Full metadata record
DC Field | Value | Language |
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dc.contributor.author | 이미진 | - |
dc.date.accessioned | 2024-04-01T04:21:34Z | - |
dc.date.available | 2024-04-01T04:21:34Z | - |
dc.date.issued | 2024-02-05 | - |
dc.identifier.citation | PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS | en_US |
dc.identifier.issn | 0378-4371 | en_US |
dc.identifier.uri | https://www.sciencedirect.com/science/article/pii/S0378437124000888 | en_US |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/189531 | - |
dc.description.abstract | A pandemic, the worldwide spread of a disease, can threaten human beings from both social and biological perspectives and paralyze existing living habits. To stave off the more devastating disaster and return to normal life, people make tremendous efforts at multiscale levels, from individuals to the global population: paying attention to hand hygiene, developing social policies such as wearing masks, practicing social distancing, quarantine, and inventing vaccines and remedies. Regarding the current severe pandemic, namely the coronavirus disease 2019, we explore the spreading -suppression effect when adopting the aforementioned efforts. In this numerical study, we especially consider quarantine and vaccination since they are representative primary treatments for blocking the spread and preventing the disease at the government level. We establish a compartment model consisting of susceptible (S), vaccinated (V), exposed (E), infected (I), quarantined (Q), and recovered (R) compartments, called the SVEIQR model. We examine the number of infected cases in Seoul and consider three kinds of vaccines: Pfizer, Moderna, and AstraZeneca. The values of the relevant parameters are obtained from empirical data from Seoul and clinical data for the vaccines and estimated through Bayesian inference. After confirming the plausibility of our SVEIQR model, we test various scenarios by adjusting the associated parameters with the quarantine and vaccination policies around the current values. The quantitative results obtained from our model could suggest guidelines for policy making on effective vaccination and social policies. | en_US |
dc.description.sponsorship | This research was supported by the National Research Foundation (NRF) of Korea through the Grant Numbers. NRF-2023R1A2C1007523 (S.-W.S.), NRF-2021R1C1C1007918 (M.J.L.). This work was also partly supported by Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No. RS-2022-00155885, Artificial Intelligence Convergence Innovation Human Resources Development (Hanyang University ERICA)) (S.-W.S.). We also acknowledge the hospitality at APCTP where part of this work was done. | en_US |
dc.language | en_US | en_US |
dc.publisher | ELSEVIER | en_US |
dc.relation.ispartofseries | v. 637;1-9 | - |
dc.subject | Epidemic model | en_US |
dc.subject | Vaccination | en_US |
dc.subject | Quarantine | en_US |
dc.title | Effectiveness of vaccination and quarantine policies to curb the spread of COVID-19 | en_US |
dc.type | Article | en_US |
dc.relation.volume | 637 | - |
dc.identifier.doi | 10.1016/j.physa.2024.129580 | en_US |
dc.relation.page | 1295801-1295809 | - |
dc.relation.journal | PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS | - |
dc.contributor.googleauthor | Jang, Gyeong Hwan | - |
dc.contributor.googleauthor | Kim, Sung Jin | - |
dc.contributor.googleauthor | Lee, Mi Jin | - |
dc.contributor.googleauthor | Son, Seung-Woo | - |
dc.relation.code | 2024002691 | - |
dc.sector.campus | E | - |
dc.sector.daehak | COLLEGE OF SCIENCE AND CONVERGENCE TECHNOLOGY[E] | - |
dc.sector.department | DEPARTMENT OF APPLIED PHYSICS | - |
dc.identifier.pid | mijinlee | - |
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