| Abstract: |
| Compartment modeling has been used extensively in epidemics to understand and predict infectious diseases. With the increasing data availability, mathematical models fit cumulative data are used to estimate disease key transmission parameters. During this process, one important question arises regarding the model identifiability which handles the question of whether parameters can be correctly and accurately recovered given available data. In this talk, I will demonstrate the problems in incidence data accuracy with Covid 19 cases in Imperial Vally. Then, I use both a simple SEIR model and a SI vector-host model to demonstrate the impact of data type, data resolution, and optimization tools used in parameter estimation in accessing models` identifiability. |
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