A Mixed-Effects Model to Predict COVID-19 Hospitalizations Using Wastewater Surveillance DOI Creative Commons
Maria L. Daza–Torres, J. Cricelio Montesinos-López, Heather N. Bischel

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Aug. 16, 2023

Abstract During the COVID-19 pandemic, many countries and regions investigated potential use of wastewater-based disease surveillance as an early warning system. Initially, methods were created to detect presence SARS-CoV-2 RNA in wastewater. Investigators have since conducted extensive studies examine link between viral concentration wastewater cases areas served by sewage treatment plants over time. However, only a few reports attempted create predictive models for hospitalizations at county-level based on concentrations This study implemented linear mixed-effects model that observes association levels virus hospitalizations. The was then utilized predict short-term hospitalization trends 21 counties California data from March 21, 2022, May 2023. modeling framework proposed here permits repeated measurements well fixed random effects. assumed input variable, instead or test positivity rate, showed strong performance successfully captured Additionally, allows prediction two weeks ahead. Forecasts could provide crucial information hospitals better allocate resources prepare surges patient numbers.

Language: Английский

Human viral nucleic acids concentrations in wastewater solids from Central and Coastal California USA DOI Creative Commons
Alexandria B. Boehm, Marlene K. Wolfe, Krista R. Wigginton

et al.

Scientific Data, Journal Year: 2023, Volume and Issue: 10(1)

Published: June 22, 2023

Abstract We measured concentrations of SARS-CoV-2, influenza A and B virus, respiratory syncytial virus (RSV), mpox human metapneumovirus, norovirus GII, pepper mild mottle nucleic acids in wastewater solids at twelve treatment plants Central California, USA. Measurements were made daily for up to two years, depending on the plant. using digital droplet (reverse-transcription–) polymerase chain reaction (RT-PCR) following best practices making environmental molecular biology measurements. These data can be used better understand disease occurrence communities contributing wastewater.

Language: Английский

Citations

47
Introduction to WBE case estimation: A practical toolset for public health practitioners DOI
Gabriel K. Innes, Andrew N. Patton,

Sarah M. Prasek

et al.

The Science of The Total Environment, Journal Year: 2025, Volume and Issue: 980, P. 179487 - 179487

Published: April 28, 2025

Language: Английский

Citations

0
Academic institution extensive, building-by-building wastewater-based surveillance platform for SARS-CoV-2 monitoring, clinical data correlation, and potential national proxy DOI Creative Commons
Arnoldo Armenta-Castro, Mariel Araceli Oyervides-Muñoz, Alberto Aguayo-Acosta

et al.

PLOS Global Public Health, Journal Year: 2025, Volume and Issue: 5(5), P. e0003756 - e0003756

Published: May 9, 2025

In this work, we report on the performance of an extensive, building-by-building wastewater surveillance platform deployed across 38 locations largest private university system in Mexico, spanning 19 32 states, to detect SARS-CoV-2 genetic materials during COVID-19 pandemic. Sampling took place weekly from January 2021 and June 2022. Data 343 sampling sites was clustered by campus state evaluated through its correlation with seven-day average daily new cases each cluster. Statistically significant linear correlations (p-values below 0.05) were found 25 campuses 13 states. Moreover, evaluate effectiveness epidemiologic containment measures taken institution potential as representative points for future public health emergencies Monterrey Metropolitan Area, between viral loads samples be stronger Dulces Nombres, treatment plant city (Pearson coefficient: 0.6456, p-value: 6.36710 −8 ), than study 0.4860, 8.288x10 −5 ). However, when comparing data after urban mobility returned pre-pandemic levels, levels both became comparable (0.894 0.865 Nombres). This work provides a basic framework implementation analysis similar decentralized platforms address sanitary emergencies, allowing efficient return priority in-person activities while preventing becoming transmission hotspots.

Language: Английский

Citations

0
Data-driven estimation of the instantaneous reproduction number and growth rates for the 2022 monkeypox outbreak in Europe DOI Creative Commons
Fernando Saldaña, Maria L. Daza–Torres, Maíra Aguiar

et al.

