Questions about Mitigation Interventions

[schaupets]

I have three questions about the behaviour of the Mitigation Interventions:

1: Overlapping Interventions
Per default, there are 2 interventions, with overlapping time

• 1. Intervention#1 20.march - 1.Sep = 50%
• 2. Intervention#2 29.march - 1.Sep = 60%

The interventions seem to be added somehow.
But simple addition of 50%+60% = 110% does not make sense!?
I can add a third intervention with 40% which also has an effect, but not equivalent to 100%

Question: how are the overlapping interventions added/merged/combined/used?

2: Intervention = 100%
An Intervention of 100% should immediately stop new infections.
The model does this, but has some strange effects in the timeline, which I do not understand:
Example for Germany:
Intervention from 1.July to 30.Sept = 100%

• a) The number of infecctious decreases to zero only after 4 Weeks, altough latencies+infectious = 3+3 days . So I would expect a much faster decline after 6 days.
• b) the number of ICU and Severly ill decreases even slower and are greater Zero still after 2 Month. With an hospital-stay = 3 days and ICU = 14 Days I would expect a decline to zero after about 3 weeks.

Question: What did I miss?

3: Interventions value for Effective-R0=1
My assumption for the algorithm is Effective-R0 = Average-R0 * (1- Intervention%)
To get an Effective-R0=1 for Germany this would require an
Intervention-R1 = 1 - 1/Average-R0 = 1 - 1/3.6 = 72.22% (ignoring seasonal variations)

With Effective-R0=1 the number of infectious should remains constant.
The model does behave like this.

Question: Is my algorithm "Intervention-R1 = 1 - 1/Average-R0" correct?

Related to all questions: Screenshot of my testing examples:

Thats what I found: https://covid19-scenarios.org/about
Transmission reduction: The tool allows one to explore temporal variation in the reduction of transmission by infection control measures

[AxiaTim]

Hi,

I had the same question as your first one. I found this in the Questions, discussions thread:

#18 (reply in thread)

an overlap of a 40% and 60% measure would results in a reduction of transmission by (1-0.4)*(1-0.6)