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Hi,
Hope you are all well. I am wondering if it is possible to ask turtles to change a turtle-owned value as a link-owned value changes?
Much thanks!
Hei
16/10/2021 午後3:15、Pradeesh Kumar K V <prade...@gmail.com>のメール:
Hi,
You cannot arrive at a specific value from the model. The ability of virus to infect depends on many factors in the model like the network structure, the number of nodes and connectivity, recovery-chance etc. Moving the virus-spread-chance with other factors kept constant provides an idea of its effect on virus spread.
The best way to utilize the model is (in my opinion) to set particular value for the selected factor, mentally figure out what will happen, simulate the model and then compare the results with what you thought would happen. If there is a mismatch, you will gain insight on the impact of factor(s) on virus spread. Repeat this by increasing / decreasing factor values.
Hope this helps.
Best,
Pradeesh
On Wed, Oct 13, 2021 at 12:53 PM Alla <chocolat...@gmail.com> wrote:
Could anyone help me with these questions on the Virus on a Network model from the model library? I really just want to understand this model and I have a few ideas already but I am unsure if I'm right.
<Screen Shot 2021-10-13 at 8.18.17 PM.png>
When setting gain-resistance to 0, I noticed that if VIRUS-SPREAD-CHANCE is below 1.6% approximately, the virus will still die out. However I'm not sure if that's the exact percentage. Could anyone help me out with these questions?
Thank you!--
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16/10/2021 午後3:15、Pradeesh Kumar K V <prade...@gmail.com>のメール:
Hi,
You cannot arrive at a specific value from the model. The ability of virus to infect depends on many factors in the model like the network structure, the number of nodes and connectivity, recovery-chance etc. Moving the virus-spread-chance with other factors kept constant provides an idea of its effect on virus spread.
The best way to utilize the model is (in my opinion) to set particular value for the selected factor, mentally figure out what will happen, simulate the model and then compare the results with what you thought would happen. If there is a mismatch, you will gain insight on the impact of factor(s) on virus spread. Repeat this by increasing / decreasing factor values.
Hope this helps.
Best,
Pradeesh
On Wed, Oct 13, 2021 at 12:53 PM Alla <chocolat...@gmail.com> wrote:
Could anyone help me with these questions on the Virus on a Network model from the model library? I really just want to understand this model and I have a few ideas already but I am unsure if I'm right.
<Screen Shot 2021-10-13 at 8.18.17 PM.png>
When setting gain-resistance to 0, I noticed that if VIRUS-SPREAD-CHANCE is below 1.6% approximately, the virus will still die out. However I'm not sure if that's the exact percentage. Could anyone help me out with these questions?
Thank you!--
You received this message because you are subscribed to the Google Groups "netlogo-users" group.
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