《MedRixv,2月25日,Intrinsic growth rules of patients infected, dead and cured with 2019 novel coronavirus in mainland China》

  • 来源专题:COVID-19科研动态监测
  • 编译者: zhangmin
  • 发布时间:2020-02-26
  • Intrinsic growth rules of patients infected, dead and cured with 2019 novel coronavirus in mainland China

    Chuanliang Han, Yimeng Liu, Saini Yang

    doi: https://doi.org/10.1101/2020.02.23.20024802

    Abstract

    Background An outbreak of a novel coronavirus (SARS-CoV-2)-infected pneumonia (COVID-19) was first occurred in Wuhan, China, in December 2019 and then spread rapidly to other regions. It has been declared that at least one confirmed case infected by SARS-CoV-2 was found in each province of China by late January 2020. Methods We collected the time series data of the cumulative number of confirmed infected, dead, and cured cases from the health commissions in 31 provinces in mainland China. A simple descriptive model in a logistic form was formulated to infer the intrinsic epidemic rules of COVID-19.

    *注,本文为预印本论文手稿,是未经同行评审的初步报告,其观点仅供科研同行交流,并不是结论性内容,请使用者谨慎使用.

  • 原文来源:https://www.medrxiv.org/content/10.1101/2020.02.23.20024802v1
相关报告
  • 《MedRixv,2月13日,Statistics based predictions of coronavirus 2019-nCoV spreading in mainland China》

    • 来源专题:COVID-19科研动态监测
    • 编译者:zhangmin
    • 发布时间:2020-02-14
    • Statistics based predictions of coronavirus 2019-nCoV spreading in mainland China Igor Nesteruk doi: https://doi.org/10.1101/2020.02.12.20021931 Abstract Background. The epidemic outbreak cased by coronavirus 2019-nCoV is of great interest to researches because of the high rate of spread of the infection and the significant number of fatalities. A detailed scientific analysis of the phenomenon is yet to come, but the public is already interested in the questions of the duration of the epidemic, the expected number of patients and deaths. For long time predictions, the complicated mathematical models are necessary which need many efforts for unknown parameters identification and calculations. In this article, some preliminary estimates will be presented. Objective. Since the reliable long time data are available only for mainland China, we will try to predict the epidemic characteristics only in this area. We will estimate some of the epidemic characteristics and present the most reliable dependences for victim numbers, infected and removed persons versus time. Methods. In this study we use the known SIR model for the dynamics of an epidemic, the known exact solution of the linear equations and statistical approach developed before for investigation of the children disease, which occurred in Chernivtsi (Ukraine) in 1988-1989. Results. The optimal values of the SIR model parameters were identified with the use of statistical approach. The numbers of infected, susceptible and removed persons versus time were predicted. Conclusions. Simple mathematical model was used to predict the characteristics of the epidemic caused by coronavirus 2019-nCoV in mainland China. The further research should focus on updating the predictions with the use of fresh data and using more complicated mathematical models. *注,本文为预印本论文手稿,是未经同行评审的初步报告,其观点仅供科研同行交流,并不是结论性内容,请使用者谨慎使用.
  • 《MedRxiv,2月23日,Association of radiologic findings with mortality of patients infected with 2019 novel coronavirus in Wuhan, China》

    • 来源专题:COVID-19科研动态监测
    • 编译者:xuwenwhlib
    • 发布时间:2020-02-24
    • Association of radiologic findings with mortality of patients infected with 2019 novel coronavirus in Wuhan, China Mingli Yuan, Wen Yin, Zhaowu Tao, Weijun Tan, Yi Hu doi: https://doi.org/10.1101/2020.02.22.20024927 Abstract Radiologic characteristics of 2019 novel coronavirus (2019-nCoV) infected pneumonia (NCIP) which had not been fully understood are especially important for diagnosing and predicting prognosis. We retrospective studied 27 consecutive patients who were confirmed NCIP, the clinical characteristics and CT image findings were collected, and the association of radiologic findings with mortality of patients was evaluated. 27 patients included 12 men and 15 women, with median age of 60 years (IQR 47-69). 17 patients discharged in recovered condition and 10 patients died in hospital. The median age of mortality group was higher compared to survival group (68 (IQR 63-73) vs 55 (IQR 35-60), P = 0.003). The comorbidity rate in mortality group was significantly higher than in survival group (80% vs 29%, P = 0.018). The predominant CT characteristics consisted of ground glass opacity (67%), bilateral sides involved (86%), both peripheral and central distribution (74%), and lower zone involvement (96%). The median CT score of mortality group was higher compared to survival group (30 (IQR 7-13) vs 12 (IQR 11-43), P = 0.021), with more frequency of consolidation (40% vs 6%, P = 0.047) and air bronchogram (60% vs 12%, P = 0.025). An optimal cutoff value of a CT score of 24.5 had a sensitivity of 85.6% and a specificity of 84.5% for the prediction of mortality. 2019-nCoV was more likely to infect elderly people with chronic comorbidities. CT findings of NCIP were featured by predominant ground glass opacities mixed with consolidations, mainly peripheral or combined peripheral and central distributions, bilateral and lower lung zones being mostly involved. A simple CT scoring method was capable to predict mortality. *注,本文为预印本论文手稿,是未经同行评审的初步报告,其观点仅供科研同行交流,并不是结论性内容,请使用者谨慎使用.