Re: a test or experiment in epidemiology

[Ashish]

According to your program, it will take 32 days to end people around 7 billion.
Quite dangerous.

[bplus]

Didn't I post something here suggesting graphics and talking about people who survive the virus and build resistance and modelling something other than a nose dive into death and desolation?

Maybe I forgot to hit the post button.

OK now I checked, it's posted. I will work up a graphic to show what I mean.

[bplus]

Sorry for not getting back to you, I find my enthusiasm for Pandemic modeling anemic.

Plus could not think of good example to follow. I was thinking Predator Pray might kick in where too much success for Predator leads to starvation and death of that population, virus not quite the same, virus does not have 100% kill no where near that! In fact virus does not kill, it's the body's reaction to virus that is deadly specially when health is already compromised so the models have to consider sub groups of people at different health risks.

What I really dislike about the OP and follow up reply is that there is no accounting for immunity, everybody dies in that catastrophic model when in fact everyone mostly lives and gets some sort of immunity but also possible lung or other body damage.  eh! too complex.

[bplus]

Here is something interesting, Numberphile talking about disease modeling:

[bplus]

OK, I confess, I fudged numbers until the graphs matched the video :P

Code: QB64: [Select]

1. _TITLE "The Curve: Blue = Susceptible, Red Infected, Green = Neither S nor I"
2. ' Numberphile math model of disease spread
3. ' [youtube]https://www.youtube.com/watch?v=k6nLfCbAzgo[/youtube]
4.  
5. SCREEN _NEWIMAGE(1000, 400, 32)
6. DIM SHARED S, I, R, Trans, Recov, dt
7. Trans = 3.2
8. Recov = .23
9. maxT = 1
10. I = .01
11. S = 1 - I
12. dt = .01
13. WHILE t < 1000
14.     newS = S + dSdt
15.     newI = I + dIdt
16.     newR = R + dRdt
17.     PSET (t, 400 - 400 * newS), &HFF0000FF
18.     PSET (t, 400 - 400 * newI), &HFFFF0000
19.     PSET (t, 400 - 400 * newR), &HFF00BB00
20.     S = newS
21.     I = newI
22.     R = newR
23.     t = t + 1
24. WEND
25. SLEEP
26. FUNCTION dSdt ()
27.     dSdt = (-Trans * S * I) * dt
28. END FUNCTION
29. FUNCTION dIdt ()
30.     dIdt = (Trans * S * I - Recov * I) * dt
31. END FUNCTION
32. FUNCTION dRdt ()
33.     dRdt = (Recov * I) * dt
34. END FUNCTION
35.  

[bplus]

Man at my age I am still studying the curves!

Here is a model where the disease dies out leaving a portion of the population still susceptible! by lowering the transmission rate = Trans, I also increased dt = the time periods of snap shots lets say, because the model stretches out over time to play itself out.

Code: QB64: [Select]

1. _TITLE "The Curve: Blue = Susceptible, Red Infected, Green = Neither S nor I"
2. ' Numberphile math model of disease spread
3. ' [youtube]https://www.youtube.com/watch?v=k6nLfCbAzgo[/youtube]
4.  
5. SCREEN _NEWIMAGE(1000, 400, 32)
6. DIM SHARED S, I, R, Trans, Recov, dt
7. Trans = .9 ' Transmission Rate - this number is the one we might greatest control over
8. Recov = .23 ' Recovery Rate - mostly up to nature but medicines might speed up recovery rate
9. I = .001 ' Infected 1/1000 infected
10. S = 1 - I ' Susceptible to Infection
11. R = 0 'obvious at start none have recovered
12. dt = .02 ' as reduce Trans time periods 3.2 start dt at .01 increase dt time period because it drags out life of infection
13. WHILE t < 1000
14.     newS = S + dSdt
15.     newI = I + dIdt
16.     newR = R + dRdt
17.     PSET (t, 400 - 400 * newS), &HFF0000FF
18.     PSET (t, 400 - 400 * newI), &HFFFF0000
19.     PSET (t, 400 - 400 * newR), &HFF00BB00
20.     S = newS
21.     I = newI
22.     R = newR
23.     t = t + 1
24. WEND
25. SLEEP
26. FUNCTION dSdt ()
27.     dSdt = (-Trans * S * I) * dt
28. END FUNCTION
29. FUNCTION dIdt ()
30.     dIdt = (Trans * S * I - Recov * I) * dt
31. END FUNCTION
32. FUNCTION dRdt ()
33.     dRdt = (Recov * I) * dt
34. END FUNCTION
35.  

[bplus]

This one looks perfect for InForm, hope I am not too rusty, it worked great in JB.