scholarly journals A Predictive Modelling Framework for COVID-19 Transmission to Inform the Management of Mass Events

2021 ◽  
Author(s):  
Claire Donnat ◽  
Freddy Bunbury ◽  
Jack Kreindler ◽  
Filippos T. Filippidis ◽  
Austen El-Osta ◽  
...  
Keyword(s):  
Risk Mitigation ◽  
Contextual Information ◽  
Predictive Modelling ◽  
Transmission Dynamics ◽  
Risk Models ◽  
Vaccination Rates ◽  
Public Events ◽  
Modelling Framework ◽  
Main Components ◽  
And Control

Modelling COVID-19 transmission at live events and public gatherings is essential to evaluate and control the probability of subsequent outbreaks. Model estimates can be used to inform event organizers about the possibility of super-spreading and the predicted efficacy of safety protocols, as well as to communicate to participants their personalised risk so that they may choose whether to attend. Yet, despite the fast-growing body of literature on COVID transmission dynamics, current risk models either neglect contextual information on vaccination rates or disease prevalence or do not attempt to quantitatively model transmission, thus limiting their potential to provide insightful estimates. This paper attempts to bridge this gap by providing informative risk metrics for live public events, along with a measure of their associated uncertainty. Starting with a thorough review of the literature and building upon existing models, our approach ties together three main components: (a) reliable modelling of the number of infectious cases at the time of the event, (b) evaluation of the efficiency of pre-event screening and risk mitigation protocols, and (c) modelling the transmission dynamics during the event. We demonstrate how uncertainty in the input parameters can be included in the model using Monte Carlo simulations. We discuss the underlying assumptions and limitations of our approach and implications for policy around live events management.

A Predictive Modelling Framework for COVID-19 Transmission to Inform the Management of Mass Events (Preprint)

2021 ◽  
Author(s):  
Claire Donnat
Keyword(s):  
Prediction Interval ◽  
Contextual Information ◽  
Predictive Modelling ◽  
Transmission Dynamics ◽  
Background Rate ◽  
Vaccination Rates ◽  
Modelling Framework ◽  
R Shiny ◽  
Order Of Magnitude ◽  
Main Components

BACKGROUND Modelling COVID-19 transmission at live events and public gatherings is essential to control the probability of subsequent outbreaks and communicate to participants their personalised risk. Yet, despite the fast-growing body of literature on COVID transmission dynamics, current risk models either neglect contextual information on vaccination rates or disease prevalence or do not attempt to quantitatively model transmission. OBJECTIVE This paper attempts to bridge this gap by providing informative risk metrics for live public events, along with a measure of their uncertainty. METHODS Building upon existing models, our approach ties together three main components: (a) reliable modelling of the number of infectious cases at the time of the event, (b) evaluation of the efficiency of pre-event screening, and (c) modelling of the event’s transmission dynamics and their uncertainty along using Monte Carlo simulations. RESULTS We illustrate the application of our pipeline for a concert at the Royal Albert Hall and highlight the risk’s dependency on factors such as prevalence, mask wearing, or event duration. We demonstrate how this event held on three different dates (August 3rd 2020, January 18th 2021, and March 8th 2021) would likely lead to transmission events only slightly above background rates (0.5 vs 0.2, 6.7 vs 3.5, and 5.4 vs 2.5, respectively. However, the 97.5 percentile of the prediction interval for the infections would likely be substantially higher than the background rate (6.8 vs 2, 89 vs 8, and 71 vs 7), further demonstrating that sole reliance on vaccination and antigen testing to gain entry would likely significantly underestimate the tail risk of the event. CONCLUSIONS Despite the unknowns surrounding COVID-19 transmission, our estimation pipeline opens the discussion on contextualized risk assessment by combining the best tools at hand to assess the order of magnitude of the risk. Our model can be applied to any future event, and is presented in a user-friendly R Shiny interface.

Adaptive Signal Analysis and Interpretation for Real-time Intelligent Patient Monitoring

1994 ◽  
Vol 33 (01) ◽  
pp. 60-63 ◽  
Author(s):  
E. J. Manders ◽  
D. P. Lindstrom ◽  
B. M. Dawant
Keyword(s):  
Computer Architecture ◽  
Real Time ◽  
Data Abstraction ◽  
Monitoring Strategy ◽  
Intelligent Monitoring ◽  
Patient Status ◽  
On Line ◽  
Main Components ◽  
And Control ◽  
Adaptive Signal

Abstract:On-line intelligent monitoring, diagnosis, and control of dynamic systems such as patients in intensive care units necessitates the context-dependent acquisition, processing, analysis, and interpretation of large amounts of possibly noisy and incomplete data. The dynamic nature of the process also requires a continuous evaluation and adaptation of the monitoring strategy to respond to changes both in the monitored patient and in the monitoring equipment. Moreover, real-time constraints may imply data losses, the importance of which has to be minimized. This paper presents a computer architecture designed to accomplish these tasks. Its main components are a model and a data abstraction module. The model provides the system with a monitoring context related to the patient status. The data abstraction module relies on that information to adapt the monitoring strategy and provide the model with the necessary information. This paper focuses on the data abstraction module and its interaction with the model.

