Tag Archives: COVID-Like Illness

November Pandemic Perspective

18 Wednesday Nov 2020

Posted by in Coronavirus, Pandemic, Uncategorized

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I hope readers share my compulsion to see updated COVID numbers. It’s become a regular feature on this blog and will probably remain one until infections subside, vaccine or otherwise. Or maybe when people get used to the idea of living normally again in the presence of an endemic pathogen, as they have with many other pathogens and myriad risks of greater proportions, and as they should. That might require more court challenges, political changes, and plain old civil disobedience.

So here, then, is an update on the U.S. COVID numbers released over the past few days. The charts below are attributable to Don Wolt (@tlowdon on Twitter).

First, reported deaths began to creep up again in the latter half of October and have escalated in November. They’ve now reached the highs of the mid-summer wave in the south, but this time the outbreak is concentrated in the midwest and especially the upper midwest.

Reported deaths are the basis of claims that we are seeing 1,500 people dying every day, which is an obvious exaggeration. There have been recent days when reported deaths exceeded that level, but the weekly average of reported deaths is now between 1,100 and 1,200 a day.

It’s important to understand that deaths reported in a given week actually occurred earlier, sometimes eight or more weeks before the week in which they are reported. Most occur within three weeks of reporting, but sometimes the numbers added from four-plus weeks earlier are significant.

The following chart reproduces weekly reported deaths from above using blue bars, ending with the week of November 14th. Deaths by actual date-of-death (DOD) are shown by the orange bars. The most recent three-plus weeks always show less than complete counts of deaths by DOD. But going back to mid-October, actual weekly deaths were running below reported deaths. If the pattern were to follow the upswings of the first two waves of infections, then actual weekly deaths would exceed reported deaths by perhaps the end of October. However, it’s doubtful that will occur, in part because we’ve made substantial progress since the spring and summer in treating the disease.

To reinforce the last point, it’s helpful to view deaths relative to COVID case counts. Deaths by DOD are plotted below by the orange line using the scale on the right-hand vertical axis. New positive tests are represented by the solid blue line, using the left-hand axis, along with COVID hospitalizations. There is no question that the relationship between cases, hospitalizations, and deaths has weakened over time. My suspicions were aroused somewhat by the noticeable compression of the right axis for deaths relative to the two charts above, but on reviewing the actual patterns (peak relative to troughs) in those charts, I’m satisfied that the relationships have indeed “decoupled”, as Wolt puts it.

Cases are going through the roof, but there is strong evidence that a large share of these cases are false positives. COVID hospitalizations are up as well, but their apparent co-movement with new cases appears to be dampening with successive waves of the virus. That’s at least partly a consequence of the low number of tests early in the pandemic.

So where is this going? The next chart again shows COVID deaths by DOD using orange bars. Wolt has concluded, and I have reported here, that the single-best short-term predictor of COVID deaths by DOD is the percentage of emergency room visits at which patients presented symptoms of either COVID-like illness (CLI) or influenza-like illness (ILI). The sum of these percentages, CLI + ILI, is shown below by the dark blue line, but the values are shifted forward by three weeks to better align with deaths. This suggests that actual COVID deaths by DOD will be somewhere around 7,000 a week by the end of November, or about 1,000 a day. Beyond that time, the path will depend on a number of factors, including the weather, prevalence and immunity levels, and changes in mobility.

I am highly skeptical that lockdowns have any independent effect in knocking down the virus, though interventionists will try to take credit if the wave happens to subside soon for any other reason. They won’t take credit for the grim lockdown deaths reaped by their policies.

Despite the bleak prospect of 1,000 or more COVID-attributed deaths a day by the end of November, the way in which these deaths are counted is suspect. Early in the pandemic, the CDC significantly altered guidelines for the completion of death certificates for COVID such that deaths are often improperly attributed to the virus. Some COVID deaths stem from false-positive PCR tests, and again, almost since the beginning of the pandemic, hospitals were given a financial incentive to classify inpatients as COVID-infected.

It’s also important to remember that while any true COVID fatality is premature, they are generally not even close to the prematurity of lockdown deaths. That’s a simple consequence of the age profile of COVID deaths, which indicate relatively few life-years lost, and the preponderance of co-morbidities among COVID fatalities.

