Evidence map›Paper›PMID 39427054›Full record

ArticleScientific reports2024

Development of a wastewater based infectious disease surveillance research system in South Korea.

Yun-Tae Kim, Kyungwon Lee, Hyukmin Lee, Bokyung Son, Myeongwon Song, Seung-Hyun Lee, Miran Kwon, Dong-Soo Kim, Tae-Hun Noh, Sanghoo Lee and 3 more

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Coupling wastewater-based epidemiology with data-driven machine learning for managing public health risks.Risk analysis : an official publication of the Society for Risk Analysis · 2025
    Article
  8. Article
  9. 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

13 authors.

Yun-Tae KimDepartment of R&D Innovation Center, Seoul Clinical Laboratories, Yongin-si, Gyeonggi-do, Republic of Korea. ytkim@scllab.co.kr.
Kyungwon LeeDepartment of Laboratory Medicine, Research Institute of Bacterial Resistance, Yonsei University College of Medicine, Seoul, Republic of Korea.
Hyukmin LeeDepartment of Laboratory Medicine, Research Institute of Bacterial Resistance, Yonsei University College of Medicine, Seoul, Republic of Korea.
Bokyung SonDepartment of R&D Innovation Center, Seoul Clinical Laboratories, Yongin-si, Gyeonggi-do, Republic of Korea.
Myeongwon SongDepartment of R&D Innovation Center, Seoul Clinical Laboratories, Yongin-si, Gyeonggi-do, Republic of Korea.
Seung-Hyun LeeDepartment of R&D Innovation Center, Seoul Clinical Laboratories, Yongin-si, Gyeonggi-do, Republic of Korea.
Miran KwonDepartment of R&D Innovation Center, Seoul Clinical Laboratories, Yongin-si, Gyeonggi-do, Republic of Korea.
Dong-Soo KimDepartment of R&D Innovation Center, Seoul Clinical Laboratories, Yongin-si, Gyeonggi-do, Republic of Korea.
Tae-Hun NohDepartment of R&D Innovation Center, Seoul Clinical Laboratories, Yongin-si, Gyeonggi-do, Republic of Korea.
Sanghoo LeeSCL Healthcare Inc. Gyeonggi-do, Yongin-si, Gyeonggi-do, Republic of Korea.
Young-Jin KimSeoul Clinical Laboratories, Yongin-si, Gyeonggi-do, Republic of Korea.
Mi-Kyeong LeeSeoul Clinical Laboratories, Yongin-si, Gyeonggi-do, Republic of Korea.
Kyoung-Ryul LeeSeoul Clinical Laboratories, Yongin-si, Gyeonggi-do, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wastewater-based epidemiology has been used in pathogen surveillance for microorganisms at the community level. This study was conducted to determine the occurrence and trends of infectious pathogens in sewage from Yongin city and the relationships between these pathogens and the incidence of infectious diseases in the community. From December 2022 to November 2023, we collected inflow water from six wastewater treatment plants in Yongin city twice a month. The analyzed microorganisms included 15 respiratory viruses, 7 pneumonia-causing bacteria, 19 acute diarrhea-causing pathogens, SARS-CoV-2, Zika virus, hepatitis A virus, poliovirus, Mpox, and measles. They were detected through real-time PCR and conventional PCR. The concentrations of 9 pathogens among them were additionally analyzed using quantitative real time PCR. The correlation was confirmed through statistical analysis with the rate of detection for pathogens reported by the Korea Disease Control and Prevention Agency. Influenza A virus, human adenovirus, and human rhinovirus were moderately correlated (rho values of 0.45 to 0.58). Campylobacter spp. and sapovirus were strong correlated (rho values of 0.62, 0.63). Enteropathogenic E. coli, human coronavirus, and norovirus GII were very strong correlated (rho values of 0.86 to 0.92). We were able to identify the prevalence of respiratory viral infections, pneumonia, and acute diarrhea-causing pathogens in the community through wastewater-based epidemiology data. This study will be helpful in establishing a system for future surveillance of infectious diseases present in sewage.

Indexed as

WastewaterCommunicable DiseasesHumansRepublic of KoreaSewageWastewater-Based Epidemiological MonitoringSewageWastewaterDiarrhea-causing microorganismsPneumonia-causing bacteriaPublic healthReal-time PCRRespiratory virusesWastewater-based epidemiology

Identifiers

PMID39427054
PMCPMC11490628

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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.