新型冠状病毒肺炎疫情确诊病例的统计分析及自回归建模

Translated title of the contribution: Statistical analysis and autoregressive modeling of confirmed coronavirus disease 2019 epidemic cases

曹文静, 刘小菲, 韩卓, 冯鑫*, 张琳*, 刘肖凡, 许小可, 吴晔

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

7 Citations (Scopus)

Abstract

Based on the information about more than 800 case reported by Anhui provincial health commission on February 19 2020, the directional transmission relationship between the confirmed patients is constructed according to the contact history published in the cases, and it is found that the majority of the patients who can infect others are male and most of the patients who are infected are female.  According to the analysis of case information, the early confirmed coronavirus disease 2019 (COVID-19) cases in Anhui province had the history of residence or exposure in Wuhan. In the later stage, the cases spread in small communities mainly by local transmission, and the strict prevention and control measures can effectively cut off further transmission in the communities. The time interval between diagnosing the source-infected patients and infected patients is fitted by G distribution, with a median of 2 days and an average of 2.67 days. Based on the statistical characteristics of directional transmission relationship, an autoregressive transmission model is constructed in the late stage of epidemic development in Anhui province, and the simulation results are consistent with the epidemic development data.  Autoregressive model and simulation are also used for predicting the data of confirmed cases in the whole country except for Hubei province. This discovery can be referenced by regional epidemic prevention and control except for where it originated. Through strict protection measures and isolation measures, the spread of the epidemic outside the original place is highly viscous.  It usually spreads by close contact between family members, and the local spread of COVID-19 can be effectively controlled.
Translated title of the contributionStatistical analysis and autoregressive modeling of confirmed coronavirus disease 2019 epidemic cases
Original languageChinese (Simplified)
Article number090203
Number of pages7
Journal物理学报
Volume69
Issue number9
DOIs
Publication statusPublished - 5 May 2020

Research Keywords

  • 新型冠状病毒肺炎疫情
  • 缓慢增长期
  • 有向传播关系
  • 自回归
  • coronavirus disease 2019 epidemic
  • slow growth period
  • directed transmission
  • autoregression

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