Open AccessSimulation model for Covid-19 pandemic
Author(s) -
T.P. Borhade,
Adarsh Kulkarni
Publication year - 2021
Publication title -
cardiometry
Language(s) - English
DOI - 10.18137/cardiometry.2021.20.125133
Subject(s) - pandemic , covid-19 , quarantine , computer science , globe , epidemic model , futures contract , identification (biology) , data science , operations research , infectious disease (medical specialty) , business , medicine , engineering , environmental health , population , botany , disease , finance , pathology , biology , ophthalmology
This paper outlines computer modeling algorithms designedto predict and forecast a COVID-19. In this paper, we considera deterministic model. Theongoing COVID-19 epidemic quicklyspread across the globe. Significant behavioural, social initiativesto limit city transport, case identification and touch tracking,quarantine, advice, and knowledge to the public, creationof detection kits, etc. and state measures were conducted toreduce the epidemic and eliminate coronavirus persistence inhumans around theworld from stopping the global coronavirusoutbreak. In this paper, we propose a basic SIR epidemic modelto show a simulation, the MATLAB algorithm using bouncingdots to depict safe and sick people to simulate infection spread.The graphical model shown here is implemented using MATLABpackage version 3.0.In this paper, we discuss the importance of models becausethey help one explore what could happen. They demonstratehow different possible futures might be shaped by what weare doing now. We can examine the effects of specific interventionsin different ways such as quarantine or a lockdown &explore how simulations may predict, how infectious diseasesadvanced to show the possible result of an outbreak, and betterguide initiatives in public health regarding the pandemicresponse andpandemic past including an overview of the keycharacteristics of adverse pandemic consequences and epidemicoutbreak.