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SIR-M Epidemic Model: A SARS-CoV-2 Perspective
Lecture Notes on Data Engineering and Communications Technologies ; 142:499-508, 2023.
Article in English | Scopus | ID: covidwho-2243647
ABSTRACT
The outbreak of SARS-CoV-2 in November 2019 has been modeled into the Susceptible-Infectious-Recovery (SIR) model initially. The second wave outbreak of the mutant SARS-CoV-2 has statistically proved to hold an exponential growth of mortality rate, especially in India. The infection-recovery strategy observed could be easily modeled to the SIR(Susceptible-Infectious-Recovery) model. Also, the studies included the exposure to the virus resulting in SIER (Susceptible-Infection-Exposure-Recovery) model. The daily statistics published by the World Health Organization (WHO) also reveal unavoidable statistics that represent the count of deaths. As of May 30, 2021, India has reported 27 million total infected cases, and 32 hundred thousand deaths have been reported. This alarms that the spread of pandemics cannot be visualized as a simple SIR model. The significant ratio between the infected and the mortals leads to remodeling the SIR model as SIR-M(Susceptible-Infectious-Recovery-Mortality) model. This paper includes the death count into the model and remodels the SIR model as SIR-M(Susceptible-Infectious-Recovery-Mortality) model. Our proposed model includes a factor, namely δ, which primarily depends on the medical condition. This δ is the primary cause of the deaths in the SARS-Cov-2-affected patients. We have studied the causes of mortality in COVID-19 patients and have validated our model with the real-time COVID dataset. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: Lecture Notes on Data Engineering and Communications Technologies Year: 2023 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: Lecture Notes on Data Engineering and Communications Technologies Year: 2023 Document Type: Article