Total Wait Research Articles

ACHIEVING EQUITABLE ACCESS TO ELECTIVE ARTHROPLASTY FOR ABORIGINAL AND TORRES STRAIT ISLANDER POPULATION IN A REGIONAL NSW HEALTH DISTRICT: COMPARISON WITH NATIONAL DATA

Aboriginal and Torres Strait Islander (ATSI) people have higher elective wait times compared to non-ATSI population in Australia. The Murrumbidgee Local Health District (MLHD) in southern New South Wales services 125,242km2 and a population of 287,000 people, with 5.8% identifying as ATSI. The aim of this study is to investigate the arthroplasty waitlist time of ATSI, and the impact of rurality on joint replacement, within the MLHD and compared to the Australian national data.1435 consecutive patients who underwent elective hip or knee arthroplasty from July 2018 to June 2021 were collated. Demographics, ATSI status, total wait time, readiness for care, and rurality were collected. Rurality was measured by distance from the arthroplasty hospital within MLHD. 1,151 patients were included after excluding patients with missing data or underwent emergent surgery.Within this cohort, 72 of 1,151 patients (6.2%) identified as ATSI. ATSI were younger than non-ATSI population (60.7y v 66.4y). There was no difference between Aboriginal status and ready for care wait time (368.0 v 349.9 days; p=0.116). The rurality of the groups was similar and increasing rurality did not affect total wait time (ATSI 103.1km v 98.6km; p=0.309). There was no difference in total or not-ready-for-care time between the groups (p: 0.68).Findings suggest equitable access to joint arthroplasty in the MLHD between ATSI and non-ATSI populations, which differs from the national experience. There is no significant difference between rurality and accessibility in the MLHD. This may be a result of the increased focus to ATSI and rural health within the district. A state or national study would be beneficial in identifying high performing regions and reviewing processes that enable equitable and accessible care.MLHD provides equitable access to arthroplasty surgery between ATSI and non-ATSI, as well as patients from rural areas within the LHD.

Waiting Times of Women versus Men Undergoing Transcatheter Aortic Valve Implantation.

Increasing transcatheter aortic valve implantation (TAVI) rates have resulted in prolonged waiting times. These have been associated with heart failure hospitalisations (HFH) and mortality yet sex differences have not yet been reported. All patients who underwent TAVI for severe aortic stenosis at a tertiary referral hospital in Australia were prospectively included. Total waiting time was divided into 'work-up' waiting time (period from referral date until heart team approval) and, 'procedural' waiting time (period from heart team approval until procedure date). Patients were analysed according to sex. Cohorts were matched to correct for differences in baseline and procedural variables. The primary endpoints were waiting times. Secondary outcomes included a composite of 30-day mortality and HFH, quality of life and mobility. A total of 407 patients (42% women) were included. After matching of the two cohorts (345 patients), women had significantly longer total waiting times than men: median 156 [interquartile range (IQR) 114-220] days in women versus 147 [IQR 92-204] days in men (p=0.032) including longer work-up (83 [IQR 50-128] versus 71 [IQR 36-119], p=0.195) and procedural waiting times (65 [IQR 44-100] versus 58 [IQR 30-93], p=0.021). Increasing waiting times were associated with higher 30-day mortality and HFH (p=0.01 for work-up waiting time, p=0.02 for procedural waiting time) and decreased 30-day mobility (p=0.044 for procedural waiting time) in women, but not in men. TAVI waiting times are significantly longer in women compared to men and are associated with increased mortality and HFH and reduced mobility at 30-days.

Estimating Passenger Queue for Bus Resource Optimization Using LoRaWAN-Enabled Ultrasonic Sensors

Anecdotal evidence has shown that bus stops around our University campus, specifically those serving express buses to city center, can get very crowded during certain times. This not only causes immense frustration to students who experience large variations in wait-time, but also creates challenges for the university and transport authority in knowing when to schedule extra buses. This article outlines our efforts to instrument a main bus stop on our university campus with Internet of Things (IoT) sensors to monitor passengers queue length. Our specific contributions are as follows: 1) We begin by developing a LoRaWAN ultrasonic sensor for detecting people in the queue. The sensor emits an ultrasonic tone pulse every few seconds, and determines whether someone is in front of it based on the reflections received, if any. Ten sensor units are built, tested, and tuned in a lab environment to achieve optimum detection accuracy and data transmission rate; 2) Next, we install these sensors at a 6-m interval along the campus fence bordering the bus-stop. We develop an algorithm to infer the number of passengers in the queue from sensor data and demonstrate that it achieves reasonable accuracy with a mean absolute error of 10.7 people (for a queue size of up to 100 people); and 3) we develop an optimization model to reschedule bus dispatching time, aiming to minimize total wait time of passengers. We show that a reduction of up to 42.93% in passengers’ wait time can be achieved by adopting demand-driven bus scheduling.

