This is part 2 of a 4-part series dedicated to un-masking children. Jump to other parts below.
Part 4: The Plan to Un-Mask Children
In order for people to make data-driven decisions with respect to COVID-19, they must be given the best data available, and it must be presented relative to other risks they incur on a daily basis. The CDC has utterly--and possibly deliberately--failed to do this.
The result is that people--especially younger people, under 50--wildly over-estimate their risk from COVID-19. Children are at significantly lower risk of death from COVID-19 than from flu. Of the 65,000 deaths last year for people under 25, only 252 were from COVID-19--about half the number of a standard flu season. There were, potentially, an additional 30--about the number of people each year who die from lightning strikes--due COVID-19-related Multi-system Inflammatory Syndrome, deaths which many clinicians believe could have been avoided, had parents not been frightened of bringing their children into the hospital and exposing themselves and their children to COVID-19.
Yes despite these very small numbers, parents of children with "co-morbidities" across the country are afraid to send their kids to school. All of the risk factors for COVID-19 are also risk factors for fatal influenza, yet not only do these parents not keep their children home during flu season--it would be illegal for them to do so. The lower death rates for children from COVID-19 vs. flu tell us that these risk factors are even less of a concern for COVID, not more.
Still other parents are afraid of their children infecting them, or elderly relatives. In part one, of this series, we looked extensively children's role in transmitting COVID-19, it is trivial, with many studies unable to find even a single example of child-to-adult transmission. Yet what if these studies had found the opposite? Children are a major driver of flu transmission to the elderly, yet they are not kept out of school for fear of infecting their grandparents. Once again, doing so would be illegal. Not only is child-destroying hypochondria no longer frowned upon, it is actively stoked by one of the world's foremost "health" agencies--the CDC. The result is that many children across the country have been kept not just out of school, but away from friends for a full year.
All of this could be easily fixed, if the CDC were focused on calming fears, and putting risks into perspective. But they have no desire to do so. Instead, they fan the flames of fear in order to gain compliance with spectacularly failed health policies. People in low-risk groups must be helped to to self-identify as such, so that they are not frightened into making decisions that are harmful to themselves or their families in the long-term, out of an abundance of misplaced caution (i.e. not sending children to school, resigning from jobs, not exercising, not socializing). It is also important that people understand how the harsh measures that have and continue to be advocated by many in public health have had demonstrably negative impacts on those groups they claim to wish to protect.
This post will be dedicated to presenting the data available from the CDC about relative risk by age, co-morbidities, and ethnicity, and providing it in a way that makes it useable for individuals to assess their own risk profile and risk tolerance.
Part 1: Age
The risk for COVID-19 is highly stratified by age and co-morbidities—we will look at both. While to some extent this is common knowledge, the degree of stratification is not common knowledge. Nor have public health officials made any efforts to put this risk into context with other diseases or behaviors. The chart below is based on the CDC’s estimated number of infections by age through 12/26/20, and deaths by age through 1/09/21. The CDC creates these charts every year for flu—but with one important difference. When the create these charts for flu, the ALWAYS include the estimated deaths by age. When the CDC released this chart for COVID, they conspicuously did not include the estimated deaths—despite having these numbers. I extracted that data and “finished” the chart for them.
Table 1: CDC Estimated Infection Fatality Rate (IFR) for COVID-19 Infections through 12/31/20 relative to 2017-2018 flu (worst recent flu year)
Sources: COVID-19 Deaths Weekly Number of Deaths by Age (deaths through week of 1/15 included); COVID-19 Estimated Disease Burden; 2017-2018 Estimated Disease Burden, Influenza:
COVID-19 poses a significantly lower risk to school age children than the flu. Given the wide availability of vaccines, this fact alone, ought to make it clear that children should be allowed to return to all activities un-masked next year, if not earlier. As of this writing, we are quickly reaching the point where most seniors and who wish to be vaccinated across the country have been vaccinated.
