The lines going across in the second chart make it eslightly asier to eyeball the number for a point along the curve. The first chart doesn’t have this.
‘What does copies per mL mean?’*
Having the north and south plots together.**
*It might make more sense if you had, say, a plot of probable cases broken down by north and south, based on the data (as a guess). The obvious thing to connect cases to is population. (And maybe a sum showing ‘people who have had covid so far’[1] - this is more important if the risk of re-infection is lower, and that info is helpful for predicting spread falling at or below a certain level at a certain time (like ‘2 months from now, things will be better (if another strain doesn’t show up.’)
[1] Of course if people move around this is harder to tell. The actual number could be lower or higher.
**But for simplicity, combining both together into one chart might be more understandable.
Simpler approach: percentage/fraction breakdown of cases (including past, but people got better) to explain where the pandemic is at now. (Contact tracing wise—it might easier to tell a story if you could say stuff like
a) a lot of people got it at the grocery store on Tuesday
b) (maybe comparing to overall spread, and going through how it’s changed over time) - this person we know got it on this day at school, and there’s a lot of people at school which is why cases went up
Of course it might not be possible to break things down that finely, and you might not know who you know who got it, and when, and want to share that.)
Things that might be confusing about the charts:
The lines going across in the second chart make it eslightly asier to eyeball the number for a point along the curve. The first chart doesn’t have this.
‘What does copies per mL mean?’*
Having the north and south plots together.**
*It might make more sense if you had, say, a plot of probable cases broken down by north and south, based on the data (as a guess). The obvious thing to connect cases to is population. (And maybe a sum showing ‘people who have had covid so far’[1] - this is more important if the risk of re-infection is lower, and that info is helpful for predicting spread falling at or below a certain level at a certain time (like ‘2 months from now, things will be better (if another strain doesn’t show up.’)
[1] Of course if people move around this is harder to tell. The actual number could be lower or higher.
**But for simplicity, combining both together into one chart might be more understandable.
Simpler approach: percentage/fraction breakdown of cases (including past, but people got better) to explain where the pandemic is at now. (Contact tracing wise—it might easier to tell a story if you could say stuff like
a) a lot of people got it at the grocery store on Tuesday
b) (maybe comparing to overall spread, and going through how it’s changed over time) - this person we know got it on this day at school, and there’s a lot of people at school which is why cases went up
Of course it might not be possible to break things down that finely, and you might not know who you know who got it, and when, and want to share that.)