Evidence map›Paper›PMID 35062776›Full record

ArticleVaccines2022

Vaccination Schedule under Conditions of Limited Vaccine Production Rate.

Roger Książek, Radosław Kapłan, Katarzyna Gdowska, Piotr Łebkowski

Abstract read
In one paragraph

Article in Vaccines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. 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

4 authors.

Roger KsiążekFaculty of Management, AGH University of Science and Technology, 30-059 Cracow, Poland.ORCID 0000-0002-9156-6995
Radosław KapłanFaculty of Management, AGH University of Science and Technology, 30-059 Cracow, Poland.ORCID 0000-0003-1596-9749
Katarzyna GdowskaFaculty of Management, AGH University of Science and Technology, 30-059 Cracow, Poland.ORCID 0000-0002-7964-3724
Piotr ŁebkowskiFaculty of Management, AGH University of Science and Technology, 30-059 Cracow, Poland.ORCID 0000-0002-5203-4099

Funding

AGH University of Science and Technology Działanie 4 w Projekcie "Inicjatywa Doskonałości - Uczelnia Badawcza" w AGH
6 · The paper itself

Abstract

The paper is devoted to optimal vaccination scheduling during a pandemic to minimize the probability of infection. The recent COVID-19 pandemic showed that the international community is not properly prepared to manage a crisis of this scale. Just after the vaccines had been approved by medical agencies, the policymakers needed to decide on the distribution strategy. To successfully fight the pandemic, the key is to find the equilibrium between the vaccine distribution schedule and the available supplies caused by limited production capacity. This is why society needs to be divided into stratified groups whose access to vaccines is prioritized. Herein, we present the problem of distributing protective actions (i.e., vaccines) and formulate two mixed-integer programs to solve it. The problem of distributing protective actions (PDPA) aims at finding an optimal schedule for a given set of social groups with a constant probability of infection. The problem of distributing protective actions with a herd immunity threshold (PDPAHIT) also includes a variable probability of infection, i.e., the situation when herd immunity is obtained. The results of computational experiments are reported and the potential of the models is illustrated with examples.

Indexed as

COVID-19 vaccinationdecision-makingherd immunemathematical modeloptimizationschedulingvaccination schedule

Identifiers

PMID35062776
PMCPMC8781133

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.