Priority and age specific vaccination algorithm for the pandemic diseases: a comprehensive parametric prediction model

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dc.authoridTutsoy, Onder/0000-0001-6385-3025
dc.contributor.authorTutsoy, Önder
dc.contributor.authorTanrikulu, Mahmud Yusuf
dc.date.accessioned2025-01-06T17:37:16Z
dc.date.available2025-01-06T17:37:16Z
dc.date.issued2022
dc.description.abstractBackground There have been several destructive pandemic diseases in the human history. Since these pandemic diseases spread through human-to-human infection, a number of non-pharmacological policies has been enforced until an effective vaccine has been developed. In addition, even though a vaccine has been developed, due to the challenges in the production and distribution of the vaccine, the authorities have to optimize the vaccination policies based on the priorities. Considering all these facts, a comprehensive but simple parametric model enriched with the pharmacological and non-pharmacological policies has been proposed in this study to analyse and predict the future pandemic casualties. Method This paper develops a priority and age specific vaccination policy and modifies the non-pharmacological policies including the curfews, lockdowns, and restrictions. These policies are incorporated with the susceptible, suspicious, infected, hospitalized, intensive care, intubated, recovered, and death sub-models. The resulting model is parameterizable by the available data where a recursive least squares algorithm with the inequality constraints optimizes the unknown parameters. The inequality constraints ensure that the structural requirements are satisfied and the parameter weights are distributed proportionally. Results The results exhibit a distinctive third peak in the casualties occurring in 40 days and confirm that the intensive care, intubated, and death casualties converge to zero faster than the susceptible, suspicious, and infected casualties with the priority and age specific vaccination policy. The model also estimates that removing the curfews on the weekends and holidays cause more casualties than lifting the restrictions on the people with the chronic diseases and age over 65. Conclusion Sophisticated parametric models equipped with the pharmacological and non-pharmacological policies can predict the future pandemic casualties for various cases.
dc.identifier.doi10.1186/s12911-021-01720-6
dc.identifier.issn1472-6947
dc.identifier.issue1
dc.identifier.pmid34991566
dc.identifier.scopus2-s2.0-85122505552
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1186/s12911-021-01720-6
dc.identifier.urihttps://hdl.handle.net/20.500.14669/2170
dc.identifier.volume22
dc.identifier.wosWOS:000739960300003
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherBmc
dc.relation.ispartofBmc Medical Informatics and Decision Making
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20241211
dc.subjectCOVID-19
dc.subjectPandemic
dc.subjectPriority and age specific vaccination policy
dc.subjectParametric model
dc.subjectPrediction
dc.titlePriority and age specific vaccination algorithm for the pandemic diseases: a comprehensive parametric prediction model
dc.typeArticle

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