Most teachers and staff fall into the 18-49 category whose risk, while slightly above their risk of flu, is still minimal—3 in 10,000, roughly the same as the risk of dying in childbirth. As noted in the first post in this series, based on the deaths of teachers reported by EdWeek, teachers appear to be at even lower risk as a group, something also supported by studies out of the U.K. and Sweden.
Looking at weekly all-cause deaths in Florida—where deadly restrictions have been removed—by age, we see that deaths below 45 have ceased to be elevated much above flu levels since Governor DeSantis removed restrictions (which in this age group, were almost certainly leading to deaths of despair). Even among 45-64, deaths, while elevated above flu levels are only slightly so.
Figure 1: Weekly Deaths by Age, in Florida, 2015-2019
Source: CDC All-Cause Deaths by State and Age (To do this for your state, go to the link, scroll down, select the “weekly number of deaths by age.” Be sure to click “update dashboard”. Select your jurisdiction from the drop-down, and then click “update dashboard” again.)
Part 2: Co-morbidities
This is not to say that there is not risk for those above 45. For the people in the 50-64 group, the IFR is of slightly more concern—equivalent to 6x this group’s risk of dying in a car accident in any given year. That is not a huge risk, but it is a slight elevation in risk. But it is important to remember that the reason that age increases risk has everything to do with co-morbidities. Age is essentially a proxy for co-morbidities. The table below shows deaths in NYC through April 30, 2020. What this table shows, is that if people do not have co-morbidities—regardless of age—they are not at significant risk—in NYC, there was also excessive use of ventilators, which, for the young and healthy, may have elevated the number of deaths in these groups.
Figure 2: Deaths by Age and Comorbidity through April 30th, 2020
Source: https://www1.nyc.gov/assets/doh/downloads/pdf/imm/covid-19-daily-data-summary-deaths-05012020-1.pdf
Let’s dive a little deeper here. What this means is that of all deaths in NYC, only 0.5% of them occurred in people who did not have a comorbidity. Current CDC data shows that on average, people dying of COVID-19 had 3.8 co-morbidities. So these people aren’t just unhealthy, they are very unhealthy—many on deaths door (89% of those who died of COVID had a DNR, which is similar to the 91.7% who have DNRs and die during a normal period. 70% of those hospitalized with COVID who did not die had a DNR, indicating the level of ill-health of most hospitalized for COVID).
Seroprevlanece (antibody) studies from the same period show us that there were more than 1.6 million infections in New York City at this time. The question is, what portion of those people were healthy? New York State is one of the healthier states, with an obesity level of only 27.1%. Obesity itself triggers other co-morbidities. So while people will say there are x percent of people with this condition, and y percent of people with that, in truth, there is significant overlap—as we see in the 3.8 co-morbidities number. Nationally, across all age groups, the level of people without co-morbidities is around 60%. If NYC follows this trend, that would mean that roughly 978,000 healthy people across all age groups had been infected, with 81 deaths, resulting in an infection fatality rate for healthy people of 0.008%. Or about 27x less deadly than childbirth.
The chart below gives an estimate of mortality in New York City for healthy people by age group. From this estimate, we see that even among the oldest age groups, the risk of death for healthy people from COVID is similar to that of dying in childbirth—3/10,000—and several times higher than their risk of dying by accidental death.
Table 3: Estimated Age-based IFR for People in NYC without Co-morbidities
Detailed sources and methodology, here.
The CDC has made no efforts to draw attention to this, and that has left vulnerable people at greater risk. This is because if there are some people with lower risk than shown by a blended average, there are also those who are at higher risk. Indeed, we see a physical reminder of this when we look at the teachers who have died. Most are overweight, likely with multiple co-morbidities—many of whom never set foot in a classroom, but who may have been lulled into a sense of safety by universal masking, and public health officials in this respect, as elsewhere, downplaying the high degree of risk stratification.
Our school policies ought not re-capitulate this failure by the CDC. To the extent that there are teachers or staff at high-risk, temporary alternative arrangements ought to be made to accommodate and protect them to the degree they wish to be accommodated and protected—in a way that does not disrupt and adversely impact other groups, as the policy for the past year has unquestionably done.
