Environmental Detection and Monitoring of SARS-CoV-2 for COVID-19 Risk Prediction DOI
Rita R. Colwell, Kyle D. Brumfield, Moiz Usmani

et al.

Springer eBooks, Journal Year: 2024, Volume and Issue: unknown, P. 65 - 77

Published: Jan. 1, 2024

Language: Английский

From pandemic to endemic: Divergence of COVID-19 positive-tests and hospitalization numbers from SARS-CoV-2 RNA levels in wastewater of Rochester, Minnesota DOI Creative Commons

Ramanath Majumdar,

Biruhalem Taye,

Corey Bjornberg

et al.

Heliyon, Journal Year: 2024, Volume and Issue: 10(6), P. e27974 - e27974

Published: March 1, 2024

Traditionally, public health surveillance relied on individual-level data but recently wastewater-based epidemiology (WBE) for the detection of infectious diseases including COVID-19 became a valuable tool in arsenal. Here, we use WBE to follow course pandemic Rochester, Minnesota (population 121,395 at 2020 census), from February 2021 December 2022. We monitored impact SARS-CoV-2 infections by comparing three sets data: quantitative measurements viral RNA wastewater as an unbiased reporter virus level community, positive results or antigen tests nasal swabs reflecting community reporting, and hospitalization data. From August 2022 levels were closely correlated with oscillating case numbers. However, September cases remained low numbers dropped, whereas continued oscillate. The reported may reflect virulence reduction combined abated inclination report, divergence shifting endemic. WBE, which also detects asymptomatic infections, can provide early warning impending cases, offers crucial insights during waves transition endemic phase.

Language: Английский

Citations

0
Microbial Metagenomics Developments for Environmental and Public Health Monitoring DOI
Susanta Sinha Roy, Smrita Singh,

Ashutosh Singh Chauhan

et al.

Published: Jan. 1, 2024

Language: Английский

Citations

0
Exploring the Secrets of Microbes: Unveiling the Hidden World Through Microbial Omics in Environment and Health DOI
Bhagaban Mallik, Tarun Mishra, Poornima Dubey

et al.

Published: Jan. 1, 2024

Language: Английский

Citations

0
Integromics: Tracking the Multi-omic Expanse in Theragnostics DOI

Shambhavee Srivastav,

Lavanya Lavanya,

Anupama Sharma Avasthi

et al.

Published: Jan. 1, 2024

Language: Английский

Citations

0
Computational Omics Protocol for the Comparative Study of Microbiome Analysis DOI
Upasna Srivastava, Minu Kesheri, Swarna Kanchan

et al.

Published: Jan. 1, 2024

Language: Английский

Citations

0
Current Status and Future Strategy in Crop Improvement Using Epigenomics DOI
Prerna Priya,

Raj Kumar Sardar,

Swarna Kanchan

et al.

Published: Jan. 1, 2024

Language: Английский

Citations

0
Planet in Peril: Unveiling the Microbial Consequences of Environmental Degradation on Human Health Through Omics Approaches DOI
Nityendra Shukla,

A. Bhatia,

Minu Kesheri

et al.

Published: Jan. 1, 2024

Language: Английский

Citations

0
A Multi-City COVID-19 Categorical Forecasting Model Utilizing Wastewater-Based Epidemiology DOI Creative Commons

Naomi Rankin,

Samee Saiyed, Hongru Du

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 16, 2024

Abstract The COVID-19 pandemic highlighted shortcomings in forecasting models, such as unreliable inputs/outputs and poor performance at critical points. As remains a threat, it is imperative to improve current approaches by incorporating reliable data alternative targets better inform decision-makers. Wastewater-based epidemiology (WBE) has emerged viable method track transmission, offering more metric than reported cases for outcomes like hospitalizations. Recognizing the natural alignment of wastewater systems with city structures, ideal leveraging WBE data, this study introduces multi-city, wastewater-based model categorically predict Using hospitalization six US cities, accompanied other epidemiological variables, we develop Generalized Additive Model (GAM) generate two categorization types. Hospitalization Capacity Risk Categorization (HCR) predicts burden on healthcare system based number available hospital beds city. Rate Trend (HRT) trajectory growth rate these categorical thresholds, create probabilistic forecasts retrospectively risk trend category cities over 20-month period 1, 2, 3 week windows. We also propose new methodology measure change points, or time periods where sudden changes outbreak dynamics occurred. explore influence predictor hospitalizations, showing its inclusion positively impacts model’s performance. With study, are able capacity disease trends novel useful way, giving decision-makers tool

Language: Английский

Citations

0
Environmental Detection and Monitoring of SARS-CoV-2 for COVID-19 Risk Prediction DOI
Rita R. Colwell, Kyle D. Brumfield, Moiz Usmani

et al.

Springer eBooks, Journal Year: 2024, Volume and Issue: unknown, P. 65 - 77

Published: Jan. 1, 2024

Language: Английский

Citations

0