Problem with the logistic function

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Homework Help Overview

The discussion revolves around a problem involving the logistic function in the context of modeling the spread of an epidemic among a native population of Hawaiians. The original poster presents a scenario where a sailor introduces measles to a population of 5000, leading to confusion regarding the correct formulation of the logistic model and the relationship between infection rate and growth constant.

Discussion Character

  • Exploratory, Conceptual clarification, Assumption checking

Approaches and Questions Raised

  • Participants explore the formulation of the logistic equation and question the assumptions regarding the infection rate and growth constant. There is a discussion about how to derive the number of uninfected individuals from the number of infected, as well as confusion over the correct interpretation of the parameters in the logistic model.

Discussion Status

Participants are actively engaging with the problem, raising questions about the relationship between infection rate and growth rate. Some have offered insights into potential misunderstandings, while others are seeking clarification on the definitions and relationships involved in the model.

Contextual Notes

There is a noted lack of clarity in the textbook regarding the relationship between the infection rate and the growth constant, which has contributed to the confusion among participants. The original poster is studying independently and has expressed difficulty in finding answers within the provided materials.

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Homework Statement



The native Hawaiians lived for centuries in isolation from other peoples. When foreigners finally came to the islands they brought with them diseases such as measles, whooping cough, and smallpox, which decimated the population. Suppose such an island has a native population of 5000, and a sailor from a visiting ship introduces measles, which has an infection rate of 0.00005. Also suppose that the model for spread of an epidemic described in Example 3* applies.

a. Write an equation for the number of natives who remain uninfected. Let t represent time in days.

Homework Equations



*The model for spread of an epidemic described in Example 3: \frac{dy}{dt}=k(1-y/N)y

Where in modeling population growth y is the population, k is a growth constant, and N is the carrying capacity.

The Attempt at a Solution



Okay, so the general solution to this differential equation is:

y=\frac{N}{1+be^{-kt}}

where b=\frac{N-y_{0}}{y_{0}}

(y_{0} is the initial population size).

If we apply this model to the current problem, y could represent the number of people affected. Therefore, the number of people unaffected is x=N-y. Solving for x:

N-\frac{N}{1+be^{-kt}}

Setting y_{0}=1 (since there is one affected individual initially), the solution of the above equation is:

x=\frac{24955000}{4999+e^{0.00005t}}

Now, I thought I had solved the problem, but when I looked at the correct answer, it was:

x=\frac{24955000}{4999+e^{0.25t}}

I checked several times if I made a mistake anywhere in my calculations, but I couldn't find it (not that it's still not possible I keep missing something obvious; hopefully you guys will help me spot it if so).

I went back to the chapter where the logistic function was introduced for the first time and there it said (right after the general solution was given):

"This function was introduced in Section 4.4 on Derivatives of Exponential Functions in the form:

G(t)=\frac{m}{1+(m/G_{0})e^{-kmt}}

where m is the limiting value of the population, G_{0} is the initial number present, and k is a positive constant."

First of all, I can't see how this equation follows from N-\frac{N}{1+be^{-kt}} (or how the latter could be rewritten in this form. But second, I tried using it and still couldn't get the correct answer. I decided to go back to the chapter where this second form was first introduced and I found the following:

G(t)=\frac{m}{1+(m/G_{0}-1)e^{-kmt}}

Which is different from the one above it (there is an extra negative one in the denominator). This is all very confusing. First of all, is this a just a typo (that is, they just missed writing the negative in the first equation I wrote above) or am I missing something? Second, when I now plug in m and G_{0}, I do get the correct response. And the reason is, there is an extra m at the exponent of the e term. Where did it come from? I keep solving and resolving the differential equation \frac{dy}{dt}=k(1-y/N)y and simply can't get to this general solution.

I am very confused and have been stuck on this problem. Any input will be appreciated.
 
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You are assuming that the "infection rate", 0.00005, is the same as the "growth constant", k. Is that true? Also, I believe, in the equation you give, y is the number of infected persons while your question asks you ton "Write an equation for the number of natives who remain uninfected".
 
No, I did solve for the uninfected, as I subtracted the number of infected from 5000 (which is the total population).

It is true that I'm assuming infection rate to be the same as the growth constant. Is this a mistake? Perhaps this is where the problem's coming from? Could you explain?
 
Sorry to bump this but could anybody explain the relationship between the infection rate and the growth rate (in this the growth of the number of infected people)? Are we supposed to multiply the carrying capacity with the infection rate to get the growth rate? This doesn't make any immediate sense to me, but it would lead to the correct answer. If that's indeed what must be done, can anybody explain the logic behind it?
 
la6ki said:
Sorry to bump this but could anybody explain the relationship between the infection rate and the growth rate (in this the growth of the number of infected people)? Are we supposed to multiply the carrying capacity with the infection rate to get the growth rate? This doesn't make any immediate sense to me, but it would lead to the correct answer. If that's indeed what must be done, can anybody explain the logic behind it?

I would venture the guess that since YOU are taking the course in which these concepts appear, you will know better than any of us what is meant by the terms. Is it in your textbook? Is it in your course notes? If not, can you ask your instructor for clarification? Then, there is always Google: a search under 'epidemic models' turns up lots of hits.


RGV
 
I'm not taking any course, I'm just studying on my own. And I was stuck on this problem for a few hours (reading the chapters of the book very carefully) but couldn't find the answer to the question.
 
la6ki said:
I'm not taking any course, I'm just studying on my own. And I was stuck on this problem for a few hours (reading the chapters of the book very carefully) but couldn't find the answer to the question.

Well, the ".25" in the exponent given as the answer is 5000 times the 0.00005 that you used. As I see it (not being expert in epidemiology), the 0.00005 is a kind of "transmission" probability per contact, so if the population is 5000 there are 5000 potential contacts, hence a 5000 times larger probability of infecting somebody.

RGV
 
Yeah, I guess it could be that, it does make sense. The strange thing is that it doesn't seem obvious, yet there is no word on this in the book where this problem was for.

Thanks for the responses though!
 

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