Evidence map›Paper›PMID 36118159›Full record

ArticleFEMS microbes2022

Improving correlation of wastewater SARS-CoV-2 gene copy numbers with COVID-19 public health cases using readily available biomarkers.

Justin M Hutchison, Zhengxi Li, Chi-Ning Chang, Yasawantha Hiripitiyage, Megan Wittman, Belinda S M Sturm

Open access · goldAbstract read
In one paragraph

Article in FEMS microbes, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.8field-weighted citation impact, top 14% 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

10 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
  2. Article
  3. Dynamics of SARS-CoV-2 variants in southwest Ohio municipal wastewater.Environmental science : water research & technology · 2025
    Article
  4. Article
  5. Article
  6. Review
  7. Simultaneous detection and quantification of multiple pathogen targets in wastewater.medRxiv : the preprint server for health sciences · 2023
    Article
  8. Review
  9. Article
  10. 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

6 authors at 1 institution in 1 country.

Justin M HutchisonCivil, Environmental, and Architectural Engineering, University of Kansas, 1530 W 15 St., Lawrence, KS 66049.
Zhengxi LiCivil, Environmental, and Architectural Engineering, University of Kansas, 1530 W 15 St., Lawrence, KS 66049.
Chi-Ning ChangLife Span Institute, University of Kansas, 1000 Sunnyside Ave, Lawrence, KS 66045.
Yasawantha HiripitiyageCivil, Environmental, and Architectural Engineering, University of Kansas, 1530 W 15 St., Lawrence, KS 66049.
Megan WittmanCivil, Environmental, and Architectural Engineering, University of Kansas, 1530 W 15 St., Lawrence, KS 66049.
Belinda S M SturmCivil, Environmental, and Architectural Engineering, University of Kansas, 1530 W 15 St., Lawrence, KS 66049.
University of Kansas · US

Funding

Synthetic Chemical Biology CoreP20GM113117 · NIGMS · UNIVERSITY OF KANSAS LAWRENCE · PI OROZCO, ROBIN C. · 2016 to 2025
$23.9M
NIGMS NIH HHS P20 GM113117
6 · The paper itself

Abstract

The COVID-19 pandemic has highlighted the potential role that wastewater-based epidemiology can play in assessing aggregate community health. However, efforts to translate SARS-CoV-2 gene copy numbers obtained from wastewater samples into meaningful community health indicators are nascent. In this study, SARS-CoV-2 nucleocapsid (N) genes (N1 and N2) were quantified weekly using reverse transcriptase droplet digital PCR from two municipal wastewater treatment plants for seven months. Four biomarkers (ammonium, biological oxygen demand (BOD), creatinine, and human mitochondrial gene NADH dehydrogenase subunit 5) were quantified and used to normalize SARS-CoV-2 gene copy numbers. These were correlated to daily new case data and one-, two-, and three-week cumulative case data. Over the course of the study, the strongest correlations were observed with a one-day case data lag. However, early measurements were strongly correlated with a five-day case data lag. This indicates that in the early stages of the pandemic, the wastewater samples may have indicated active COVID-19 cases before clinical indications. Mitochondrial and creatinine normalization methods showed the strongest correlations throughout the study, indicating that human-specific biomarkers were better at normalizing wastewater data than ammonium or BOD. Granger causality tests supported this observation and showed that gene copies in wastewater could be predictive of new cases in a sewershed.

Identifiers

PMID36118159
PMCPMC9480869
OpenAlexW4220687530

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.