Evidence map›Paper›PMID 42197449›Full record

ArticleMicroorganisms2026

Multidimensional Analysis of SARS-CoV-2 RNA in Nine Sites Located in Campania Region, Italy.

Annalisa Lombardi, Patrizia Riccio, Maria Ragosta, Mariagrazia D'Emilio, Dario Bruzzese, Vito Imbrenda, Tonia Borriello, Giuseppina La Rosa, Elisabetta Suffredini, Ida Torre and 1 more

Abstract read
In one paragraph

Article in Microorganisms, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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

11 authors.

Annalisa LombardiDepartment of Public Health, University "Federico II", Via Sergio Pansini 5, 80131 Naples, Italy.
Patrizia RiccioDepartment of Molecular Medicine and Medical Biotechnology, University "Federico II", Via Sergio Pansini 5, 80131 Naples, Italy.
Maria RagostaDepartment of Health Sciences, University of Basilicata, Viale dell' Ateneo Lucano 10, 85100 Potenza, Italy.ORCID 0000-0002-2172-1523
Mariagrazia D'EmilioInstitute of Methodologies for Environmental Analysis, Italian National Research Council IMAA CNR, UDR Napoli, Corso Nicolangelo Protopisani, 80146 Naples, Italy.
Dario BruzzeseDepartment of Public Health, University "Federico II", Via Sergio Pansini 5, 80131 Naples, Italy.ORCID 0000-0001-9911-4646
Vito ImbrendaInstitute of Methodologies for Environmental Analysis, Italian National Research Council IMAA CNR, Contrada Santa Loja, Tito, 85050 Potenza, Italy.ORCID 0000-0002-1846-7704
Tonia BorrielloDepartment of Public Health, University "Federico II", Via Sergio Pansini 5, 80131 Naples, Italy.
Giuseppina La RosaNational Center for Water Safety (CeNSiA), Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, Italy.ORCID 0000-0002-2657-100X
Elisabetta SuffrediniDepartment of Food Safety, Nutrition and Veterinary Public Health, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, Italy.ORCID 0000-0001-7605-0539
Ida TorreDepartment of Public Health, University "Federico II", Via Sergio Pansini 5, 80131 Naples, Italy.
Francesca PenninoDepartment of Public Health, University "Federico II", Via Sergio Pansini 5, 80131 Naples, Italy.ORCID 0000-0002-6106-2956

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wastewater monitoring has been recognized as a valid tool for monitoring coronavirus disease 2019 (COVID-19) diffusion. In this paper we analyse a dataset composed by the measurements of SARS-CoV-2 RNA load in 605 raw wastewater samples collected from nine wastewater treatment plants (WWTPs) in the Campania region from October 2021 to May 2025. We analyse the correlation structure of the dataset using multivariate statistical techniques with the aim of identifying the most representative sentinel WWTPs and thus optimizing the number of samples. Results of spatial analysis showed that there are two isolated elements, SA3 and NA1, with the highest and lowest SARS-CoV-2 load values, respectively, and other two clusters (Cl1 and Cl2) from the other WWTPs. Temporal analysis showed that NA3 WWTP had a statistically significant difference in SARS-CoV-2 load from 2022 to 2023. Our method suggests limiting samplings to three sites, as follows: SA3 (which can act as a sentinel site because it is the first site that records variation in viral load) and two with the higher variation coefficients (CV%) belonging to the two clusters, as follows: CE1 for Cl1 and NA4 for Cl2. This data analysis procedure could allow to focus only on certain WWTPs for SARS-CoV-2 monitoring, to promptly identify outbreaks.

Indexed as

cluster analysisepidemiologymultivariate analysisSARS-CoV-2wastewater

Identifiers

PMID42197449
PMCPMC13209735

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.