Estimating the Impact of Asymptomatic Carriers on the spread of Infectious Diseases: An interaction-based Model

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dc.contributor.authorRavid, Yaniv
dc.contributor.authorSeidmann, Abraham
dc.date.accessioned2021-12-24T18:19:17Z
dc.date.available2021-12-24T18:19:17Z
dc.date.issued2022-01-04
dc.description.abstractEpidemiological models are commonly used to predict and describe the spread of a viral outbreak among a population. Many such models use differential equations and transition rates to predict the growth dynamics of the infectious and exposed groups with a greater population. These methods do not distinguish between infectious individuals. In this paper, we propose a new model that includes asymptomatic carriers while holding constant many of the transition rates and assumptions of the classical models. Seeking to replicate realistic outbreak scenarios, we introduce a way to estimate the reproduction number R0 of epidemics and apply these estimations to our model. Our results replicate those described in similar research papers, showing that a small proportion of asymptomatic carriers can be responsible for a majority of the transmissions. We propose possible extensions to our model, underlining the impactful applications it may have on healthcare management and public safety policymaking.
dc.format.extent8 pages
dc.identifier.doi10.24251/HICSS.2022.788
dc.identifier.isbn978-0-9981331-5-7
dc.identifier.urihttp://hdl.handle.net/10125/80128
dc.language.isoeng
dc.relation.ispartofProceedings of the 55th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectDigital Transformations of Business Operations
dc.subjectdata science
dc.subjectepidemiology
dc.subjectpublic health
dc.titleEstimating the Impact of Asymptomatic Carriers on the spread of Infectious Diseases: An interaction-based Model
dc.type.dcmitext

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