Evidence map›Paper›PMID 35761926›Full record

ArticleEnvironmental technology & innovation2022

Application of human RNase P normalization for the realistic estimation of SARS-CoV-2 viral load in wastewater: A perspective from Qatar wastewater surveillance.

Shimaa S El-Malah, Jayaprakash Saththasivam, Khadeeja Abdul Jabbar, Arun K K, Tricia A Gomez, Ayeda A Ahmed, Yasmin A Mohamoud, Joel A Malek, Laith J Abu Raddad, Hussein A Abu Halaweh and 3 more

Abstract read
In one paragraph

Article in Environmental technology & innovation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 2 pooled it
–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

8 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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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

13 authors.

Shimaa S El-MalahQatar Environment and Energy Research Institute (QEERI), Hamad Bin Khalifa University, Qatar Foundation, P.O. Box 34110, Doha, Qatar.
Jayaprakash SaththasivamQatar Environment and Energy Research Institute (QEERI), Hamad Bin Khalifa University, Qatar Foundation, P.O. Box 34110, Doha, Qatar.
Khadeeja Abdul JabbarQatar Environment and Energy Research Institute (QEERI), Hamad Bin Khalifa University, Qatar Foundation, P.O. Box 34110, Doha, Qatar.
Arun K KQatar Environment and Energy Research Institute (QEERI), Hamad Bin Khalifa University, Qatar Foundation, P.O. Box 34110, Doha, Qatar.
Tricia A GomezQatar Environment and Energy Research Institute (QEERI), Hamad Bin Khalifa University, Qatar Foundation, P.O. Box 34110, Doha, Qatar.
Ayeda A AhmedGenomics Laboratory, Weill Cornell Medicine-Qatar (WCM-Q), Cornell University, Doha, Qatar.
Yasmin A MohamoudGenomics Laboratory, Weill Cornell Medicine-Qatar (WCM-Q), Cornell University, Doha, Qatar.
Joel A MalekGenomics Laboratory, Weill Cornell Medicine-Qatar (WCM-Q), Cornell University, Doha, Qatar.
Laith J Abu RaddadInfectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar.
Hussein A Abu HalawehDrainage Network Operation & Maintenance Department, Public Works Authority, Doha, Qatar.
Roberto BertolliniMinistry of Public Health, Doha, Qatar.
Jenny LawlerQatar Environment and Energy Research Institute (QEERI), Hamad Bin Khalifa University, Qatar Foundation, P.O. Box 34110, Doha, Qatar.
Khaled A MahmoudQatar Environment and Energy Research Institute (QEERI), Hamad Bin Khalifa University, Qatar Foundation, P.O. Box 34110, Doha, Qatar.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The apparent uncertainty associated with shedding patterns, environmental impacts, and sample processing strategies have greatly influenced the variability of SARS-CoV-2 concentrations in wastewater. This study evaluates the use of a new normalization approach using human RNase P for the logic estimation of SARS-CoV-2 viral load in wastewater. SARS-CoV-2 variants outbreak was monitored during the circulating wave between February and August 2021. Sewage samples were collected from five major wastewater treatment plants and subsequently analyzed to determine the viral loads in the wastewater. SARS-CoV-2 was detected in all the samples where the wastewater Ct values exhibited a similar trend as the reported number of new daily positive cases in the country. The infected population number was estimated using a mathematical model that compensated for RNA decay due to wastewater temperature and sewer residence time, and which indicated that the number of positive cases circulating in the population declined from 765,729 ± 142,080 to 2,303 ± 464 during the sampling period. Genomic analyses of SARS-CoV-2 of thirty wastewater samples collected between March 2021 and April 2021 revealed that alpha (B.1.1.7) and beta (B.1.351) were among the dominant variants of concern (VOC) in Qatar. The findings of this study imply that the normalization of data allows a more realistic assessment of incidence trends within the population.

Indexed as

Municipal wastewaterSARS-CoV-2 monitoringSequencingVariant of concernWastewater-based epidemiology (WBE)Wastewater surveillance

Identifiers

PMID35761926
PMCPMC9220754

What OpenQuestion holds

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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.