Optimal selection of COVID-19 vaccination sites in the Philippines at the municipal level
In this work, we present an approach to determine the optimal location of coronavirus disease 2019 (COVID-19) vaccination sites at the municipal level. We assume that each municipality is subdivided into smaller administrative units, which we refer to as barangays. The proposed method solves a minim...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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PeerJ Inc.
2022-09-01
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| Series: | PeerJ |
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| Online Access: | https://peerj.com/articles/14151.pdf |
| _version_ | 1797422094630256640 |
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| author | Kurt Izak Cabanilla Erika Antonette T. Enriquez Arrianne Crystal Velasco Victoria May P. Mendoza Renier Mendoza |
| author_facet | Kurt Izak Cabanilla Erika Antonette T. Enriquez Arrianne Crystal Velasco Victoria May P. Mendoza Renier Mendoza |
| author_sort | Kurt Izak Cabanilla |
| collection | DOAJ |
| description | In this work, we present an approach to determine the optimal location of coronavirus disease 2019 (COVID-19) vaccination sites at the municipal level. We assume that each municipality is subdivided into smaller administrative units, which we refer to as barangays. The proposed method solves a minimization problem arising from a facility location problem, which is formulated based on the proximity of the vaccination sites to the barangays, the number of COVID-19 cases, and the population densities of the barangays. These objectives are formulated as a single optimization problem. As an alternative decision support tool, we develop a bi-objective optimization problem that considers distance and population coverage. Lastly, we propose a dynamic optimization approach that recalculates the optimal vaccination sites to account for the changes in the population of the barangays that have completed their vaccination program. A numerical scheme that solves the optimization problems is presented and the detailed description of the algorithms, which are coded in Python and MATLAB, are uploaded to a public repository. As an illustration, we apply our method to determine the optimal location of vaccination sites in San Juan, a municipality in the province of Batangas, in the Philippines. We hope that this study may guide the local government units in coming up with strategic and accessible plans for vaccine administration. |
| first_indexed | 2024-03-09T07:27:11Z |
| format | Article |
| id | doaj.art-657998b3d1a840068ebcc6e88e821560 |
| institution | Directory Open Access Journal |
| issn | 2167-8359 |
| language | English |
| last_indexed | 2024-03-09T07:27:11Z |
| publishDate | 2022-09-01 |
| publisher | PeerJ Inc. |
| record_format | Article |
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| spelling | doaj.art-657998b3d1a840068ebcc6e88e8215602023-12-03T06:51:47ZengPeerJ Inc.PeerJ2167-83592022-09-0110e1415110.7717/peerj.14151Optimal selection of COVID-19 vaccination sites in the Philippines at the municipal levelKurt Izak CabanillaErika Antonette T. EnriquezArrianne Crystal VelascoVictoria May P. MendozaRenier MendozaIn this work, we present an approach to determine the optimal location of coronavirus disease 2019 (COVID-19) vaccination sites at the municipal level. We assume that each municipality is subdivided into smaller administrative units, which we refer to as barangays. The proposed method solves a minimization problem arising from a facility location problem, which is formulated based on the proximity of the vaccination sites to the barangays, the number of COVID-19 cases, and the population densities of the barangays. These objectives are formulated as a single optimization problem. As an alternative decision support tool, we develop a bi-objective optimization problem that considers distance and population coverage. Lastly, we propose a dynamic optimization approach that recalculates the optimal vaccination sites to account for the changes in the population of the barangays that have completed their vaccination program. A numerical scheme that solves the optimization problems is presented and the detailed description of the algorithms, which are coded in Python and MATLAB, are uploaded to a public repository. As an illustration, we apply our method to determine the optimal location of vaccination sites in San Juan, a municipality in the province of Batangas, in the Philippines. We hope that this study may guide the local government units in coming up with strategic and accessible plans for vaccine administration.https://peerj.com/articles/14151.pdfCOVID-19Dynamic programmingFacility locationGenetic algorithmMulti-objective optimizationOpen street maps |
| spellingShingle | Kurt Izak Cabanilla Erika Antonette T. Enriquez Arrianne Crystal Velasco Victoria May P. Mendoza Renier Mendoza Optimal selection of COVID-19 vaccination sites in the Philippines at the municipal level PeerJ COVID-19 Dynamic programming Facility location Genetic algorithm Multi-objective optimization Open street maps |
| title | Optimal selection of COVID-19 vaccination sites in the Philippines at the municipal level |
| title_full | Optimal selection of COVID-19 vaccination sites in the Philippines at the municipal level |
| title_fullStr | Optimal selection of COVID-19 vaccination sites in the Philippines at the municipal level |
| title_full_unstemmed | Optimal selection of COVID-19 vaccination sites in the Philippines at the municipal level |
| title_short | Optimal selection of COVID-19 vaccination sites in the Philippines at the municipal level |
| title_sort | optimal selection of covid 19 vaccination sites in the philippines at the municipal level |
| topic | COVID-19 Dynamic programming Facility location Genetic algorithm Multi-objective optimization Open street maps |
| url | https://peerj.com/articles/14151.pdf |
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