Assessment of a COVID-19 Control Plan on an Urban University Campus During a Second Wave of the Pandemic

JAMA Network Open, Journal Year: 2021, Volume and Issue: 4(6), P. e2116425 - e2116425

Published: June 25, 2021

Importance

The COVID-19 pandemic has severely disrupted US educational institutions. Given potential adverse financial and psychosocial effects of campus closures, many institutions developed strategies to reopen campuses in the fall 2020 semester despite ongoing threat COVID-19. However, opted have limited reopening minimize risk spread SARS-CoV-2.

Objective

To analyze how Boston University (BU) fully reopened its controlled transmission worsening Boston, Massachusetts.

Design, Setting, Participants

This multifaceted intervention case series was conducted at a large urban university Massachusetts, during semester. BU response included high-throughput SARS-CoV-2 polymerase chain reaction testing facility with capacity deliver results less than 24 hours; routine asymptomatic screening for COVID-19; daily health attestations; adherence monitoring feedback; robust contact tracing, quarantine, isolation on-campus facilities; face mask use; enhanced hand hygiene; social distancing recommendations; dedensification classrooms public places; enhancement all building air systems. Data were analyzed from December 20, 2020, January 31, 2021.

Main Outcomes Measures

diagnosis confirmed by reverse transcription–polymerase anterior nares specimens sources transmission, as determined through tracing.

Results

Between August more 500 000 tests identified 719 individuals COVID-19, including 496 students (69.0%), 11 faculty (1.5%), 212 staff (29.5%). Overall, 718 individuals, or 1.8% community, had test positive Of 837 close contacts traced, 86 (10.3%) tracers source 370 (51.5%), 206 (55.7%) identifying non-BU source. Among 5 84 known infection, most reported outside (all members [100%] 67 [79.8%]). A 108 183 undergraduate (59.0%) 39 98 graduate (39.8%); notably, no traced classroom setting.

Conclusions Relevance

In this used coordinated strategy testing, isolation, management oversight, control an

Language: Английский

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Extended Kalman filter based on stochastic epidemiological model for COVID-19 modelling

Computers in Biology and Medicine, Journal Year: 2021, Volume and Issue: 137, P. 104810 - 104810

Published: Aug. 28, 2021

Language: Английский

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A scenario modeling pipeline for COVID-19 emergency planning

Scientific Reports, Journal Year: 2021, Volume and Issue: 11(1)

Published: April 6, 2021

Coronavirus disease 2019 (COVID-19) has caused strain on health systems worldwide due to its high mortality rate and the large portion of cases requiring critical care mechanical ventilation. During these uncertain times, public decision makers, from city departments federal agencies, sought use epidemiological models for support in allocating resources, developing non-pharmaceutical interventions, characterizing dynamics COVID-19 their jurisdictions. In response, we developed a flexible scenario modeling pipeline that could quickly tailor makers seeking compare projections epidemic trajectories healthcare impacts multiple intervention scenarios different locations. Here, present components configurable features COVID Scenario Pipeline, with vignette detailing current use. We also model limitations active areas development meet ever-changing maker needs.

Language: Английский

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Modelling the potential impact of mask use in schools and society on COVID-19 control in the UK

Scientific Reports, Journal Year: 2021, Volume and Issue: 11(1)

Published: April 22, 2021

As the UK reopened after first wave of COVID-19 epidemic, crucial questions emerged around role for ongoing interventions, including test-trace-isolate (TTI) strategies and mandatory masks. Here we assess importance masks in secondary schools by evaluating their impact over September 1-October 23, 2020. We show that, assuming TTI levels from August 2020 no fundamental changes virus's transmissibility, adoption would have reduced predicted size a second wave, but preventing it required 68% or 46% those with symptoms to seek testing (assuming masks' effective coverage 15% 30% respectively). With community settings not schools, rates increase 76% 57%.

Language: Английский

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Agent-based modeling of COVID-19 outbreaks for New York state and UK: Parameter identification algorithm

Infectious Disease Modelling, Journal Year: 2021, Volume and Issue: 7(1), P. 30 - 44

Published: Nov. 27, 2021

This paper uses Covasim, an agent-based model (ABM) of COVID-19, to evaluate and scenarios epidemic spread in New York State (USA), the UK, Novosibirsk region (Russia). Epidemiological parameters such as contagiousness (virus transmission rate), initial number infected people, probability being tested depend on region's demographic geographical features, containment measures introduced; they are calibrated data about COVID-19 interest. At first stage our study, epidemiological (numbers people tested, diagnoses, critical cases, hospitalizations, deaths) for each mentioned regions were analyzed. The characterized terms seasonality, stationarity, dependency spaces, extrapolated using machine learning techniques specify unknown model. second stage, Optuna optimizer based tree Parzen estimation method objective function minimization was applied determine model's parameters. validated with historical 2020. modeled results State, UK have demonstrated that if level testing is preserved, positive cases will remain same during March 2021, while it reduce. Due features (two datasets stationary series 1), forecast precision relatively high but lower new COVID-19.

Language: Английский

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