Closed Inglezos closed 3 years ago
SIR-FV model needs the number of vaccinated people, but we do not have it. This is used for scenario analysis at this time. https://lisphilar.github.io/covid19-sir/usage_theoretical.html#Scenario-analysis-with-theoretical-data
SEWIR-F: we need to calculate rho1 and rho2 with case reports. (linelist). https://www.kaggle.com/lisphilar/covid-19-data-with-sir-model#SIR-F-with-exposed/waiting-cases
SIR-FV model needs the number of vaccinated people, but we do not have it. This is used for scenario analysis at this time. https://lisphilar.github.io/covid19-sir/usage_theoretical.html#Scenario-analysis-with-theoretical-data
SEWIR-F: we need to calculate rho1 and rho2 with case reports. (linelist). https://www.kaggle.com/lisphilar/covid-19-data-with-sir-model#SIR-F-with-exposed/waiting-cases
So essentially, the SIR-FV and SEWIR-F models cannot be used at all for the moment on actual data, because for SIR-FV we don't have any actual data on vaccinated people and for SEWIR-F we can't calculate these two parameters without proper linelist data?
Yes at this moment.
What is the advantage of SIR-X model? https://arxiv.org/abs/2002.07572 http://rocs.hu-berlin.de/corona/docs/forecast/model/
From what I know, the only advantage is that it adds an extra compartment X for the quarantined people. With this, we can have an overview of how the number of the quarantined people changes. The SIRX model can easily be extended to SIRF-X model (I had done that on April during my tests at that time, before abandoning the whole model because of the author note at http://rocs.hu-berlin.de/corona/docs/forecast/results_by_country/ )
I don't propose to use that SIRX model. What I propose is to consider including an X/quarantined compartment as an extension to the pre-existing SIRF model, as an extra feature perhaps.
It is difficult to use X/quarantined because we have no records of the number of quarantined cases/people. I suggest that we use quarantine rate as a factor (Sq, Wq, Iq) of rho parameter. Please refer to the Kaggle notebook. https://www.kaggle.com/lisphilar/covid-19-data-with-sir-model#Factors-of-model-parameters
If this implementation for quarantine factor is something relatively easy, okay yes, otherwise I think that we can close this issue and move on from SIRX idea completely. This is not very important for now. Maybe move on to #379 for other models examples?
Thank you, we will move forward to #379 and new issues.
Summary of question
Besides the SIRF model, the other models (SEIRF, SEWIR, SEWIRF, etc) models you mention, are indeed reliable and can be fully used without any problems? Are they fully functional, implemented and tested? Will you demonstrate them for specific countries scenarios in the notebook analysis soon? Did you have the time to investigate and integrate perhaps the SIRX model? -> http://rocs.hu-berlin.de/corona/docs/forecast/model/ https://github.com/michibo/COVID-19-JHU-CSSE-data-SIRX-evaluation https://nbviewer.jupyter.org/github/michibo/COVID-19-JHU-CSSE-data-SIRX-evaluation/tree/master/
Environment