There are 258 confirmed deaths of COVID-19 for children. This is probably an underestimate, but I doubt it’s a two-fold underestimate. There are 74 million Americans who are in this age range. For comparison, 169 children under 15 years old died of asthma in 2016. In 2018 636 children age 12 and under died in car accidents.
The reason I’m posting this is I still hear fears about children dying now and then. The main issue with children is the spread of the disease. That’s why adults should vaccinate.
I haven’t been talking about coronavirus much. What’s there to talk about? In April I tried to be optimistic, and well that didn’t work out. We’re not at worst-case disaster scenarios, but likely “excess deaths” of 200,000 don’t look good. The idea expressed by some (and which I really hoped for) that weather or decreased virulence would “take care” of coronavirus seems to have not panned out.
The two very positive things for me are:
– children seem relatively unscathed. The original age-trends hold
– the outdoor spread is very low. The “superspreader” events tend to happen indoors
A possible point of optimism, which I’m uncertain of, is that “herd immunity” may in some cases be lower than 70%. In many areas, it looks like “herd immunity” is really what’s going to happen, though treatments and vaccines may be important for some regions (e.g., Taiwan).
Anyway, I was curious about public and media concern about coronavirus, so I looked at Google Trends. You can see the public, against the baseline peak, tends to delay a bit. The American media also seems to have gotten bored with coronavirus into the middle of February, just like all of society (this is when some of the really stupid pieces making fun of coronavirus alarmists showed up in the bluecheck clickbait world).
There have been striking differences in COVID-19 severity/penetration by region. There are all sorts of reasons posited. This post from Derek Lowe at In The Pipeline, New Data on T Cells and the Coronavirus, suggests a possibility:
And turning to patients who have never been exposed to either SARS or the latest SARS CoV-2, this new work confirms that there are people who nonetheless have T cells that are reactive to protein antigens from the new virus. As in the earlier paper, these cells have a different pattern of reactivity compared to people who have recovered from the current pandemic (which also serves to confirm that they truly have not been infected this time around). Recognition of the nsp7 and nsp13 proteins is prominent, as well as the N protein. And when they looked at that nsp7 response, it turns out that the T cells are recognizing particular protein regions that have low homology to those found in the “common cold” coronaviruses – but do have very high homology to various animal coronaviruses.
Very interesting indeed! That would argue that there has been past zoonotic coronavirus transmission in humans, unknown viruses that apparently did not lead to serious disease, which have provided some people with a level of T-cell based protection to the current pandemic. This could potentially help to resolve another gap in our knowledge, as mentioned in that recent post: when antibody surveys come back saying that (say) 95% of a given population does not appear to have been exposed to the current virus, does that mean that all 95% of them are vulnerable – or not? I’ll reiterate the point of that post here: antibody profiling (while very important) is not the whole story, and we need to know what we’re missing.
It seems that later we will find out that perhaps the Vietnamese benefited from some immunity conferred by a previous asymptomatic coronavirus outbreak? If you’ve been following Spencer Wells (more specifically, here, here, and here on the general hypotheses) on Twitter you know he’s been suggesting this for several months. The pattern seems to extend to neighboring nations too.
I haven’t posted on COVID-19 in a while. What’s there to say? The last month or so has been a great muddle. We soldier on, without purpose or direction. At least here in the United States of America. In regards to the pandemic, we’re in, all I can say is that I feel a sense of listless ennui. But perhaps I should say something, just for historical purposes of tracking where we’re at for this weblog?
On March 23th, T. A. Frank mentioned me in Vanity Fair as being a COVID-hawk. You can search this weblog and note I was relatively sanguine at the end of January, but we began to stockpile in early February. By the middle of February, I was alarmed. On February 19th news broke that Covid-19 was spreading Iran, and to be frank I flipped out.
Between February 20th and March 10th, there was a slow and gradual shift in thinking. But the real switch was flipped between March 10th and March 15th, as broad swaths of the culture moved into a high state of alarmism. It was curious seeing scientists who I followed who were fixated on Richard Dawkins in February joining the alarm about Covid-19. When they’d give a thought many (though not as many privately!) were reassuring.
