Intermediate Dynamic Modeling II
Intermediate Dynamic Modeling II shows the development of a cohesive modeling project focused on the
COVID-19 pandemic with its challenges of long viral incubation times and large asymptomatic populations. Policy
options such as shutdowns, quarantines, social distancing, masking, and vaccinations are explored, as well as
human reactions to both the disease and these measures. The model is calibrated to USA data.
Join Dr. Karim Chichakly as he guides you, step by step, through some of the key components in the process of effective model creation. During each 55-minute class, you'll learn the
ins and outs of model creation as he shares his personal workflow and additional tips and tricks that he’s learned in more than 20 years of experience in the field.
Each class is followed with a question and answer session with Dr. Chichakly. Online access to these class recordings, sample models, handouts, and homework assignments are
included to cement your learning.
Class 1: Framing the Problem
The COVID-19 pandemic is introduced. Both the reference mode and dynamic hypothesis are
developed. The core set of epidemiological models are reviewed.
Class 2: Adding Realism
After selecting a core epidemiological model, the policies of quarantining those who show symptoms
or who test positive are explored. The distribution of delays in the system is explored and the proper
delay type is integrated into the model.
Class 3: Adding Policies and Behavior
What impacts do shutdowns and masking and social distancing have on the spread of the virus? What
is the impact of people’s reactions to the spread of the disease and of people’s behavior in different
seasons? After adding these impacts, the model is calibrated to USA data.
Class 4: Modeling Vaccines
Vaccines need to be manufactured and administered to people willing to be vaccinated.
The impact of vaccine hesitancy is also explored. The model is recalibrated with vaccines
included. Model extensions are discussed.