Occurrence and Reduction of Viruses in Sludge from Full-Scale Wastewater and Organic Waste Treatment Plants During Anaerobic Digestion

Water Air & Soil Pollution, Journal Year: 2025, Volume and Issue: 236(2)

Published: Jan. 10, 2025

Language: Английский

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Hyperplex PCR enables highly multiplexed analysis of point mutations in wastewater: long-term SARS-CoV-2 variant surveillance in Sweden as a case study

Water Research, Journal Year: 2025, Volume and Issue: 274, P. 123154 - 123154

Published: Jan. 16, 2025

Language: Английский

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The Crucial Role of Laboratory Medicine in Addressing Future Public Health Infectious Threats: Insights Gained from the COVID-19 Pandemic

Diagnostics, Journal Year: 2025, Volume and Issue: 15(3), P. 323 - 323

Published: Jan. 30, 2025

Laboratory testing has played a pivotal role throughout the coronavirus disease 2019 (COVID-19) pandemic, exemplifying importance of in vitro diagnostics addressing public health threats posed by outbreaks infectious diseases. This article aims to present key insights from our expertise, derived evidence gathered during COVID-19 inform strategies for managing future challenges. Current scientific underscores that patient sample not only allows diagnose an acute severe respiratory syndrome 2 (SARS-CoV-2) infection, but also supports outbreak prediction, improved control measures, anticipation pressure on healthcare system, mitigation adverse clinical outcomes, and early detection emerging SARS-CoV-2 variants. Additionally, wastewater monitoring emerged as powerful tool forecasting burden, including both prevalence severity. Collectively, these findings underscore value diagnostic surveillance guiding planning optimizing resource allocation offering valid framework be applied threats, especially any potential “Disease X” may emerge future.

Language: Английский

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Predicting hospital admissions due to COVID-19 in Denmark using wastewater-based surveillance

The Science of The Total Environment, Journal Year: 2025, Volume and Issue: 966, P. 178674 - 178674

Published: Feb. 1, 2025

Wastewater surveillance has become a fundamental tool to monitor the circulation of SARS-CoV-2 in order prepare timely public health responses. In this study we integrate available clinical data on hospital admissions with wastewater and investigate if predictions number due COVID-19 Danish hospitals are improved by including concentrations SARS-CoV-2. We implement state space models describe relationship between COVID-19, three-week classification delay, more recent numbers total COVID-19. Including SARS-CoV-2, consider five-week As result translate into two hindcasts, one nowcast forecasts. The predicted values for all time frames follow observed well. find that log likelihood higher when (across horizons) lagging observations whether changes occur before does not further improvements. Our shows improve estimates implying add valuable information about underlying transmission imminent development near-future disease burden from is better informed carefully concentrations.

Language: Английский

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Examining the Impact of Different Scales on COVID-19 Monitoring in Sewerage Catchment Areas: Insights from Latvia

Journal of Hazardous Materials Advances, Journal Year: 2025, Volume and Issue: unknown, P. 100676 - 100676

Published: March 1, 2025

Language: Английский

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Measuring SARS-CoV-2 RNA in Bangkok wastewater treatment plants and estimating infected population after fully opening the country in 2023, Thailand

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 20, 2025

Wastewater-based epidemiology (WBE) has been employed for monitoring the presence of SARS-CoV-2 infected population. Herein, study aims to apply WBE surveillance and in Bangkok, where highest official covid-19 cases reported Thailand, during fully opening international tourists early 2023. A total 200 wastewater samples (100 influent 100 effluent samples) were collected from 10 treatment plants (WWTPs) January–May RNA was detected by real time qRT-PCR with accounting 51% (102/200). Of these, 88% (88/100) 14% (14/100) samples, respectively. The concentration ranged 4.76 × 102–1.48 105 copies/L. amount increased approximately 4 times lag phase (January–March) log (April–May). Spearman's correlation coefficient revealed that between estimated population weekly statistically significant (p-value = 0.017). had a relationship (r 0.481, p-value < 0.001). Lag analysis warning 1–3 weeks before rising observed. GIS applied spatial-temporal at province level, suggesting dashboard should be further developed.

