 Consider the epidemic model with vaccination
S˙ = µN − βS I
N
− (µ + φ) S
˙I = βS I
N
− (µ + γ) I
V˙ = γI + φS − µV,
where S, I and V are the susceptible, infected and vaccinated populations respectively.
9
(a) Define the parameters µ, φ and γ.
(b) Show that this is a constant population model

(a) **Defining the Parameters:**

- **µ (Mu)**: This is the *birth and death rate* in the population. It represents the per capita rate at which individuals are born into the population and die from natural causes. It's assumed to be constant across all groups (susceptible, infected, and vaccinated).
  
- **φ (Phi)**: This is the *vaccination rate*. It represents the rate at which susceptible individuals (S) are vaccinated and move into the vaccinated class (V).

- **γ (Gamma)**: This is the *recovery rate*. It represents the rate at which infected individuals (I) recover and move into the vaccinated class (V).

---

(b) **Proving that this is a Constant Population Model:**

In a constant population model, the total population \( N \) remains unchanged over time, meaning the sum of the susceptible (S), infected (I), and vaccinated (V) populations should remain constant.

The total population \( N \) is given by:
\[
N = S + I + V
\]

Now, to show that the population is constant, we differentiate \( N \) with respect to time:
\[
\dot{N} = \frac{d}{dt}(S + I + V) = \dot{S} + \dot{I} + \dot{V}
\]

Substituting the given equations for \( \dot{S} \), \( \dot{I} \), and \( \dot{V} \):

\[
\dot{S} = \mu N - \frac{\beta S I}{N} - (\mu + \phi) S
\]
\[
\dot{I} = \frac{\beta S I}{N} - (\mu + \gamma) I
\]
\[
\dot{V} = \gamma I + \phi S - \mu V
\]

Summing these, we get:
\[
\dot{N} = (\mu N - \frac{\beta S I}{N} - (\mu + \phi) S) + \left(\frac{\beta S I}{N} - (\mu + \gamma) I\right) + (\gamma I + \phi S - \mu V)
\]

Simplifying:
\[
\dot{N} = \mu N - \mu S - \mu I - \mu V
\]

Since \( N = S + I + V \), this simplifies to:
\[
\dot{N} = \mu N - \mu N = 0
\]

This shows that \( \dot{N} = 0 \), meaning the total population \( N \) remains constant over time.

Therefore, the model is a **constant population model**.

---

Would you like further details or have any questions?

Here are 5 related questions for deeper exploration:
1. What is the basic reproduction number \( R_0 \) in this epidemic model?
2. How does increasing the vaccination rate \( \phi \) affect the dynamics of the model?
3. How would you modify this model to include a death rate due to the disease?
4. Can this model predict herd immunity? If yes, how?
5. How would a time-dependent vaccination rate affect the model's dynamics?

**Tip:** In a constant population model, the total rate of entry into the population (births) equals the total rate of exit (natural death, recovery, or vaccination).

Consider the epidemic model with vaccination S˙ = µN − βS I / N − (µ + φ) S, ˙I = βS I / N − (µ + γ) I, V˙ = γI + φS − µV, where S, I, and V are the susceptible, infected, and vaccinated populations respectively. (a) Define the parameters µ, φ, and γ. (b) Show that this is a constant population model.

Explore an advanced epidemic model with vaccination, where susceptible, infected, and vaccinated populations interact. Learn how parameters like birth rate, vaccination rate, and recovery rate are defined, and see a detailed proof showing that this model describes a constant population. Suitable for advanced undergraduate students studying mathematical epidemiology.

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