Evidence map›Paper›PMID 41333891›Full record

ReviewJugan geon-gang gwa jilbyeong2023

[Comparing International Computing Systems of COVID-19 Core Indicators and Measures to Improve Usability].

Naae Lee, Yeon-Gyeong Kim, Seungpil Jung, Woojoo Lee, Juhwan Oh, Seung-Sik Hwang

Abstract readEnglish AbstractReview
In one paragraph

Review in Jugan geon-gang gwa jilbyeong, 2023. 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

6 authors.

Naae Lee서울대학교 보건대학원 보건학과.
Yeon-Gyeong Kim서울대학교 보건대학원 보건학과.
Seungpil Jung서울대학교 보건대학원 보건학과.
Woojoo Lee서울대학교 보건대학원 보건학과.
Juhwan Oh서울대학교 의과대학 의학과.
Seung-Sik Hwang서울대학교 보건대학원 보건학과.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

For effective pandemic control of coronavirus disease 2019 (COVID-19), production and management of relevant indicators to predict and analyze epidemic patterns, development and evaluation of dashboards that visually represent data have not yet been achieved. In this study, we utilized medical quality assessment methods to review key COVID-19 prevention indicators and evaluated both domestic and international dashboards in terms of usability. Most countries provide major prevention indicators focusing on COVID-19 incidence and hospital bed-related indicators. In Republic of Korea (ROK), a significant number of management indicators are also provided, but there is a shortage of publicly available indicators for specific targets and time periods. Therefore, it is necessary to develop indicators that encompass various infection and socio-economic vulnerability factors and to develop estimation models that can reflect the characteristics of infection in ROK through policy development and the utilization of these indicators. Interactive dashboards are the most useful in the COVID-19 pandemic situation. The interactive dashboards enable data management and processing, provide information to users at their view point, and implement appropriate visual elements. In addition, dashboard improvements that consider the use of clear indicators, easy accessibility, and information placement readability are needed.

Indexed as

ActionabilityCOVID-19DashboardsPrevention indicators

Identifiers

PMID41333891
PMCPMC12551755

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.