Tag Archives: COVID Time Series

COVID at Midsummer

04 Tuesday Aug 2020

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It’s been several weeks since I last posted on the state of the coronavirus pandemic (also see here). The charts below show seven-day moving averages of new confirmed cases and reported C19 deaths from the COVID Tracking Project as of August 3. Daily new cases began to flatten about three weeks ago and then turned down (it can take a few days for such changes to show up in a moving average). Daily C19-attributed deaths began climbing again in early July, lagging new cases by a few weeks, and they slowed just a bit over the past several days. Obviously, both are good news if those changes are maintained. The other thing to note is that deaths have remained far below their levels of April and early May.

The daily death count is that reported on each date, not when the deaths actually occurred. Each day’s report consists of deaths that were spread across several previous weeks or even a month or more. That makes the slight downturn in deaths more tenuous from a data perspective. There are sometimes large numbers of deaths from preceding weeks reported together on a single day, so reporting can be ragged and the final pattern of actual deaths is not known for some time. More on that below.

States

The increase in cases and deaths during late June and July was concentrated in four states: Arizona, California, Florida, and Texas. Here’s how those states look now in terms of cases and deaths, from the interactive COVID Time Series site:

 

New cases began to flatten or drop in these states two to three weeks ago, driving the change in the national data. Daily deaths have not turned convincingly, but again, these are reported deaths, which actually occurred over previous weeks. One more chart that is suggestive: current hospitalizations in these four states. The recent declines should bode well for the trend in reported deaths, but it remains to be seen. 

Meanwhile, other parts of the country have seen an uptrend in cases and deaths, such as Illinois, Missouri, South Carolina, and Tennessee. Here are new cases in those states:

It’s worth emphasizing that the elevated level of new cases this summer has not been associated with the rates of fatality experienced in the Northeast during the spring. There are many reasons: better patient care, new treatments, more direct summer sunlight, higher humidity, and tighter controls in nursing homes.

More On the Timing of Deaths

Back to the discrepancies in the timing of reported deaths and actual deaths. This is important because the reported totals each day and each week can be highly misleading, even to the point of frightening the public and policy makers, with consequent psychological and economic impacts.

The latest summary of provisional vs. reported deaths is shown below, courtesy of Kyle Lamb, who posts updates on his Twitter feed. This report ends with the last complete week ending August 1. It’s a little hard to read, but you might get a better look if you click on it or turn your phone sideways. Some of the key series are also graphed below. 

The table shows the actual timing of deaths in the fourth column, with dates alongside. The pattern differs from the statistics reported by the Covid Tracking Project (CTP) in the top row (shaded orange), and from the totals of actual deaths by reporting day in the third row (shaded gray). The reporting dates are always later than the dates of death. This can be seen in the chart below. The most obvious illustration is how many of the deaths from around the peak in mid-April were reported in May. In March and April, the daily reports were short of the ultimate actual death counts because so few deaths with associated dates were known by then.

 

The right-hand end of the red line shows that many deaths reported by CTP have not yet been placed at an actual date of death by the CDC.  At this point, the actual date of death has not been placed for over 10,000 deaths! Again, those will be spread over earlier weeks.

The blue line is dashed over the last four weeks because those counts are most “highly” provisional. Small changes in the actual counts are likely for dates even before that, but the last four weeks are subject to fairly substantial upward revisions. Eventually, the right end of the blue line will more closely approximate the totals shown in red.

To get an indication of trends in the actual timing of deaths, I plotted the weekly actual deaths reported for the last four reporting weeks going back in time. In the table, those are the four lowest, color-coded diagonals. In the graph below, which should include the qualifier “by recency of report week”, actual deaths in the most recent report week are represented by the blue line, the prior weekly report is red, followed by green (three weeks prior), and purple (four weeks prior… sorry, the colors are not consistent with those in the table). The lines extend farther to the right for more recent report weeks.

The increase in actual deaths occurring in July has declined or flattened in each of the four most recent report weeks. Only the second-to-last week increased as of the August 1st report. On the whole, those changes seem favorable, but we shall see.

Closing

It’s getting trite to say, but the next few weeks will be interesting. The increase in deaths in July was a sad development, but at least the extent of it appears to have been limited. Even with a somewhat higher death count, the fatality rate continued to decline. Let’s hope any further waves of infections are even less deadly.

