Deploying Vaccine Distribution Sites for Improved Accessibility and Equity to Support Pandemic Response.

George Z Li, Ann Li, Madhav Marathe, Aravind Srinivasan, Leonidas Tsepenekas, Anil Vullikanti

Abstract readPreprint

In one paragraph

Article in ArXiv, 2022. 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

6 authors.

George Z LiDepartment of Computer Science, University of Maryland.

Ann LiBiocomplexity Institute and Initiative, University of Virginia.

Madhav MaratheBiocomplexity Institute and Initiative, University of Virginia.

Aravind SrinivasanDepartment of Computer Science, University of Maryland.

Leonidas TsepenekasDepartment of Computer Science, University of Maryland.

Anil VullikantiBiocomplexity Institute and Initiative, University of Virginia.

Funding

Systems Analysis of Social Pathways of Epidemics to Reduce Health DisparitiesR01GM109718 · NIGMS · VIRGINIA POLYTECHNIC INST AND ST UNIV · PI MARATHE, ACHLA, VULLIKANTI, ANIL · 2014 to 2022

$3.6M

NIGMS NIH HHS R01 GM109718

6 · The paper itself

Abstract

In response to COVID-19, many countries have mandated social distancing and banned large group gatherings in order to slow down the spread of SARS-CoV-2. These social interventions along with vaccines remain the best way forward to reduce the spread of SARS CoV-2. In order to increase vaccine accessibility, states such as Virginia have deployed mobile vaccination centers to distribute vaccines across the state. When choosing where to place these sites, there are two important factors to take into account: accessibility and equity. We formulate a combinatorial problem that captures these factors and then develop efficient algorithms with theoretical guarantees on both of these aspects. Furthermore, we study the inherent hardness of the problem, and demonstrate strong impossibility results. Finally, we run computational experiments on real-world data to show the efficacy of our methods.

Identifiers

PMID35169596

PMCPMC8845506

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.