The Calm Before the Storm

There are clear increases in traffic as well as full parking lots at building supply stores, grocery stores, and some department stores. Traffic has slowly been building and recently I see more and more cars in parking lots of businesses. I suspect that this is happening in other parts of the country as well. Of course, there is data to support that as well. The drop occurred around March 12, when many states started issuing orders to related to what has been commonly called “locking down,” although there isn’t a specific definition of what that means in any state. The impact of those orders is clear in the data.

The problem lies in that things are beginning to creep back toward baseline around the end of April as those restrictions are being lifted. There are a number of variables to consider to put together a timeline that relates policy changes to outcome.

A recent study in the Annals of Internal Medicine had some very important results with quoting. “There were 181 confirmed cases with identifiable exposure and symptom onset windows to estimate the incubation period of COVID-19. The median incubation period was estimated to be 5.1 days (95% CI, 4.5 to 5.8 days), and 97.5% of those who develop symptoms will do so within 11.5 days (CI, 8.2 to 15.6 days) of infection. These estimates imply that, under conservative assumptions, 101 out of every 10 000 cases (99th percentile, 482) will develop symptoms after 14 days of active monitoring or quarantine.”

About 19% of those who are infected will develop severe to critical disease. Dyspnea develops in about 5-8 days, which is a good marker for the need for hospital care, and a way to capture another point on the timeline. When combining that with symptom onset data, that means that the need for hospitalization may not start until 9-24 days after exposure.

The other important marker that gets capture in statistics is death. The average time reported from symptom onset to death or hospital discharge in one study of 191 patients is 21 days, and ranges from 17-25.

The main point is that there is about a three week lag for outcomes from policy decisions to start showing up in the data. Because of the time it takes for more spread to start or be stopped by policy, I would estimate that sufficient number to see significant impact don’t show up until 4-6 weeks after policy changes. That means that the loosening of restrictions when there still is inadequate testing, and therefore contact tracing, will mean that while we have flattened the curve, we are also only delaying it.

It should also be noted that the next curve will be much larger by comparison. That is because we will be starting with a much larger number of cases at the outset and more beds already filled in the hospitals. When dealing with a disease that is spread exponentially, starting a much higher initial volume has drastic impacts for successive generations of spread.

For illustration, think of how the growth would vary by simple doubling of the reproductive rate (R0=2) at two different starting points over five generations:

2, 4, 8, 16, 32
8, 16, 32, 64, 128

See the problem? Unfortunately, the it’s even far worse than this. The initial estimates of the R0 for COVID-19 were 2-2.5, so pretty close to what I illustrated in the numbers above. However, there is now evidence that the median R0 might be 5.7 meaning that this virus spreads even more rapidly that initially thought.

Turning to the raw data graphs I have used, there are a couple of points to make about the US.

1. The case fatality rate (CFR) seems to be stabilizing at about 6%.
2. While the number of cases is on a decline trend recently, it needs to be emphasized that this is related to lockdown and social distancing measures.

The problem lies in that many places around the US are either opening to early or selectively opening too early. I think that means that our case count will begin rising again within weeks.

There were a number of approaches to choose. I’ve already written about how a very relaxed approach like was done in Sweden is likely to be a mistake. New Zealand took a much more aggressive approach and appears to have had success, although time will tell for them as well. We had a chance to do something similar, but missed it.

I fear that we are in the biological eye of a Category 5 hurricane that is developing around us. When the eye wall hits, we are in for an awful ride.

STAY HOME