Cases & Testing

Cases & Tests

The graph below shows testing and cases on the same graph, with the scale for testing 10x cases. This means that when cases are higher than the testing line, it corresponds to positivity >10% and when the testing line is higher than cases, it corresponds to positivity <10%. I find this an easy way to see at a high level how cases and testing are moving in relation to each other.

Test Positivity

The graph below shows the 7-day aggregate test positivity for PCR and antigen testing by collection date, which avoids any issues from old test data being reported late. The most recent few days are excluded due to incomplete data. PCR testing often has higher positivity because it’s used less for screening and more for symptomatic patients, especially in hospitals. It also remains positive for up to 3 months after initial infection. Antigen tests are more commonly used for screening tests so include tests from more healthy, asymptomatic individuals.

The percentage of positive PCR tests by report date are shown in the graph below. I also include the 2-week % positive by lab collection date to this graph, in orange, so you can see how it tracks along with the 7-day aggregate of % positive by report date.

Case Epicurve by Age Group

The graph below shows age-based data for confirmed (PCR) COVID cases. Additional age-based data is available from GA DPH:

Antibody Testing

The graph below shows the 14-day aggregate test positivity for serology testing by report date. There are two types of antibody tests – S antibody tests will show positive after infection or vaccination, while N antibody tests show positive only after natural infection. I believe this includes both types of tests, so it is impossible to separate the effects of infections vs vaccination in the graph below.

Epicurve Changes Over Time

The graph below shows what the epicurve of confirmed (PCR) cases by onset looked like at the end of every week. See how the epicurve has changed over time to understand why it’s important to view the final weeks of the epicurve with caution. However, you can see that once it starts declining from the previous week, it indicates we’re past the peak.

Cases, Hospitalizations, & Deaths Among Healthcare Workers