COVID update – April 27

The full COVID update for Tuesday is here.

In the USA, cases are up 61% in the past two weeks, and there are now more states in the “new cases” red zone than out, 29 to 21. And the official numbers are probably low because more and more people are testing at home rather than heading out to a lab or clinic. Positive home tests have a way of staying out of the official stats.

The official testing percentages are creeping steadily upward. No states have re-entered the red zone yet, but a handful are getting close.

There is also some good news. COVID total hospitalizations and ICU cases remain steady, and fatalities are still declining. Only five states are in the fatality red zone.

Only one state (Kentucky) is in the red zone for both new cases and fatalities.

238 thoughts on “COVID update – April 27

  1. Let’s not forget that vaccine protected breakthrus suppress transmission before we start talking up “more contagious but milder”.

    Vaccine immunity closes the contagiousness window faster. Downstream, there’s less of the virus infecting the unvaccinated.

    The mRNA booster is even more protective: neutralizing antibodies. Which you don’t get from a breakthru. Nor can you get that from “convalescent plasma”.

    Either way, R goes down. Once we account for vaccine immunity, the raw value of R is now something like 10x higher than Delta. But a community’s vaccinated are like the control rods in a reactor.

    Details: The case counts we’re seeing now are even more of an undercount than in the past. The biggie, for the “milder” claim: CFR for the unvaccinated has held constant.

    1. And then there’s this current headline… “South Africa’s Covid Positivity Rate Hits Three-Month High…” That’s where omicron started.

  2. At least we’re not Sweden…

    “ Sweden was well equipped to prevent the pandemic of COVID-19 from becoming serious. Over 280 years of collaboration between political bodies, authorities, and the scientific community had yielded many successes in preventive medicine. Sweden’s population is literate and has a high level of trust in authorities and those in power. During 2020, however, Sweden had ten times higher COVID-19 death rates compared with neighbouring Norway. In this report, we try to understand why, using a narrative approach to evaluate the Swedish COVID-19 policy and the role of scientific evidence and integrity. We argue that that scientific methodology was not followed by the major figures in the acting authorities—or the responsible politicians—with alternative narratives being considered as valid, resulting in arbitrary policy decisions. In 2014, the Public Health Agency merged with the Institute for Infectious Disease Control; the first decision by its new head (Johan Carlson) was to dismiss and move the authority’s six professors to Karolinska Institute. With this setup, the authority lacked expertise and could disregard scientific facts. The Swedish pandemic strategy seemed targeted towards “natural” herd-immunity and avoiding a societal shutdown. The Public Health Agency labelled advice from national scientists and international authorities as extreme positions, resulting in media and political bodies to accept their own policy instead. The Swedish people were kept in ignorance of basic facts such as the airborne SARS-CoV-2 transmission, that asymptomatic individuals can be contagious and that face masks protect both the carrier and others. Mandatory legislation was seldom used; recommendations relying upon personal responsibility and without any sanctions were the norm. Many elderly people were administered morphine instead of oxygen despite available supplies, effectively ending their lives. If Sweden wants to do better in future pandemics, the scientific method must be re-established, not least within the Public Health Agency. It would likely make a large difference if a separate, independent Institute for Infectious Disease Control is recreated. We recommend Sweden begins a self-critical process about its political culture and the lack of accountability of decision-makers to avoid future failures, as occurred with the COVID-19 pandemic.”
    From NATURE this week.

  3. Thanks for keeping this issue on a front burner!

    Regarding relaxing masking and other protocols, I don’t think we’re out of the woods yet. It’s been found that the virus is widespread among white-tailed deer, and that minks can transmit the virus to humans.

    Minks are mustelids which also include wolverines, badgers, weasels, stoats, otters, etc. These animals hunker down over the winter and become more active in the spring. Some have indiscriminate diets, including scavenging frozen deer carcasses! Blood to blood transmission is most effective, and these animals are often sporting cuts from fighting among their species and others. Safe to say some of these animals will come into close contact with virus variants in deer that have been mutating all winter.

