Evidence map›Paper›PMID 36199283›Full record

ArticlePeerJ2022

Optimal selection of COVID-19 vaccination sites in the Philippines at the municipal level.

Kurt Izak Cabanilla, Erika Antonette T Enriquez, Arrianne Crystal Velasco, Victoria May P Mendoza, Renier Mendoza

Abstract read
In one paragraph

Article in PeerJ, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Optimizing the Selection of Mass Vaccination Sites: Access and Equity Consideration.International journal of environmental research and public health · 2024
    Article
  2. Location Optimization of COVID-19 Vaccination Sites: Case in Hillsborough County, Florida.International journal of environmental research and public health · 2022
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Kurt Izak Cabanilla *Institute of Mathematics, University of the Philippines Diliman, Quezon City, Philippines.
Erika Antonette T Enriquez *Institute of Mathematics, University of the Philippines Diliman, Quezon City, Philippines.
Arrianne Crystal VelascoInstitute of Mathematics, University of the Philippines Diliman, Quezon City, Philippines.
Victoria May P MendozaInstitute of Mathematics, University of the Philippines Diliman, Quezon City, Philippines.
Renier MendozaInstitute of Mathematics, University of the Philippines Diliman, Quezon City, Philippines.ORCID 0000-0003-3507-0327

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

COVID-19AlgorithmsCOVID-19 VaccinesHumansPhilippinesVaccinationCOVID-19 VaccinesCOVID-19Dynamic programmingFacility locationGenetic algorithmMulti-objective optimizationOpen street mapsPhilippinesVaccination

Identifiers

PMID36199283
PMCPMC9528907

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.