Wastewater-based epidemiology predicts COVID-19-induced weekly new hospital admissions in over 150 USA counties

Nature Communications, Journal Year: 2023, Volume and Issue: 14(1)

Published: July 28, 2023

Although the coronavirus disease (COVID-19) emergency status is easing, COVID-19 pandemic continues to affect healthcare systems globally. It crucial have a reliable and population-wide prediction tool for estimating COVID-19-induced hospital admissions. We evaluated feasibility of using wastewater-based epidemiology (WBE) predict weekly new hospitalizations in 159 counties across 45 states United States America (USA), covering population nearly 100 million. Using county-level wastewater surveillance data (over 20 months), WBE-based models were established through random forest algorithm. accurately predicted admissions, allowing preparation window 1-4 weeks. In real applications, periodically updated showed good accuracy transferability, with mean absolute error within 4-6 patients/100k upcoming hospitalization numbers. Our study demonstrated potential WBE as an effective method provide early warnings systems.

Language: Английский

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The fate of intracellular and extracellular antibiotic resistance genes during Ultrafiltration-Ultraviolet-Chlorination

Journal of Hazardous Materials, Journal Year: 2025, Volume and Issue: 486, P. 137088 - 137088

Published: Jan. 1, 2025

Language: Английский

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A multi-city COVID-19 categorical forecasting model utilizing wastewater-based epidemiology

The Science of The Total Environment, Journal Year: 2025, Volume and Issue: 960, P. 178172 - 178172

Published: Jan. 1, 2025

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. Hospitaization Capacity Risk Categorization (HCR) predicts burden on healthcare system based number available hospital beds city. Hospitalization 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

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COVID-19 Transmission During the Winter 2023-24 Surge: A Comparative Analysis of Surveillance Estimates in the U.S., Canada, and the U.K.

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 9, 2025

Background: Better estimates of COVID-19 transmission are needed since testing has declined. The present investigation examined the correspondence among during winter 2023-24 surge using wastewater-derived for U.S. and Canada testing-derived estimate in U.K. to evaluate validity provide vital public health data on levels. Methods: study used from (Pandemic Mitigation Collaborative dashboard) (COVID-19 Resources testing-based surveillance (Health Security Agency). Data sets were linked by date relative peak within each set. Analyses focused UKHSA period November 2023 March 2024. 1) described day, 2) agreement patterns via correlations, 3) absolute proportion population actively infectious across two months transmission, 4) populations infected months. Results: On day infections, an estimated 1.95 million people U.S., 148 thousand Canada, 431 U.K., meaning 2.5%-4.5% these infectious. Estimates showed high throughout wave, especially between (r=.974, p<.001). During 93.5% 68.8% had excellent or better with data. An >100 months, 20.9%-26.0% population. Discussion: Findings support ongoing significance documenting levels surge. Transmission methodologies nations. More resources prevent diagnose treat long-term sequelae.

Language: Английский

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COVID-19 hospitalizations and deaths predicted by SARS-CoV-2 levels in Boise, Idaho wastewater

The Science of The Total Environment, Journal Year: 2023, Volume and Issue: 907, P. 167742 - 167742

Published: Oct. 17, 2023

Language: Английский

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Sustainability of global small-scale constructed wetlands for multiple pollutant control

npj Clean Water, Journal Year: 2024, Volume and Issue: 7(1)

Published: June 6, 2024

Abstract The global wastewater surge demands constructed wetlands (CWs) to achieve the UN’s Sustainable Development Goals (SDG); yet pollutant removal interactions and sustainability of small CWs are unclear. This study synthesizes CW data from 364 sites worldwide. efficiency organic matter nutrient pollutants had a 75th percentile 68.8–84.0%. Bivariate analysis found consistent synergies between removals, lasting 3–12 years. optimal thresholds for maintaining synergistic effects were as follows: area size—17587 m 2 , hydraulic loading rate—0.45 m/d, retention time—8.2 days, temperature—20.2 °C. When considering co-benefits multi-pollutants control, promoting small-scale could be an effective sustainable solution managing diverse while simultaneously minimizing land requirements. holds potential address challenges posed by water scarcity resulting discharge pollution.

Language: Английский

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Wastewater-based epidemiology for COVID-19 surveillance and beyond: A survey

Epidemics, Journal Year: 2024, Volume and Issue: 49, P. 100793 - 100793

Published: Sept. 26, 2024

Language: Английский

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Advancing Real-time Pandemic Forecasting Using Large Language Models: A COVID-19 Case Study

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: May 3, 2024

Forecasting the short-term spread of an ongoing disease outbreak is a formidable challenge due to complexity contributing factors, some which can be characterized through interlinked, multi-modality variables such as epidemiological time series data, viral biology, population demographics, and intersection public policy human behavior. Existing forecasting model frameworks struggle with multifaceted nature relevant data robust results translation, hinders their performances provision actionable insights for health decision-makers. Our work introduces PandemicLLM, novel framework multi-modal Large Language Models (LLMs) that reformulates real-time text reasoning problem, ability incorporate real-time, complex, non-numerical information -- textual policies genomic surveillance previously unattainable in traditional models. This approach, unique AI-human cooperative prompt design representation learning, encodes LLMs. By redefining process ordinal classification task, PandemicLLM yields more trustworthy predictions, facilitating decision-making. The applied COVID-19 pandemic, trained utilize policies, surveillance, spatial, subsequently tested across all 50 states U.S. duration 16 weeks. Empirically, shown high-performing pandemic effectively captures impact emerging variants provide timely accurate predictions. proposed opens avenues incorporating various pandemic-related heterogeneous formats exhibits performance benefits over existing study illuminates potential adapting LLMs learning enhance forecasting, illustrating how AI innovations strengthen responses crisis management future.

Language: Английский

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Recovery of economic activities in China uncovered by remotely sensed nighttime light data under the pandemic new normal

Applied Geography, Journal Year: 2025, Volume and Issue: 175, P. 103506 - 103506

Published: Jan. 5, 2025

Language: Английский

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Lifting of travel restrictions brings additional noise in COVID-19 surveillance through wastewater-based epidemiology in post-pandemic period

Water Research, Journal Year: 2025, Volume and Issue: 274, P. 123114 - 123114

Published: Jan. 7, 2025

The post-pandemic world still faces ongoing COVID-19 infections, although international travel has returned to pre-pandemic conditions. Wastewater-based epidemiology (WBE) is considered an efficient tool for the population-wide surveillance of infections during pandemic. However, performance WBE in era with restrictions lifted remains unknown. Utilizing weekly county-level wastewater data from June 2021-November 2022 222 counties 49 states (covering 104 million people) United States America, we retrospectively evaluated correlations between SARS-CoV-2 RNA (C

Language: Английский

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