Infectious Diseases
Table of Contents
Lab 2 - Infectious Disease Modelling
Introduction
Epidemiologists study the demographics and patterns of disease which is necessary to make informed public health and safety decisions. Modeling disease prevalence allows scientists to quantify the spread of an infectious disease to help limit the spread. Students will model the prevalence of an infectious disease to demonstrate an understanding of how infectious diseases spread.
Learning Objectives
Students understand the modelling process.
Students can create scientific models to answer word problems.
Students can implement math models as computational models in MATLAB.
Students can create plots to communicate the output of computational models in MATLAB.
I Do
An example of setting up parameters for each variable, including the number of iterations to be calculated is provided.
We Do
A comparison of the effects of changing one parameter at a time, seeing the effect on the final result at the end of the time period.
You Do
Model global HIV prevalence from 1990 to 2019 using the incidence and mortality.
Epidemiology
Measurement types
Prevalence is the proportion of the population with an infection or disease at a given time.
Incidence is the rate of new cases of infection or disease at a given time.
Mortality is the rate of death due to an infection or disease in a population at a given time.
Birth-Death Model
A birth-death model is a simple model that tracks changes in a population over time. The same concept can be used to model diseases using the same formula with epidemiological measurements.
P(t + 1) = P(t) + deltat * (birth - death) * P(t)
In this formula, birth rate refers to new cases, or incidence, death rate refers to the mortality rate, and deltat is the amount of time that passes.
Practice changing these parameters below by pressing 'Model.m' under 'Files' on the left of the screen, editing the script to change any of the variables, and pressing 'Run' to view the resulting plot.
SIR Model
The SIR model accounts for the three possible states of an individual in a population: people that are Susceptible (S), Infected (I), and Recovered (R). To determine the proportions of each role, the infection rate (β) , removal rate (γ) , and life expectancy (1/μ) have to be considered. These measures are used to calculate the reproduction rate (R0) and the life expectancy. The equations for each of these variables are shown below.
μ=birth-death rate
R0=β/(γ+μ)
S=1/R0
I=(μ/β)*(R0–1)
R=1-S-R
Follow the link to change the parameters of the SIR model:
Data Source
The global health data exchange compile health and demographic data from a variety of sources including WHO, Integrated Public Use Microdata Series, and the CIA World Factbook. Data can be filtered by demographic information for different diseases. Follow the link to look at a disease of your choice.