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.

Course Overview

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.