Evidence map›Paper›PMID 42440250›Full record

ArticleHealth care management science2026

Optimizing vaccine site locations while considering travel inconvenience and public health outcomes.

Suyanpeng Zhang, Sze-Chuan Suen, Han Yu, Maged Dessouky, Fernando Ordonez

Abstract read
In one paragraph

Article in Health care management science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Suyanpeng ZhangDaniel J. Epstein Department of Industrial and Systems Engineering, Viterbi School of Engineering, University of Southern California, 3715 McClintock Ave, 90089, Los Angeles, CA, USA. suyanpen@usc.edu.ORCID http://orcid.org/0000-0002-8957-1293
Sze-Chuan SuenDaniel J. Epstein Department of Industrial and Systems Engineering, Viterbi School of Engineering, University of Southern California, 3715 McClintock Ave, 90089, Los Angeles, CA, USA.
Han YuDaniel J. Epstein Department of Industrial and Systems Engineering, Viterbi School of Engineering, University of Southern California, 3715 McClintock Ave, 90089, Los Angeles, CA, USA.
Maged DessoukyDaniel J. Epstein Department of Industrial and Systems Engineering, Viterbi School of Engineering, University of Southern California, 3715 McClintock Ave, 90089, Los Angeles, CA, USA.
Fernando OrdonezDepartment of Industrial Engineering, Universidad de Chile, Beauchef 850, 8370451, Santiago, Región Metropolitana, Chile.

Funding

National Science Foundation 2237959U.S. National Library of Medicine 5R21LM013697
6 · The paper itself

Abstract

During the COVID-19 pandemic, selecting vaccination sites and allocating limited doses required balancing accessibility, disease control, and fairness. We formulate a multi-objective mixed-integer linear programming model that jointly determines the locations of mega-sites and allocates vaccine doses while explicitly incorporating travel inconvenience, disease dynamics, and equitable distribution. The model incorporates commuting patterns from both residential and workplace origins to more accurately capture population mobility, and employs a tractable objective formulation that proxies key public health goals, enabling efficient and equitable mass vaccination planning. Compared with the solution empirically used in Los Angeles County in 2020, we recommend more dispersed mega-site locations that result in a 26% reduction in travel inconvenience and avert an additional 200 infections.

Indexed as

COVID-19COVID-19 VaccinesPublic HealthTravelVaccinationHumansLos AngelesSARS-CoV-2TransportationCOVID-19 VaccinesCOVID-19Travel inconvenienceVaccine allocationVaccine sites

Identifiers

PMID42440250
PMCPMC13364939

What Socratic 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 Socratic graph.