scholarly journals The contribution of reduced COVID-19 test time in controlling the spread of the disease: A simulation-based approach

2022 ◽  
Vol 12 (2) ◽  
Author(s):  
Youness Frichi ◽  
Abderrahmane Ben Kacem ◽  
Fouad Jawab ◽  
Said Boutahari ◽  
Oualid Kamach ◽  
...  
Keyword(s):  
Discrete Event ◽  
Mass Scale ◽  
Test Time ◽  
Test Duration ◽  
Accurate Identification ◽  
Event Simulation ◽  
Simulation Results ◽  
Precautionary Measures ◽  
Novel Coronavirus ◽  
The Impact

The novel coronavirus COVID-19 has known a large spread over the globe threatening human health. Recommendations from WHO and specialists insist on testing on a mass scale. However, health systems do not have enough resources. The current process requires the isolation of testees in the hospitals’ isolation rooms for several hours until the test results are revealed, limiting hospitals’ capacities to test large numbers of cases. The aim of this paper was to estimate the impact of reducing the COVID-19 test time on controlling the pandemic spread, through increasing hospitals’ capacities to test on a mass scale. First, a discrete-event simulation was used to model and simulate the COVID-19 testing process in Morocco. Second, a mathematical model was developed to demonstrate the effect of accurate identification of infected cases on controlling the disease’s spread. Simulation results showed that hospitals’ testing capacities could be increased six times if the test duration fell from 10 hours to 10 minutes. The reduction of test time would increase testing capacities, which help to identify all the infected cases. In contrast, the simulation results indicated that if the infected population is not accurately identified and no precautionary measures are taken, the virus will continue to spread until it reaches the total population. Reducing test time is a vital component of the response to the COVID-19 pandemic. It is essential for the effective implementation of policies to contain the virus.

scholarly journals Balancing scarce hospital resources during the COVID-19 pandemic using discrete-event simulation

2021 ◽  
Author(s):  
G.J. Melman ◽  
A.K. Parlikad ◽  
E.A.B. Cameron
Keyword(s):  
Resource Allocation ◽  
Discrete Event Simulation ◽  
Elective Surgery ◽  
Discrete Event ◽  
Specific Patient ◽  
Event Simulation ◽  
The Impact ◽  
Allocation Decisions ◽  
Allocation Strategies ◽  
Resource Allocation Decisions

AbstractCOVID-19 has disrupted healthcare operations and resulted in large-scale cancellations of elective surgery. Hospitals throughout the world made life-altering resource allocation decisions and prioritised the care of COVID-19 patients. Without effective models to evaluate resource allocation strategies encompassing COVID-19 and non-COVID-19 care, hospitals face the risk of making sub-optimal local resource allocation decisions. A discrete-event-simulation model is proposed in this paper to describe COVID-19, elective surgery, and emergency surgery patient flows. COVID-19-specific patient flows and a surgical patient flow network were constructed based on data of 475 COVID-19 patients and 28,831 non-COVID-19 patients in Addenbrooke’s hospital in the UK. The model enabled the evaluation of three resource allocation strategies, for two COVID-19 wave scenarios: proactive cancellation of elective surgery, reactive cancellation of elective surgery, and ring-fencing operating theatre capacity. The results suggest that a ring-fencing strategy outperforms the other strategies, regardless of the COVID-19 scenario, in terms of total direct deaths and the number of surgeries performed. However, this does come at the cost of 50% more critical care rejections. In terms of aggregate hospital performance, a reactive cancellation strategy prioritising COVID-19 is no longer favourable if more than 7.3% of elective surgeries can be considered life-saving. Additionally, the model demonstrates the impact of timely hospital preparation and staff availability, on the ability to treat patients during a pandemic. The model can aid hospitals worldwide during pandemics and disasters, to evaluate their resource allocation strategies and identify the effect of redefining the prioritisation of patients.

scholarly journals Assessing asset monitoring levels for maintenance operations

2015 ◽  
Vol 26 (5) ◽  
pp. 632-659 ◽  
Author(s):  
Abdullah A Alabdulkarim ◽  
Peter Ball ◽  
Ashutosh Tiwari
Keyword(s):  
Asset Management ◽  
Business Models ◽  
Discrete Event ◽  
Dynamic Modelling ◽  
Simulation Models ◽  
Content Type ◽  
Event Simulation ◽  
Product Service ◽  
Asset Monitoring ◽  
The Impact

