Advanced Analytics for Medical Supply Chain Resilience in Healthcare Systems: An Infection Disease Case

The COVID-19 impacts go beyond healthcare systems as they also challenge global markets and society. A comprehensive knowledge involving the elements to contain the virus is fundamental for properly planning and implementing a quick response to the problems faced worldwide. Learning to coexist with the COVID-19 pandemic has become part of our daily life. Hence, the scientific community’s capabilities to continuously provide solutions for pandemics are crucial to mitigate the spread of the pandemic. The main contribution of this work is to propose applications of advanced analytics (AA) in healthcare treatment networks that predict epidemiology curves and the distribution of patients’ severity towards. These tools assist the optimization of such networks with innovative solutions aiming to increase the capacity, responsiveness, and preparedness of the infrastructure and management in healthcare systems. Such a decision-making environment can forecast the spread of the disease by utilizing given inputs such as social distance, out-of-stock of personal protective equipment (PPE) items, lockdown policies, environmental factors, etc. These forecasts are especially important to allow a) medical corporations to design and operate healthcare treatment systems and b) governments to develop policies aiming to maintain the balance between social progress and a sustainable economy.