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  1. Article: Modeling and forecasting the spread tendency of the COVID-19 in China.

    Sun, Deshun / Duan, Li / Xiong, Jianyi / Wang, Daping

    Advances in difference equations

    2020  Volume 2020, Issue 1, Page(s) 489

    Abstract: To forecast the spread tendency of the COVID-19 in China and provide effective strategies ... tendency of COVID-19 in China and the model can be applied for other countries with appropriate ... 10 to March 3. The model was used to forecast the spread tendency of the disease. The key factors ...

    Abstract To forecast the spread tendency of the COVID-19 in China and provide effective strategies to prevent the disease, an improved SEIR model was established. The parameters of our model were estimated based on collected data that were issued by the National Health Commission of China (NHCC) from January 10 to March 3. The model was used to forecast the spread tendency of the disease. The key factors influencing the epidemic were explored through modulation of the parameters, including the removal rate, the average number of the infected contacting the susceptible per day and the average number of the exposed contacting the susceptible per day. The correlation of the infected is 99.9% between established model data in this study and issued data by NHCC from January 10 to February 15. The correlation of the removed, the death and the cured are 99.8%, 99.8% and 99.6%, respectively. The average forecasting error rates of the infected, the removed, the death and the cured are 0.78%, 0.75%, 0.35% and 0.83%, respectively, from February 16 to March 3. The peak time of the epidemic forecast by our established model coincided with the issued data by NHCC. Therefore, our study established a mathematical model with high accuracy. The aforementioned parameters significantly affected the trend of the epidemic, suggesting that the exposed and the infected population should be strictly isolated. If the removal rate increases to 0.12, the epidemic will come to an end on May 25. In conclusion, the proposed mathematical model accurately forecast the spread tendency of COVID-19 in China and the model can be applied for other countries with appropriate modifications.
    Keywords covid19
    Language English
    Publishing date 2020-09-14
    Publishing country Germany
    Document type Journal Article
    ZDB-ID 2132815-8
    ISSN 1687-1847 ; 1687-1839
    ISSN (online) 1687-1847
    ISSN 1687-1839
    DOI 10.1186/s13662-020-02940-2
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Modeling and forecasting the spread tendency of the COVID-19 in China

    Deshun Sun / Li Duan / Jianyi Xiong / Daping Wang

    Advances in Difference Equations, Vol 2020, Iss 1, Pp 1-

    2020  Volume 16

    Abstract: Abstract To forecast the spread tendency of the COVID-19 in China and provide effective strategies ... tendency of COVID-19 in China and the model can be applied for other countries with appropriate ... 10 to March 3. The model was used to forecast the spread tendency of the disease. The key factors ...

    Abstract Abstract To forecast the spread tendency of the COVID-19 in China and provide effective strategies to prevent the disease, an improved SEIR model was established. The parameters of our model were estimated based on collected data that were issued by the National Health Commission of China (NHCC) from January 10 to March 3. The model was used to forecast the spread tendency of the disease. The key factors influencing the epidemic were explored through modulation of the parameters, including the removal rate, the average number of the infected contacting the susceptible per day and the average number of the exposed contacting the susceptible per day. The correlation of the infected is 99.9% between established model data in this study and issued data by NHCC from January 10 to February 15. The correlation of the removed, the death and the cured are 99.8%, 99.8% and 99.6%, respectively. The average forecasting error rates of the infected, the removed, the death and the cured are 0.78%, 0.75%, 0.35% and 0.83%, respectively, from February 16 to March 3. The peak time of the epidemic forecast by our established model coincided with the issued data by NHCC. Therefore, our study established a mathematical model with high accuracy. The aforementioned parameters significantly affected the trend of the epidemic, suggesting that the exposed and the infected population should be strictly isolated. If the removal rate increases to 0.12, the epidemic will come to an end on May 25. In conclusion, the proposed mathematical model accurately forecast the spread tendency of COVID-19 in China and the model can be applied for other countries with appropriate modifications.
    Keywords COVID-19 ; Mathematical modeling ; Parameter estimation ; Forecasting ; Control strategy ; Mathematics ; QA1-939 ; covid19
    Subject code 612
    Language English
    Publishing date 2020-09-01T00:00:00Z
    Publisher SpringerOpen
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: Modeling and forecasting the spread tendency of the COVID-19 in China

    Sun, Deshun / Duan, Li / Xiong, Jianyi / Wang, Daping

    Advances in Difference Equations

    2020  Volume 2020, Issue 1

    Abstract: Abstract To forecast the spread tendency of the COVID-19 in China and provide effective strategies ... tendency of COVID-19 in China and the model can be applied for other countries with appropriate ... 10 to March 3. The model was used to forecast the spread tendency of the disease. The key factors ...

