A Complete-Data Likelihood for Epidemic Processes on Partially Observed Dynamic Networks
部分观测动态网络上的传染病过程完全数据似然
Inference for infectious disease transmission on dynamic contact networks is complicated by latent infection times, partially observed network evolution, measurement error in contact data, and infection originating from outside the observed population. Existing likelihood-based approaches typically address these challenges separately and often rely on restrictive assumptions such as fully observed networks, closed populations, or symptom onset as a surrogate for infection…