Time Series Forecasting for Personal Protective Equipment During COVID-19 Pandemic: A Case Study of Quebec

Commencing in early 2020, the United States has grappled with an acute scarcity of Personal Protective Equipment (PPE), which is indispensable for healthcare professionals battling the COVID-19 outbreak. Media reports have highlighted protests by healthcare workers who analogized their situation to firefighters attempting to quell flames without water or soldiers entering combat outfitted in cardboard armor. The accelerated proliferation of the COVID-19 virus has precipitated a global surge in the demand for medical supplies, engendering substantial disruptions in the international supply chain and leading to critical shortages. In the present research, we undertake a comprehensive analysis of scholarly work concerning healthcare supply chains, with a focus on the constrained availability of PPE during the COVID-19 period. We offer perspectives on the extant circumstances and explore the utilization of advanced analytical techniques for forecasting future demand, particularly in anticipation of potentially more severe pandemics. In particular, we train a machine learning algorithm based on the real-data between 2020 and 2021 in the province of Quebec and predict the future demand in a similar situation in crisis and with more intensity in demand. Furthermore, we underscore the imperative for maintaining an optimized inventory of essential PPE to mitigate prospective risks.