# Susceptible-Infected-Recovered (SIR) Modeling the Focus of NISS/ASA Tutorial

The Susceptible-Infected-Recovered (SIR) model is being used by scientists around the world to study the infectious disease dynamics of the COVID-19 epidemic and guide public health policy decisions for mitigating the impact of the disease. The National Institute of Statistical Sciences (NISS) and the American Statistical Association Section on Statistics in Epidemiology (ASA-SIE) teamed up to co-sponsor a special two-hour tutorial on SIR methods. The instructor for this session was Dr. Ottar Bjornstad, Ph.D. (Penn State University), an exceptional researcher whose specialty is the mathematical and computational aspects of population ecology and population dynamics.

Ottar Bjornstad is not a conventional webinar presenter.  For online webinars, the convention is to create a series of slides and then use these to work your way through the content you want to present.  This is very straightforward, but does this one format always lend itself to what you are trying to explain?

Instead, Ottar braved the technological elements by switching formats to fit the need of the concepts or methods he was trying to convey.  Amazingly, he pulled this off pretty well!
Ottar started with slides that helped to set the stage for the session but then quickly moved to the whiteboard in order to establish the mathematical foundations for understanding the flows of transmission, which in turn lead defining the characteristics of the key parameter, reproduction number or basic reproduction ratio, represented by the notation R0, and further, the probabilities involved in a simple SIR model.

From here Ottar moved to sharing his screen to show the explanation and then manipulation R code examples of the integration of the ordinary differential equations used in the SIR model using RStudio in order to demonstrate the modeling of these methods.  Ottar was then able to move to sharing a Shiny app where the concepts and the coding that he was talking about earlier was able to come to life!  And, it was here that he was able to play a bit with the parameters to see and comment on what resulted.

Questions from attendees were forwarded to Ottar by Jim Rosenberger who served as the moderator of this event.  Some involved clarification of what was being implemented and these elicited detailed remarks around the structuring of various models from Ottar.  Other questions were much more broad, for example, “What strategies should universities implement in the future? Fall 2020?”

This tutorial described the background and theory of the SIR modeling approach, how it is applied to understand the spread of COVID and other infectious diseases, and how to use R software to fit basic and more complicated SIR models.  You can find the materials, readings, codes and links to Shiny apps that were shared in this presentation below.

#### Tutorial Session Materials

Bjørnstad, O.N., Shea, K., Krzywinski, M. and Altman, N., "Modeling infectious epidemics." Nature methods 17 (2020): 455-456.
with associated online Shiny App  https://shiny.bcgsc.ca/posepi1/

Bjørnstad, O.N., Shea, K., Krzywinski, M. and Altman, N., "The SEIRS model for infectious disease dynamics." Nature methods 17 (2020): 557-558.
with associated online Shiny App  https://shiny.bcgsc.ca/posepi2/

All the data and functions to be discussed are in the R-package:  https://CRAN.R-project.org/package=epimdr

And the  Chapter on SIR of the publication Epidemics: Models and data using R, by Ottar N. Bjornstad, provides more detailed documentation.

Slides used during the presentation:  Presentation slides