They shouldn’t have been.
Some considerations and observations:
The COVID-doves: early in the pandemic there were critics who were accusing me of alarmism. This was March, so who knew? I asked for some numbers. One individual said that at most there would be 20,000 deaths. We are around 100,000 now. Over time the initial wave of skeptics faded away because the numbers were too high.
But, the second round of skeptics emerged. The interesting thing here though is that the second wave of skeptics was more focused on the opportunity costs of the lock-down. The key problem I have with this wave of COVID-doves is that I wish they would just admit that 250,000 miserable deaths may be the price we have to pay. Perhaps. We just need to put the numbers on the table and remember that the deaths seem quite unpleasant and protracted.
I am on friendly terms with many COVID-doves. I disagree with them, but I have friends and many who are liberals too, and I disagree with them. In fact, in an ideal world, I would be convinced by their arguments, and become a COVID-dove. I am not convinced by their arguments. Yet.
There is a broader class of COVID-skeptic which is, to be frank, unhinged, conspiratorial, and a promoter of misinformation. This is a serious problem.
TheCOVID-hysterics: another class of individuals are those who are hysterical about the impact of COVID. They want a two-year-long lockdown. They believe that the governor of Georgia has blood on his hands. They believe that COVID could kill anyone! Any skepticism or cost-vs.-benefit thinking is anathema to the COVID-hysteric.
The data is clear now that COVID-19 is particularly dangerous for older people. But the number of media profiles of young women who die of COVID-19 is quite high. There is, to my mind, a clear attempt by the media to make it seem like everyone is at risk. In fact, for people in their 20s and younger the seasonal flu seems to be more risk. The spate of stories about Kawasaki disease and children is, in my opinion, part of the issue. To convince COVID-skeptics those who wish people to take this pandemic seriously need to not exaggerate, or they’ll lose all credibility.
The IFR: I now believe that the infection fatality rate in the United States is around 0.75%. This is, as the above comment should make clear, not unconditional. For the young, it is quite low. For the aged, it is much higher. But when estimating how many Americans may die of COVID-19, this is the number that I think is reasonable. Perhaps higher. Perhaps lower. But this it the ballpark. If 50% of Americans become infected, that’s 1.2 million or so deaths. The IFR, like the R, is not a fixed parameter. Perhaps the virus will change. Perhaps our therapeutics will get better. But we go to war with the parameters we have, not the ones we want.
The uncertainty: There is still a great deal of uncertainty as we proceed forward. We know some things (e.g., no, children are not at high risk of death), but not enough. I have stopped paying attention to whether the weather impacts COVID-19. I think it does, but more in the range of 25-50% changes in the R, not an order of magnitude. There are lots of small things that are having impacts that we don’t know. And there are likely stochastic factors as well. We look through the mirror darkly.
Perhaps COVID-19 will fade away. Burn itself out. But that’s hope. A guess. We have no idea. We’re still not clear why the outbreak in New York City was so much worse on the West coast of the USA. Why Southeast Asia has been left relatively unscathed.
Pre-COVID-19 times
The quarantine: The major lacunae in the Western response has been quarantine-containment. The lockdown has, on the whole, not taken COVID-19 positive people, and put them in some sort of quarantine. It doesn’t look like it will happen.
That means COVID-19 is endemic. For now.
Where are we? It looks like as we move into fall the number of American deaths will be in the low 100,000s. This is a victory, after a fashion. My family is still self-quarantining. We have no date when we’re not going to keep doing this, at least for the foreseeable future. My children have grandparents that they want to see. What are we supposed to do? But the day will come when we go back out into the world…
When does COVID-19 get more dangerous than the flu? The CDC has some deaths listed for COVID-19. It also has deaths recorded for influenza. These are not perfect records, but, they give us a general comparative sense.
