Pandemics like COVID-19 disrupt not only acute care but also delay regular treatments, leading to growing waiting lists and long-term strain on healthcare systems. My research aims to develop and extend data-driven models to better understand and manage these disruptions. A first focus is on refining existing hospital inflow forecasting models through collaboration with hospitals and other stakeholders. A second component explores how waiting lists for non-pandemic care evolve when a pandemic shocks a system initially in equilibrium. Additional work investigates GP workload during the pandemic, combining clinical data with statistical testing to quantify pressure on primary care. Finally, designing optimization methods for scaling hospital capacity between acute and elective care will play a role. The overall goal is to enable more resilient healthcare responses during crises.
