Evidence map›Paper›PMID 40762590›Full record

ArticleJournal of Korean medical science2025

National Wastewater Surveillance of SARS-CoV-2 Across Provinces and Regions in the Republic of Korea From January to August 2023.

You-Jung Choi, Lan Hee Kim, Jinhwa Jang, Shin Young Park, Sejin Jeong, Sungpyo Kim, Sangwon Lee, Seong-Sun Kim

Abstract read
In one paragraph

Article in Journal of Korean medical science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

8 authors.

You-Jung Choi *Data Analysis Team, Epidemiological Investigation and Analysis Task Force, Central Disease Control Headquarters, Korea Disease Control and Prevention Agency, Cheongju, Korea.ORCID https://orcid.org/0000-0002-5631-2842
Lan Hee Kim *Research Institute for Advanced Industrial Technology, Korea University, Sejong, Korea.ORCID https://orcid.org/0000-0003-3026-320X
Jinhwa JangDivision of Epidemiological Data Analysis, Department of Disease Data Science, Korea Disease Control and Prevention Agency, Cheongju, Korea.ORCID https://orcid.org/0000-0002-8580-2904
Shin Young ParkDivision of Epidemiological Data Analysis, Department of Disease Data Science, Korea Disease Control and Prevention Agency, Cheongju, Korea.ORCID https://orcid.org/0000-0002-9622-3633
Sejin JeongDivision of Disease Control Research Planning, Department of Disease Data Science, Korea Disease Control and Prevention Agency, Cheongju, Korea.ORCID https://orcid.org/0000-0002-5783-4212
Sungpyo KimInstitute for Infectious Disease Management Technologies, K-AD Inc., Sejong, Korea.ORCID https://orcid.org/0000-0002-6648-2984
Sangwon LeeDepartment of Disease Data Science, Korea Disease Control and Prevention Agency, Cheongju, Korea.ORCID https://orcid.org/0000-0003-0027-0134
Seong-Sun KimDivision of Epidemiological Data Analysis, Department of Disease Data Science, Korea Disease Control and Prevention Agency, Cheongju, Korea. sskim0719@korea.kr.ORCID https://orcid.org/0000-0001-5277-492X

Funding

Division of Public Health Emergency Response Research 2023-03-004
6 · The paper itself

Abstract

backgroundWastewater surveillance (WS) technology has gained significant attention in many countries due to its role in the monitoring of infectious diseases within communities and complementing clinical testing to prevent coronavirus disease 2019 (COVID-19) outbreaks. In 2023, the Korea Disease Control and Prevention Agency (KDCA) launched the Korea Wastewater Surveillance (KOWAS) project in collaboration with 17 cities and provinces to track COVID-19 outbreaks.

methodsFrom January to August 2023, the concentrations of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) E gene in wastewater were monitored in 19 institutes of health and environmental research, all within local governments. Influent samples were collected from 62 wastewater treatment plants (WWTPs) and weekly trends in SARS-CoV-2 E gene concentrations in wastewater were compared to those of new COVID-19 cases.

resultsDuring 34 weeks, the concentration of SARS-CoV-2 in wastewater samples closely mirrored the trends in new COVID-19 cases, showing the effectiveness of WS in detecting the presence of the virus. However, the efficacy of the WS method varied between provinces. Although some provinces showed a significant positive correlation between new COVID-19 cases and SARS-CoV-2 E gene concentrations in wastewater, this correlation was inconsistent between all locations. However, when data were analyzed on a broader regional scale, defined as a grouping of multiple provinces, a higher proportion of regions showed significant correlations. This suggests that analyzing WS data on a broader scale, with larger aggregated populations and higher coverage rates, reduces the influence of local variabilities, such as the proportion of combined sewer types, WWTPs coverage rate, and foot traffic, which may affect alignment at the provincial level.

conclusionThe synchrony between trends in SARS-CoV-2 E gene concentrations in wastewater and new COVID-19 cases highlights the effectiveness of KOWAS in tracking new clinical cases. However, measured SARS-CoV-2 RNA concentrations can be affected by socioenvironmental factors (e.g., WWTP treatment capacity, sewer pipeline distances, and coverage populations). Further refinement will involve expanding the surveillance network to include additional WWTPs and a more comprehensive range of monitoring targets.

Indexed as

COVID-19SARS-CoV-2WastewaterWastewater-Based Epidemiological MonitoringHumansRepublic of KoreaWastewaterCOVID-19KOWASRepublic of KoreaSARS-CoV-2Wastewater Surveillance

Identifiers

PMID40762590
PMCPMC12322592

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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.