The total count in their data for the column I’ve plotting is about half of or so of the current death total for the USA. With that said, COVID-19 seems to be a really marginal disease in terms of mortality for those 24 years and under. For those 85 years or old COVID-19 is killing order of magnitude more than the flu.
Of course, there is morbidity as well as mortality. COVID-19 seems to have a longer course of progression for the symptomatic, and, there is the worry that it may cause lifetime problems in many people who survive from the severe cases (and even possibly the asymptomatic).
But, the number of people who are under the age of 40 who are dying doesn’t seem that high. And yet when I see headlines and profiles in the media, a huge number of feature focuses seem to be about younger people who die of COVID-19. Why? Obviously, because the deaths of the younger are surprising. But, I also think that part of it is the same rationale for the HIV-AIDS campaign: by pretending as if everyone is vulnerable, you obtain mass social mobilization.
I happen to know lots of people will not look at the raw data to understand what’s happening. But enough will to get annoyed.
50% of the deaths in Europe are in care homes. My family is self-quarantining no because we feel at risk, we’re not. But because there are older people in our family from whom we don’t want to be exiled. Does the media think if we admit and highlight the enormous danger that older people in particular face, we’ll conclude that they’re disposable?
Spencer and I recorded another coronavirus episode of The Insight. It should be live in a day or so. Therefore, I thought it was good to take stock and make some comments (my Twitter autodeletes).
– A few weeks ago I had been optimistic and suggested that the USA would have 40,000 deaths. That seems unlikely. I will remain optimistic and suggest 85,000 deaths by August 31st.
– I think most of the country will “open up” between May 15th and June 15th.
– Heterogeneity in trajectory persists. Some of this is through clear policy (e.g., Taiwan). But some of it is through demographics (USA is 40% obese, Japan is 3% obese). And, some of it is probably genetics.
– Many commentators make the correct observation that “no evidence of X” is not good evidence. E.g., “we have no evidence of human-to-human transmission…”
– The term “conspiracy theory” is totally debased. Just like the word racist or squish.
– High levels of uncertainty on everything. For example, many preprints which find confusing associations between weather and COVID-19 somehow transform in the media to titles of the form “COVID-19 won’t disappear in the summer!”
There has been a fair amount of anecdotal and a bit of statistical evidence that obesity is somehow associated with individuals who have worse progression of COVID-19. The data out of China I saw wasn’t significant statistically speaking. The problem? There didn’t seem to be enough obese people in their samples. Then anecdotes and some data came out of Europe implicating obesity as a risk factor. And, doctors started reporting a disproportionate number of obese patients in the ICU.
We conducted a cross-sectional analysis of all patients with laboratory-confirmed Covid-19 treated at a single academic health system in New York City between March 1, 2020 and April 2, 2020, with follow up through April 7, 2020. Primary outcomes were hospitalization and critical illness (intensive care, mechanical ventilation, hospice and/or death). We conducted multivariable logistic regression to identify risk factors for adverse outcomes, and maximum information gain decision tree classifications to identify key splitters….Strongest hospitalization risks were age ≥75 years (OR 66.8, 95% CI, 44.7-102.6), age 65-74 (OR 10.9, 95% CI, 8.35-14.34), BMI>40 (OR 6.2, 95% CI, 4.2-9.3), and heart failure (OR 4.3 95% CI, 1.9-11.2)…In the decision tree for admission, the most important features were age >65 and obesity; for critical illness, the most important was SpO2<88, followed by procalcitonin >0.5, troponin <0.1 (protective), age >64 and CRP>200. Conclusions: Age and comorbidities are powerful predictors of hospitalization; however, admission oxygen impairment and markers of inflammation are most strongly associated with critical illness.
click to enlarge
I’ve reformated table 3 of the regression below. It’s important to note here that the whole population is infected. The table is assessing the risk out of the infected sample that someone is going to go critical (which means a host of things, but entails hospitalization). Remember that a lot of the comorbidities associated with obesity are in the table. That means the risk of obesity is viewed as an independent variable. One can make some mechanistic arguments about the inflammatory effects of lipids, etc. That’s neither here nor there.