Delays to Surgery in Emergency Department Cases of Ectopic Pregnancy: A Quality Improvement Study

ObjectiveCreate a process map for emergency department (ED) presentations of surgical ectopic pregnancy, and identify areas of management amenable to quality improvement. MethodsA retrospective chart review of all patients undergoing surgical management of ectopic pregnancy at a large, urban, academic tertiary care centre from 2015 to 2017 was performed. ResultsSeventy-three patients were included. There were 6 (8.2%) unstable A cases (recommended time to operating room [OR] 0–2 hours), 23 (31.5%) stable A cases, and 44 (60%) B cases (recommended time to OR 2–8 hours). The percent of patients who were in the OR within the recommended time window were 6 (100%) for unstable A cases, 13 (56%) stable A cases, and 29 (65.9%) stable B cases, respectively (P = 0.139). Notable time delays include the time from gynaecology referral to the time seen by gynaecology (29.7% of total wait time for stable A cases from ED to OR) and the time the OR was booked to the time the patient was brought to the OR (53.2% of total wait time for stable B cases). Of the patients seen by physician at the emergency department first, the time from triage to the OR was significantly shorter for patients that received bedside ultrasound only (0.67 ± 0.5 hours vs. 2.1 ± 1.8 hours [P = 0.007]). ConclusionThis is the first study to map the ED presentation of surgical ectopic pregnancy. The management of ectopic pregnancy would benefit from the development of surgical triage decision aids, a surgical care pathway, and increased use of screening bedside ultrasound.

Approximating a ride-sourcing system with block matching

On-demand matching between waiting passengers and idle drivers is one of the most important components in a ride-sourcing system. A variety of matching mechanisms have been developed to meet different needs of ride-sourcing platforms, e.g. mitigating supply–demand imbalance, maximizing platform revenue. In this paper, we focus on a block matching system, a special type of matching mechanism, where the region of interest is partitioned into blocks, and on-demand matching is separately and simultaneously conducted in each block. Block matching can bring many benefits, such as limiting order assignment with long pick-up distance, simplifying the process of deployment, etc. However, it still remains a challenging yet interesting issue to determine the block size for the matching system, which is a key decision variable governing passengers’ waiting time. To solve the problem, we model the ride-sourcing system with block matching via a M/M/c queue, in which the service rate is endogenous and partially determined by passengers’ average pick-up time. Based on the model, we find that the average queueing time of passengers decreases with block size increasing, while the average pick-up time may increase instead. In addition, the average total waiting time (sum of average queueing and pick-up time) become nearly invariant to the change of block size when the block size is large, which we call plateau phenomenon. In the plateau, ride-sourcing platforms can choose the block size based on other standards while the average total waiting time is always maintained at the nearly lowest value. The findings are verified via an agent-based simulation study, demonstrating that the proposed model can be an effective tool to approximate block matching system.

Modeling of Traffic Flow on Roundabouts

The aim of this research is to create the modeling of roundabouts. First of all, the three-arm roundabout is created for validation with the existing model. Then, the model is expanded to the four-arm roundabout. In the development of a modern intelligent transportation system, the effectiveness of dealing with the non-linear, time-varying and congested traffic flow is imperative in achieving traffic control and accuracy. In this paper, the roundabout is modelled as a circuit of 2×2 junction comprising a main lane and a secondary lane. The rotation of the roundabout is in the clockwise direction, as in the case of Malaysia. In mathematical modelling, the traffic flow is created, based on one-dimensional hyperbolic conservation laws which are represented by non-linear partial differential equations where the unknown variable is a conserved quantity. As a scheme used in the computation and analysis, the Godunov method computes the fluxes at the interfaces of each cell in order to advance the solution of a Riemann Problem. In addition, the Courant-Friedrichs-Levy (CFL) condition is proposed and used to ensure the stability and accuracy of the numerical algorithm where the time step is not a constant. The optimization on the roundabout for Total Travel Time and Total Waiting Time with several parameters is applied to generate numerous results which will assist in assessing the reasonableness of the roundabout. The comparison data of the three-arm roundabout with our model and the existing model are discussed. In comparison, our results show similar properties with higher readings than in other published papers because our calculations involved all arms and roads. In addition, the comparison data between three-arm and four-arm roundabouts are reasonable and logical. Lastly, our model is more flexible and realistic, as compared to the existing model.

