]. 北京: 中国统计出版社, 1997.
|
|
[5]
|
孙荣恒. 随机过程及其应用[M]. 北京: 清华大学出版社, 2004.
|
|
[6]
|
王梓坤. 随机过程论[M]. 北京: 科学出版社, 1978.
|