An Improved Epidemiological Model for the Underprivileged People in the Contemporary Pandemics.
In this work, we introduce an improved form of the basic SEIRD model based on Python simulation for the troublesome people who are oblivious about the contemporary pandemics due to diverse social impediments, especially those economically underprivileged. In the extant epidemiological models, some u...
| Publicado en: | BioMed Research International pp. 1 - 15 |
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| Autores principales: | , , , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
10/11/2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=159720892&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 159720892 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 10/11/2022 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 159720892 159720892 159720892 10.1155/2022/7890821 159720892 ppf: 1 ppct: 14 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: An Improved Epidemiological Model for the Underprivileged People in the Contemporary Pandemics. aug: au: Uddin, Mahtab Mugdha, Shafayat Bin Shabbir Shermin, Tamanna Chowdhury, Kawsar Newaz affil: Institute of Natural Sciences, United International University, Dhaka 1212, Bangladesh sug: subj: COVID-19 Pandemic Medically Underserved Models, Statistical Human Data Analytics Regression Illiteracy Algorithms Correlational Studies Theory Validation Validation Studies Poverty ab: In this work, we introduce an improved form of the basic SEIRD model based on Python simulation for the troublesome people who are oblivious about the contemporary pandemics due to diverse social impediments, especially those economically underprivileged. In the extant epidemiological models, some unorthodox issues are yet to be considered, such as poverty, illiteracy, and carelessness towards health issues, significantly influencing the data modeling. Our focus is to overcome these issues by adding two more branches, for instance, uncovered and apathetic people, which significantly influence the practical purposes. For the data simulation, we have used the Python-based algorithm that trains the desired system based on a set of real-time data with the proposed model and provides predicted data with a certain level of accuracy. Comparative discussions, statistical error analysis, and correlation-regression analysis have been introduced to validate the proposed epidemiological model. To show the numerical evidence, the investigation comprised the figurative and tabular modes for both real-time and predicted data. Finally, we discussed some concluding remarks based on our findings. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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