1 Ocak 2020 Dergi makalesi Açık Erişim

Naik, Parvaiz Ahmad; Yavuz, Mehmet; Qureshi, Sania; Zu, Jian; Townley, Stuart

DataCite XML

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  <identifier identifierType="URL">https://aperta.ulakbim.gov.tr/record/3429</identifier>
  <creators>
    <creator>
      <creatorName>Naik, Parvaiz Ahmad</creatorName>
      <givenName>Parvaiz Ahmad</givenName>
      <familyName>Naik</familyName>
      <affiliation>Xi An Jiao Tong Univ, Sch Math &amp; Stat, Xian 710049, Shaanxi, Peoples R China</affiliation>
    </creator>
    <creator>
      <creatorName>Yavuz, Mehmet</creatorName>
      <givenName>Mehmet</givenName>
      <familyName>Yavuz</familyName>
    </creator>
    <creator>
      <creatorName>Qureshi, Sania</creatorName>
      <givenName>Sania</givenName>
      <familyName>Qureshi</familyName>
      <affiliation>Mehran Univ Engn &amp; Technol, Dept Basic Sci &amp; Related Studies, Jamshoro 76062, Pakistan</affiliation>
    </creator>
    <creator>
      <creatorName>Zu, Jian</creatorName>
      <givenName>Jian</givenName>
      <familyName>Zu</familyName>
      <affiliation>Xi An Jiao Tong Univ, Sch Math &amp; Stat, Xian 710049, Shaanxi, Peoples R China</affiliation>
    </creator>
    <creator>
      <creatorName>Townley, Stuart</creatorName>
      <givenName>Stuart</givenName>
      <familyName>Townley</familyName>
      <affiliation>Univ Exeter, Coll Engn Math &amp; Phys Sci, Dept Math, Penryn TR10, Cornwall, England</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Modeling And Analysis Of Covid-19 Epidemics With Treatment In Fractional Derivatives Using Real Data From Pakistan</title>
  </titles>
  <publisher>Aperta</publisher>
  <publicationYear>2020</publicationYear>
  <dates>
    <date dateType="Issued">2020-01-01</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Journal article</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://aperta.ulakbim.gov.tr/record/3429</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1140/epjp/s13360-020-00819-5</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="http://www.opendefinition.org/licenses/cc-by">Creative Commons Attribution</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">Coronaviruses are a large family of viruses that cause different symptoms, from mild cold to severe respiratory distress, and they can be seen in different types of animals such as camels, cattle, cats and bats. Novel coronavirus called COVID-19 is a newly emerged virus that appeared in many countries of the world, but the actual source of the virus is not yet known. The outbreak has caused pandemic with 26,622,706 confirmed infections and 874,708 reported deaths worldwide till August 31, 2020, with 17,717,911 recovered cases. Currently, there exist no vaccines officially approved for the prevention or management of the disease, but alternative drugs meant for HIV, HBV, malaria and some other flus are used to treat this virus. In the present paper, a fractional-order epidemic model with two different operators called the classical Caputo operator and the Atangana-Baleanu-Caputo operator for the transmission of COVID-19 epidemic is proposed and analyzed. The reproduction number R-0 is obtained for the prediction and persistence of the disease. The dynamic behavior of the equilibria is studied by using fractional Routh-Hurwitz stability criterion and fractional La Salle invariant principle. Special attention is given to the global dynamics of the equilibria. Moreover, the fitting of parameters through least squares curve fitting technique is performed, and the average absolute relative error between COVID-19 actual cases and the model's solution for the infectious class is tried to be reduced and the best fitted values of the relevant parameters are achieved. The numerical solution of the proposed COVID-19 fractional-order model under the Caputo operator is obtained by using generalized AdamsBashforth-Moulton method, whereas for the Atangana-Baleanu-Caputo operator, we have used a new numerical scheme. Also, the treatment compartment is included in the population which determines the impact of alternative drugs applied for treating the infected individuals. Furthermore, numerical simulations of the model and their graphical presentations are performed to visualize the effectiveness of our theoretical results and to monitor the effect of arbitrary-order derivative.</description>
  </descriptions>
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