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Ideally, counties would report cases, deaths, and tests timeseries by assigning each count to the day the positive test was collected, or the day of death, as close in time as possible to the actual event.
Instead, many counties are assigning count to date reported, or the day they found out about the positive case, or death. This means we're looking at picture of when the county found out about things, vs. when they actually happened. This also means we can't in good faith aggregate counties that assign by date collected with the other counties.
So, we should indicate in our data feeds whether the county assigns by date reported, or date collected, perhaps by adding a field to each timeseries in our data model. When we address this, we probably want to also address other changes to the data model mentioned in #78
Below is a snapshot of each county's approach to timeseries data, July 6. 2020.
The text was updated successfully, but these errors were encountered:
Ideally, counties would report cases, deaths, and tests timeseries by assigning each count to the day the positive test was collected, or the day of death, as close in time as possible to the actual event.
Instead, many counties are assigning count to date reported, or the day they found out about the positive case, or death. This means we're looking at picture of when the county found out about things, vs. when they actually happened. This also means we can't in good faith aggregate counties that assign by date collected with the other counties.
So, we should indicate in our data feeds whether the county assigns by date reported, or date collected, perhaps by adding a field to each timeseries in our data model. When we address this, we probably want to also address other changes to the data model mentioned in #78
Below is a snapshot of each county's approach to timeseries data, July 6. 2020.
The text was updated successfully, but these errors were encountered: