Infection Model
Modeling the Spread of an Epidemic |
By developing a computer model of the spread of an infectious disease, the student develops an understanding of the role of the infection rate and the removal rate on the spread of the disease. The Threshold Theorem of Epidemiology claims that the extent of spread of an epidemic can be predicted if three values are known: initial number of susceptible people (S(0)), the infection rate (K), and the removal rate (by quarantine or cure) (Q). The extent of the spread of the epidemic is indicated by the percentage of susceptible who become infected. Diseases that are easily transmitted spread quickly unless measures are taken to quarantine or cure infected people quickly. The three epidemic models below can each be used to experiment with various factors to see the impact on the populations. Vensim or STELLA software is needed to run the models. Right-click on the model link to download the model. Simple Epidemic Model - Vensim
Simple Epidemic Model - STELLA
Assumes the infected people never leave the system | | Infectious(t) = Infectious(t - dt) + (sick_per_day) * dt INIT Infectious = 1
Susceptible(t) = Susceptible(t - dt) + (- sick_per_day) * dt INIT Susceptible = 999 sick_per_day = Infectious*Susceptible*infection_rate infection_rate = .0015 | |
1. The simple epidemic model may be used to explore the impact of the infection rate variable on the healthy and infected populations. Change the infection rate and record the change in the output of the model. How does the shape of the s-shaped growth curve change? At what time does the model stabilize? Infection Rate Stabilization Time Shape of Curve 2. Exponential growth usually occurs when the rate of change is proportional to the amount present. Steady-state occurs when the system reaches equilibrium. Why does
By developing a computer model of the spread of an infectious disease, the student develops an understanding of the role of the infection rate and the removal rate on the spread of the disease. The Threshold Theorem of Epidemiology claims that the extent of spread of an epidemic can be predicted if three values are known: initial number of susceptible people (S(0)), the infection rate (K), and the removal rate (by quarantine or cure) (Q). The extent of the spread of the epidemic is indicated by the percentage of susceptible who become infected. Diseases that are easily transmitted spread quickly unless measures are taken to quarantine or cure infected people quickly. The three epidemic models below can each be used to experiment with various factors to see the impact on the populations. Vensim or STELLA software is needed to run the models. Right-click on the model link to download the model. Simple Epidemic Model - Vensim
Simple Epidemic Model - STELLA
Assumes the infected people never leave the system | | Infectious(t) = Infectious(t - dt) + (sick_per_day) * dt INIT Infectious = 1
Susceptible(t) = Susceptible(t - dt) + (- sick_per_day) * dt INIT Susceptible = 999 sick_per_day = Infectious*Susceptible*infection_rate infection_rate = .0015 | |
1. The simple epidemic model may be used to explore the impact of the infection rate variable on the healthy and infected populations. Change the infection rate and record the change in the output of the model. How does the shape of the s-shaped growth curve change? At what time does the model stabilize? Infection Rate Stabilization Time Shape of Curve 2. Exponential growth usually occurs when the rate of change is proportional to the amount present. Steady-state occurs when the system reaches equilibrium. Why does