    Can others transmit to humans, we don’t know, but the latest thinking is that the virus originated from infected civets in live markets. Civets are less closely related to minks than minks to other mustelids, so my guess is that vectors are not going to be restricted to just civets and minks, maybe a lot more candidates.

    If you hear about some nasty cervid/mustelid crossover variant, originating say out of the Western US or Canada, remember you saw it here first!

  4. Ummm…
    Mar. 15, 2022 — COVID-19 cases may surge again in the United States if wastewater testing proves to be a reliable predictor.

    ABC News reported that 37% of wastewater sites monitored by the CDC from Feb. 24-March 10 have seen an increase of 100% or more in COVID-19 viral levels found in the wastewater. About 30% of those sites showed an increase of 1,000% or more.

    “It is likely we will see a new rise in cases across the United States as our wastewater data is showing a concerning signal,” Rebecca Weintraub, assistant professor of global health and social medicine at Harvard Medical School, told ABC News.

    1. Not that y’all need my opinion, but I’ve always sided with the right-wingnuts in the sense that they believe case stats are a distortion.

      PCR tests distort because positivity correlates only by accident with contagion. That is, among possible scenarios, either that tiny viral loads aren’t contagious, or that the virus (pathogen) may spread but disease severity is low, dominate the odds.

      The main advantage of antigen tests was always their relative lack of sensitivity. The convenience factors — timely results & low in cost & infrastructure — are really the icing on the cake.

      Essential, IMO, as convenience determines participation, but sensitivity to a load comparable to spread threshold, that’s the red meat.

      The exact same thing can be said for the official decision to favor vaccine delivery by injections & without regard to the logistics (special freezers). This was the achilles heel in Project Warp Speed for which I don’t consider it to be the big success it’s widely credited with.

      It was MedBiz turf protection — or call it Regulatory-Industrial complex — that prioritized maintaining strict controls vs. high availability.

      The low impact of omicron in well-vaccinated areas uncovers the weakness of policy extremes. For instance, China’s zero-tolerance lockdowns. Tactics need to evolve as conditions change. China & Hong Kong are stuck in that loop right now. Even New Zealand realized it need to shift to keep standing.

      Here in the U.S., in spite of vaccination resisters, it just so happens that omicron variant spread like wildfire & incidentally left behind a coat of natural immunity without the earlier devastation.

      The main reason, as we’ve discussed, is simply because “severity = novelty”. COVID is not new to enough of us that both its spread & impact are closer to tolerable than at the outset.

      We’re firmly in the territory where PCR detection is mostly unhitched from bad outcomes. Conspiracy mongers calling out case counts as lies are correct… lately. They were more wrong than right before, but life’s complicated. Situations change facts.

      That’s what makes me a “moderate”. I believe in the good intentions we tend to ascribe to leftists. I just also believe — left or right — results matter. If your prejudices lead you to favor counterproductive tactics, you’re doing it wrong!

      1. Yeah…what’s a million or so Covid deaths…the virus could care less about your opinion.

        1. Yeah, “in the sense that” is carrying a lot of water. It’s literally so, that the virus bears no special malice vs. its victim.

          I’ve believed that PCR was a misleading test because it lumps together transmissible viral loads with residual genetic fragments. Ie, leftover junk.

          I don’t thereby conclude, as the wingnuts do, that the whole picture we can get by looking at a spectrum of data (hospitalization/deaths, distribution of cases, etc) is necessarily wrong. It’s wrong if we draw the wrong conclusions. Which we don’t have to.

          But journalists in particular have been routinely misled by their poor/shallow understanding of the data.

          There is also an element of scare-mongering, ie, propaganda, in exhibiting big case numbers while in fact we may have succeeded in “flattening the curve”.