scholarly journals Improving Stress Management and Sleep Hygiene in Intelligent Homes

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2398
Author(s):  
Asterios Leonidis ◽  
Maria Korozi ◽  
Eirini Sykianaki ◽  
Eleni Tsolakou ◽  
Vasilios Kouroumalis ◽  
...  
Keyword(s):  
Sleep Disturbances ◽  
Contextual Information ◽  
High Stress ◽  
Sleep Hygiene ◽  
Poor Sleep ◽  
Health Issues ◽  
Time Data ◽  
Intelligent Home ◽  
And Control

High stress levels and sleep deprivation may cause several mental or physical health issues, such as depression, impaired memory, decreased motivation, obesity, etc. The COVID-19 pandemic has produced unprecedented changes in our lives, generating significant stress, and worries about health, social isolation, employment, and finances. To this end, nowadays more than ever, it is crucial to deliver solutions that can help people to manage and control their stress, as well as to reduce sleep disturbances, so as to improve their health and overall quality of life. Technology, and in particular Ambient Intelligence Environments, can help towards that direction, when considering that they are able to understand the needs of their users, identify their behavior, learn their preferences, and act and react in their interest. This work presents two systems that have been designed and developed in the context of an Intelligent Home, namely CaLmi and HypnOS, which aim to assist users that struggle with stress and poor sleep quality, respectively. Both of the systems rely on real-time data collected by wearable devices, as well as contextual information retrieved from the ambient facilities of the Intelligent Home, so as to offer appropriate pervasive relaxation programs (CaLmi) or provide personalized insights regarding sleep hygiene (HypnOS) to the residents. This article will describe the design process that was followed, the functionality of both systems, the results of the user studies that were conducted for the evaluation of their end-user applications, and a discussion about future plans.

scholarly journals Establishment and lineage dynamics of the SARS-CoV-2 epidemic in the UK

Science ◽  
2021 ◽  
pp. eabf2946
Author(s):  
Louis du Plessis ◽  
John T. McCrone ◽  
Alexander E. Zarebski ◽  
Verity Hill ◽  
Christopher Ruis ◽  
...  
Keyword(s):  
Large Scale ◽  
Phylogenetic Analyses ◽  
Transmission Dynamics ◽  
Genetic Lineage ◽  
Size Dependent ◽  
Spatio Temporal ◽  
The Uk ◽  
Lineage Structure ◽  
And Control ◽  
Lineage Diversity

The UK’s COVID-19 epidemic during early 2020 was one of world’s largest and unusually well represented by virus genomic sampling. Here we reveal the fine-scale genetic lineage structure of this epidemic through analysis of 50,887 SARS-CoV-2 genomes, including 26,181 from the UK sampled throughout the country’s first wave of infection. Using large-scale phylogenetic analyses, combined with epidemiological and travel data, we quantify the size, spatio-temporal origins and persistence of genetically-distinct UK transmission lineages. Rapid fluctuations in virus importation rates resulted in >1000 lineages; those introduced prior to national lockdown tended to be larger and more dispersed. Lineage importation and regional lineage diversity declined after lockdown, while lineage elimination was size-dependent. We discuss the implications of our genetic perspective on transmission dynamics for COVID-19 epidemiology and control.

Ground Adaptability Characterization for Digging in Complex Geotechnical Conditions and Risk Mitigation

2011 ◽  
Vol 415-417 ◽  
pp. 1431-1434
Author(s):  
Wei Wei Yu ◽  
Xuan Guo
Keyword(s):  
Risk Factors ◽  
Control Method ◽  
Risk Mitigation ◽  
Tunnel Construction ◽  
Soil Pressure ◽  
Ground Movements ◽  
Construction Risk ◽  
And Control ◽  
Methods Of Control

Characterization of geotechnical digging and control the dynamical settlement is very necessary to mitigate construction risk. The metro tunnels of being constructed access to each other or near to the ground is high risk and physically difficult and costly. The control method becomes imperative. Some cases of digging prediction of ground movements and assessment of risk of damage to above or adjacent constructions have become an important issue especially in urban projec. Ground adaptability characterization is the key of control the tunneling in complex geotechnical conditions both in rock and soft stratum. High and changed water-soil pressure also is risk factors to effect tunneling process. Beside discussion of risk mitigation associate to tunnel construction, the developing settlement control and simulations are given to describe the methods of control risk.

scholarly journals Systemic Management of Pandemic Risks in Dental Practice: A Consolidated Framework for COVID-19 Control in Dentistry

2021 ◽  
Vol 8 ◽  
Author(s):  
Habib Benzian ◽  
Eugenio Beltrán-Aguilar ◽  
Richard Niederman
Keyword(s):  
Infection Control ◽  
Occupational Safety ◽  
Risk Mitigation ◽  
Healthcare Setting ◽  
Mitigation Measures ◽  
Health Administration ◽  
Safety And Health ◽  
Clinical Responses ◽  
And Control ◽  
The U.S