The real-time on-demand bus routing problem: The cost of dynamic requests

The real-time on-demand bus routing problem (ODBRP) supports the online routing of buses in a large-scale ride-sharing system. Given are a set of buses with fixed capacity, a set of bus stations and a set of transportation requests, only part of which are known before the planning horizon. A request consists of a set of possible departure and arrival stations, as well as an earliest departure and latest arrival time. The aim is to (1) assign each passenger to a departure and arrival bus station and (2) develop a set of bus routes to fulfill each request within its time window while minimizing the sum of the total waiting time and the total user ride time.Including the possibility for requests to be issued after the start of the planning horizon, i.e., when buses have already started servicing other requests, requires a dynamic re-optimization of a partially executed solution. Compared to the case in which all requests are known beforehand, the solution quality, expressed as the total waiting and user ride time, is expected to decline. This decline in objective function value can be seen as the “cost” of the dynamic requests. In this paper, we introduce the real-time ODBRP as an extension of its static problem variant and present a heuristic to deal with dynamic requests. In addition, an extensive set of experiments allows us to conclude that dynamic requests indeed lead to higher waiting and user ride times, especially for passengers who submit their request at the last minute. Passengers are therefore encouraged, if possible, to send their request well in advance, as this results in lower and more stable service promises, higher customer satisfaction, and higher revenues for the operating on-demand bus company.

Multi-depot green capacitated location routing problem considering uncertainty and in-facility queuing

Nowadays, designing a framework for an environmentally-friendly waste collection network is of higher importance due to population growth. This study presents a multi-depot green capacitated location routing problem (MGCLRP) considering the time window and in-facility queuing under uncertainty. A scenario-based robust optimization is employed to deal with demand and travelling time uncertainties. Moreover, the M/M/c queuing system calculates the expected total wait time at a recycling center. As a solution method, we develop an algorithm to find the optimal number of potential locations and use this optimal number to find the main objectives of the problem. Then, two versions of NSGA-III, enhanced by greedy initializations, are proposed to solve the large-scale instances. The obtained results show the superiority of the proposed NSGA-III over the simple version of this algorithm. Finally, we investigate the applicability of the given model in a practical case study for Tehran. • Designing a Green Capacitated Location Routing Problem Considering Uncertainty and In-Facility Queuing. • Applying a scenario-based robust optimization method to manage the uncertainty. • Proposing two hybrid metaheuristic algorithms to efficiently solve the problem.

Caregivers' Satisfaction with Routine Immunization Services in Primary, Secondary and Tertiary Health Institutions in Sokoto Metropolis, Nigeria

Background: Caregivers' satisfaction is one of the most frequently used outcome measures for quality of care offered by routine immunization (RI) service providers. It has been shown to positively influence compliance of caregivers with subsequent RI visits. This study assessed caregivers' satisfaction with RI services in primary, secondary and tertiary health facilities in Sokoto metropolis, Nigeria Materials and method: A descriptive cross-sectional study was conducted in three health facilities in Sokoto metropolis. A structured questionnaire was used to collect data from 217 caregivers who were selected via multistage sampling technique. Results: Mean age of respondents was 27 years ±5.49 and majority were Hausa-Fulani [183(84.3%)]. Majority of the caregivers in all the three categories of health facilities (HFs) surveyed spent more than 30 minutes to immunize their children (median total clinic wait time = 48 minutes). Caregivers were largely satisfied with most activities of the clinics; overall, 91.7% (n=199) of them were satisfied. Several factors were associated with caregivers' satisfaction; however, the significant predictors were tribe, providing adequate information about vaccine given to the child and availability of vaccines at all times (p<0.05). Conclusion: Up to three-fourth of the caregivers spent more than half an hour to receive RI services however, the overall satisfaction was excellent. The main predictors of caregivers' satisfaction were tribe, provision of information regarding the vaccine and availability of vaccines at all times. There is need for more efforts to be made by heads of the HFs and service providers to reduce waiting time at the RI clinics and also ensure vaccines are available at all times.

