2020-11-18 18:42:40

Introduction

Simulation modeling is an approach that builds computer models for some setting/scenario (e.g. the spread of COVID in the US) and uses the models to understand what is going on, to make forecasts and to evaluate the impact of different interventions.

Simulation modeling areas

Source: NOAA

Source: NOAA

  • Weather forecasting.
  • Simulations of man-made, engineered system.
  • Predicting the economy.
  • Infectious disease transmission.

Simulation modeling overview

  • Build a model that simulates the process of disease transmission.
  • Include any details that are relevant for the question, omit everything else.

Simulation modeling uses - Understanding

See later example

Simulation modeling uses - Forecasting

Simulation modeling uses - Intervention Assessment

Simulation modeling - challenges

  • It takes time to learn how to build, use and interpret models.
  • One generally needs to write code to build simulation models.
Markus Spiske on Unsplash

Markus Spiske on Unsplash

Simulation modeling - a solution

DSAIDE - Dynamical Systems Approach to Infectious Disease Epidemiology

  • Software that can teach uses of simulation modeling.
  • Does not require any coding.
  • Allows for active/hands-on learning.

DSAIDE characteristics

  • Free and open source.
  • Based on the widely used R programming language.
  • Options for students to move beyond the graphical interface and use the underlying models directly.

ID Epi & DSAIDE example

  • We’ll look at one example that shows how to use models to understand the impact of interventions.
  • We’ll walk through the general idea first, then try it in DSAIDE.

The scenario

  • For a single infectious disease outbreak, more intervention/control (through e.g. drugs or vaccines or social distancing) is generally better.
  • If multiple outbreaks are likely and no control is possible beyond the first outbreak how does the best control strategy change?
  • Use a simple model to understand/explore optimal intervention strategies for multi-outbreak settings.
  • Details: Handel et al “What is the best control strategy for multiple infectious disease outbreaks?” Proceedings of the Royal Society B 2007.

The basic SIR model

  • We’ll now look at the most basic model for population level infectious disease modeling.
  • This model tracks individuals (humans or animals) in 3 states, susceptible, infected/infectious and recovered/removed. It is called the SIR model.

\[ \begin{aligned} \dot S & = -bSI \\ \dot I & = bSI - gI \\ \dot R & = gI \\ \end{aligned} \]

The overshoot concept

The overshoot concept.

The overshoot concept.

The basic SIR model with interventions

\[ \begin{aligned} \dot S & = -(1-f)bSI \\ \dot I & = (1-f)bSI - gI \\ \dot R & = gI \\ \end{aligned} \]

Interventions during a single outbreak

Control during multiple outbreaks

Control during multiple outbreaks

Control during multiple outbreaks

Try for yourself

Summary