Validating Optimal COVID-19 Vaccine Distribution Models
21st International Conference on Computational Science, ICCS 2021
; 12742 LNCS:352-366, 2021.
Article
in English
| Scopus | ID: covidwho-1342943
ABSTRACT
With the approval of vaccines for the coronavirus disease by many countries worldwide, most developed nations have begun, and developing nations are gearing up for the vaccination process. This has created an urgent need to provide a solution to optimally distribute the available vaccines once they are received by the authorities. In this paper, we propose a clustering-based solution to select optimal distribution centers and a Constraint Satisfaction Problem framework to optimally distribute the vaccines taking into consideration two factors namely priority and distance. We demonstrate the efficiency of the proposed models using real-world data obtained from the district of Chennai, India. The model provides the decision making authorities with optimal distribution centers across the district and the optimal allocation of individuals across these distribution centers with the flexibility to accommodate a wide range of demographics. © 2021, Springer Nature Switzerland AG.
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Prognostic study
Topics:
Vaccines
Language:
English
Journal:
21st International Conference on Computational Science, ICCS 2021
Year:
2021
Document Type:
Article
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