Measuring impact of a quality improvement initiative on glaucoma clinic flow using an automated real-time locating system

BackgroundLean methodology helps maximize value by reducing waste, first by defining what value and waste are in a system. In ophthalmology clinics, value is determined by the number of patients flowing through the clinic for a given time. We aimed to increase value using a lean-methodology guided policy change, then assessed its impact on clinic flow using an automated radiofrequency identification (RFID) based real-time locating system (RTLS).MethodsA total of 6813 clinical visits occurred at a single academic institution’s outpatient glaucoma clinic between January 5, 2018 to July 3, 2018. Over that period, 1589 patients comprising 1972 (29%) of visits were enrolled, with 1031 clinical visits occurring before and 941 visits after a policy change. The original policy was to refract all patients that improved with pinhole testing. The policy change was not to refract patients with a visual acuity ≥20/30 unless a specific request was made by the patient. Pre-post analysis of an automated time-motion study was conducted for the data collected 3 months before and 3 months after the policy change occurred on March 30, 2018. Changes to process and wait times were summarized using descriptive statistics and fitted to linear mixed regression models adjusting for appointment type, clinic volume, and daily clinic trends.ResultsOne thousand nine hundred twenty-three visits with 1588 patients were included in the analysis. Mean [SD] age was 65.9 [14.7] years and 892 [56.2%] were women. After the policy change, technician process time decreased by 2.9 min (p < 0.0001) while daily clinical patient volume increased from 51.9 ± 16.8 patients to 58.4 ± 17.4 patients (p < 0.038). No significant difference was found in total wait time (p = 0.18) or total visit time (p = 0.83).ConclusionsReal-time locating systems are effective at capturing clinical flow data and assessing clinical practice change initiatives. The refraction policy change was associated with reduced technician process time and overall the clinic was able to care for 7 more patients per day without significantly increasing patient wait time.

Evaluation of factors impacting patient satisfaction in a pediatric otolaryngology clinic

ObjectivesWith an emphasis on patient-centered care and provider transparency, patient satisfaction measures have become a key indicator of healthcare quality. Using the Press Ganey Outpatient Medical Practice Survey (PGOMPS), we sought to determine key factors that impact patient satisfaction. MethodsWe conducted a retrospective review of new pediatric (<18 years old) outpatient otolaryngology visits between January 1, 2014 and December 31, 2018 at a children's hospital clinic and satellite clinics. Univariate and multivariate binary logistic regression analysis were used to determine factors correlated with patient satisfaction for both the PGOMPS Total Score and Provider Sub-Score. ResultsA total of 1,050 patient or parent responses were included. The mean patient age was 5.6 ± 5.0 years with 54.7% identified as male. Univariate analysis demonstrated that for each 10-min increase in Total Wait Time, the odds of being satisfied were significantly decreased on both the Total Score (odds ratio [OR] 0.5; P < 0.001) and Provider Sub-Score (OR 0.8; P < 0.001). Furthermore, for each additional 5-year increase in patient age, patients were significantly more likely to report satisfaction on Total Score (OR 1.21; P = 0.011). Multivariate analysis revealed that the odds of achieving satisfaction for each decile increase in Total Wait Time were 0.5 for Total Score (P < 0.001) and 0.8 for Provider Sub-Score (P < 0.001), independent of patient age, sex, insurance category, socioeconomic disadvantage level, and patient community type. ConclusionsWait time is a significant factor impacting patients’ likelihood of being satisfied with their overall care in a pediatric otolaryngology clinic setting.

Calibration and validation of matching functions for ride-sourcing markets

Ride-sourcing services have become increasingly important in meeting people's mobility needs since their emergence. Compared to traditional street-hailing taxi services, ride-sourcing services significantly reduce the matching frictions in the markets by matching drivers and passengers with relatively distant distances through an online platform. Motivated by this new feature as well as the need for designing operating and regulating strategies, researchers have attempted to describe these innovative ride-sourcing markets through mathematical models, the core of which is the matching functions for characterizing matching frictions. Previous studies have developed a variety of matching functions for ride-sourcing markets, including perfect matching function, Cobb-Douglas type matching function, queuing models, and some physical models. However, less is known about the applicability and performance of these matching functions, that is, under what situations each of these matching functions well characterizes the real market. To address this issue, this paper makes one of the first attempts to calibrate, validate, and compare the prevailing matching functions in the literature, and ascertain the conditions of their applicability. In particular, we establish a simulator to simulate a total of 420 scenarios of the ride-sourcing market under different combinations of supply and demand. The key performance metrics, including the matching rate in the market, passengers' average matching time, passengers' average pick-up time, and passengers' average total waiting time, are utilized to test and compare seven widely used matching functions under various market scenarios.

