Allen Jing, April Nellis
Abstract: The COVID-19 outbreak is a global crisis and drive-through (DT) testing centers have been shown to increase testing capabilities in other communities. In Michigan, Detroit and the surrounding Wayne County have been hit particularly hard by the virus. We therefore decided to tackle the question of how best to maximize DT testing capacity while ensuring accessibility for all Wayne County residents. This led to two questions - what is the maximum testing capacity for the county? And, where should the testing centers be located for maximum impact? From our model and the associated data, we can conclude that the main factor affecting testing capacity in Wayne County is the daily operating budget, while the construction budget plays less of a role overall. So, the number of tests performed per day is limited mainly by the ability of the government to purchase test kits and to pay healthcare workers to administer them. However, the distribution of the DT testing centers is determined by a variety of factors, including the maximum allowable travel time between municipalities and the minimum capacity constraints.
Dingyi Sun, Xinyao Zhang, Zewen Ai
Abstract: The outbreak of coronavirus disease 2019 (COVID-19) has caused a health crisis. In the past three weeks, the virus spread across Washtenaw County, MI. To prevent the county’s health system from being overwhelmed, it is necessary to set up some drive-through screening facilities in available pharmacies. For limited test kits and pharmacy locations to launch in facilities, the government have recommended people who contacted with confirmed patients test in nearest medical detection points. Considering the uncertainty of this epidemic, the government would spend less budgets on setting up the test system at this stage and save financial resources to avoid worse situations in the future. Besides the financial cost for the essential facilities, several other risks exist, including transition risk and cross infection risk. To reduce the spread risk of infectious diseases, the suspected people who need to be detected should choose the nearest path to the detection point as close as possible. What’s more, the more people in the same facility, the higher infection risk for them is. Through the “linear scalarization” method, both risks and the maintenance cost switch to the total cost in the same unit formulation. To reduce the total cost, we will build an integer programming model to minimize that and solve the problem through an IP solver under the limited test kits, potential node, and facilities. To construct more facilities and maintain the spent in the government budget, we add the volunteers to help the staff in the pharmacy in an extension model. Compared with the initial model, we proved the assistance from the volunteer in the location selection and cost-reducing.
Heya Ouyang, Xinyu Liang
Abstract: During the COVID-19 outbreak, timely testing has been proved to be an effective tool to mitigate the pandemic. Facing increasing pressure in allocating limited medical resources, optimal testing models and policy implications are in urgent need by the government. We study how to best select the screening facility locations under the COVID-19 pandemic. We formulate a mixed-integer programming model and use the following methods to tackle this problem: (1) relaxed LP model;(2) Gomory’s cut; (3) branch and bound algorithm. We generate insights on how to set and utilize the budget and discuss the impact of testing population requirements.
Caleb Goldstein, Alexander Mize, Nhat Minh Nguyen
Abstract: This project aims to tackle the issue of rolling-out drive-through test clinics (DTCs) in Michigan as optimally as possible to conserve resources and meet public demand. Our analysis will recommend an optimal set of schedules that could have been implemented to roll-out DTCs in different Michigan regions and counties with the South Korean DTC system as the basis, and assumed capability to supply the schedule if the US government was more apt.
Yiting Xu, Ding Zhou
Abstract: Our object in this project is to infer the spatio-temporal path of infection through a social-contact network for an ongoing outbreak scenario under the assumption that limited infection information is available.
Wenqing Zhou, Shiyun Zhou, Jiaxi Zhou
Abstract: Mass screening and testing are crucial in fighting the COVID-19 pandemic. In this project, we imagined a mass screening of 2% of the population is going to take place in the city of Ann Arbor. The objective is to find the optimal drive-through screening facility locations with minimum travel-related costs. The problem is mathematically modeled as an integer linear program using the facility location problem model with an objective function reflecting the travel costs of both residents taking tests and setting up screening locations with different weighting factors. The experimental design is based on real-world population data and parking facility data available online, and the cost is calculated based on travel distance obtained using Google Maps service. A set of optimal solutions with respect to various combinations of weighting factors is obtained. The sensitivity analysis reveals that the weighting factor ratio would significantly affect the choice of screening locations.
Yuxiang Wu, Weihsiu Hu, Mengjun Hou
Abstract: This project considered how to search the optimal strategy in distributing people for testing virus and building new test sites. Our project based on Modular Capacitated Location Model and extended it to the multiple time version to give a more detailed analysis on where to build test sites, how to operate test sites and how to distribute people into the test sites over time horizon. After formulating models, we first run the model under simulated data and get a preliminary result for the model. This result is shown in the appendix. After the simulation, we obtain real data in the Washtenaw County and apply our model into the data and get some results that have direction role for the strategy to test people under background of COVID-19 outbreak.
Meng Wang, Ruohan Wang, Rudy Rao
Abstract: In our project, we conduct a research on the Screening Facility Location Problem to find the optimal screening facility establishment solution in an epidemic setting. The objective of our model is to minimize the total cost while given a limited screening capacity in each facility. We determine whether or not to open a facility in each city.