          We’ve used case numbers with the ulterior motive to coerce people to vaccinate. Not that this motive isn’t well-intentioned. The freedom to infect one other isn’t a civil right, after all.

          Convincing people to accept a common obligation is a reasonable goal. It’s just that, well, trying to do so thru misleading numbers is dishonest & demeaning. It may be a “white” lie, but there might be backlash—and if so, it’s karma.

          1. On Thursday, South Korea recorded its deadliest day during the pandemic, with 429 deaths in a 24-hour period. The Korea Disease Control and Prevention Agency reported 621,328 cases (1 percent of the population of 50 million), another daily record and a 55 percent increase from 400,730 the day before. More than 85 percent of the country’s population is fully vaccinated, and more than 60 percent have received a booster shot.

            Let’s see how this develops.

  5. Well, the theory why surges sink as fast as they rise is interesting in its simplicity. The virus exhausts its ready supply of victims. I suggest this is a spinoff of “herd immunity” which let’s call “herd thinning”.

    1. Yes, that is mathematically correct. Imagine if you will, a new disease so contagious that everyone, let’s say in City A of a million people, catches it in the first week. New cases go from zero to a million in week one. Therefore, mathematically, the number of new cases in week two must drop right back to zero – there’s nobody left uninfected. That’s obviously an exaggeration, but it illustrates the point that a high rate of contagion will very rapidly attack those who are vulnerable, thus rapidly exhausting the number of potential victims, followed by a period in which new cases fall rapidly as the disease simply runs out of targets.

      Not only should the slope of increase be very similar to the slope of decrease, but the rate of contagion should be inversely related to the duration of the wave of new cases. (100% instant transmissibility = more or less zero duration). Thus Delta climbed slowly but lasted long, while Omicron climbed fast with a much shorter duration.

      I have another speculation that I haven’t done the math to justify. I’m going to guess that when the total case numbers can be tallied, that they will be similar for delta and omicron. Delta will be a comparatively low number per week for many weeks, while omicron will be a higher number per week for fewer weeks, and I’m guessing that the multiplication will produce sort of similar totals. Again, I have not tried to run any preliminary numbers on that hypothesis, but I think I am making a reasonable conjecture. Of course Delta and Omicron faced different conditions in terms of prophylaxis, and that will muddy the results, but no study in the real world is absolutely clean or completely accurate because, to word it technically as Einstein used to do, shit happens.

      1. This is a variation on the classical mathematical models used to describe the time course of predator-prey populations (e.g., foxes vs. rabbits vs. grass). A few papers have been published on this, although they are mostly focused on predicting the trajectories of numbers of infected and recovered, and not so much fatalities.

        1. In practical terms, the thing you’d like to be able to predict is the burden on the health care system, so that hospitals are never overrun and can treat each case appropriately. Where we got lucky with omicron is that its high level of transmissibility was not matched by a high hospitalization rate, so there was generally no need to “flatten the curve.” We would have had no way to handle the situation if those days with 800,000 new cases had produced hospitalizations in proportion to the original strain.

          1. Agreed. Couple of tidbits to add. The main idea here dates to at least ~ 1800, paper by Malthus.

            The multiplication Scoopy refers to is called area. Ie width times average height = area under the curve. AKA “fundamental theorem of calculus.”

            We see in COVID charts some curves of “cumulative” stats. Such a curve is of course the running total, ie the total area to the left of each point.

            Scoopy’s conjecture is basically Kepler’s 2nd law, AKA “Kepler’s area law”. Which dates to ~ 1600.

            Academics refer to exponential growth/decay scenarios as “Malthusian”.

            So we have 2 helpful search terms: malthusian, “Kepler’s area law”. Quite nice image results illustrate the latter.

            As to Scoopy’s allusion to real-world confounding factors: Yes, mitigations muddy the simple scenario.

            To fwald: Seems to me, fatalities = (infected – recovered), doesn’t it? (I mean, in the long run.)

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