Hi.
Using Excel you can find the models by linearizing de exponential models
Where y is the viral load at a time x, a is the initial vital load and r is the growth rate
This can be calculated using a model like:
and linarizing is you get:
to find Log a and Log b you use least squares regression.
a. We make the following table to find m and c for Patient 1
x days | P1 | Log(y) | x*Log(y) | x^2 | |
14 | 10081 | 4.003504 | 56.04905 | 196 | |
16 | 33612 | 4.526494 | 72.42391 | 256 | |
21 | 706640 | 5.849198 | 122.8332 | 441 | |
23 | 1097500 | 6.040405 | 138.9293 | 529 | |
∑ | 74 | 20.4196 | 390.2354 | 1422 |
For Patient 1 the model is:
Meaning that the initial viral load is 5.636
The growth rate is 0.718
And the doubling time can be calculated by:
We make the following table to find m and c for Patient 2
x days | P2 | Log(y) | x*Log(y) | x^2 | |
12 | 1353 | 3.131298 | 37.57557 | 144 | |
16 | 79232 | 4.898901 | 78.38241 | 256 | |
21 | 798550 | 5.902302 | 123.9483 | 441 | |
23 | 1680700 | 6.22549 | 143.1863 | 529 | |
∑ | 72 | 20.15799 | 383.0926 | 1370 |
For Patient 2 the model is:
Meaning that the initial viral load is 1.3 approx 6
The growth rate is 0.879
And the doubling time can be calculated by:
b. Using desmos graphing calculator to graph the models we get
c. From the graph you can see that even so the Patient 1 started with a higher initial viral load the growth rate is lower that for Patient 2, and with the over time patient 2 will eventually have a higher viral load because his initial viral load was lower but the growth rate was higher.
Note: i personally recomend that you get more meassurements, if you can twice a day, if you can get more data, you can have a more precise model to predict the behavior of the virus.
If you liked my answer please dont forget to give it a thumbs up, it would help me a lot. Best regards
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