During the review of our proposal for anresis funding the discussion of what cut-off values are the best to use for antibiotic resistance has come up. This seems to be a very sensitive issue for some "experts in the field", and Markus, Silvio and I agree that we have to address this more properly. As we will hopefully soon have more accurate automatically imported data on antibiotic resistance in Switzerland, our old system of using the one-third cut-offs will become somewhat obsolete (as these broad cut-offs admittedly only really make sense as long as we had to rely on inaccurate "default" data).
So my questions:
1. What do you think of using 10 different colours from green (for low prevalence of non-susceptibility) over orange (intermediate non-susceptibility) to red (high prevalence of non-susceptibility) in 10% steps? Or even 5% steps and 20 colours? The matrix would then look more like a heat map (which I personally quite like).
2. How would we solve the problem that default data only has 3 categories (as for some species there possibly isn't any better data even after automatic import from anresis) in a 10 or 20 category colour scheme? For example, we could either stop using default data at all (and treat the species without an automatic or manual number as "no data"), or assume each category to be a certain number (like 0%, 50% or 100% non-susceptible).
fxstr
commented
7 years ago 
During the review of our proposal for anresis funding the discussion of what cut-off values are the best to use for antibiotic resistance has come up. This seems to be a very sensitive issue for some "experts in the field", and Markus, Silvio and I agree that we have to address this more properly. As we will hopefully soon have more accurate automatically imported data on antibiotic resistance in Switzerland, our old system of using the one-third cut-offs will become somewhat obsolete (as these broad cut-offs admittedly only really make sense as long as we had to rely on inaccurate "default" data).
So my questions: 1. What do you think of using 10 different colours from green (for low prevalence of non-susceptibility) over orange (intermediate non-susceptibility) to red (high prevalence of non-susceptibility) in 10% steps? Or even 5% steps and 20 colours? The matrix would then look more like a heat map (which I personally quite like). 2. How would we solve the problem that default data only has 3 categories (as for some species there possibly isn't any better data even after automatic import from anresis) in a 10 or 20 category colour scheme? For example, we could either stop using default data at all (and treat the species without an automatic or manual number as "no data"), or assume each category to be a certain number (like 0%, 50% or 100% non-susceptible).