Purpose – Asset management has recently gained significance due to emerging business models such as Product Service Systems where the sale of asset use, rather than the sale of the asset itself, is applied. This leaves the responsibility of the maintenance tasks to fall on the shoulders of the manufacturer/supplier to provide high asset availability. The use of asset monitoring assists in providing high availability but the level of monitoring and maintenance needs to be assessed for cost effectiveness. There is a lack of available tools and understanding of their value in assessing monitoring levels. The paper aims to discuss these issues. Design/methodology/approach – This research aims to develop a dynamic modelling approach using Discrete Event Simulation (DES) to assess such maintenance systems in order to provide a better understanding of the behaviour of complex maintenance operations. Interviews were conducted and literature was analysed to gather modelling requirements. Generic models were created, followed by simulation models, to examine how maintenance operation systems behave regarding different levels of asset monitoring. Findings – This research indicates that DES discerns varying levels of complexity of maintenance operations but that more sophisticated asset monitoring levels will not necessarily result in a higher asset performance. The paper shows that it is possible to assess the impact of monitoring levels as well as make other changes to system operation that may be more or less effective. Practical implications – The proposed tool supports the maintenance operations decision makers to select the appropriate asset monitoring level that suits their operational needs. Originality/value – A novel DES approach was developed to assess asset monitoring levels for maintenance operations. In applying this quantitative approach, it was demonstrated that higher asset monitoring levels do not necessarily result in higher asset availability. The work provides a means of evaluating the constraints in the system that an asset is part of rather than focusing on the asset in isolation.

Abstract 2524: Increasing the Proportion of Patients Treated with Stroke Thrombolysis: Reducing In-hospital Delays has Substantially More Impact than Extension of the Time Window

Stroke ◽  
2012 ◽  
Vol 43 (suppl_1) ◽  
Author(s):  
Martin A James ◽  
Thomas Monks ◽  
Ken Stein ◽  
Martin Pitt
Keyword(s):  
Time Window ◽  
Discrete Event ◽  
Fold Increase ◽  
Service Improvement ◽  
Disability Benefit ◽  
Prospective Data ◽  
Stroke Service ◽  
Event Simulation ◽  
Simulation Based ◽  
The Impact

Background Pooled analyses show the benefit of IV alteplase for ischemic stroke up to 4·5 hours after onset, and expert guidelines have been updated to reflect this. However, the benefit from thrombolysis is critically time-dependent, and the additional benefit from extending the time window may be jeopardised by in-hospital delays. Methods We developed a discrete-event simulation based on prospective data from 1142 acute stroke patients arriving at our large district hospital over a two-year period to April 2011, modelling the time spent in the ED for triage and assessment, brain imaging and, if applicable, thrombolysis. Outputs from the model included arrival to treatment times (ATT), percentage of strokes thrombolysed, and the number of thrombolysed patients with a 90 day modified Rankin Scale (mRS) of 0-1. We sought to model the current stroke pathway (treatment <3 hours of onset), and compare it with developmental scenarios exploring the impact of extending treatment from 3 to 4.5 hours, of ED staff alerting the stroke service at triage, of ambulance pre-alert to the stroke service, and combinations of these measures. Results The model illustrates that extending the treatment window modestly increases the percentage of acute strokes thrombolysed, from 5% to 6% (95% CI 5.8-6.1%), and increases the number of thrombolysed patients with mRS 0-1 by 7 per year (95% CI 5.9-8.0). Both the triage alert and ambulance pre-alert scenarios increase thrombolysis rates to 15% (95% CI 14.9% to 15.7%); but the ambulance pre-alert reduces ATT by a mean of 27 mins (95% CI 26.3-28.4) compared to the triage alert scenario. The ambulance pre-alert scenario increases the number of thrombolysed patients with mRS 0-1 by 35/year (95% CI 32.9-37.7) compared to 22 (95% CI 20.4-23.5) in the triage alert scenario. Combining the treatment extension with either alerting measure does not increase the thrombolysis rate further (15%, 95% CI 14.7-15.1%). Sensitivity analysis illustrates that the pre-alert system is the least vulnerable to a drop in compliance rates. Conclusions Our simulation model shows that the greatest disability benefit accrues from measures to substantially reduce in-hospital delays to alteplase treatment - a potential three-fold increase in the proportion of patients treated. Compared to extending the time window for alteplase from 3 to 4.5 hours, eradicating in-hospital delays to treatment offers a five-fold greater disability benefit, and this should be the pre-eminent focus of service improvement for all emergency receiving hospitals.

