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Simulation Model for Covid-19 Pandemic

* Corresponding author

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This paper outlines computer modeling algorithms designed to predict and forecast a COVID-19. In this paper, we consider a deterministic model. Theongoing COVID-19 epidemic quickly spread across the globe. Significant behavioural, social initiatives to limit city transport, case identification and touch tracking, quarantine, advice, and knowledge to the public, creation of detection kits, etc. and state measures were conducted to reduce the epidemic and eliminate coronavirus persistence in humans around theworld from stopping the global coronavirus outbreak. In this paper, we propose a basic SIR epidemic model to show a simulation, the MATLAB algorithm using bouncing dots to depict safe and sick people to simulate infection spread. The graphical model shown here is implemented using MATLAB package version 3.0. In this paper, we discuss the importance of models because they help one explore what could happen. They demonstrate how different possible futures might be shaped by what we are doing now. We can examine the effects of specific interventions in different ways such as quarantine or a lockdown & explore how simulations may predict, how infectious diseases advanced to show the possible result of an outbreak, and better guide initiatives in public health regarding the pandemic response andpandemic past including an overview of the key characteristics of adverse pandemic consequences and epidemic outbreak.


Trupti P. Borhade, Apoorva Kulkarni. Simulation Model for Covid-19 Pandemic. Cardiometry; Issue 20; November 2021; p.125-133; DOI: 10.18137/cardiometry.2021.20.125133; Available from:


Simulation modeling,  Flatten the curve,  Pandemic,  COVID-19,  Coronavirus
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