Evidence map›Paper›PMID 34045533›Full record

ArticleScientific reports2021

Suggestion of a simpler and faster influenza-like illness surveillance system using 2014-2018 claims data in Korea.

HeeKyoung Choi, Won Suk Choi, Euna Han

Abstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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.

HeeKyoung Choi *College of Pharmacy, Yonsei Institute of Pharmaceutical Research, Yonsei University, 162-1 Songdo-dong, Yeonsu-gu, Incheon, Seoul, Republic of Korea.
Won Suk Choi *Division of Infectious Diseases, Department of Internal Medicine, Ansan Hospital, Korea University College of Medicine, Ansan, Republic of Korea.
Euna HanCollege of Pharmacy, Yonsei Institute of Pharmaceutical Research, Yonsei University, 162-1 Songdo-dong, Yeonsu-gu, Incheon, Seoul, Republic of Korea. eunahan@yonsei.ac.kr.ORCID 0000-0003-2656-7059

Funding

NIEHS NIH HHS 27307C0010
6 · The paper itself

Abstract

Influenza is an important public health concern. We propose a new real-time influenza-like illness (ILI) surveillance system that utilizes a nationwide prospective drug utilization monitoring in Korea. We defined ILI-related claims as outpatient claims that contain both antipyretic and antitussive agents and calculated the weekly rate of ILI-related claims, which was compared to weekly ILI rates from clinical sentinel surveillance data during 2014-2018. We performed a cross-correlation analysis using Pearson's correlation, time-series analysis to explore actual correlations after removing any dubious correlations due to underlying non-stationarity in both data sets. We used the moving epidemic method (MEM) to estimate an absolute threshold to designate potential influenza epidemics for the weeks with incidence rates above the threshold. We observed a strong correlation between the two surveillance systems each season. The absolute thresholds for the 4-years were 84.64 and 86.19 cases per 1000claims for claims data and 12.27 and 16.82 per 1000 patients for sentinel data. The epidemic patterns were more similar in the 2016-2017 and 2017-2018 seasons than the 2014-2015 and 2015-2016 seasons. ILI claims data can be loaded to a drug utilization review system in Korea to make an influenza surveillance system.

Indexed as

AdultEpidemicsHumansInfluenza, HumanPublic HealthRepublic of KoreaSentinel Surveillance

Identifiers

PMID34045533
PMCPMC8159991

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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.