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A Mathematical Model to Study the Effectiveness of Some of the Strategies Adopted in Curtailing the Spread of COVID-19.
Baba, Isa Abdullahi; Baba, Bashir Abdullahi; Esmaili, Parvaneh.
  • Baba IA; Bayero University, Kano, Nigeria.
  • Baba BA; Near East University, TRNC, Turkey.
  • Esmaili P; Near East University, TRNC, Turkey.
Comput Math Methods Med ; 2020: 5248569, 2020.
Article in English | MEDLINE | ID: covidwho-883419
ABSTRACT
In this paper, we developed a model that suggests the use of robots in identifying COVID-19-positive patients and which studied the effectiveness of the government policy of prohibiting migration of individuals into their countries especially from those countries that were known to have COVID-19 epidemic. Two compartmental models consisting of two equations each were constructed. The models studied the use of robots for the identification of COVID-19-positive patients. The effect of migration ban strategy was also studied. Four biologically meaningful equilibrium points were found. Their local stability analysis was also carried out. Numerical simulations were carried out, and the most effective strategy to curtail the spread of the disease was shown.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Coronavirus Infections / Pandemics / Betacoronavirus / Models, Biological Type of study: Diagnostic study / Experimental Studies / Observational study / Prognostic study Limits: Humans Language: English Journal: Comput Math Methods Med Journal subject: Medical Informatics Year: 2020 Document Type: Article Affiliation country: 2020

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Coronavirus Infections / Pandemics / Betacoronavirus / Models, Biological Type of study: Diagnostic study / Experimental Studies / Observational study / Prognostic study Limits: Humans Language: English Journal: Comput Math Methods Med Journal subject: Medical Informatics Year: 2020 Document Type: Article Affiliation country: 2020