Language: Английский

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Machine Learning Approaches for Real-Time ZIP Code and County-Level Estimation of State-Wide Infectious Disease Hospitalizations Using Local Health System Data

Epidemics, Journal Year: 2025, Volume and Issue: 51, P. 100823 - 100823

Published: April 6, 2025

The lack of conventional methods estimating real-time infectious disease burden in granular regions inhibits timely and efficient public health response. Comprehensive data sources (e.g., state department data) typically needed for such estimation are often limited due to 1) substantial delays reporting 2) geographic granularity provided researchers. Leveraging local system presents an opportunity overcome these challenges. This study evaluates the effectiveness machine learning statistical approaches using estimate current previous COVID-19 hospitalizations South Carolina. Random Forest models demonstrated consistently higher average median percent agreement accuracy compared generalized linear mixed weekly across 123 ZIP codes (72.29 %, IQR: 63.20-75.62 %) 28 counties (76.43 70.33-81.16 with sufficient coverage. To account underrepresented populations systems, we combined Classification Regression Trees (CART) imputation. was 61.02 % (IQR: 51.17-72.29 all 72.64 66.13-77.69 counties. Median cumulative over 6 months 80.98 68.99-89.66 81.17 68.55-91.33 These findings emphasize utilizing burden. Moreover, methodologies developed this can be adapted other diseases, offering a valuable tool officials respond swiftly effectively various crises.

Language: Английский

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Multi-factor normalisation of viral counts from wastewater improves the detection accuracy of viral disease in the community

Environmental Technology & Innovation, Journal Year: 2024, Volume and Issue: 36, P. 103720 - 103720

Published: June 29, 2024

The detection of viruses (e.g. SARS-CoV-2, norovirus) in wastewater represents an effective way to monitor the prevalence these pathogens circulating within community. However, accurate quantification viral concentrations wastewater, proportional human input, is constrained by a range uncertainties, including (i) dilution sewer network, (ii) degradation RNA during transit, (iii) catchment population and facility use, (iv) efficiency concentration extraction from (v) inhibition amplification RT-qPCR step. Here, we address uncertainties investigating several potential normalisation factors ammonium orthophosphate. A faecal indicator virus (crAssphage), recovery process-control (murine norovirus bacteriophage Phi6), used for quality control step, were also considered. We found that multi-factor SARS-CoV-2 data was optimal using combination crAssphage, recovery, improve prediction accuracy relative clinical test data. Using multi-normalised data, lasso regression model with random forest modelled residuals lowers error positives 46 %, compared single linear raw This approach enables more wastewater-based predictions cases up five days advance identifying trends disease before testing, demonstrates pathogen currently monitored emerging diseases.

Language: Английский

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Surveillance for variants of SARS-CoV-2 to inform risk assessments

Bulletin of the World Health Organization, Journal Year: 2023, Volume and Issue: 101(11), P. 706 - 716

Published: Nov. 1, 2023

Since the beginning of coronavirus disease 2019 (COVID-19) pandemic, numerous severe acute respiratory syndrome 2 (SARS-CoV-2) variants have emerged, some leading to large increases in infections, hospitalizations and deaths globally.The virus's impact on public health depends many factors, including emergence new viral their global spread.Consequently, early detection surveillance characterization clinical effects are vital for assessing risk.The unprecedented capacity genomic sequencing data sharing built globally during pandemic has enabled be rapidly detected assessed.This article describes main circulating between January 2020 June 2023, genetic features driving variant evolution, epidemiological these across countries regions.Second, we report how integrating with event-based surveillance, through a network World Health Organization partners, supported risk assessment helped provide guidance responses.In addition, given evolutionary characteristics immune status populations, propose future directions sustainable SARS-CoV-2 variants, both nationally internationally: (i) optimizing by environmental monitoring; (ii) coordinating laboratory evolution phenotype; (iii) linking data; (iv) expanding additional pathogens.Experience COVID-19 shown that pathogens can essential, timely evidence-based information decision-making.

Language: Английский

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Notes from the Field: The National Wastewater Surveillance System’s Centers of Excellence Contributions to Public Health Action During the Respiratory Virus Season — Four U.S. Jurisdictions, 2022–23

MMWR Morbidity and Mortality Weekly Report, Journal Year: 2023, Volume and Issue: 72(48), P. 1309 - 1312

Published: Nov. 30, 2023

Language: Английский

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