Value-based optimization of healthcare resource allocation for COVID-19 hot spots

摘要: With the emerging COVID-19 crisis, a critical task for public health officials and policy makers is to decide how prioritize, locate, allocate scarce resources. To answer these questions, decision need be able determine location of required resources over time based on hot spot locations. Hot spots are defined as concentrated areas with sharp increases in COVID19 cases. place stress existing healthcare resources, resulting demand potentially exceeding current capacity. This research will describe value resource allocation approach that seeks coordinate demand, by uncertain epidemiological forecasts, adding additional such hospital beds. Value framed function expected usage marginal (bed, ventilator, etc). Subject certain constraints, decisions operationalized using nonlinear programming model, allocating new beds across number geographical The results show assist at all levels making best possible highly dynamic COVID environment.