Part 3: Ethnicity
Race discrepancies have been used as an argument for children not returning to school full-time, in-person. Of all of the shameful public health messaging over the past year, this one is by far the most despicable. This argument relies on the disastrous results of harsh lockdowns which, by driving the virus almost exclusively to people in lower economic strata, resulted in a significantly higher proportion of deaths amongst minorities. These deaths, which were a direct result of public health policy, are now being used by public health officials and unions to justify keeping schools and business closed—both of which more acutely impact minorities, and those same communities hit hard by deaths.
The graph below shows weekly all-cause excess deaths/million by race in the U.S., Florida and NYC. All-cause deaths are a better metric than COVID-19 alone, because they incorporate deaths caused by COVID response (e.g. fewer hospital visits, fewer cancer screenings, despair, etc.), as well as any potential COVID deaths that might have been miscounted. They also address the claim by some that Florida’s numbers have been gerrymandered (despite ample evidence to the contrary, and an A+ data quality rating from The COVID Tracking Project).
Figure 3
What these graphs show quite clearly, is that while harsh measures advocated by the CDC were in place, there was both significantly higher excess mortality, as well as a much larger discrepancy between deaths/million of whites vs. minorities. Almost as soon as these restrictions were removed in Florida, deaths/million by race equalized, with whites in Florida now dying at slightly higher rates than minorities. Since removing restrictions, Floridians of all races are dying at lower rates than the national average—despite (or possibly because of) Florida having some of the least stringent mitigation measures in the nation.
Comparing Florida at 47th most stringent, California, the most stringent state, underscores the point. California and Florida are both demographically and latitudinally/climactically well-paired—infections in both places rise at roughly the same time of year. In California, we see that with the harshest restrictions in the country, deaths for all races are much higher than Florida’s since removing restrictions—and that minorities are dying at significantly higher rates than whites, where in Florida, they are roughly equal, with whites dying at slightly higher rates for most of the post-restriction period. This is in spite of Florida having the second oldest population, and California the 5th youngest.
Figure 4
Same sources as Figure 3.
In Boston, as well, where some of the harshest restrictions were put in place, we see that there is an almost linear correlation between decreasing education levels, and increasing COVID infections.
Source: Rational Ground
It is important, also, to note that other vulnerable groups have also seen a reduction in deaths, once restrictions were removed. The table below compares Florida and Massachusetts by age, adjusting for differences in population structure relative to age. Looking at it in this fashion, and relative to prior flu seasons, we see that across all age groups, deaths in Florida were significantly less elevated above prior flu seasons than in Massachusetts, with its harsh restrictions—in several age groups, deaths in Florida by age group did not exceed flu levels at all. Even now, when the virus is basically endemic in Massachusetts, and restrictions in Massachusetts are among the highest in the nation, deaths/million by age-group population remain significantly more elevated in Massachusetts than Florida.
Figure 5: 2020 all-Cause Deaths/Million by Age Group
Nor was any of this unexpected. According to Dr. Marc Lipsitch in 2009 (sadly, now one of the strongest proponents of lockdowns):
“Epidemic theory dictates that a reduction in the force of infection by a pathogen is associated with an increase in the average age at which individuals are exposed. For those pathogens that cause more severe disease among hosts of an older age, interventions that limit transmission can paradoxically increase the burden of disease in a population.”
Looking at the results of these two vulnerable populations—minorities and the elderly—in states with harsh restrictions versus moderate, the accuracy of this theory has proven out. It has done so in a singularly deadly way in the states with the tightest restrictions.
We must not allow the mistakes of the CDC and other public health authorities in March to be used to frighten the most economically vulnerable in our community away from school and employment.
Continue to Part 3: Mask (In)Effectiveness in Slowing COVID-19 Transmission, or go back to Part 1: The Role of Children in COVID-19 Transmission in Schools.