Your modelling - how well does it match the actual data? Does it reproduce the actual data from the countries (China, Iran, Italy) furthest in the epidemic's lifetime correctly?
What does the terms moderate mitigation, weak mitigation, strong mitigation mean? What measures are required to go from none to weak, to moderate mitigation?
This is the next push for our modeling. We are trying to integrate live case count data to provide more accurate scenarios for people. Once we have that data we can try to fit a few parameters to improve predictions. I should note we are actively looking for people to help us curate data sources if you are interested!
I think the most intuitive explanation to your second question is a reduction of number of contacts you have per day - i.e. .6 corresponds to 60% reduction in social contacts in a given day. This is not exact but should provide you rough handrails for the mitigation numbers.
1) the parameters that don't fit with the already observed data should be visibly marked in a sense how much they are away from the observation. That's the most important use of the tool: to show which parameters simply don't match: for each parameter one should assume that others remain the same, then show how much that specific parameter has to be for the observations to match. If the parameter can't be any value with the rest unchanged to produce the observed output, it should be marked as n/a or whatever, otherwise the difference from the nearest possible should be shown.
2) you should allow longer time frame for the simulation (it should be possible to run it for e.g. 12 months).
Thank you very much for this, it's really great work.
Do you have a sense, or any benchmarks, for where the current responses across the world lie along the weak - strong mitigation scale? Or is that something we'll need to estimate using the model as the situation evolves more?
Not enough that I would feel confident publically stating. I think our best hope for accurate calibration would be to fit the data as it comes out (hence why we are focusing our efforts here) or to do a post-hoc analysis of a few examples, e.g. Wuhan vs South Korea. I'll note that mitigation effects will be best measured as a reduction in exponential growth.
What does the terms moderate mitigation, weak mitigation, strong mitigation mean? What measures are required to go from none to weak, to moderate mitigation?