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Assessing the impact of adherence to Non-pharmaceutical interventions and indirect transmission on the dynamics of COVID-19: a mathematical modelling study.
Iyaniwura, Sarafa A; Rabiu, Musa; David, Jummy F; Kong, Jude D.
  • Iyaniwura SA; Department of Mathematics and Institute of Applied Mathematics, University of British Columbia, Vancouver, BC, Canada.
  • Rabiu M; School of Mathematics, Statistics & Computer Science, University of KwaZulu-Natal, Durban, South Africa.
  • David JF; Department of Mathematics and Statistics, York University, Toronto, Ontario, Canada.
  • Kong JD; Canadian Centre for Diseases Modeling (CCDM), York University, Toronto, Ontario, Canada.
Math Biosci Eng ; 18(6): 8905-8932, 2021 10 15.
Article in English | MEDLINE | ID: covidwho-1502565
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ABSTRACT
Adherence to public health policies such as the non-pharmaceutical interventions implemented against COVID-19 plays a major role in reducing infections and controlling the spread of the diseases. In addition, understanding the transmission dynamics of the disease is also important in order to make and implement efficient public health policies. In this paper, we developed an SEIR-type compartmental model to assess the impact of adherence to COVID-19 non-pharmaceutical interventions and indirect transmission on the dynamics of the disease. Our model considers both direct and indirect transmission routes and stratifies the population into two groups those that adhere to COVID-19 non-pharmaceutical interventions (NPIs) and those that do not adhere to the NPIs. We compute the control reproduction number and the final epidemic size relation for our model and study the effect of different parameters of the model on these quantities. Our results show that there is a significant benefit in adhering to the COVID-19 NPIs.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Epidemics / COVID-19 Type of study: Experimental Studies / Randomized controlled trials Limits: Humans Language: English Journal: Math Biosci Eng Year: 2021 Document Type: Article Affiliation country: Mbe.2021439

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Epidemics / COVID-19 Type of study: Experimental Studies / Randomized controlled trials Limits: Humans Language: English Journal: Math Biosci Eng Year: 2021 Document Type: Article Affiliation country: Mbe.2021439