Epidemic-supply-demand optimization under disease resource allocation strategies

Infectious diseases pose significant threats to the economy and social order, and their control is often constrained by limited resources. A key challenge for decision-makers is how to optimize resource allocation under such constraints to curb pathogen transmission and minimize the collective damage caused. Focusing on the COVID-19 pandemic in China, this study presents an Epidemic-Supply-Demand model that integrates transmission dynamics with a supply-demand framework to evaluate antiviral distribution strategies under time-varying transmission rates and their implications for medication needs and hospital capacity. We show that prioritizing antiviral delivery to infected individuals significantly increased medication availability for symptomatic infections, relative to unrestricted purchases, thereby reducing hospital strain. Adjusting drug allocation rates between infected and non-infected populations mitigated epidemic severity and lowered fatality rates. Additionally, maximizing the supply of ventilators and medications proved crucial in controlling virus spread and reducing mortality. Integrating medication distribution dynamics with virus transmission models is essential for informing rational resource allocation policies. The results of this research are valuable for decision-makers in effectively addressing resource allocation challenges during pandemics.