Wow very impressive data collection in South Korea. Here in the US, or specifically NY, I’m not aware of any datasets at that level of detail. All I’ve seen are tables for positive, negative, and pending tests (NYS and NYC), but probably because we’re still relatively behind on both the number of cases and our ability to test widely. Perhaps on the west coast where there are more cases and they’ve been facing this for longer, there might be more or better data
While working this past week, some questions have come up around the ever-changing guidelines and algorithms for testing, which may be hard to answer because it is more COVID specific than for viral illnesses in general.
–Given some of the limitations in our ability to test patients at scale (hopefully resolved by the study-a-thon but perhaps not), who should we test? Who is most likely to test positive? Of patients who come in with URI symptoms or pneumonia on CXR, which of these is caused by COVID?
–And related but more generalizable to other viral illnesses, of those who test positive, who is most likely to require hospitalization, supplemental oxygen, ICU stay, intubation, or die?
Basically, for patients with a viral illness (I might consider individual viruses–coronavirus, RSV, adeno, paraflu, flu, etc separately and then together), who is most likely to require those interventions or higher levels of care? Who is most likely to get a bacterial superinfection and/or pneumonia? [for resource utilization, level of care triage, admit or not. Existing pneumonia severity scores are also very old, can we build better risk prediction models?]