Solving for Infection Growth: A Guide with a Diff. Equation

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In summary, Qbert says that the solution to the differential equation is x(t)=Ae^{-kt}+150000, and that you can solve for t by taking the ln of both sides. Once you have these values, you can easily solve for what t yields 120000.
  • #1
TSN79
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The following diff.equation determines the number of people with a spesific illness:
[tex]
\frac{{dx}}{{dt}} = k\left( {150000 - x\left( t \right)} \right)
[/tex]
At t=0, 30000 people are infected, and at t=15, 60000. How long will it take for 120000 are infected? Here is my work:
[tex]
\begin{array}{l}
x\left( t \right) = 30000 \cdot e^{k \cdot t} \\
x\left( {15} \right) = 30000 \cdot e^{k \cdot 15} = 60000 \\
\Rightarrow k = 0,046 \\
x\left( t \right) = 30000 \cdot e^{0,046 \cdot t} = 120000 \\
\end{array}
[/tex]
Problem is that this leads to no good, the answer is supposed to be about t=72 (days), but I'm not sure how to implement the 150000 in the beginning (at least I think that's the prob)...anyone?
 
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  • #2
dx/dt = k*(p - x) has solutions of the form x = Aexp(-kt) + p,
not just x = A*exp(-k*t).
 
  • #3
Solving your DE will give an extra constant and you already had the constant k. You can determine the values of these two constants with x(0) = 30000 and x(15) = 60000. Are you sure of your solution of the DE?
 
  • #4
You mean am I sure it's supposed to be 72? That's just what it says in the back of the book that's all...
I just want to know where in my attempt I turned wrong...
 
  • #5
No, I'm talking about the solution of the differential equation.
 
  • #6
No, I'm not at all sure about my solution becasue I'm not taking the 150000 into effect since I don't know where or how to do so. How would you go about solving it?
 
  • #7
TSN79 said:
No, I'm not at all sure about my solution becasue I'm not taking the 150000 into effect since I don't know where or how to do so. How would you go about solving it?

TSN, as Qbert stated, the solution to the DE is:

[tex]x(t)=Ae^{-kt}+150000[/tex]

right?

You arrange it into the form:

[tex]x^{'}+kx=150000k[/tex]

obtain an integrating factor, integrate, done deal.

So you have two unknowns in the solution above, k and A, but you have two conditions:

x(0)=30000

x(15)=60000

Substituting the first condition into the equation yields:

[tex]30000=Ae^{-0k}+150000[/tex]

you can solve for A right?

now that you have A, substitute the second condition:

[tex]60000=Ae^{-15k}+150000[/tex]

That allows you to find k then. You know, rearrange, take the ln of both sides, solve for k.

Then once you have these values, you can easily solve for what t yields 120000:

[tex]120000=Ae^{-kt}+150000[/tex]

I bet you can do this.:smile:
 

What is a differential equation?

A differential equation is a mathematical equation that relates a function to its derivatives. In this context, it is used to model the growth of infections over time.

Why is it important to use a differential equation to solve for infection growth?

A differential equation allows us to model the complex and dynamic nature of infection growth, taking into account factors such as population size, contact rates, and recovery rates. This can provide more accurate predictions and aid in developing effective strategies for controlling the spread of infections.

What are the key variables and parameters in the differential equation for infection growth?

The key variables in the differential equation for infection growth are the number of infected individuals (I) and the number of susceptible individuals (S). The parameters include the contact rate (β), the recovery rate (γ), and the initial values of I and S.

How can we use the differential equation to make predictions about infection growth?

By solving the differential equation, we can obtain a mathematical expression for the relationship between the number of infected individuals and time. This can then be used to make predictions about the future growth of infections, as well as to analyze the effects of different control measures.

What are the limitations of using a differential equation to model infection growth?

A differential equation is based on certain assumptions and simplifications, and may not accurately capture all the complexities and uncertainties of infection growth. Additionally, the input parameters used in the equation may not always be known or may change over time, leading to potential inaccuracies in the predictions.

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