Lean Management Improves the Process Efficiency of Controlled Ovarian Stimulation Monitoring in IVF Treatment.

Background Evaluation of patients' experiences and satisfaction is vital for assessing the quality of healthcare service, including in fertility clinics. One promising concept that has recently been widely used to increase efficiency and service quality in hospitals is the lean concept. Lean is a form of philosophy that focuses on reducing waste of a process and continuous improvement so that consumers receive greater value. This study aims to identify waste and improve efficiency using lean management methods in the controlled ovarian stimulation (COS) monitoring process during in vitro fertilization (IVF) treatment in a fertility clinic. Methods This study used an action research approach by observing the total service time of monitoring ovarian stimulation in IVF patients (n = 40). The identified waste and solutions were then compiled for use in a focus group discussion (FGD). From the FGD, a priority plan was obtained for the implementation of lean management. This study uses the PDCA cycle for improvement. Results Three priority solutions were chosen, which are as follows: (1) evaluating ovarian stimulation via USG only; (2) allocating more time during doctor's counselling; and (3) increasing counselling time by nurses in the injection room. The total patient wait time was reduced to 6 hours 32 minutes over the three visits, 13 hours 35 minutes decrease from before the intervention. In addition, the value-added ratio (VAR) was increased from 9% to 22% after the intervention. Conclusion This research provides theoretical and practical contributions for the lean management principles in IVF treatment. The findings of this study will contribute to the pursuit of knowledge and dissemination of lean principles in the management of healthcare, including IVF clinics.

"Internet +" Configuration Taxi Resource Era

This paper mainly studies the problem of the difficulty of taking a taxi, first of all, the degree of matching supply and demand is affected by taxis and passengers, so the indicators can be established from both drivers and passengers. The indicators we established are taxi idling rate, people ownership, passenger waiting time. Then, we take the maximum matching number between driver and passenger and the minimum total waiting time of passengers as the objective function to establish the maximum matching model between passenger and driver. The case analysis shows that this method can achieve better utilization of taxi resources and has strong operability.

A single-entry model and wait time for hip and knee replacement in eastern health region of Newfoundland and Labrador 2011\u20132019

BackgroundA single-entry model in healthcare consolidates waiting lists through a central intake and allows patients to see the next available health care provider based on the prioritization. This study aimed to examine whether and to what extent the prioritization reduced wait times for hip and knee replacement surgeries.MethodThe survival regression method was used to estimate the effects of priority levels on wait times for consultation and surgery for hip and knee replacements. The sample data included patients who were referred to the Orthopedic Central Intake clinic at the Eastern Health region of Newfoundland and Labrador and had surgery of hip and knee replacements between 2011 and 2019.ResultAfter adjusting for covariates, the hazard of having consultation booked was greater in patients with priority 1 and 2 than those in priority 3 when and at 90 days after the referral was made for both hip and knee replacements. Regarding wait time for surgery after the decision for surgery was made, while the hazard of having surgery was lower in priority 2 than in priority 3 when and indifferent at 182 days after the decision was made, it was not significantly different between priority 1 and priority 3 among hip replacement patients. Priority levels were not significantly related to the hazard of having surgery for a knee replacement after the decision for surgery was made. Overall, the hazard of having surgery after the referral was made by a primary care physician was greater for patients in high priority than those in low priority. Preferring a specific surgeon indicated at referral was found to delay consultation and it was not significantly related to the total wait time for surgery. Incomplete referral forms prolonged wait time for consultation and patients under age 65 had a longer total wait time than those aged 65 or above.ConclusionPatients with high priority could have a consultation booked earlier than those with low priority and prioritization in a single entrance model shortens the total wait time for surgery. However, the association between priority levels and wait for surgery after the decision for surgery was made has not well-established.

Outpatient Appointment Optimization: A Case Study of a Chemotherapy Service

In this paper, we study a complex outpatient planning problem in the chemotherapy department. The planning concerns sequences of patients’ treatment sessions subject to exact in-between resting periods (i.e., exact time-lags). The planning is constrained by the hospital infrastructure and the availability of medical staff (i.e., multiple time-varying resources’ availability). In order to maximize the patients’ service quality, the objective of the function considered is to minimize the total wait times, which is equivalent to the criteria for minimizing the total completion time. Our main contribution is a thorough analysis of this problem, using the Hybrid Flow Shop problem as a theoretical framework to study the problem. A novel Mixed Integer Linear Programming (MILP) is introduced. Concerning the resolution methods, priority-based heuristics and an adapted genetic algorithm (GA) are presented. Numerical experiments are conducted on historical data to compare the performances of the approximate resolution methods against the MILP solved by CPLEX. Numerical results confirm the performances of the proposed methods.

