000100718 001__ 100718
000100718 005__ 20230519145418.0
000100718 0247_ $$2doi$$a10.31349/RevMexFis.67.123
000100718 0248_ $$2sideral$$a123399
000100718 037__ $$aART-2021-123399
000100718 041__ $$aeng
000100718 100__ $$aRamirez-Torres, E.E.
000100718 245__ $$aMathematical modeling and forecasting of COVID-19: experience in Santiago de Cuba province
000100718 260__ $$c2021
000100718 5060_ $$aAccess copy available to the general public$$fUnrestricted
000100718 5203_ $$aIn the province of Santiago de Cuba, Cuba, the COVID-19 epidemic has a limited progression that shows an early small-number peak of infections. Most published mathematical models fit data with high numbers of confirmed cases. In contrast, small numbers of cases make it difficult to predict the course of the epidemic. We present two known models adapted to capture the noisy dynamics of COVID-19 in the Santiago de Cuba province. Parameters of both models were estimated using the approximate-Bayesian-computation framework with dedicated error laws. One parameter of each model was updated on key dates of travel restrictions. Both models approximately predicted the infection peak and the end of the COVID-19 epidemic in Santiago de Cuba. The first model predicted 57 reported cases and 16 unreported cases. Additionally, it estimated six initially exposed persons. The second model forecasted 51 confirmed cases at the end of the epidemic. In conclusion, an opportune epidemiological investigation, along with the low number of initially exposed individuals, might partly explain the favorable evolution of the COVID-19 epidemic in Santiago de Cuba. With the available data, the simplest model predicted the epidemic evolution with greater precision, and the more complex model helped to explain the epidemic phenomenology.
000100718 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
000100718 590__ $$a1.702$$b2021
000100718 592__ $$a0.248$$b2021
000100718 594__ $$a1.9$$b2021
000100718 591__ $$aPHYSICS, MULTIDISCIPLINARY$$b55 / 86 = 0.64$$c2021$$dQ3$$eT2
000100718 593__ $$aPhysics and Astronomy (miscellaneous)$$c2021$$dQ3
000100718 593__ $$aEducation$$c2021$$dQ3
000100718 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000100718 700__ $$aCastaneda, A.R.S.
000100718 700__ $$aRodriguez-Aldana, Y.
000100718 700__ $$aDominguez, S.S.
000100718 700__ $$aGarcia, L.E.V.
000100718 700__ $$aPalü-Orozco, A.
000100718 700__ $$aOliveros-Dominguez, E.R.
000100718 700__ $$aZamora-Matamoros, L.
000100718 700__ $$aLabrada-Claro, R.
000100718 700__ $$aCobas-Batista, M.
000100718 700__ $$aSedai-Yanes, D.
000100718 700__ $$aSoler-Narino, O.
000100718 700__ $$aValdés-Sosa, P.A.
000100718 700__ $$0(orcid)0000-0001-6120-4427$$aMontijano, J.I.$$uUniversidad de Zaragoza
000100718 700__ $$aCabrales, L.E.B.
000100718 7102_ $$12005$$2595$$aUniversidad de Zaragoza$$bDpto. Matemática Aplicada$$cÁrea Matemática Aplicada
000100718 773__ $$g67, 1 (2021), 123-136$$pRev. mex. fis.$$tREVISTA MEXICANA DE FISICA$$x0035-001X
000100718 8564_ $$s243574$$uhttps://zaguan.unizar.es/record/100718/files/texto_completo.pdf$$yVersión publicada
000100718 8564_ $$s1469759$$uhttps://zaguan.unizar.es/record/100718/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000100718 909CO $$ooai:zaguan.unizar.es:100718$$particulos$$pdriver
000100718 951__ $$a2023-05-18-14:04:06
000100718 980__ $$aARTICLE