Again, COVId deaths are bad enough, but we are seeing an unacceptable and ongoing level of lockdown deaths. This is now to the point where they may account for almost all of the continuing excess deaths, even with the fall COVID wave. It’s probable that public health would be better served with reduced emphasis on COVID-mitigation for the general population and more intense focus on protecting the vulnerable, including the distribution of vaccines.

Predicted November COVID Deaths

08 Sunday Nov 2020

Posted by in Pandemic, Public Health

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Reported COVID deaths do not reflect deaths that actually occurred in the reporting day or week, as I’ve noted several times. Here is a nice chart from @tlowdon on Twitter showing the difference between reported deaths and actual deaths for corresponding weeks. The blue bars are weekly deaths reported by the COVID Tracking Project. The solid orange bars are the CDC’s “provisional” deaths by actual week of death, which is less than complete for recent weeks because of lags in reporting. Still, it’s easy to see that reported deaths have overstated actual deaths each week since late August.

I should note that the orange bars represent deaths that involved COVID-19, though a COVID infection might not have actually killed them. This CDC report, updated on November 4th, shows the importance of co-morbidities, which in many cases are the actual cause of death according to pre-COVID, CDC guidance on death certificates.

Leading Indicators

Researchers have studied several measures in an effort to find leading indicators of COVID deaths. The list includes new cases diagnosed (PCR positivity) and the percentage of emergency room visits presenting symptoms of COVID-like illness (%CLI). These indicators are usually evaluated after shifting them in time by a few weeks in order to observe correlations with COVID deaths a few weeks later. Interestingly, @tlowdon reports that the best single predictor of actual COVID deaths over the course of a few weeks is the sum of the %CLI and the percentage of ER patients presenting symptoms of influenza-like illness (%ILI). Perhaps adding %ILI to %CLI strengthens the correlation because the symptoms of the flu and COVID are often mistaken for one another.

The chart below reproduces the orange bars from above representing deaths at actual dates of death. Also plotted are the %Positivity from COVID tests (shifted forward 2 weeks), %CLI (3 weeks), the %ILI (3 weeks), and the sum of %CLI and %ILI (3 weeks, the solid blue line). My guess is that %ILI contributes to the correlation with deaths mainly because %ILI’s early peak (which occurred in March) led the peak in deaths in April. Otherwise, there is very little variation in %ILI. That might change with the current onset of the flu season, but as I noted in my last post, the flu has been very subdued since last winter.

What About November?

So where does that leave us? The chart above ends with our leading indicator, CLI + ILI, brought forward from the first half of October. What’s happened to CLI + ILI since then? And what does that tell us to expect in November? The chart below is from the CDC’s web site. The red line is %CLI and the yellow line is %ILI. The sum of the two isn’t shown. However, there is no denying the upward trend in CLI, though the slope of CLI + ILI would be more moderate.

As of 10/31, CLI + ILI has increased by almost 40% since it’s low in early October. If the previous relationship holds up, that implies an increase of almost 40% in actual weekly COVID deaths from about 4,000 per week to about 5,500 per week by November 21 (a little less than 800 per day).

FiveThirtyEight has a compilation of 13 different forecast models with projections of deaths by the end of November. The estimate of 5,500 per week by November 21, or perhaps slightly less per week over the full month of November, would put total COVID deaths at the top of the range of the MIT, UCLA, Iowa State, and University of Texas models, but below or near the low end of ranges for eight other models. However, those models are based on reported deaths, so the comparison is not strictly valid. Reported deaths are still likely to exceed actual deaths by the end of November, and the actual death prediction would be squarely in the range of multiple reported death predictions. That reinforces the expectation an upward trend in actual deaths.

Third Wave States

States in the upper Midwest and upper Mountain regions have had the largest increases in cases per capita over the past few weeks. Using state abbreviations, the top ten are ND, SD, WI, IA, MT, NE, WY, UT, IL, and MN, with ID at #11 (according to the CDC’s COVID Data Tracker). One factor that might mediate the increase in cases, and ultimately deaths, is the possibility of early herd immunity: in the earlier COVID waves, the increase in infections abated once seroprevalence (the share of the population with antibodies from exposure) reached a level of 15% to 25%.

Unfortunately, estimates of seroprevalence by state are very imprecise. Thus far, reliable samples have been limited to states and metro areas that had heavy infections in the first and second waves. One rule of thumb, however, is that seroprevalence is probably less than 10x the cumulative share of a population having tested positive. To be very conservative, let’s assume a seroprevalence of four times cumulative cases. On that basis, half the states in the “top ten” listed above would already have seroprevalence above 15%. Those states are ND, SD, WI, IA, and NE. The others are mostly in a range of 12% to 15%, with MI coming in the lowest at about 9%.