Abstracts for the 40th emergencies in medicine conference

Abstracts for the 40^th emergencies in medicine conference

Atomization Behavior of O/W Emulsion Droplets Made with Porous Glass Membranes

We conducted an experimental study of effects of dispersed oil droplet diameter on micro-explosion of oil-in-water (O/W) emulsion droplet during spheroid-type evaporation on a heated surface. The base fuel was n-dodecane, the surfactant was polyoxyethylene (6) lauryl ether. O/W emulsion was made with Shirasu Porous Glass (SPG) membrane, which is hydrophilic and has numerous and continuous pores, and then degassed. Also, the emulsion was stirred at low speed during the experiment. The hot surface temperature was 700 K, the initial droplet diameter was 1.95 mm, and the water content was 0.4. The pore diameter of the membrane was varied from 5 μm to 50 μm. The experiment of dropping the emulsion was conducted more than 30 times for each condition. The particle size distribution showed that the dispersed oil droplet diameter and its Sauter mean diameter decreased with the decrease of the membrane’s pore diameter. And as the pore diameter became smaller, the start time of phase separation was delayed. Total waiting time for disruptive microexplosion and its Weibull average increased with the decrease of the pore diameter. These results are considered to be due to the delay in the start time of phase separation as the dispersed oil droplet diameter decreases.

Ontario wait times for delayed surgical treatment of traumatic peripheral nerve injury.

Background:To better understand the occurrence and operative treatment of peripheral nerve injury (PNI) and the potential need for additional resources, it is essential to define the frequency and distribution of peripheral nerve procedures being performed. The objective of this study was to evaluate Ontario’s wait times for delayed surgical treatment of traumatic PNI.Methods:We retrieved data on wait times for peripheral nerve surgery from the Ontario Ministry of Health and Long-Term Care Wait Time Information System. We reviewed the wait times for delayed surgical treatment of traumatic PNI among adult patients (age ≥ 18 yr) from April 2009 to March 2018. Data collected included total cases, mean and median wait times, and demographic characteristics.Results:Over the study period, 7313 delayed traumatic PNI operations were reported, with variability in the case volume distribution across Local Health Integration Networks (LHINs). The highest volume of procedures (2788) was performed in the Toronto Central LHIN, and the lowest volume (< 6) in the Waterloo Wellington and North Simcoe Muskoka LHINs. The population incidence of traumatic PNI requiring surgery was 5.1/10 000. The mean and median wait times from surgical decision to surgical repair were 45 and 27 days, respectively. Both the longest and shortest wait times occurred in LHINs with low case volumes. The provincial target wait time was met in 93% of cases, but women waited significantly longer than men (p < 0.001).Conclusion:The provincial distribution of traumatic PNI surgery was variable, and the highest volumes were in the LHINs with large populations. The provincial wait time strategy for traumatic PNI surgery is effective, but women waited longer than men. Precise reporting from all hospitals is necessary to accurately capture and understand the delivery of care after traumatic PNI.

Optimal Deployment of Cordon Sanitaire with Available Testing Capacity

During the COVID-19 pandemic, authorities in many places have implemented various countermeasures, including setting up a cordon sanitaire to restrict population movement. This paper proposes a bi-level programming model to deploy a limited number of parallel checkpoints at each entry link around the cordon sanitaire to achieve a minimum total waiting time for all travelers. At the lower level, it is a transportation network equilibrium with queuing for a fixed travel demand and given road network. The feedback process between trip distribution and trip assignment results in the predicted waiting time and traffic flow for each entry link. For the lower-level model, the method of successive averages is used to achieve a network equilibrium with queuing for any given allocation decision from the upper level, and the reduced gradient algorithm is used for traffic assignment with queuing. At the upper level, it is a queuing network optimization model. The objective is the minimization of the system’s total waiting time, which can be derived from the predicted traffic flow and queuing delay time at each entry link from the lower-level model. Since it is a nonlinear integer programming problem that is hard to solve, a genetic algorithm with elite strategy is designed. An experimental study using the Nguyen-Dupuis road network shows that the proposed methods effectively find a good heuristic optimal solution. Together with the findings from two additional sensitivity tests, the proposed methods are beneficial for policymakers to determine the optimal deployment of cordon sanitaire given limited resources.