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Applicability of time fractional derivative models for simulating the dynamics and mitigation scenarios of COVID-19

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dc.contributor.authorZhang, Yong
dc.contributor.authorYu, Xiangnan
dc.contributor.authorSun, HongGuang
dc.contributor.authorTick, Geoffrey R.
dc.contributor.authorWei, Wei
dc.contributor.authorJin, Bin
dc.contributor.otherUniversity of Alabama Tuscaloosa
dc.contributor.otherHohai University
dc.contributor.otherNanjing Normal University
dc.contributor.otherNanjing Medical University
dc.date.accessioned2023-09-28T19:38:49Z
dc.date.available2023-09-28T19:38:49Z
dc.date.issued2020
dc.description.abstractFractional calculus provides a promising tool for modeling fractional dynamics in computational biology, and this study tests the applicability of fractional-derivative equations (FDEs) for modeling the dynamics and mitigation scenarios of the novel coronavirus for the first time. The coronavirus disease 2019 (COVID19) pandemic radically impacts our lives, while the evolution dynamics of COVID-19 remain obscure. A time-dependent Susceptible, Exposed, Infectious, and Recovered (SEIR) model was proposed and applied to fit and then predict the time series of COVID-19 evolution observed over the last three months (up to 3/22/2020) in China. The model results revealed that 1) the transmission, infection and recovery dynamics follow the integral-order SEIR model with significant spatiotemporal variations in the recovery rate, likely due to the continuous improvement of screening techniques and public hospital systems, as well as full city lockdowns in China, and 2) the evolution of number of deaths follows the time FDE, likely due to the time memory in the death toll. The validated SEIR model was then applied to predict COVID-19 evolution in the United States, Italy, Japan, and South Korea. In addition, a time FDE model based on the random walk particle tracking scheme, analogous to a mixing-limited bimolecular reaction model, was developed to evaluate non-pharmaceutical strategies to mitigate COVID-19 spread. Preliminary tests using the FDE model showed that self-quarantine may not be as efficient as strict social distancing in slowing COVID-19 spread. Therefore, caution is needed when applying FDEs to model the coronavirus outbreak, since specific COVID-19 kinetics may not exhibit nonlocal behavior. Particularly, the spread of COVID-19 may be affected by the rapid improvement of health care systems which may remove the memory impact in COVID-19 dynamics (resulting in a short-tailed recovery curve), while the death toll and mitigation of COVID-19 can be captured by the time FDEs due to the nonlocal, memory impact in fatality and human activities. (C) 2020 Elsevier Ltd. All rights reserved.en_US
dc.format.mediumelectronic
dc.format.mimetypeapplication/pdf
dc.identifier.citationZhang, Y., Yu, X., Sun, H., Tick, G. R., Wei, W., & Jin, B. (2020). Applicability of time fractional derivative models for simulating the dynamics and mitigation scenarios of COVID-19. In Chaos, Solitons & Fractals (Vol. 138, p. 109959). Elsevier BV. https://doi.org/10.1016/j.chaos.2020.109959
dc.identifier.doi10.1016/j.chaos.2020.109959
dc.identifier.orcidhttps://orcid.org/0000-0002-5517-5057
dc.identifier.orcidhttps://orcid.org/0000-0003-2918-7107
dc.identifier.orcidhttps://orcid.org/0000-0002-1097-4234
dc.identifier.urihttps://ir.ua.edu/handle/123456789/11672
dc.languageEnglish
dc.language.isoen_US
dc.publisherPergamon
dc.subjectFractional calculus
dc.subjectBiology
dc.subjectCOVID-19
dc.subjectSEIR
dc.subjectFractional derivative equation
dc.subjectEPIDEMIC
dc.subjectWUHAN
dc.subjectMathematics, Interdisciplinary Applications
dc.subjectPhysics, Multidisciplinary
dc.subjectPhysics, Mathematical
dc.titleApplicability of time fractional derivative models for simulating the dynamics and mitigation scenarios of COVID-19en_US
dc.typeArticle
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