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  1. Article: Effect of the early use of antivirals on the COVID-19 pandemic. A computational network modeling approach.

    Benlloch, José-María / Cortés, Juan-Carlos / Martínez-Rodríguez, David / Julián, Raul-S / Villanueva, Rafael-J

    Chaos, solitons, and fractals

    2020  Volume 140, Page(s) 110168

    Abstract: ... the early use of antivirals may significantly reduce the incidence of COVID-19 and may avoid a new collapse ... a good option that we study in this work. In this paper, we propose a computational random network model ... we use it to simulate several scenarios where effective antivirals are available. The results show how ...

    Abstract It seems that we are far from controlling COVID-19 pandemics, and, consequently, returning to a fully normal life. Until an effective vaccine is found, safety measures as the use of face masks, social distancing, washing hands regularly, etc., have to be taken. Also, the use of appropriate antivirals in order to alleviate the symptoms, to control the severity of the illness and to prevent the transmission, could be a good option that we study in this work. In this paper, we propose a computational random network model to study the transmission dynamics of COVID-19 in Spain. Once the model has been calibrated and validated, we use it to simulate several scenarios where effective antivirals are available. The results show how the early use of antivirals may significantly reduce the incidence of COVID-19 and may avoid a new collapse of the health system.
    Keywords covid19
    Language English
    Publishing date 2020-08-18
    Publishing country England
    Document type Journal Article
    ZDB-ID 2003919-0
    ISSN 1873-2887 ; 0960-0779
    ISSN (online) 1873-2887
    ISSN 0960-0779
    DOI 10.1016/j.chaos.2020.110168
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Effect of the early use of antivirals on the COVID-19 pandemic. A computational network modeling approach

    Benlloch, José-María / Cortés, Juan-Carlos / Martínez-Rodríguez, David / Julián, Raul-S. / Villanueva, Rafael-J.

    Chaos, Solitons & Fractals

    2020  Volume 140, Page(s) 110168

    Keywords General Mathematics ; covid19
    Language English
    Publisher Elsevier BV
    Publishing country us
    Document type Article ; Online
    ZDB-ID 2003919-0
    ISSN 1873-2887 ; 0960-0779
    ISSN (online) 1873-2887
    ISSN 0960-0779
    DOI 10.1016/j.chaos.2020.110168
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article: Effect of the early use of antivirals on the COVID-19 pandemic. A computational network modeling approach

    Benlloch, José-María / Cortés, Juan-Carlos / Martínez-Rodríguez, David / Julián, Raul-S / Villanueva, Rafael-J

    Chaos Solitons Fractals

    Abstract: ... the early use of antivirals may significantly reduce the incidence of COVID-19 and may avoid a new collapse ... a good option that we study in this work. In this paper, we propose a computational random network model ... we use it to simulate several scenarios where effective antivirals are available. The results show how ...

    Abstract It seems that we are far from controlling COVID-19 pandemics, and, consequently, returning to a fully normal life. Until an effective vaccine is found, safety measures as the use of face masks, social distancing, washing hands regularly, etc., have to be taken. Also, the use of appropriate antivirals in order to alleviate the symptoms, to control the severity of the illness and to prevent the transmission, could be a good option that we study in this work. In this paper, we propose a computational random network model to study the transmission dynamics of COVID-19 in Spain. Once the model has been calibrated and validated, we use it to simulate several scenarios where effective antivirals are available. The results show how the early use of antivirals may significantly reduce the incidence of COVID-19 and may avoid a new collapse of the health system.
    Keywords covid19
    Publisher WHO
    Document type Article
    Note WHO #Covidence: #718682
    Database COVID19

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