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The impact of community containment implementation timing on the spread of COVID-19: A simulation study.
Mohsen, Attayeb; Alarabi, Ahmed.
  • Mohsen A; Laboratory of Bioinformatics, Artificial Intelligence Center for Health and Biomedical Research (ArCHER). National Institutes of Biomedical Innovation, Health and Nutrition., Ibaraki city, Osaka, 567-0085, Japan.
  • Alarabi A; Department of Pharmaceutical Sciences, Irma Lerma Rangel College of Pharmacy, Texas A&M University, Kingsville, Texas, 78363, USA.
F1000Res ; 9: 452, 2020.
Article in English | MEDLINE | ID: covidwho-776308
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ABSTRACT

Background:

Community containment is one of the common methods used to mitigate infectious disease outbreaks. The effectiveness of such a method depends on how strictly it is applied and the timing of its implementation. An early start and being strict is very effective; however, at the same time, it impacts freedom and economic opportunity. Here we created a simulation model to understand the effect of the starting day of community containment on the final outcome, that is, the number of those infected, hospitalized and those that died, as we followed the dynamics of COVID-19 pandemic.

Methods:

We used a stochastic recursive simulation method to apply disease outbreak dynamics measures of COVID-19 as an example to simulate disease spread. Parameters are allowed to be randomly assigned between higher and lower values obtained from published COVID-19 literature.

Results:

We simulated the dynamics of COVID-19 spread, calculated the number of active infections, hospitalizations and deaths as the outcome of our simulation and compared these results with real world data. We also represented the details of the spread in a network graph structure, and shared the code for the simulation model to be used for examining other variables.

Conclusions:

Early implementation of community containment has a big impact on the final outcome of an outbreak.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Time Factors / Computer Simulation / Communicable Disease Control / Coronavirus Infections / Pandemics Type of study: Experimental Studies / Prognostic study / Randomized controlled trials Limits: Humans Language: English Journal: F1000Res Year: 2020 Document Type: Article Affiliation country: F1000research.24156.1

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Time Factors / Computer Simulation / Communicable Disease Control / Coronavirus Infections / Pandemics Type of study: Experimental Studies / Prognostic study / Randomized controlled trials Limits: Humans Language: English Journal: F1000Res Year: 2020 Document Type: Article Affiliation country: F1000research.24156.1