Model distinguishability and inference robustness in mechanisms of cholera transmission and loss of immunity.

ABSTRACT: Mathematical models of cholera and waterborne disease vary widely in their structures, in terms of transmission pathways, loss of immunity, and a range of other features. These differences can affect model dynamics, with different models potentially yielding different predictions and parameter estimates from the same data. Given the increasing use of mathematical models to inform public health decision-making, it is important to assess model distinguishability (whether models can be distinguished based on fit to data) and inference robustness (whether inferences from the model are robust to realistic variations in model structure). In this paper, we examined the effects of uncertainty in model structure in the context of epidemic cholera, testing a range of models with differences in trans

SUBMITTER: Lee EC 

PROVIDER: S-EPMC5412123 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature