Lessons from the Lockdown Why are so many fewer children dying? A White Paper from Health Choice By Amy Becker and Mark Blaxill June 18, 2020


Lessons from the Lockdown

Why are so many fewer children dying?

A White Paper from Health Choice

By Amy Becker and Mark Blaxill June 18, 2020

Covid19 is a serious public health issue, but the breathless reporting among the media of positive tests and an ever‐rising death toll does little to instruct us about the true nature of the virus and the unprecedented steps taken to prevent its impact. As in many complex and pervasive health phenomena, there are many ways to measure health effects, but in our view the proper measure of impact is not a narrow or intermediate metric, but rather total health outcomes. In the case of a pandemic virus affecting large populations and where the immediate concern is sharp increases in deaths, the best measure of outcomes is not a selective measure of deaths somehow attributed to the disease but instead is deaths from all causes. For perspective, these deaths must be compared to historical death rates from all causes in prior years (Percent of Expected Deaths). As we will show, a balanced view of the broader American Covid19 experience demonstrates both the scale and variability of its negative outcomes in older American, especially the elderly, but also some unexpected positives. Surprisingly, U.S. mortality rates have declined among young people during the lockdown, especially among infants. These trends have gone largely unnoticed and remain unexplained.

Death rates from all causes vary widely and somewhat predictably. The most pronounced variation occurs by age cohort (most deaths occur in the elderly) and by time of year and to a lesser extent by geography. All‐cause deaths are cyclical, commonly rising in the winter months and “flu season” and then falling to lower levels as warmer weather arrives. To the extent that death rates vary by region, this is mostly a result of differences in the age mix of residents. In the case of Covid19, death rates are not yet known to be cyclical but they do vary significantly by age and geography.

In the analysis that follows we have examined the evidence on total death rates by geography (mostly by state), by age group and by week (and flu season). We have extracted eight main lessons. Some of these are part of the ongoing conversation around Covid19; others are unexpected or at least have not been widely circulated. Why this discrepancy? Since the infectious disease establishment has controlled the “pandemic” narrative, the variance between this evidence and conventional wisdom is largely driven by longstanding bias and error patterns among the experts in that community.

1. Overall US trend.
The Covid19 impact on all‐ cause deaths has been sharp and clear. Tens of thousands more Americans than expected died in a brief period. (1)
Before mid‐March, overall U.S. deaths were trending at a level no different from recent years at between 55‐ 60,000 per week. Beginning in the week ending on March 28, all‐cause deaths began rising sharply, peaking in the week ending April 11 at around 75,000, or 137% of Expected Deaths for the week. Immediately



thereafter, all‐cause deaths began dropping sharply. Within five weeks, all‐cause deaths were back to their typical range. By the week ending May 16, the measurable pandemic death impact had ended even though Covid19‐related deaths most certainly had not. (2)

Attributing a Cause of Death (COD) to COVID‐19 is not always clear‐cut, due to significant overlap among COVID‐19, Pneumonia, Influenza, and presumably other primary CODs. (2)

That said, the spike in deaths officially attributed to COVID‐ 19 occurred in tandem with the spike in all‐cause deaths, leaving little doubt that Covid19 was the main contributor to the excess of expected deaths between March 22 and May 9.



At least in this 8‐week period, the Covid19 pandemic was considerably worse than a typical flu season. To the extent that all‐cause deaths fell back to expected levels during May, the excess mortality attributable to the pandemic has passed. (1)

2. Localization. Increases in all‐cause death rates during the pandemic have been extremely localized, varying widely by state/jurisdiction. For the 3 1⁄2 month period surrounding the pandemic, starting on February 1 through May 16 (the most recent period with 100% reporting), total deaths in the US came in at 105% of expectations. (2)


Many states actually saw lower than expected deaths during the period. To be sure, an excess death rate of 5% for the entire U.S. is considerable but also far short of the apocalyptic narrative the pandemic has received.