PLoS ONE, Journal Year: 2023, Volume and Issue: 18(9), P. e0290387 - e0290387

Published: Sept. 13, 2023

Objective To estimate the instantaneous reproduction number R t and epidemic growth rates for 2022 monkeypox outbreaks in European region. Methods We gathered daily laboratory-confirmed cases most affected countries from beginning of outbreak to September 23, 2022. A data-driven estimation is obtained using a novel filtering type Bayesian inference. phenomenological model coupled with sequential approach update forecasts over time used obtain time-dependent several countries. Results The Spain, France, Germany, UK, Netherlands, Portugal, Italy. At early phase outbreak, our , which can be as proxy basic 0 was 2.06 (95% CI 1.63 − 2.54) 2.62 2.23 3.17) 2.81 2.51 3.09) 1.82 1.52 2.18) 2.84 2.07 3.91) 1.13 0.99 1.32) 3.06 2.48 3.62) Cumulative these present subexponential rather than exponential dynamics. Conclusions Our findings suggest that current limited transmission chains human-to-human secondary infection so possibility huge pandemic very low. Confirmed are decreasing significantly region, decline might attributed public health interventions behavioral changes population due increased risk perception. Nevertheless, further strategies toward elimination essential avoid subsequent evolution virus result new outbreaks.

Language: Английский

Citations

7
Bayesian sequential approach to monitor COVID-19 variants through positivity rate from wastewater DOI Creative Commons
J. Cricelio Montesinos-López, Maria L. Daza–Torres, Yury E. García

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Jan. 11, 2023

Trends in COVID-19 infection have changed throughout the pandemic due to myriad factors, including changes transmission driven by social behavior, vaccine development and uptake, mutations virus genome, public health policies. Mass testing was an essential control measure for curtailing burden of monitoring magnitude during its multiple phases. However, as progressed, new preventive surveillance mechanisms emerged. Implementing programs, wastewater (WW) surveillance, at-home tests reduced demand mass severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing. This paper proposes a sequential Bayesian approach estimate positivity rate (PR) using SARS-CoV-2 RNA concentrations measured WW through adaptive scheme incorporating dynamics. PR estimates are used compute thresholds data CDC low, substantial, high transmission. The effective reproductive number calculated from data. provides insights into dynamics evolution analytical framework that combines different sources continue trends. These results can provide guidance reduce future outbreaks variants emerge. proposed modeling applied City Davis campus University California Davis.

Language: Английский

Citations

4
A mixed-effects model to predict COVID-19 hospitalizations using wastewater surveillance DOI Creative Commons
Maria L. Daza–Torres, J. Cricelio Montesinos-López, Heather N. Bischel

et al.

Journal of environmental chemical engineering, Journal Year: 2024, Volume and Issue: 12(2), P. 112485 - 112485

Published: March 12, 2024

During the COVID-19 pandemic, many countries and regions investigated potential use of wastewater-based disease surveillance as an early warning system. Initially, methods were created to detect presence SARS-CoV-2 RNA in wastewater. Investigators have since conducted extensive studies examine link between viral concentration wastewater cases areas served by sewage treatment plants over time. However, only a few reports attempted create predictive models for hospitalizations at county-level based on concentrations This study implemented linear mixed-effects model that evaluates association levels virus hospitalizations. The was then utilized predict short-term hospitalization trends 21 counties California data from March 21, 2022, May 2023. modeling framework proposed here permits repeated measurements, well fixed random effects. incorporated input variable rather than or test positivity rate exhibited robust performance effectively captured discernible Additionally, allows prediction SARS CoV-2 two weeks ahead. Forecasts could provide crucial information hospitals better allocate resources prepare surges patient numbers.

Language: Английский

Citations

1
A Mixed-Effects Model to Predict COVID-19 Hospitalizations Using Wastewater Surveillance DOI Creative Commons
Maria L. Daza–Torres, J. Cricelio Montesinos-López, Heather N. Bischel

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Aug. 16, 2023

Abstract During the COVID-19 pandemic, many countries and regions investigated potential use of wastewater-based disease surveillance as an early warning system. Initially, methods were created to detect presence SARS-CoV-2 RNA in wastewater. Investigators have since conducted extensive studies examine link between viral concentration wastewater cases areas served by sewage treatment plants over time. However, only a few reports attempted create predictive models for hospitalizations at county-level based on concentrations This study implemented linear mixed-effects model that observes association levels virus hospitalizations. The was then utilized predict short-term hospitalization trends 21 counties California data from March 21, 2022, May 2023. modeling framework proposed here permits repeated measurements well fixed random effects. assumed input variable, instead or test positivity rate, showed strong performance successfully captured Additionally, allows prediction two weeks ahead. Forecasts could provide crucial information hospitals better allocate resources prepare surges patient numbers.

Language: Английский

Citations

1