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An SEIR Model for Investigation on Covid-19 Pandemic of Indian Kerala Region with Vaccination and Quarantine

Yi Yang
Biomedical Engineering, Rutgers University, New Jersey, United States

AbstractThe covid-19 pandemic has caused a considerable number of casualties around the whole world. Although the vaccine has been developed and spread to society, the new variants Delta (B1.617.2) are gradually overwhelming the efficiency of the vaccine. In India, where the B1.617.2 variant originated, the total confirmed cases of a specific region named Kerala had exceeded 4.5 million at the beginning of October 2021. To help simulate and predict the tendency of the new B1.617.2 variant in this region, we develop a new Susceptible-Exposed-Infected-Removed (SEIR) model that also contains the two vaccine shot variables and two quarantine variables to simulate the spread of this kind of new variant much closer to reality. The whole SEIR model has 9 ODE functions and 14 constant parameters. We used MATLAB to calculate the 14 constant parameters with the actual dataset for the Kerala region and to make the final prediction on five specific variables: Infection, Death, Recovery, Vaccine 1st shot, Vaccine 2nd Shot. The final result shows that this SEIR model can make a satisfactory prediction on those variables.
Index Terms—SEIR, COVID-19, Kerala, prediction, model, vaccine shot, quarantine

Cite: Yi Yang, "An SEIR Model for Investigation on Covid-19 Pandemic of Indian Kerala Region with Vaccination and Quarantine," International Journal of Pharma Medicine and Biological Sciences, Vol. 11, No. 4, pp. 76-83, October 2022. doi: 10.18178/ijpmbs.11.4.76-83

Copyright © 2022 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.
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