    Abstract Abstract To forecast the spread tendency of the COVID-19 in China and provide effective strategies to prevent the disease, an improved SEIR model was established. The parameters of our model were estimated based on collected data that were issued by the National Health Commission of China (NHCC) from January 10 to March 3. The model was used to forecast the spread tendency of the disease. The key factors influencing the epidemic were explored through modulation of the parameters, including the removal rate, the average number of the infected contacting the susceptible per day and the average number of the exposed contacting the susceptible per day. The correlation of the infected is 99.9% between established model data in this study and issued data by NHCC from January 10 to February 15. The correlation of the removed, the death and the cured are 99.8%, 99.8% and 99.6%, respectively. The average forecasting error rates of the infected, the removed, the death and the cured are 0.78%, 0.75%, 0.35% and 0.83%, respectively, from February 16 to March 3. The peak time of the epidemic forecast by our established model coincided with the issued data by NHCC. Therefore, our study established a mathematical model with high accuracy. The aforementioned parameters significantly affected the trend of the epidemic, suggesting that the exposed and the infected population should be strictly isolated. If the removal rate increases to 0.12, the epidemic will come to an end on May 25. In conclusion, the proposed mathematical model accurately forecast the spread tendency of COVID-19 in China and the model can be applied for other countries with appropriate modifications.
    Keywords Algebra and Number Theory ; Applied Mathematics ; Analysis ; covid19
    Language English
    Publisher Springer Science and Business Media LLC
    Publishing country us
    Document type Article ; Online
    ZDB-ID 2132815-8
    ISSN 1687-1847 ; 1687-1839
    ISSN (online) 1687-1847
    ISSN 1687-1839
    DOI 10.1186/s13662-020-02940-2
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article: Modeling and forecasting the spread tendency of the COVID-19 in China

    Sun, D. / Duan, L. / Xiong, J. / Wang, D.

    Adv Differ Equ

    Abstract: To forecast the spread tendency of the COVID-19 in China and provide effective strategies ... tendency of COVID-19 in China and the model can be applied for other countries with appropriate ... 10 to March 3 The model was used to forecast the spread tendency of the disease The key factors ...

    Abstract To forecast the spread tendency of the COVID-19 in China and provide effective strategies to prevent the disease, an improved SEIR model was established The parameters of our model were estimated based on collected data that were issued by the National Health Commission of China (NHCC) from January 10 to March 3 The model was used to forecast the spread tendency of the disease The key factors influencing the epidemic were explored through modulation of the parameters, including the removal rate, the average number of the infected contacting the susceptible per day and the average number of the exposed contacting the susceptible per day The correlation of the infected is 99 9% between established model data in this study and issued data by NHCC from January 10 to February 15 The correlation of the removed, the death and the cured are 99 8%, 99 8% and 99 6%, respectively The average forecasting error rates of the infected, the removed, the death and the cured are 0 78%, 0 75%, 0 35% and 0 83%, respectively, from February 16 to March 3 The peak time of the epidemic forecast by our established model coincided with the issued data by NHCC Therefore, our study established a mathematical model with high accuracy The aforementioned parameters significantly affected the trend of the epidemic, suggesting that the exposed and the infected population should be strictly isolated If the removal rate increases to 0 12, the epidemic will come to an end on May 25 In conclusion, the proposed mathematical model accurately forecast the spread tendency of COVID-19 in China and the model can be applied for other countries with appropriate modifications
    Keywords covid19
    Publisher WHO
    Document type Article
    Note WHO #Covidence: #757104
    Database COVID19

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