Evidence map›Paper›PMID 38737862›Full record

ArticleFrontiers in public health2024

K-Track-Covid: interactive web-based dashboard for analyzing geographical and temporal spread of COVID-19 in South Korea.

Hanbyul Song, Kyulhee Han, Jiwon Park, Zhe Liu, Taewan Goo, Ashok Krishnamurthy, Taesung Park

Abstract read
In one paragraph

Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Hanbyul SongInterdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea.
Kyulhee HanInterdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea.
Jiwon ParkInterdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea.
Zhe LiuInterdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea.
Taewan GooInterdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea.
Ashok KrishnamurthyDepartment of Mathematics and Computing, Mount Royal University, Calgary, AB, Canada.
Taesung ParkDepartment of Statistics, Seoul National University, Seoul, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic has necessitated the development of robust tools for tracking and modeling the spread of the virus. We present 'K-Track-Covid,' an interactive web-based dashboard developed using the R Shiny framework, to offer users an intuitive dashboard for analyzing the geographical and temporal spread of COVID-19 in South Korea. Our dashboard employs dynamic user interface elements, employs validated epidemiological models, and integrates regional data to offer tailored visual displays. The dashboard allows users to customize their data views by selecting specific time frames, geographic regions, and demographic groups. This customization enables the generation of charts and statistical summaries pertinent to both daily fluctuations and cumulative counts of COVID-19 cases, as well as mortality statistics. Additionally, the dashboard offers a simulation model based on mathematical models, enabling users to make predictions under various parameter settings. The dashboard is designed to assist researchers, policymakers, and the public in understanding the spread and impact of COVID-19, thereby facilitating informed decision-making. All data and resources related to this study are publicly available to ensure transparency and facilitate further research.

Indexed as

COVID-19InternetEpidemiological ModelsHumansPandemicsRepublic of KoreaSARS-CoV-2User-Computer InterfaceCOVID-19infectious diseaseinteractive dashboardmathematical modelR shinySouth Korea

Identifiers

PMID38737862
PMCPMC11082270

What OpenQuestion holds

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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.