  This primer describes the statistical uncertainty in mechanistic models and
provides R code to quantify it. We begin with an overview of mechanistic models
for infectious disease, and then describe the sources of statistical
uncertainty in the context of a case study on SARS-CoV-2. We describe the
statistical uncertainty as belonging to three categories: data uncertainty,
stochastic uncertainty, and structural uncertainty. We demonstrate how to
account for each of these via statistical uncertainty measures and sensitivity
analyses broadly, as well as in a specific case study on estimating the basic
reproductive number, $R_0$, for SARS-CoV-2.