Case Fatality, Stale Ratios and Exaggerated Loss

14 Tuesday Jul 2020

Posted by in Analytics, Pandemic

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I hope someday I won’t feel compelled to write or worry about the coronavirus. However, as the pandemic wears on, it seems to take only a few days for issues to pile up, and I just can’t resist comment. Today I have a couple of beefs with uses of data and concomitant statements I’ve seen posted of late.

People are still quoting case fatality rates (CFRs) as if those cumulative numbers are relevant to the number of deaths we can expect going forward. They are not. Just as hair-brained are applications of cumulative hospitalization and ICU admittance rates to produce “rough and ready” estimates of what to expect going forward. Or, I’ve seen people express hospitalizations as ratios to CFR, as if those ratios will be the same going forward. Again, they are not. Let me try to explain.

The chart below shows the course of the U.S. CFR since the start of the pandemic. It’s taken from the interactive Covid Time Series site. My apologies if you have to click on the chart for decent viewing (or you can visit the site). The CFR at any date is the cumulative number of deaths to-date divided by the cumulative number of confirmed cases. It is a summary of past history, but it is not well-suited to making predictions about death rates in the future. The CFR began to taper a little before Memorial Day, and it is now at about 4% (as of July 13).

Out of curiosity, I also generated CFRs for AZ, CA, FL, GA, and TX, which now average about half of the national CFR. There’s an obvious lesson: if you must use CFRs, understand that they vary from place to place.

Again, CFRs are cumulative. Their changes over time can tell us something about recent trends, but even then they are flawed. For example, case counts have risen dramatically with more widespread testing. Those testing positive more recently are concentrated in younger age cohorts, for whom infections are much less severe. Treatment has improved dramatically as well, so there is little reason to expect the CFR’s of recently diagnosed cases to be as high as the latest CFRs shown above.

There is no easy way to calculate an unflawed “marginal” CFR for a recent period, though an effort to do so might improve the predictive value. Deaths lag behind case counts because the progression from early symptoms to death can take several weeks. Even more vexing for constructing a valid, recent fatality rate is that reporting of deaths is itself delayed, as I explained in my last post. Each day’s report of deaths captures deaths that may have occurred over a period of several weeks in the past, and sometimes many more.

Finally no CFR can capture the true mortality rate of the virus without ongoing, ubiquitous testing. As the state of testing stands, the true mortality rate must reflect undiagnosed cases in the denominator. The CDC’s latest “best” estimate of the true mortality rate is just 0.3%, and 0.05% for those aged 50 years or less. Those figures are based on serological tests for the presence of antibodies to C19 in more random samples of the population. Those findings reflect the extent of undiagnosed and/or asymptomatic cases.

The point is one shouldn’t be too blithe about throwing numbers around like 4% mortality based on the CFR, or even 1% mortality as a “nice, round number”, without heavy qualification. Those numbers are gross exaggerations of what we are likely to see going forward.

The same criticisms can be leveled at claims that hospitalizations will proceed at some fixed ratio relative to diagnosed cases, or some fixed ratio relative to deaths. Again, new cases tend to be less severe, so hospitalizations are likely to be a much lower ratio to cases than what is reflected in cumulative totals. Because of improved treatment, the ratio of deaths to hospitalizations will be much lower in the future as well.

CFRs are not a useful guide to future COVID deaths. The true mortality rate is a much better baseline, particularly for subsets of the population matching the current case load. Finally, and this is the only disclaimer I’ll bother to provide today, we all know that suffering is not confined to terminal cases, and it is not confined to the hospitalized subset. But don’t exaggerate the extent of your preferred interpretation of suffering by applying inappropriate cumulative calculations.

 

Cases Climb, Most Patients Faring Better

30 Tuesday Jun 2020

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There’s been much speculation about whether recent increases in confirmed cases of COVID-19 (first chart above) will lead to a dramatic increase in fatalities (second chart). More generally, there is curiosity or perhaps hope as to whether the virus is not as dangerous to these new patients as it was early in the pandemic. I have discussed this point in several posts, most recently here. Based on the national data (above), we’re at the point at which an upturn in deaths might be expected. Based on the experience of many individual states, however, deaths should have trended upward by now, but they haven’t done so. Cases are generally less severe and are resolving more quickly.

