Evidence map›Paper›PMID 39851079›Full record

Observational studyJMIR public health and surveillance2025

Wastewater Monitoring During the COVID-19 Pandemic in the Veneto Region, Italy: Longitudinal Observational Study.

Honoria Ocagli, Marco Zambito, Filippo Da Re, Vanessa Groppi, Marco Zampini, Alessia Terrini, Franco Rigoli, Irene Amoruso, Tatjana Baldovin, Vincenzo Baldo and 2 more

Abstract readObservational Study
In one paragraph

Observational study in JMIR public health and surveillance, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. 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

12 authors.

Honoria Ocagli *Unit of Biostatistics, Epidemiology and Public Health, Department of Cardio-Thoraco-Vascular Sciences and Public Health, University of Padova, Via Loredan 18, Padova, Italy, 39 049 8275384.ORCID 0000-0002-5823-1659
Marco Zambito *Unit of Biostatistics, Epidemiology and Public Health, Department of Cardio-Thoraco-Vascular Sciences and Public Health, University of Padova, Via Loredan 18, Padova, Italy, 39 049 8275384.ORCID 0009-0003-5279-9694
Filippo Da ReDirectorate of Prevention, Food Safety and Veterinary Public Health-Veneto Region, Venice, Italy.ORCID 0009-0006-7366-0108
Vanessa GroppiDirectorate of Prevention, Food Safety and Veterinary Public Health-Veneto Region, Venice, Italy.ORCID 0009-0005-2386-018X
Marco ZampiniARPAV - Agenzia Regionale per la Prevenzione e Protezione Ambientale del Veneto, U.O. Biologia, Padova, Italy.ORCID 0009-0009-3485-3945
Alessia TerriniARPAV - Agenzia Regionale per la Prevenzione e Protezione Ambientale del Veneto, U.O. Biologia, Padova, Italy.ORCID 0009-0000-1699-6680
Franco RigoliARPAV - Agenzia Regionale per la Prevenzione e Protezione Ambientale del Veneto, U.O. Biologia, Padova, Italy.ORCID 0009-0004-9574-3452
Irene AmorusoUnit of Hygiene and Public Health, Department of Cardiac, Thoracic, Vascular Sciences, and Public Health, University of Padova, Padova, Italy.ORCID 0000-0003-4954-5848
Tatjana BaldovinUnit of Hygiene and Public Health, Department of Cardiac, Thoracic, Vascular Sciences, and Public Health, University of Padova, Padova, Italy.ORCID 0000-0002-7375-9187
Vincenzo BaldoUnit of Hygiene and Public Health, Department of Cardiac, Thoracic, Vascular Sciences, and Public Health, University of Padova, Padova, Italy.ORCID 0000-0001-6012-9453
Francesca Russo *Directorate of Prevention, Food Safety and Veterinary Public Health-Veneto Region, Venice, Italy.ORCID 0009-0007-9557-7361
Dario Gregori *Unit of Biostatistics, Epidemiology and Public Health, Department of Cardio-Thoraco-Vascular Sciences and Public Health, University of Padova, Via Loredan 18, Padova, Italy, 39 049 8275384.ORCID 0000-0001-7906-0580

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: As the COVID-19 pandemic has affected populations around the world, there has been substantial interest in wastewater-based epidemiology (WBE) as a tool to monitor the spread of SARS-CoV-2. This study investigates the use of WBE to anticipate COVID-19 trends by analyzing the correlation between viral RNA concentrations in wastewater and reported COVID-19 cases in the Veneto region of Italy. Objective: We aimed to evaluate the effectiveness of the cumulative sum (CUSUM) control chart method in detecting changes in SARS-CoV-2 concentrations in wastewater and its potential as an early warning system for COVID-19 outbreaks. Additionally, we aimed to validate these findings over different time periods to ensure robustness. Methods: This study analyzed the temporal correlation between SARS-CoV-2 RNA concentrations in wastewater and COVID-19 clinical outcomes, including confirmed cases, hospitalizations, and intensive care unit (ICU) admissions, from October 2021 to August 2022 in the Veneto region, Italy. Wastewater samples were collected weekly from 10 wastewater treatment plants and analyzed using a reverse transcription-quantitative polymerase chain reaction. The CUSUM method was used to detect significant shifts in the data, with an initial analysis conducted from October 2021 to February 2022, followed by validation in a second period from February 2022 to August 2022. Results: The study found that peaks in SARS-CoV-2 RNA concentrations in wastewater consistently preceded peaks in reported COVID-19 cases by 5.2 days. Hospitalizations followed with a delay of 4.25 days, while ICU admissions exhibited a lead time of approximately 6 days. Notably, certain health care districts exhibited stronger correlations, with notable values in wastewater anticipating ICU admissions by an average of 13.5 and 9.5 days in 2 specific districts. The CUSUM charts effectively identified early changes in viral load, indicating potential outbreaks before clinical cases increased. Validation during the second period confirmed the consistency of these findings, reinforcing the robustness of the CUSUM method in this context. Conclusions: WBE, combined with the CUSUM method, offers valuable insight into the level of COVID-19 outbreaks in a community, including asymptomatic cases, thus acting as a precious early warning tool for infectious disease outbreaks with pandemic potential.

Indexed as

COVID-19WastewaterHumansItalyLongitudinal StudiesPandemicsRNA, ViralSARS-CoV-2RNA, ViralWastewaterCOVID-19cumulative sum chartCUSUMSARS-CoV-2wastewater-based epidemiologyWBE

Identifiers

PMID39851079
PMCPMC11750127

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.