Evidence map›Paper›PMID 41941528›Full record

ArticlePloS one2026

The impact of human behavioral adaptation stratified by immune status on COVID-19 spread with application to South Korea.

Sileshi Sintayehu Sharbayta, Youngji Jo, Jaehun Jung, Bruno Buonomo

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Sileshi Sintayehu SharbaytaDepartment of Public Health Sciences, School of Medicine, University of Connecticut Health Center, Farmington, Connecticut, United States of America.ORCID https://orcid.org/0000-0003-1838-616X
Youngji JoDepartment of Public Health Sciences, School of Medicine, University of Connecticut Health Center, Farmington, Connecticut, United States of America.ORCID https://orcid.org/0000-0002-1440-2786
Jaehun JungDepartment of Preventive Medicine, Korea University College of Medicine, Seoul, South Korea.
Bruno BuonomoDepartment of Mathematics and Applications, University of Naples Federico II, Naples, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As the COVID-19 pandemic continues with ongoing variant waves and vaccination efforts, population-level immunity and public risk perceptions have shifted. This study presents a behavioral transmission model to assess how virus spread and care-seeking behavior differ based on individuals' immunity status. We categorized the population into two groups: "partially immune" and "susceptible," which influenced their response to vaccination and testing, as well as their prioritization of information related to disease prevalence and severity. Using COVID-19 data from South Korea (February 1, 2022 - May 31, 2022), we calibrated our model to explore these dynamics. Simulation results suggest that increasing reactivity to information among partially immune individuals to the same level as susceptible individuals could reduce peak active cases by 33%. Conversely, if partially immune individuals shift their risk perception focus from prevalence (90% prevalence vs. 10% severity) to severity (90% severity vs. 10% prevalence), the peak in active cases could increase by 57%. These findings highlight the need for adaptive vaccination and testing strategies as public risk perceptions evolve due to prior exposures and vaccinations. As new variant waves emerge in the post-pandemic endemic era, our study offers insights into how immunity-based behavioral differences can shape future infection peaks.

Indexed as

COVID-19HumansPandemicsRepublic of KoreaSARS-CoV-2Vaccination

Identifiers

PMID41941528
PMCPMC13052854

What OpenQuestion holds

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Registered trials

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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.