Dental teams and their workplaces are among the most exposed to airborne and bloodborne infectious agents, and therefore at the forefront of pandemic-related changes to how dental care is organized and provided to patients. The increasing complexity of guidelines makes is challenging for clinicians to navigate the multitude of COVID-19 guidelines issued by different agencies. A comparative analysis of guidance issued for managing COVID-19 in dental settings leading U.S. agencies was conducted, including documents of the Occupational Safety and Health Administration (OSHA), an agency of the U.S. Secretary of Labor, and of the U.S. Centers for Disease Prevention and Control (CDC), an agency of the U.S. Secretary of Health and Human Services. Details of infection control and other risk mitigation measures were reviewed for consistency, overlaps and similarities, then clustered according to thematic areas covering all domains of managing a dental healthcare setting. The analysis revealed five distinct areas of pandemic control, comprising (1) planning and protocols, (2) patient screening, (3) preparation of facilities, (4) PPE and infection control, and (5) procedures and aerosol control; thereby covering systematically all aspects requiring adaptation in a pandemic context. The “Pandemic-5 Framework for COVID-19 Control in Dentistry” provides an opportunity to simplify comprehensive decision-making from a clinical practitioner perspective. The framework supports a comprehensive systems-driven approach by using dental clinics as a setting to integrate pandemic clinical responses with the implementation of appropriate infection control protocols. Traditionally these two aspects are addressed independently from each other in separate concepts.

scholarly journals Three-axis air-bearing based platform for small satellite attitude determination and control simulation

2005 ◽  
Vol 3 (03) ◽  
Author(s):  
J. Prado ◽  
G. Bisiacchi ◽  
L. Reyes ◽  
E. Vicente ◽  
F. Contreras ◽  
...  
Keyword(s):  
Attitude Control ◽  
Attitude Determination ◽  
Center Of Mass ◽  
Measurement Unit ◽  
Simulation Platform ◽  
Air Bearing ◽  
Small Satellites ◽  
Main Components ◽  
Free Environment ◽  
And Control

A frictionless environment simulation platform, utilized for accomplishing three-axis attitude control tests in small satellites, is introduced. It is employed to develop, improve, and carry out objective tests of sensors, actuators, and algorithms in the experimental framework. Different sensors (i.e. sun, earth, magnetometer, and an inertial measurement unit) are utilized to assess three-axis deviations. A set of three inertial wheels is used as primary actuators for attitude control, together with three mutually perpendicular magnetic coils intended for desaturation purposes, and as a backup control system. Accurate balancing, through the platform’s center of mass relocation into the geometrical center of the spherical air-bearing, significatively reduces gravitational torques, generating a virtually torque-free environment. A very practical balancing procedure was developed for equilibrating the table in the local horizontal plane, with a reduced final residual torque. A wireless monitoring system was developed for on-line and post-processing analysis; attitude data are displayed and stored, allowing properly evaluate the sensors, actuators, and algorithms. A specifically designed onboard computer and a set of microcontrollers are used to carry out attitude determination and control tasks in a distributed control scheme. The main components and subsystems of the simulation platform are described in detail.

scholarly journals Modeling infection dynamics and mitigation strategies to support K-6 in-person instruction during the COVID-19 pandemic

2021 ◽  
Author(s):  
Douglas E. Morrison ◽  
Roch Nianogo ◽  
Vladimir Manuel ◽  
Onyebuchi A. Arah ◽  
Nathaniel Anderson ◽  
...  
Keyword(s):  
School Attendance ◽  
Secondary Infection ◽  
Mitigation Strategies ◽  
Transmission Dynamics ◽  
Model Parameters ◽  
Safety Education ◽  
Vaccination Rates ◽  
Health Authorities ◽  
Infection Dynamics ◽  
Public Health Authorities

AbstractObjectiveTo support safer in-person K-6 instruction during the coronavirus disease 2019 (COVID- 19) pandemic by providing public health authorities and school districts with a practical model of transmission dynamics and mitigation strategies.MethodsWe developed an agent-based model of infection dynamics and preventive mitigation strategies such as distancing, health behaviors, surveillance and symptomatic testing, daily symptom and exposure screening, quarantine policies, and vaccination. The model parameters can be updated as the science evolves and are adjustable via an online user interface, enabling users to explore the effects of interventions on outcomes of interest to states and localities, under a variety of plausible epidemiological and policy assumptions.ResultsUnder default assumptions, secondary infection rates and school attendance are substantially affected by surveillance testing protocols, vaccination rates, class sizes, and effectiveness of safety education.ConclusionsOur model helps policymakers consider how mitigation options and the dynamics of school infection risks affect outcomes of interest. The model’s parameters can be immediately updated in response to changes in epidemiological conditions, science of COVID-19 transmission dynamics, testing and vaccination resources, and reliability of mitigation strategies.

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