Uncovering identifiability of epidemiological models: basic reproduction number and complementary data streams
This study demonstrates that while individual parameters in epidemiological models may not be uniquely identifiable, the basic reproduction number often is, and that adding minimal complementary data can render otherwise non-identifiable models globally identifiable, thereby shifting the focus of public health surveillance toward ensuring the identifiability of decision-relevant quantities rather than complete model identifiability.