GA COVID-19 Report July 22, 2020

Daily Summary & Notes

Today’s report uses the data from the 2:50PM Report from the GA Department of Public Health.

Data

Data Notes

Prior to 5/11, all data is taken from the noonish update from the GA Department of Public Health to present even time intervals between data points which is important for graph interpretation. On 5/11, reporting schedule shifts to being at 9AM, 1PM, and 7PM, so this report will capture to the 1PM reporting time. On June 2nd, reporting was reduced to once a day at 3PM. Data does reflect multiple inefficiencies and inaccuracies in the current reporting system, including showing tests before their results are returned, delays in reporting on weekends that create artificial spikes and valleys in change data. In general, interpretation should examine the general trends, and not focus exclusively on endpoint trajectories, which are highly influenceable by these data variations.

Cumulative Confirmed Cases

Cumulative Hospitalizations

Cumulative Deaths

Cumulative ICU Use

Change Patterns

Count Level Tracking

Z Score Fluctuations

Because percentage growth becomes misleading over time, I’ve added a floating 4-week Z-score visualization for each measure to help put into perspective the magnitude of daily variation in numbers.

New Cases

For today’s cases, the 30-day mean is 2879.13 and the standard deviation is 849.06.

Hospitalizations

For today’s hospitalizations, the 30-day mean is 198.97 and the standard deviation is 119.06.

Deaths

For today’s deaths, the 30-day mean is 22.9 and the standard deviation is 19.97.

ICU Admissions

For today’s ICU Admissions, the 30-day mean is 27.07 and the standard deviation is 16.92.

Testing

These graphs contain several markers that reflect the changing nature of the testing data that has been provided over time.

Cumulative Testing

Positive Tests by Source

Total Testing Trends

COVID19 Molecular Testing Trends

COVID19 Antibody Testing Trends

Is Increased Testing Causing Increased Cases?

A popular talking point recently is that the increase in cases that are being detected is not reflective of increased spread, but rather a result of increased testing. There is a certain logic to this — the more tests that are run the more potential cases we can identify. However, this can lead us to significant logical errors, and these in turn can lead to dangerous behaviors. While our data does not allow a perfect causal analysis, we can examine what associations between testing and cases exist in our data.

Commentaries

Is Herd Immunity A Viable Solution to COVID-19?

Comorbidity (Written 7/15/2020)

I think today is a good time to remind people about comorbidity risks. I often see people insist that they have no risk because “only people with pre-existing conditions get COVID”. While pre-existing conditions are associated with increased risk, this misses both that healthy people with no prior conditions get COVID, and that what’s counted as pre-existing conditions is pretty broad. The GA DPH website indicates that the following are considered comorbid conditions in COVID19 data reporting: Chronic Lung Disease, Diabetes Mellitus, Cardiovascular Disease, Chronic Renal Disease, Chronic Liver Disease, Immunocompromised Condition, Neurologic/Neurodevelopmental Condition, and Pregnancy. These are very prevalent conditions here in Georgia — Over 6.9% of adults have COPD or other lung disease, more than 1 in 10 Georgians have diabetes, and more than 1 in 3 Georgians have some sort of cardiovascular disease. I could pull stats fo r the other conditions listed, but the implication is clear — a large proportion of our citizens are at elevated risk. Most people likely either have one of these comorbidities, or are close to someone who does, and don’t recognize the risk.

Final Thoughts

As always, I am not trained in epidemiology, and defer to recognized experts in the field on all issues. These analyses and commentary are solely designed to help lay persons approach the publicly available data and larger public health conversations.

Documentation

Code and data available here. Analysis conducted using R.