Greater‐than‐expected death rates were heavily concentrated in the Northeastern corridor. New York City and its surrounding area,
including New Jersey, New York
State (although possibly not

upstate New York), Connecticut, Massachusetts, Maryland and the District of Columbia have so far comprised 6 of top 8 jurisdictions with excess all‐cause deaths. New York City was hit especially hard. In a typical spring, New York City could expect 700‐800 all‐cause deaths per week. From mid‐ March to mid‐May, that number spiked sharply, by ten times that amount, reaching over 7500 deaths in the peak week ending April 11. (1)

Other Northeastern states saw sharp increases in expected deaths but nowhere near New York City’s rate. (2) The timing of the peaks has varied, Massachusetts came soonest, followed by Maryland, New York City New York State and New Jersey. Nevertheless, the entire region saw declines in expected deaths starting in May.

page5image17595712 page5image17594928


Many states saw no or only a modest increase in expected deaths, including some of the largest states such as California, Florida and Texas. (2) This suggests there may have been specific factors that influenced the experience in New York City that were not shared elsewhere.

3. Variation by policy environment. To the extent that policies have varied across the states, it is not clear that the imposition and/or presence of stringent lock‐down policies had much to do with the variation in excess deaths. Less stringent lockdown policies were not associated with higher death rates. In fact, the 5 states that chose not to impose a lockdown are among the roughly 20 jurisdictions with no excess deaths at all. (2)


Several states with the most
aggressive lockdowns, including
California, Maine, Minnesota and
Pennsylvania showed almost no
excess deaths effect. Despite
huge population centers,
California looked nothing like
New York City and State. Maine,
a mostly rural state, imposed
among the more draconian
policies with essentially no
reason. Minnesota followed a far
more aggressive lockdown policy
than its neighboring states of
Iowa, South Dakota, North
Dakota and Wisconsin. Yet it’s
Covid19 deaths were among the
most concentrated in the country: roughly 80% of Minnesota’s Covid19 deaths occurred among the infirm elderly who were residents of long‐term care facilities. (2)

Did aggressive lockdowns stave off the worst‐case scenario, preventing vulnerable states from becoming disaster areas like New York City? No controlled experiment will give us that answer. Pennsylvania makes the best case for that argument, with an early excess death pattern that resembled its neighbors in the Northeaster corridor but saw that rate drop precipitously by early April.—. But Pennsylvania is also an unusual geographic unit, with its largest city, Philadelphia, lying on the coast and separated from the western part of the state and its second largest city, Pittsburgh, by the Appalachian Mountains. This anomaly makes it difficult to draw clear conclusions from Pennsylvania’s Covid19 curve.

4. Age effect: elderly. One universally accepted fact of the Covid19 pandemic is that the death risk is highest among the elderly. The all‐cause death numbers show this effect clearly, with a stark increase in deaths among those 65 years and older beginning in late March, peaking in early April and then turning sharply downward in May, so that by month end the excess death rate has almost disappeared. (1) Tens of thousands of excess deaths in this age group have driven a large

page7image17636240 page7image17635792

portion of overall US excess deaths.

Adults between 18‐64 years of age show a similar pattern in excess deaths as the elderly, although the overall death toll has been less. (1)


With a dataset that provides more detailed age groupings, the impact is even more clear: the older the age cohort, the more total deaths increased during the pandemic. (3) The largest number of deaths as well as increases in deaths occur in those aged 85 years old and older, followed by those aged 75‐84, next by the age group from 65‐ 74. The sole remaining group showing an increase in deaths during the pandemic was the group aged 55‐64, with a modest increase in deaths during April. For all age cohorts with ages under 55, the impact of the pandemic is undetectable.

Most observers believe they understand this age effect and discount it. That older people die more frequently is no excuse not to protect them from the pandemic. But as we have deployed lockdowns as a blunt instrument to protect the elderly from a tragic and premature loss of life‐years, we have missed a completely unintended and beneficial benefit of the lockdowns: an unexplained collapse in excess deaths among the young, especially children and infants.