I was presuming that we (and many other readers) are already familiar with such simplistic models.
I don’t know why you are asking me to do calculations using them when my post explicitly notes some of the errors in the assumptions of such models, and how the actual spread of infectious diseases does not follow such models as scale increases.
Let’s assume there were many COVID mutated variants. What is the best model for the average of the spreading path of all those mutations? It is the SIR model, as it has less dependency. More “accurate” models have more assumptions, hypothesis and depended conditions, which are not reliable. In brief, any other models looks more or less like the result of the SIR model. The difference cancels out.
Another reason is, all extra dependent hypothesis will be explored equally at an earlier stage of a research topic. In brief, most trash papers compete each other at the earlier stage and only after some time, a dominate theory/model will be established. The competition process actually is very similar as the process of virus evolution. At the earlier stage, there is no reason to assume a dominate new model yet. Thus, no heterogenous should be assumed.
There is no reason to assume heterogeneous, as the COVID is so new and the information/knowledge about its mutation direction is very shallow till now.
Please do some simple calculation by using the SIR model. https://en.wikipedia.org/wiki/Compartmental_models_in_epidemiology
I was presuming that we (and many other readers) are already familiar with such simplistic models.
I don’t know why you are asking me to do calculations using them when my post explicitly notes some of the errors in the assumptions of such models, and how the actual spread of infectious diseases does not follow such models as scale increases.
Let’s assume there were many COVID mutated variants. What is the best model for the average of the spreading path of all those mutations? It is the SIR model, as it has less dependency. More “accurate” models have more assumptions, hypothesis and depended conditions, which are not reliable. In brief, any other models looks more or less like the result of the SIR model. The difference cancels out.
That’s a strong claim. Do you have any evidence for it?
Another reason is, all extra dependent hypothesis will be explored equally at an earlier stage of a research topic. In brief, most trash papers compete each other at the earlier stage and only after some time, a dominate theory/model will be established. The competition process actually is very similar as the process of virus evolution. At the earlier stage, there is no reason to assume a dominate new model yet. Thus, no heterogenous should be assumed.
There is no reason to assume heterogeneous, as the COVID is so new and the information/knowledge about its mutation direction is very shallow till now.
“the chance of contracting disease at all compared with those who are not vaccinated (~40-70% for Delta, reduced to maybe ~10-30% for Omicron);”
Do you have a link to the peer review papers about the above item?