For each of the Scenarios above, determine when half the population (y = 0.5) has been infected

Task 5: For each of the Scenarios above, determine when half the population (y = 0.5) has

been infected, and estimate when 80% of the vulnerable population has “caught” that strain. It

may be a lot of days, it may be quicker.

Scenario 1: Let’s assume that k = .0075 and that on Day Zero, there are an estimated 10,000

infected people out of a vulnerable population of 250,000,000

Scenario 2. Another strain of the flu is more virulent, with double the value of k. Let’s also

assume 10,000 people have been infected by Day Zero (same vulnerable population).

Scenario 3. Strain 3 is in its second year in the US, so it is estimated that 250,000 people have

had that variant. Let us also assume that it was slightly less virulent than the first strain, so that

k = .005.

Task 6: Using the three Scenarios, compare the impact of the different k values, and

compare the impact of different y 0 values you derive. Which factor seems more important—the

size of the initial population, or the virulence?

Task 7: Assume you start with an initial population of 100,000 infectees. Estimate what

value of k will result in 50% of the population being infected as of Day 270. If you calculate it

precisely using your logistic function, more power (and points) to you.

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