Evidence map›Paper›PMID 36048847›Full record

ArticlePloS one2022

Evolution and consequences of individual responses during the COVID-19 outbreak.

Wasim Abbas, Masud M A, Anna Park, Sajida Parveen, Sangil Kim

Erratum issuedAbstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Wasim AbbasDepartment of Mathematics, Pusan National University, Busan, Korea.ORCID 0000-0002-1706-1462
Masud M ANatural Product Informatics Research Center, Korea Institute of Science and Technology, Seoul, Gangneung, South Korea.
Anna ParkInstitute of Mathematical Sciences, Pusan National University, Busan, Korea.ORCID 0000-0002-5881-7246
Sajida ParveenDepartment of Mathematics, Pusan National University, Busan, Korea.ORCID 0000-0003-2639-4610
Sangil KimDepartment of Mathematics, Pusan National University, Busan, Korea.ORCID 0000-0002-4408-2904

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In a long-lasting major disease outbreak such as that of COVID-19, the challenge for public health authorities is to keep people motivated and keen on following safety guidelines. In this study, a compartmental model with a heterogeneous transmission rate (based on awareness) is utilized to hypothesize about the public adoption of preventive guidelines. Three subsequent outbreaks in South Korea, Pakistan, and Japan were analyzed as case studies. The transmission, behavior change, and behavioral change ease rates of the disease were measured in these countries. The parameters were estimated using the maximum likelihood method with an additional identifiability analysis performed to determine the uniqueness of the estimated parameters for quantitatively comparing them during the first three waves of COVID-19. The mathematical analysis and simulation results show that individual responses had a significant effect on the outbreak. Individuals declining to follow the public health guidelines in Korea and Japan between the second and third waves contributed to making the third peak the highest of the three peaks. In Pakistan, however, individual responses to following public health guidelines were maintained between the second and third waves, resulting in the third peak being lower than the first, rather than being associated with the highest transmission rate. Thus, maintaining a high level of awareness is critical for containing the spread. Improvised public health campaigns are recommended to sustain individual attention and maintain a high level of awareness.

Indexed as

COVID-19Disease OutbreaksHumansPublic HealthRepublic of KoreaSARS-CoV-2

Identifiers

PMID36048847
PMCPMC9436131

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.