Use of Predictive and Simulation Models to Develop Strategies for Better Access Specialists Care

2020 ◽  
pp. 109-136
Author(s):  
Siang Li Chua ◽  
Wai Leng Chow
Keyword(s):  
Lead Time ◽  
Discrete Event ◽  
Simulation Models ◽  
Multiple Logistic Regression ◽  
Specialist Care ◽  
Event Simulation ◽  
Patients At Risk ◽  
The Impact ◽  
Specialist Outpatient Clinic ◽  
Des Model

No-shows are patients who miss scheduled Specialist Outpatient Clinic (SOC) appointments. No-shows can impact patients' access to care and appointment lead time. This chapter describes a data-driven strategy of improving access to specialist care through first developing a stratified predictive scoring model to identify patients at risk of no-shows; second, studying the impact of a dynamic overbooking strategy that incorporates the use of the no-show prediction model using discrete event simulation (DES) on lead time. Seventeen variables related to new SOC appointments for subsidized patients in 2016 were analyzed. Multiple logistic regression (MLR) found eight variables independently associated with no-shows with area under receiver operation curve (AUC) 70%. The model was tested and validated. DES model simulated the appointment overbooking strategy as applied to the top highest volume specialties and concluded that lead time of Specialty 1 and 2 can be shortened by 27.5 days (49% improvement) and 21.3 (33%) respectively.

scholarly journals The use of a non-integer order PI controller with an active queue management mechanism

2016 ◽  
Vol 26 (4) ◽  
pp. 777-789 ◽  
Author(s):  
Adam Domański ◽  
Joanna Domańska ◽  
Tadeusz Czachórski ◽  
Jerzy Klamka
Keyword(s):  
Discrete Event ◽  
Active Queue Management ◽  
Pi Controller ◽  
Queue Management ◽  
Management Mechanism ◽  
Event Simulation ◽  
Flow Approximation ◽  
Self Similar ◽  
Fractional Order Pi Controller ◽  
The Impact

AbstractIn this paper the performance of a fractional order PI controller is compared with that of RED, a well-known active queue management (AQM) mechanism. The article uses fluid flow approximation and discrete-event simulation to investigate the influence of the AQM policy on the packet loss probability, the queue length and its variability. The impact of self-similar traffic is also considered.

Simulating the impact of facility design on operations: a study in an internal medicine ward

Facilities ◽  
2020 ◽  
Vol 38 (7/8) ◽  
pp. 501-522 ◽  
Author(s):  
Davide Schaumann ◽  
Nirit Putievsky Pilosof ◽  
Michal Gath-Morad ◽  
Yehuda E. Kalay
Keyword(s):  
Internal Medicine ◽  
Discrete Event ◽  
Building Design ◽  
Behavior Patterns ◽  
Internal Medicine Ward ◽  
Content Type ◽  
Discrete Event Simulations ◽  
Simulation Results ◽  
High Level ◽  
The Impact

Purpose This study aims to use a narrative-based simulation approach to explore potential implications of including or excluding a dayroom in the design of an internal medicine ward. Design/methodology/approach The approach involved: collecting data in facilities using field observations and experts’ interviews; modeling representative behavior patterns in the form of rule-based narratives that direct collaborative behaviors of virtual occupants; simulating the behavior patterns in two alternative design options, one of which includes a dayroom; and analyzing the simulation results with respect to selected key performance indicators of day-to-day operations and spatial occupancy, including occupant density in corridors, number and locations of staff-visitor interactions and duration of a doctors’ round procedure. Findings Simulation results suggest that the presence of a dayroom reduces visitors’ density in corridors and diminishes the number of staff–visitor interactions that can delay the performing of scheduled medical procedures. Research limitations/implications A high level of uncertainty is intrinsic to the simulation of future human behavior. Additional work is required to systematically collect large volumes of occupancy data in existing facilities, model additional narratives and develop validation protocols to assess the degree of uncertainty of the proposed model. Originality/value A limited number of studies explore how simulation can be used to study the impact of building design on operations. This study uses a narrative-based approach to address some of the limitations of existing methods, including discrete-event simulations. Preliminary results suggest that the lack of appropriate spaces for patients and visitors to socialize may cause potential disruptions to hospital operations.

A Methodology to Evaluate Complex Manufacturing Systems through Discrete-Event Simulation Models

2012 ◽  
Vol 502 ◽  
pp. 7-12 ◽  
Author(s):  
L.P. Ferreira ◽  
E. Ares ◽  
G. Peláez ◽  
M. Marcos ◽  
M. Araújo
Keyword(s):  
Discrete Event Simulation ◽  
Manufacturing Systems ◽  
Discrete Event ◽  
Simulation Models ◽  
Network Configuration ◽  
Event Simulation ◽  
Automobile Assembly ◽  
Loop Network ◽  
Complex Manufacturing Systems ◽  
The Impact

This paper proposes a methodology to analyze complex manufacturing systems, based on discrete-event simulation models. The methodology was validated by performing different simulation experiments and will be applied to a multistage multiproduct production line, based on a real case, with a closed-loop network configuration of machines and intermediate buffers consisting of conveyors, which is very common in the automobile sector. A simulation model in an Arena environment was developed, which allowed for an analysis of the important aspects not yet studied in specialized literature, namely the assessment of the impact of the production sequence on the automobile assembly line. Various sequence rules were analyzed and the performance of each of the corresponding simulation models was registered.

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