When assessing the risk of various nations is that 3% of Japanese are obese, while 40% of Americans are obese. Read More
Michael Fumento became prominent with his provocative book, The myth of heterosexual AIDS. On the whole I think Fumento’s point, that HIV-AIDS was not a major issue outside of “at-risk” groups in the United States, was the correct one.
I grew up as part of a generation that was taught about HIV-AIDS in a very apocalyptic manner. One of my health teachers even suggested that HIV-AIDS might lead to the extinction of the human race. When I saw Fumento make his case on a local public affairs television show, it was clear to me that despite everything I’d been told, he was probably correct. To counter his facts and figures the other guests appealed to anecdotes and vague predictions of the future.
COVID-19 is just the latest, albeit the most extreme, in a long series of epidemic hysterias I have covered going back to the “heterosexual AIDS explosion” (“Now No One is Safe from AIDS”) of the 1980s, avian flu, Ebola I and Ebola II, the Zika virus and others. They are known scientifically as “mass psychogenic illness,” and even more specifically as “moral panic” – the same type of hysteria that led to centuries of witch hunts.
Thus I was writing such articles as “Hysteria, Thy Name Is SARS” in 2003 while highly respected journals such as the New Scientist were screaming “SARS Could Eventually Kill Millions.” It ultimately killed only 774, and zero Americans, before simply disappearing in a hot July.
…
Yes, identified cases are still going up (albeit at a slower rate than before, per Farr’s Law), but that may just be an artifact. Indeed, it’s possible the epidemic is coming close to a worldwide plateau – in real terms, at least. The hint is in the category of “serious and critical cases.” It peaked in late February, with a steady decline to less than half that number. This in and of itself good news, of course. But why?
A lot of my Covid-19 commentary is on Twitter, but since I delete my tweets every 2 weeks it’s ephemeral. So I’ll post about once a week about a “status update” of sorts of my perceptions, predictions, and general sense.
First, I’m more optimistic than I was a few weeks ago. The main reason is that most of the nation is shut down, and social distancing is happening, broadly, albeit to various degrees. My mid-February back-of-the-envelope estimate of ~500,000 excess deaths is unlikely. I think the range of 100,000 to 200,000, given by the American government, is reasonable. But I’m hoping we can do a little better than that. Let’s say ~85,000.
The reason I’ll go on the low side is that I think there is still much to learn. And, a lot of the unknowns are “positive” for us in the medium term. If regional heterogeneity persists, that means we can learn from the successes (e.g., test-and-trace as in South Korea). Perhaps there is a “miracle drug” in the offing. We don’t know. I think the “worst-case” scenario of untrammeled infection is pretty well understood, so I don’t actually see as many downside unknowns.
A lot of people are asking me about the IHME model, and the fact that hospital bed shortfalls don’t seem to be as bad as the model predicted. I think this isn’t an issue with the model, it’s an issue with how accurate people think models are going to be. Model-building is important for fine-grained decision making but at the high level, the metrics are going to be more coarse. Currently, the COVID-19 epidemic is highly regional in the USA. A friend whose best friend is a medical resident at a New York City hospital confirms it is as bad as the media represents.
That being said, the western United States seems to be doing OK. The catastrophe in Washington state never really materialized. People are dying and have died, but the early actions of the government and populace of Washington seem to have forestalled a major outbreak. Similarly, the early actions of the Bay area leadership seem to have made a difference.
With that optimism put out there, we need to note the difference between mortality and morbidity. COVID-19 patients who have to go to the hospital use many resources and even mild cases have a longer course than the flu. More importantly, like SARS it is likely that for the severe cases, who outnumber the deaths by several folds, there will be lifetime problems.
Some parts of the USA will come out of lockdown on May 1st. Others will not. We will have a better sense of the variables that impact R and virulence as the summer progresses.
