Evidence map›Paper›PMID 35155327›Full record

ArticleFrontiers in public health2022

Analyzing COVID-19 Vaccination Behavior Using an SEIRM/V Epidemic Model With Awareness Decay.

Chao Zuo, Fenping Zhu, Yuting Ling

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 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
2.9field-weighted citation impact, top 9% of its field
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, 21 citations in OpenAlex.

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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 at 1 institution in 1 country.

Chao ZuoSchool of Management Engineering and E-Commerce, Zhejiang Gongshang University, Hangzhou, China.
Fenping ZhuSchool of Management Engineering and E-Commerce, Zhejiang Gongshang University, Hangzhou, China.
Yuting LingSchool of Management Engineering and E-Commerce, Zhejiang Gongshang University, Hangzhou, China.
Zhejiang Gongshang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Information awareness about COVID-19 spread through multiple channels can stimulate individuals to vaccinate to protect themselves and reduce the infection rate. However, the awareness individuals may lose competency over time due to the decreasing quality of the information and fading of awareness. This paper introduces awareness programs, which can not only change people from unaware to aware state, but also from aware to unaware state. Then an SEIRM/V mathematical model is derived to study the influence of awareness programs on individual vaccination behavior. We evaluate the dynamical evolution of the system model and perform the numerical simulation, and examine the effects of awareness transformation based on the COVID-19 vaccination case in China. The results show that awareness spread through various information sources is positively associated with epidemic containment while awareness fading negatively correlates with vaccination coverage.

Indexed as

COVID-19EpidemicsCOVID-19 VaccinesHumansSARS-CoV-2VaccinationCOVID-19 Vaccinesawareness fadingawareness spreadingCOVID-19epidemic modelvaccination behaviors

Identifiers

PMID35155327
PMCPMC8829349
OpenAlexW4210291863

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.