This gives some cause for optimism that the wave in these states and others will abate fairly soon, but there are a number of uncertainties: first, the estimates of seroprevalence above, while conservative, are very imprecise, as noted above; second, the point at which herd immunity might cause the increase in new cases to begin declining is real guesswork (though we might have confirmation in a few states before long); third, we are now well into the fall season, with lower temperatures, lower humidity, less direct sunlight, and diminishing vitamin D levels. We do not have experience with COVID at this time of year, so we don’t know whether the patterns observed earlier in the year will be repeated. If so, new cases might begin to abate in some areas in November, but that probably wouldn’t be reflected in deaths until sometime in December. And if the flu comes back with a corresponding increase in CLI + ILI, then we’d expect further increases in actual deaths attributed to COVID. That is only a possibility given the weakness in flu numbers in 2020, however.

Closing Thoughts

I was excessively optimistic about the course of the pandemic in the U.S. in the spring. While this post has been moderately pessimistic, I believe there are reasons to expect fewer deaths than previous relationships would predict. We are far better at treating COVID now, and the vulnerable are taking precautions that have reduced their incidence of infections relative to younger and healthier cohorts. So if anything, I think the forecasts above will err on the high side.

Evidence of Fading COVID Summer Surge

16 Sunday Aug 2020

Posted by in Pandemic

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Lately I’ve talked a lot about reported deaths each week versus deaths by actual date of death (DOD). Much of that information came from Kyle Lamb’s Twitter account, and he’s the source of the charts below as well. The first one provides a convenient summary of the data reported through last week. The blue bars are reported deaths each week from the COVID Tracking Project (CTP), which are an aggregation of deaths that actually occurred over previous weeks. Again, the blue bars do NOT represent deaths that occurred in the reporting week. The solid orange bars are “provisional” actual deaths by DOD. “Provisional” means that recent weeks are not complete, though most deaths by DOD are captured within three to four weeks. The CDC also produces a “forecast” of final death counts by DOD, shown by the hatched orange bars.   

Note that the recent surge in deaths has been much smaller than the one in the spring, which was driven by deaths in the northeast. The CDC “expects” actual deaths by DOD to have declined starting after the week of July 23rd. However, CTP was still reporting deaths of over 1,000 per day last week. The actual timing of those deaths in prior weeks, and the ultimate extent of the summer surge in COVID deaths, remains to be seen.

Certain leading indicators of deaths are signaling declines in actual deaths in August. Two of those indicators are 1) the positivity rate on standard PCR tests for infections; and 2) the share of emergency room visits made for symptoms of “COVID Like Illness” (CLI). The charts below show those indicators for FEMA regions that had the largest uptrends in cases in June and July. Florida is part of Region 4, shown in the next chart:

Here is the Region 6, which includes Texas:

Finally, Region 8 includes Arizona and California:

Out of personal interest, I’m also throwing in Region 7 with a few midwestern states, where cases have risen but not to the levels reached in Regions 4, 6, and 8:

With the exception of the last chart, the clear pattern is a peak or plateau in the positivity rate in late June through late July, followed by declines in subsequent weeks. The share or ER visits for CLI was not quite coincident with the positivity rate, but close. The decline in the CLI share is evident in Regions 4, 6 and 8. Again, these three regions include states that drove the nationwide increase in cases this summer (AZ, CA, FL, and TX), and the surge appears to have maxed out.     

Here is a chart showing the share of CLI visits to ERs for all ten FEMA region from mid-June through last week. Clearly, this measure is improving across the U.S.

Nationwide, the CLI percentage at ERs has decreased by about 47% over the past four weeks, and the positivity rate has decreased by about 28% in that time. In addition to these favorable trends, COVID hospitalizations have decreased by about 40% over the past three weeks. All of these trends bode well for a downturn in COVID-attributed deaths.

The summertime surge in the virus was not nearly as ravaging as in the spring, and it appears to be fading. We’ll await developments in the fall, but we’ve come a long way in terms of protecting the vulnerable, treating the infected, approaching herd immunity thresholds (which means reduced rates of transmission to susceptible individuals), and the real possibility that we can put the pandemic behind us.