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A novel hybrid SEIQR model incorporating the effect of quarantine and lockdown regulations for COVID-19.
Prabakaran, R; Jemimah, Sherlyn; Rawat, Puneet; Sharma, Divya; Gromiha, M Michael.
  • Prabakaran R; Protein Bioinformatics Lab, Department of Biotechnology, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India.
  • Jemimah S; Protein Bioinformatics Lab, Department of Biotechnology, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India.
  • Rawat P; Protein Bioinformatics Lab, Department of Biotechnology, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India.
  • Sharma D; Protein Bioinformatics Lab, Department of Biotechnology, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India.
  • Gromiha MM; Protein Bioinformatics Lab, Department of Biotechnology, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India. gromiha@iitm.ac.in.
Sci Rep ; 11(1): 24073, 2021 12 15.
Article in English | MEDLINE | ID: covidwho-1585794
ABSTRACT
Mitigating the devastating effect of COVID-19 is necessary to control the infectivity and mortality rates. Hence, several strategies such as quarantine of exposed and infected individuals and restricting movement through lockdown of geographical regions have been implemented in most countries. On the other hand, standard SEIR based mathematical models have been developed to understand the disease dynamics of COVID-19, and the proper inclusion of these restrictions is the rate-limiting step for the success of these models. In this work, we have developed a hybrid Susceptible-Exposed-Infected-Quarantined-Removed (SEIQR) model to explore the influence of quarantine and lockdown on disease propagation dynamics. The model is multi-compartmental, and it considers everyday variations in lockdown regulations, testing rate and quarantine individuals. Our model predicts a considerable difference in reported and actual recovered and deceased cases in qualitative agreement with recent reports.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study / Qualitative research Limits: Humans Language: English Journal: Sci Rep Year: 2021 Document Type: Article Affiliation country: S41598-021-03436-Z

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study / Qualitative research Limits: Humans Language: English Journal: Sci Rep Year: 2021 Document Type: Article Affiliation country: S41598-021-03436-Z