Of them, 53·1% were normal weight, 4·2% were underweight, 32·0% were overweight, and 10·7% were obese. Patients with obesity, versus without, were tended to have cough (P=0·03) and fever (P=0·06). After adjusting for potential confounders, compared to normal weight, overweight showed 86% higher, and obesity group showed 2·42-fold higher odds of developing severe pneumonia. Despite a non-significant sex interaction was found (P=0·09), the association appeared to be more pronounced in men than in women. The odds ratios (95% confidence intervals) for severe pneumonia in overweight and obesity was 1·96 (0·78-4·98) and 5·70 (1·83-17·76) in men, and 1·51 (0·57-4·01) and 0·71 (0·07-7·3) in women, respectively.
The average American adult has a BMI of ~26.5. We define “obese” as BMI > 30.
A friend of mine recently quipped that everyone seems to act like probability can be assigned two values 0 or 1. The same sort of logic seems to apply when it comes to talking about the environmental parameters which might affect the progress of COVID-19, such as temperature, humidity, and density. Many people seem to strenuously want to deny there is any plausible evidence that COVID-19 might exhibit seasonality. There is a fair amount of correlational work which suggests that there is an environmental factor shaping the spread and depth of COVID-19. And, we know three out of the four previous coronaviruses exhibit seasonality.
Well, I noticed this note on medRxiv today, Stability of SARS-CoV-2 in different environmental conditions. It’s a very short write-up of their experimental results. I don’t really know much about virology so I can’t evaluate it well, but you can see the figure above. As you increase the temperature the virus titer seems to drop much faster. At a very high temperature of 70 Celsius, they basically can’t detect anything after 1 minute.
Nearly every country is now combating the 2019 novel coronavirus (COVID-19). It has been hypothesized that if COVID-19 exhibits seasonality, changing temperatures in the coming months will shift transmission patterns around the world. Such projections, however, require an estimate of the relationship between COVID-19 and temperature at a global scale, and one that isolates the role of temperature from confounding factors, such as public health capacity. This paper provides the first plausibly causal estimates of the relationship between COVID-19 transmission and local temperature using a global sample comprising of 166,686 confirmed new COVID-19 cases from 134 countries from January 22, 2020 to March 15, 2020. We find robust statistical evidence that a 1◦C increase in local temperature reduces transmission by 13% [-21%, -4%, 95%CI]. In contrast, we do not find that specific humidity or precipitation influence transmission. Our statistical approach separates effects of climate variation on COVID-19 transmission from other potentially correlated factors, such as differences in public health responses across countries and heterogeneous population densities. Using constructions of expected seasonal temperatures, we project that changing temperatures between March 2020 and July 2020 will cause COVID-19 transmission to fall by 43% on average for Northern Hemisphere countries and to rise by 71% on average for Southern Hemisphere countries. However, these patterns reverse as the boreal winter approaches, with seasonal temperatures in January 2021 increasing average COVID-19 transmission by 59% relative to March 2020 in northern countries and lowering transmission by 2% in southern countries. These findings suggest that Southern Hemisphere countries should expect greater transmission in the coming months. Moreover, Northern Hemisphere countries face a crucial window of opportunity: if contagion-containing policy interventions can dramatically reduce COVID-19 cases with the aid of the approaching warmer months, it may be possible to avoid a second wave of COVID-19 next winter.
To be clear. Does this mean weather/climate determine whether COVID-19 will spread or not? No. Rather, I think that weather/climate has some effect on the margin on the R0. I am not sure of the exact reason, but if the virus degrades much faster in hot climates, that could be one explanation of why spreading is more limited. It also does not seem to be the case that tropical countries are going to avoid mass healthcare crises. Rather, as these countries formulate policies to decrease R0, it may not be as long of a haul.
I believe that many are worried that if there is some relationship between temperature and COVID-19, people will think they are safe in a particular climate. The way to deal with this is not to ratchet up skepticism to an inordinately high extent. Rather, it is to be more clear and careful in how one presents the data.
Similarly, I think density has some impact. But, South Korea, Japan, and Taiwan show that density does not seal one’s fate.
