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GD Labs: Scaling Swab Testing During COVID-19
內容大綱
In early 2020, the rapid spread of COVID-19 across the world led the most highly affected countries, such as the United States and India, to focus on rapid testing and contact tracing to break the chain of transmission. By August 25, 2020, India had tested nearly 37 million cumulative COVID-19 samples as part of the government’s “Test, Track, Treat” initiative. The efficient allocation of collected swabs with saliva samples to appropriate testing labs had become an urgent operational requirement. The senior consultant of GD Labs was appointed officer on special duty by the State Government of Chhattisgarh to devise a plan for the optimal allocation of swabs to government and private labs across the state. He decided to roll out a pilot study for two districts that had six labs—both government and private. The task required access to extensive data on the collection of swabs with saliva samples, previous backlogs, locations of labs, and the maximum capacity per lab. The goal of the project was to maximize the allocation of swabs for testing within budget constraints.
學習目標
The case is suitable for courses that discuss operations research and health care supply chain management at the undergraduate and graduate levels. It is also suitable for engineering courses that discuss decision modelling and industrial management and for postgraduate programs in management that cover topics such as introduction to quantitative decision-making and advanced mathematical modelling. The case also discusses optimization techniques for effective allocation of testing samples, which makes it suitable for courses that discuss capacity and process analysis in health care service delivery models. The case helps students devise a complex COVID-19 swab testing strategy to ensure timely results, with the goal of reducing the spread of the virus by identifying affected patients, who can then isolate to avoid spreading the virus. After completion of this case and assignment questions, students will be able to accomplish the following objectives:<ul><li>Apply linear programming to health care services by meeting the challenges of complex real-life decision-making for swab allocation to help deal effectively with a crisis such as the COVID-19 pandemic.</li><li>Use the Microsoft Excel Solver function for capacity allocation to understand the mathematical formulation of a capacity allocation problem by emphasizing cost constraints and solutions.</li><li>Address supply chain resilience to identify the specific factors behind the disruptions caused in the testing procedures due to the impact of COVID-19 in the health care supply chain.</li></ul>