TY - JOUR AU - Roosa, Kimberlyn AU - Chowell, Gerardo PY - 2019 DA - 2019/01/14 TI - Assessing parameter identifiability in compartmental dynamic models using a computational approach: application to infectious disease transmission models JO - Theoretical Biology and Medical Modelling SP - 1 VL - 16 IS - 1 AB - Mathematical modeling is now frequently used in outbreak investigations to understand underlying mechanisms of infectious disease dynamics, assess patterns in epidemiological data, and forecast the trajectory of epidemics. However, the successful application of mathematical models to guide public health interventions lies in the ability to reliably estimate model parameters and their corresponding uncertainty. Here, we present and illustrate a simple computational method for assessing parameter identifiability in compartmental epidemic models. SN - 1742-4682 UR - https://doi.org/10.1186/s12976-018-0097-6 DO - 10.1186/s12976-018-0097-6 ID - Roosa2019 ER -