{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,28]],"date-time":"2026-07-28T21:04:15Z","timestamp":1785272655102,"version":"3.55.0"},"reference-count":41,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2021,8,28]],"date-time":"2021-08-28T00:00:00Z","timestamp":1630108800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Axioms"],"abstract":"<jats:p>In this paper, the aim is to capture the global pandemic of COVID-19 with parameters that consider the interactions among individuals by proposing a mathematical model. The introduction of a parsimonious model captures both the isolation of symptomatic infected individuals and population lockdown practices in response to containment policies. Local stability and basic reproduction numbers are analyzed. Local sensitivity indices of the parameters of the proposed model are calculated, using the non-normalization, half-normalization, and full-normalization techniques. Numerical investigations show that the dynamics of the system depend on the model parameters. The infection transmission rate (as a function of the lockdown parameter) for both reported and unreported symptomatic infected peoples is a significant parameter in spreading the infection. A nationwide public lockdown decreases the number of infected cases and stops the pandemic\u2019s peak from occurring. The results obtained from this study are beneficial worldwide for developing different COVID-19 management programs.<\/jats:p>","DOI":"10.3390\/axioms10030204","type":"journal-article","created":{"date-parts":[[2021,8,29]],"date-time":"2021-08-29T21:45:16Z","timestamp":1630273516000},"page":"204","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["How Containment Can Effectively Suppress the Outbreak of COVID-19: A Mathematical Modeling"],"prefix":"10.3390","volume":"10","author":[{"given":"Bootan","family":"Rahman","sequence":"first","affiliation":[{"name":"Mathematics Unit, School of Science and Engineering, University of Kurdistan Hewl\u00ear (UKH), Erbil 44001, Iraq"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sarbaz H. A.","family":"Khoshnaw","sequence":"additional","affiliation":[{"name":"Department of Mathematics, University of Raparin, Ranya 46012, Iraq"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2198-9845","authenticated-orcid":false,"given":"Grace O.","family":"Agaba","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Computer Science, Benue State University, Makurdi P.M.B. 102119, Nigeria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3744-5524","authenticated-orcid":false,"given":"Fahad","family":"Al Basir","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Asansol Girls\u2019 College, Asansol 713304, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"109846","DOI":"10.1016\/j.chaos.2020.109846","article-title":"Mathematical modeling of COVID-19 transmission dynamics with a case study of Wuhan","volume":"135","author":"Area","year":"2020","journal-title":"Chaos Solitons Fractals"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Arcede, J.P., Caga-anan, R.L., Mentuda, C.Q., and Mammeri, Y. 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