2020/07/31 by Takashi Odagaki
Agricultural and Biological Sciences · Biochemistry, Genetics and Molecular Biology · Mathematics · Medicine · Physics and Astronomy · #2019-20 coronavirus outbreak #Agricultural risk and resilience #Basis (linear algebra) #Biology #COVID-19 epidemiological studies #Computer science #Coronavirus disease 2019 (COVID-19) #Data mining #Epidemic model #Infectious disease (medical specialty) #Mathematics #Measure (data warehouse) #Medicine #Outbreak #Pandemic #Quarantine #SARS-CoV-2 and COVID-19 Research #Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) #Statistics #Virology #physics.soc-ph #q-bio.PE
paper · pdf · doi:10.1016/j.physa.2020.125564
14 pages, 14 figures
arxiv created 2020/08/17 · openalex publication_date 2020/11/21 · arxiv updated 2020/12/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
The SIQR model is reformulated where compartments for infected and quarantined are redefined so as to be appropriate to COVID-19, and exact properties of the model are presented. It is shown that the maximum number of infected at large depends strongly on the quarantine rate and that the quarantine measure is more effective than the lockdown measure in controlling the pandemic. The peak of the number of quarantined patients is shown to appear some time later than the time that the number of infected becomes maximum. On the basis of the expected utility theory, a theoretical framework to find out an optimum strategy in the space of lockdown measure and quarantine measure is proposed for minimizing the maximum number of infected and for controlling the outbreak of pandemic at its early stage.