Database Reference
In-Depth Information
OUTFLOWS:
GET SICK
=
CONTACT RATE * (CONTAGIOUS
+
SICK) * NON IMMUNE
{
Individuals per Time Period
}
SICK(t)
=
SICK(t
−
dt)
+
(STAY IN BED
−
RECOVER
−
DIE) * dt
INIT SICK
=
0
{
Individuals
}
INFLOWS:
STAY IN BED
=
CONTAGIOUS
{
Individuals per Time Period
}
OUTFLOWS:
RECOVER
=
.9*SICK
{
Individuals per Time Period
}
DIE
=
.1*SICK
{
Individuals per Time Period
}
CONTACT RATE
=
RANDOM(.000001,.000003)
{
1/(Number of Contagious
+
Sick) * Nonimmune) per Time Period
}
Recall that the three major aspects of any model for which reality is claimed
should have feedback, randomness, and delays. Our model now has all of these as-
pects: feedback from the CONTAGIOUS to GETTING SICK, randomness in the
CONTACT RATE, and delays in STAYING IN BED and RECOVERING. The use
of stocks for CONTAGIOUS and SICK provide automatic one-week delays in each
of these stocks since the outflows are divided by one; to increase this type of de-
lay, we could divide these outflows by larger numbers. We could also change these
stocks into conveyors as we did in Chapter 1.
2.3 Loss of Immunity
How will the dynamics of our epidemic change if people lose immunity? Let us
assume for the model of Section 2.1 above that in any given week, 10 percent of the
immune population loses their immunity. All other assumptions are as before. The
corresponding model is shown in Figure 2.4.
NON IMMUNE
CONTAGIOUS
GET SICK
BIRTHS
STAY IN BED
LOSE IMMUNITY
CONTACT RATE
RECOVER
DIE
IMMUNE
SICK
Fig. 2.4