Of course, more testing produces more cases (though there has been a mild uptick in test positivity over the past two weeks), but that doesn’t really explain the entire increase in cases over the past few weeks. In particular, why are so many new cases in the south? After all, there is evidence that the virus doesn’t survive well in warm, humid climates with more direct sunlight.

As I have mentioned several times, heavy use of air-conditioning in the south may have contributed to the increase. Nate Silver speculates that this is the case. The weather warmed up in late May and especially June, and many southerners retreated indoors where the air is cool, dry, and the virus thrives. Managers of public buildings should avoid blasting the AC, and you might do well to heed the same advice if you live with others in a busy household. In fact, nearly all transmission is likely occurring indoors, as has been the case throughout the pandemic. At the same time, however, with the early reopening of many southern states, younger people flocked to gyms, bars and other venues, largely abandoning any pretense of social distancing. So it’s possible that these effects have combined to produce the spike in new cases.

Some contend that the protests following George Floyd’s murder precipitated the jump in confirmed cases. Perhaps they played a role, but I’m somewhat skeptical. Yes, these could have become so-called super-spreader events; there are certain cities in which the jump in cases lagged the protests by a few weeks, such as Austin, Houston, and Miami, and where some cases were confirmed to be among those who protested. But if the protests contributed much to the jump, why hasn’t New York City seen a corresponding increase? Not only that, but the protests were outside, and the protests dissuaded many others from going out at all!

The trend in coronavirus fatalities remains more favorable, despite the increase in daily confirmed cases. One exception is New Jersey, which decided to reclassify 1,800 deaths as “probable” COVID deaths about six days ago. You can see the spike caused by that decision in the second chart above. Reclassifications like that arouse my suspicion, especially when federal hospital reimbursements are tied to COVID cases, and in view of this description from Bloomberg (my emphasis):

“… those whose negative test results were considered unreliable; who were linked to known outbreaks and showed symptoms; or whose death certificates strongly suggested a coronavirus link.”

Deaths necessarily lag new cases by anywhere from a few days to several weeks, depending on the stage at the time of diagnosis and delays in test results. The lag between diagnosis and death seems to center on about 12 – 14 days. Thus far, there doesn’t appear to be an upward shift in the trend of fatal cases, but the big updraft in cases nationally only started about two weeks ago. More on that below.

Importantly, a larger share of new cases is now among a younger age cohort, for whom the virus is much less threatening. The most vulnerable people are probably taking more precautions than early in the pandemic, and shocking as might seem, there is probably some buildup in immunity in the surviving nursing home population at this point. We are also better at treatment, and there is generally plenty of hospital capacity. And to the extent that the surge in new cases is concentrated in the south, fewer patients are likely to have Vitamin D deficiencies, which is increasingly mentioned as a contributor to the severity of coronavirus infections.

I decided to make some casual comparisons of new cases versus COVID deaths on a state-by-state basis, but I got a little carried away. Using the COVID Time Series web site, I started by checking some of the southern states with recent large increases in case counts. I ended up looking at 15 states in the south and west, and I added Missouri and Minnesota as well. I passed over a few others because their trends were basically flat. The 17 states all had upward trends in new cases over the past one to two months, or they had an increase in new cases more recently. However, only four of those states experienced any discernible increase in daily deaths over the corresponding time frames. These are Arizona, Arkansas, Tennessee, and Texas, and their increases are so modest they might be statistical noise.

Again, deaths tend to lag new cases by a couple of weeks, so the timing of the increase in case counts matters. Five of the states were trending upward beginning in May or even earlier, and 13 of the states saw an acceleration or a shift to an upward trend in new cases after Memorial Day, in late May or June. Of those 13, the changes in trend occurred between one and five weeks ago. Six states, including Texas, had a shift within the past two weeks. It’s probably too early to draw conclusions for those six states, but in general there is little to suggest that fatal cases will soar like they did early in the pandemic. Case fatality rates are likely to remain at much lower levels.

We’ll know much more within a week or two. It’s very encouraging that the upward trend in new cases hasn’t resulted in more deaths thus far, especially at the state level, as many states have had case counts drift upward for over a month. If it’s going to occur, it should be well underway within a week or so. Much also depends on whether new cases continue to climb in July, in which case we’ll be waiting in trepidation for whether more deaths transpire.

