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Integrate Dawei's confirmed projection #87

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xunhuang opened this issue Apr 25, 2020 · 0 comments

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xunhuang commented Apr 25, 2020

https://drive.google.com/open?id=1vgNrDkDjvCM-kUoeq3MpZJE9k3T3-tCW

Please check the attached python scripts for the model and an example how it is being used. Here is the rough procedures:

Find the following information:
the_R0 = 2.4
the_positve_rate = 0.19
google_mobilitiy_report_peak_reduction = 0.55
days_to_stay_at_home = 14
stay_at_home_ramp_up_days = 35
the_siki = [0, google_mobilitiy_report_peak_reduction]
the_siki_days = [days_to_stay_at_home, stay_at_home_ramp_up_days]
the_population = 327000000
the_family_size = 3.14 # Minimum 1, USA 3.14
Then fit the model with reported cases to identify:
E0
I0
detect_rate
detect_rate_rampup_days

The above fitting needs to be run only once. After that, you just need to run once a day to normalize E0 and I0.

Then run the model with boundary siki and plot the daily cases and cumulative daily cases.

Let me know if you have any questions.

Best,

Dawei

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