Evidence map›Paper›PMID 35664237›Full record

ArticleComputational and structural biotechnology journal2022

Beyond COVID-19 pandemic: Topology-aware optimization of vaccination strategy for minimizing virus spreading.

Francesco Petrizzelli, Pietro Hiram Guzzi, Tommaso Mazza

Abstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Temporal networks in biology and medicine: a survey on models, algorithms, and tools.Network modeling and analysis in health informatics and bioinformatics · 2023
    Review
  5. Article
  6. Review
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

3 authors.

Francesco PetrizzelliLaboratory of Bioinformatics, Fondazione IRCCS Casa Sollievo della Sofferenza, Viale Capuccini, 71013 S. Giovanni Rotondo, Fg, Italy.
Pietro Hiram GuzziDepartment of Surgical and Medical Sciences, University of Catanzaro, Catanzaro, Campus S Venuta, 88100, Italy.
Tommaso MazzaLaboratory of Bioinformatics, Fondazione IRCCS Casa Sollievo della Sofferenza, Viale Capuccini, 71013 S. Giovanni Rotondo, Fg, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The mitigation of an infectious disease spreading has recently gained considerable attention from the research community. It may be obtained by adopting sanitary measurements (e.g., vaccination, wearing masks), social rules (e.g., social distancing), together with an extensive vaccination campaign. Vaccination is currently the primary way for mitigating the Coronavirus Disease (COVID-19) outbreak without severe lockdown. Its effectiveness also depends on the number and timeliness of administrations and thus demands strict prioritization criteria. Almost all countries have prioritized similar classes of exposed workers: healthcare professionals and the elderly, obtaining to maximize the survival of patients and years of life saved. Nevertheless, the virus is currently spreading at high rates, and any prioritization criterion so far adopted did not account for the structural organization of the contact networks. We reckon that a network where nodes are people while the edges represent their social contacts may efficiently model the virus's spreading. It is known that tailored interventions (e.g., vaccination) on

Indexed as

00001111Disease containmentNetwork sciencesSimulations

Identifiers

PMID35664237
PMCPMC9135485

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.