Coronavirus Framing #7: Second Wave Uncertainty

19 Friday Jun 2020

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We’re now said to be on the cusp of a “second wave” of coronavirus infections. It’s become a new focus of media attention in the past week or so. Increased infections have been reported across a number of states, especially in the south, but I’m not especially alarmed at this point for reasons explained below. Either way, the public policy response will certainly be different this time, at least in most areas. We’ve learned that a more targeted approach to managing coronavirus risk is far less costly, which means eschewing general lockdowns in favor of focusing resources on protecting the most vulnerable. That approach is supported by research weighing the costs and benefits of the alternatives (also see here and here).

The targeted approach I’ve advocated does not call for any less caution on the part of individuals. That means avoiding prolonged, close contact with others, especially indoors. I don’t mind wearing a mask when inside stores or public buildings, but I believe it should be voluntary. I do my best to stay out of close proximity to most others in public places anyway, masked or otherwise. This is voluntary social distancing. I also believe public health authorities should be more active in disseminating information on known correlates of coronavirus severity, such as Vitamin D deficiency, high LDL cholesterol, and the “reverse seasonal effect” caused by low humidity in air-conditioned spaces. I would also strongly agree that the effort to identify and mass produce vaccine candidates, known as Operation Warp Speed, should be ramped up considerably, with heavier funding and more than five vaccine candidates.

We’ve seen a continuing increase in coronavirus testing since my last “framing” post about a month ago. Testing has increased to a daily average of almost 500,000 over the past two weeks. At present we appear to have an excess supply of testing capacity in many areas, as Rich Lowry notes:

“The problem with testing nationally is becoming less a shortfall of availability of the tests and more a shortfall of people showing up to get tested. An insider in the diagnostics industry says that laboratories are reporting that they are ‘sample starved’ — i.e., they aren’t getting enough specimens. He notes, ‘We have all seen stories about sample-collection sites in some regions not seeing that many patients.’

An HHS official says that in May there was the capacity to do twice as many tests as were actually performed, calling it a function of ‘allocation and efficiency, but more just demand.’ Says Giroir, ‘We really see areas in the country now that there’s more tests available than people who want to get tested or the need for testing.'”

Before turning to some charts, a word about the data in the charts I’ve been using throughout the pandemic. Some of the nationwide information was directly from the CDC or the Johns Hopkins dashboard. In other cases, I’ve reported state level data and some nationwide data published by The COVID Tracking Project (CTP) and the COVID Time Series (CTS) dashboard, which uses state data from CTP. I first noticed a few discrepancies in the national totals in April, which have become larger with growth in the counts of cases and deaths. Here is a key part of CTP’s explanation:

“For many states, the CDC publishes higher testing numbers than the states themselves report, which raises questions about the structure and integrity of both state and federal data reporting. … Another point of contrast between the CDC’s new reporting and the official state data compiled by The COVID Tracking Project is that the CDC has not released historical, state-level testing data for the first three months of the outbreak.”

Thus, the CDC currently reports almost 120,000 U.S. deaths, while CTP reports about 112,000. Nevertheless, I will continue to report numbers from both sources for the sake of continuity, and I will try to remember to note the source in each case.

The first chart below shows the number of daily tests from CTP; the second chart shows the number of daily confirmed cases (CTP). Since mid-May, daily testing has increased by more than 50%, calculated on a moving average basis, and is now approaching half a million per day or more than 3 million per week. Pooled testing is coming, which will ultimately increase testing capacity several-fold. Daily confirmed cases have been hovered just above 20,000 since around Memorial Day, with a recent turn upward to around 24,000.

Early in the pandemic, I made the mistake of focusing too heavily on case numbers. Yes, I adjusted for population size and was aware that the initial shortage of tests was restraining diagnoses. Still, I did not foresee the great expansion in testing we’ve witnessed, the great transmissibility of the virus in some regions, nor the large number of asymptomatic cases that would ultimately be diagnosed.

The daily percentage of positive tests (CTP), which is smoothed in the chart below using a seven-day moving average to eliminate within-week variability, has declined gradually since early April to about 4% before the uptick in the last few days. Still, that’s a drop of about 75% from the peak when tests were in very short supply. Those were days when even heavily symptomatic individuals were having trouble getting tested.

