Statistical implications of relaxing the homogeneous mixing assumption in time series Susceptible-Infectious-Removed models
时间序列 SIR 模型放宽均匀混合假设的统计后果
Infectious disease epidemiologists routinely fit stochastic epidemic models to time series data to elucidate infectious disease dynamics, evaluate interventions, and forecast epidemic trajectories. To improve computational tractability, many approximate stochastic models have been proposed. In this paper, we focus on one class of such approximations -- time series Susceptible-Infectious-Removed (TSIR) models. Infectious disease modeling often starts with a homogeneous mixing…