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    Comparative infection modeling and control of COVID-19 transmission patterns in China, South Korea, Italy and Iran

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    Type
    Article
    Authors
    He, Junyu cc
    Chen, Guangwei
    Jiang, Yutong
    Jin, Runjie
    Shortridge, Ashton
    Agusti, Susana cc
    He, Mingjun
    Wu, Jiaping
    Duarte, Carlos M. cc
    Christakos, George
    KAUST Department
    Biological and Environmental Sciences and Engineering (BESE) Division
    Marine Science Program
    Red Sea Research Center (RSRC)
    Date
    2020-08-03
    Online Publication Date
    2020-08-03
    Print Publication Date
    2020-12
    Embargo End Date
    2022-08-06
    Submitted Date
    2020-07-05
    Permanent link to this record
    http://hdl.handle.net/10754/664546
    
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    Abstract
    The COVID-19 has become a pandemic. The timing and nature of the COVID-19 pandemic response and control varied among the regions and from one country to the other, and their role in affecting the spread of the disease has been debated. The focus of this work is on the early phase of the disease when control measures can be most effective. We proposed a modified susceptible-exposed-infected-removed model (SEIR) model based on temporal moving windows to quantify COVID-19 transmission patterns and compare the temporal progress of disease spread in six representative regions worldwide: three Chinese regions (Zhejiang, Guangdong and Xinjiang) vs. three countries (South Korea, Italy and Iran). It was found that in the early phase of COVID-19 spread the disease follows a certain empirical law that is common in all regions considered. Simulations of the imposition of strong social distancing measures were used to evaluate the impact that these measures might have had on the duration and severity of COVID-19 outbreaks in the three countries. Measure-dependent transmission rates followed a modified normal distribution (empirical law) in the three Chinese regions. These rates responded quickly to the launch of the 1st-level Response to Major Public Health Emergency in each region, peaking after 1–2 days, reaching their inflection points after 10–19 days, and dropping to zero after 11–18 days since the 1st-level response was launched. By March 29th, the mortality rates were 0.08% (Zhejiang), 0.54% (Guangdong) and 3.95% (Xinjiang). Subsequent modeling simulations were based on the working assumption that similar infection transmission control measures were taken in South Korea as in Zhejiang on February 25th, in Italy as in Guangdong on February 25th, and in Iran as in Xinjiang on March 8th. The results showed that by June 15th the accumulated infection cases could have been reduced by 32.49% (South Korea), 98.16% (Italy) and 85.73% (Iran). The surface air temperature showed stronger association with transmission rate of COVID-19 than surface relative humidity. On the basis of these findings, disease control measures were shown to be particularly effective in flattening and shrinking the COVID-10 case curve, which could effectively reduce the severity of the disease and mitigate medical burden. The proposed empirical law and the SEIR-temporal moving window model can also be used to study infectious disease outbreaks worldwide.
    Citation
    He, J., Chen, G., Jiang, Y., Jin, R., Shortridge, A., Agusti, S., … Christakos, G. (2020). Comparative infection modeling and control of COVID-19 transmission patterns in China, South Korea, Italy and Iran. Science of The Total Environment, 141447. doi:10.1016/j.scitotenv.2020.141447
    Sponsors
    We would like to thank Mr. Jimi He (The Chinese University of Hong Kong, Shenzhen) for his assistance with the R software coding. This work was supported in part by the National Science Foundation of China (41671399) and the Science and Technology Department of Zhejiang Province (2016C04004).
    Publisher
    Elsevier BV
    Journal
    Science of The Total Environment
    DOI
    10.1016/j.scitotenv.2020.141447
    10.1101/2020.04.09.20053223
    Additional Links
    https://linkinghub.elsevier.com/retrieve/pii/S0048969720349767
    https://www.medrxiv.org/content/medrxiv/early/2020/04/14/2020.04.09.20053223.full.pdf
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.scitotenv.2020.141447
    Scopus Count
    Collections
    Articles; Biological and Environmental Science and Engineering (BESE) Division; Red Sea Research Center (RSRC); Marine Science Program

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