We’d hope to see a resumption in the decline of the positive percentage as testing continues to grow, but even with a relatively constant positivity rate, the number of daily confirmed cases must grow as testing expands. There may be several reasons the positivity rate has remained stubbornly near 5% over the past few weeks. One is the obvious reversal in social distancing as states have opened up. People became less fearful about the virus in general, and protesters jammed the streets after the George Floyd murder in Minneapolis. Another reason is that there are new areas of focus for testing that might be picking up cases. For example, hospitals in some states are now testing all admissions for COVID-19. This will tend to pick up more infections to the extent that individuals with co-morbidities are hospitalized at higher rates in general and are also more susceptible to the coronavirus. Finally, testing more broadly is likely to pick up a larger share of asymptomatic cases even as the “true rate” of infection declines.

The daily death toll (CTP) attributed to coronavirus has continued to decline. See below. It is now running at about a third of the peak level it reached in mid-April. There are several reasons for the decline. One is the lower number of active cases, changes in which lead deaths by a few weeks. Awareness and testing capacity have undoubtedly led to earlier diagnosis of the most severe cases. There is also the strong possibility that the virus, having felled some of the most susceptible individuals, is now up against more hosts with effective immune responses. An ongoing degree of social distancing, more humid weather, and more direct sunlight have probably reduced initial viral loads from those experienced early-on, when the case load was escalating. Finally, treatment has improved in multiple ways, and there are now a few medications that have shown promise in shortening the duration and severity of infection.

The course of the pandemic has varied greatly across countries and across regions of the U.S. The New York City area was especially hard hit along with several other large cities, as well as Louisiana. CTS shows that states with the highest cumulative number of coronavirus deaths (New York (blue line), New Jersey (green), Massachusetts, Illinois, and Pennsylvania in the charts below) have experienced downward trends in positive cases per day (the first chart below), leading daily deaths downward in May and early June (the second chart — NY’s downtrend began earlier). I apologize if the charts below are difficult to read, but they have resisted my efforts at resizing. Note: I’m mainly focused on trends here, and I have not shown these series on a per capita basis.

More recently, almost two dozen states have begun to see higher daily case diagnoses. Several of these had more favorable outcomes in the early months of the pandemic and were in more advanced stages of reopening. The charts below (CTS) show results for Arizona, Florida, Georgia, and Texas. The new “hot spots” in these states are mostly urban centers. It’s not clear that the reopenings are to blame, however. The protests after George Floyd’s murder may have contributed in cities like Houston, though no increase in New York is apparent as yet. The states in the chart are all in the south or southwest, so the increases have occurred despite sunny, warm conditions. It’s possible that hot weather has prompted more intensive use of air conditioning, which dries indoor environments and can promote the spread of the virus. These southern states have not yet experienced a corresponding increase in deaths, though that would occur with a lag. 

Missouri has seen an slow upward trend in its daily positive test count over the past four weeks, even though the state’s positive rate has trended down slowly since early May. I show MO’s confirmed cases per day below (in green) together with Illinois’ (because my hometown is on the border and the two states are a nice contrast). IL is much larger and has had a much higher case load, but the downward trend in new cases in IL is impressive. Coronavirus deaths per day are shown in the second chart below, with seven-day averages superimposed. Deaths have also trended down in both states, though MO has experienced a few bad days very recently, and MO’s case fatality rate is slightly higher than in IL.

We’ll know fairly soon whether we’re really headed for a second major wave. However, the case count, in and of itself, is not too informative. Testing has increased markedly, so we would expect to see more cases diagnosed. The percent of tests that are positive is a better indicator, and it has flattened at a still uncomfortable 5% for about a month, with a slight uptick in the past few days. Even more telling will be the future path of coronavirus deaths. My expectation is that more recent infections are likely to be less deadly, if only because of the lessons learned about protecting the care-bound elderly. I also believe we’re not too far from what I have called effective herd immunity. 

The pandemic has taken a heavy toll, especially among the aged. In fact, total deaths in the U.S. have now exceeded both the Hong Kong flu of the late 1960s and the Asian flu of the late 1950s. Unfortunately, risks will remain elevated for some time. However, any reasonable estimate of the life-years lost is considerably less than in those earlier pandemics due to the differing age profiles of the victims. In any case, the coronavirus pandemic has not been the kind of apocalyptic event that was originally feared and erroneously predicted by several prominent epidemiological models. It can be tackled effectively and at much lower cost by focusing resources on protecting vulnerable segments of the population. 

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