Evidence map›Paper›PMID 34130001›Full record

ArticleThe Science of the total environment2021

Technical framework for wastewater-based epidemiology of SARS-CoV-2.

Jinyong Wu, Zizheng Wang, Yufei Lin, Lihua Zhang, Jing Chen, Panyu Li, Wenbin Liu, Yabo Wang, Changhong Yao, Kun Yang

Open access · greenAbstract read
In one paragraph

Article in The Science of the total environment, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
1.5field-weighted citation impact, top 15% of its field
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

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 29 citations in OpenAlex.

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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

10 authors at 1 institution in 1 country.

Jinyong WuDepartment of Pharmaceutical & Biological Engineering, School of Chemical Engineering, Sichuan University, Chengdu 610065, China.
Zizheng WangWest China School of Stomatology, Sichuan University, Chengdu 610041, China.
Yufei LinDepartment of Pharmaceutical & Biological Engineering, School of Chemical Engineering, Sichuan University, Chengdu 610065, China.
Lihua ZhangDepartment of Pharmaceutical & Biological Engineering, School of Chemical Engineering, Sichuan University, Chengdu 610065, China.
Jing ChenDepartment of Pharmaceutical & Biological Engineering, School of Chemical Engineering, Sichuan University, Chengdu 610065, China.
Panyu LiDepartment of Pharmaceutical & Biological Engineering, School of Chemical Engineering, Sichuan University, Chengdu 610065, China.
Wenbin LiuDepartment of Pharmaceutical & Biological Engineering, School of Chemical Engineering, Sichuan University, Chengdu 610065, China.
Yabo WangDepartment of Pharmaceutical & Biological Engineering, School of Chemical Engineering, Sichuan University, Chengdu 610065, China.
Changhong YaoDepartment of Pharmaceutical & Biological Engineering, School of Chemical Engineering, Sichuan University, Chengdu 610065, China.
Kun YangDepartment of Pharmaceutical & Biological Engineering, School of Chemical Engineering, Sichuan University, Chengdu 610065, China. Electronic address: cookyoung@scu.edu.cn.
Sichuan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wastewater-based epidemiology (WBE) is expected to become a powerful tool to monitor the dissemination of SARS-CoV-2 at the community level, which has attracted the attention of scholars all over the world. However, there is not yet a standard protocol to guide its implementation. In this paper, we proposed a comprehensive technical and theoretical framework of relative quantification via qPCR for determining the virus abundance in wastewater and estimating the infection ratio in corresponding communities, which is expected to achieve horizontal and vertical comparability of the data using a human-specific biomarker as the internal reference. Critical factors affecting the virus detectability and the estimation of infection ratio include virus concentration methods, lag-period, per capita virus shedding amount, sewage generation rate, temperature-related decay kinetics of virus/biomarker in wastewater, and hydraulic retention time (HRT), etc. Theoretical simulation shows that the main factors affecting the detectability of virus in sewage are per capita virus shedding amount and sewage generation rate. While the decay of SARS-CoV-2 RNA in sewage is a relatively slow process, which may have limited impact on its detection. Under the ideal condition of high per capita virus shedding amount and low sewage generation rate, it is expected to detect a single infected person within 400,000 people.

Indexed as

COVID-19SARS-CoV-2HumansRNA, ViralWastewaterWastewater-Based Epidemiological MonitoringRNA, ViralWastewaterCOVID-19Decay kineticsModelingRelative quantificationRT-qPCRWastewater-based epidemiology

Identifiers

PMID34130001
PMCPMC8195746
OpenAlexW3171410289

What OpenQuestion holds

Textmetadata
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.