GA COVID-19 Report December 25, 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

Probable Cases

Georgia counts cases that are reported using rapid antigen tests as “probable” cases rather than “confirmed” cases is they are not subsequently confirmed by a PCR test. These data have only become available as of 11/3. As of today, this represents 87551 cases not included in the total count, which would increase the total by about 16.3% increase. These visualizations show how the total case count would look if we incorporated that data.

Cumulative Hospitalizations

Cumulative Deaths

Probable Deaths

Georgia counts deaths that occur when a patient only has an antigen test, or when a patient has clear symptoms of COVID but no PCR is test is applied before death, as “probable deaths” rather than “confirmed deaths”. These data have only become available as of 11/3. As of today, this represents 975 deaths not included in the total count, which would increase the total by about 10.1% increase. These visualizations show how the total case count would look if we incorporated that data.

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 4202.57 and the standard deviation is 1481.07.

Hospitalizations

For today’s hospitalizations, the 30-day mean is 207.23 and the standard deviation is 108.77.

Deaths

For today’s deaths, the 30-day mean is 32.07 and the standard deviation is 18.29.

ICU Admissions

For today’s ICU Admissions, the 30-day mean is 26.33 and the standard deviation is 17.18.

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.

Correlations Between Testing and Cases

If we run a simple correlation between total number of tests and total number of cases, we get an initially persuasive graph. Note that this graph includes both antibody and molecular tests.

Correlations Between Testing and Deaths

Correlations Between Testing and Hospitalizations

Considering hospitalizations, we get this:

Correlations Between Cases and Hospitalization

Lastly, let’s look at the correlations between these indicators and cases themselves.

Correlations Between Cases and Deaths

Considering deaths, we get this:

Final Thoughts

What do we make of the information from these new graphs? I think there are a few takeaways. First, it’s safe to say that while the increase in testing does create an increased ability to detect cases, it is not the reason that cases are increasing; after all we’re seeing similar escalations in hospitalizations and deaths which couldn’t be caused by increased testing. Second, like with the correlations between new tests and new cases, we can see that there seem to be multiple groupings within this data, which likely reflect periods of escalated testing in response to increased cases and changes in how we treat patients diagnosed with COVID19. Ultimately the story we see here is much richer and more complex than those who want to blame pandemic numbers on testing are willing to acknowledge.

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.

Physical Distancing (Written 7/31/2020)

Today I want to talk briefly about social distancing. The guideline that’s been shared is to maintain 6 feet distance between people. Unfortunately, many people struggle with this. The struggles tend to fall into two areas.

  • If you could fall face forward — just straight face planting into the ground — and the other person could catch you, you’re too close.
  • If the person could hit you with a baseball bat without leaving where they’re standing, you’re too close.

On Reduced Testing (Written 8/30/2020)

I’d like to spend a little time today talking about a big problem both here in Georgia and elsewhere regarding information and attitudes about COVID19. As you may have recently seen in the AJC demand for COVID19 testing is down in Georgia. This is alarming, as Georgia has never really tested at levels sufficient to contain the virus, and the decrease will only worsen our ability to monitor and intervene. Decreased testing means more cases will not be detected, which will increase community spread and further distort our understanding of the outbreak. So let’s talk about why testing is going down, and what can be done about it.

On Underlying Conditions (Written 8/30/2020)

Yet further discouraging testing is people’s focus on the idea of underlying conditions. This has been particularly prevalent today, following news reports saying “94% of Covid-19 deaths had underlying medical conditions”. People are reading this and interpreting it to mean that only 6% of people who die from COVID would have survived if not for underlying conditions, and that the risk is wildly overblown.

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.