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Free States Maintain Survival

Advantage Over Locked States

Even After Restrictions Ease

© Colleen Huber, NMD

June 29, 2020

This update of my previous paper, "Lockdowns Failed to Reduce Deaths," finds that locked US states not only had more deaths at the time of lockdown, but now, even after some lockdowns lifted, the states that never locked down maintain a survival advantage.
Colleen Huber.2013.09.cropped.jpg

Table 2: Week ending 6/26/2020


We see that over the last seven weeks of easing of lockdowns, the average factor by which the percentage of all expected deaths are higher in locked states as a group than in free states as a group has stayed fairly consistent, between 1.08 and 1.11. 


The locked states as a group averaged an 8% to 11% higher percentage of deaths over their own previous years’ records than the free states did. This is expressed in the following tables and summarized in Graph 1, showing free states vs neighboring locked states vs all states, from tables in Endnote 11.


Let's now compare the 6 free states with 44 locked states from today’s (the day of this writing) CDC data (now including Wyoming, because June 10, 2020, is the first date of mortality data for Wyoming in the CDC tables.)  That comparison is in Tables 3a and 3b.


Table 3a: Percent of expected deaths for free states and neighboring locked states


Table 3b: Percent of expected deaths for all locked states


* The CDC counts New York City data separately from the rest of New York State.  This was considered in the average, as if New York City were a different state.  The CDC also includes data from Washington, DC.  Therefore, there are 6 states on the left, and 44 states plus two cities, NYC and DC, on the right.


As lockdowns ease, and conditions in formerly locked vs free states begin to resemble their own previous years’ conditions, these different percentages would be expected to gradually converge toward 100% for each state, and Graph 1 suggests that this has begun to happen, although it may be already too late in 2020 for those percentages to converge completely by the end of the year.   

Graph 1


We now see that not only comparing neighboring states, free vs locked, but now looking at the entire United States, there is a consistent pattern:  Free states show not only fewer than expected deaths during each week than previous years at the same times, but also free states in Spring of 2020 had a distinct survival advantage, and significantly lower mortality than locked states, when each state is compared with its own previous record.  The factor by which locked states’ mortality change (as percent of expected) exceeded free states’ mortality change (as percent of expected) was consistently positive and by a factor of 1.08 to 1.11.





Because the free states did not have increased deaths from their data in previous years, but their neighboring locked states did average increased deaths over the free states from their data in previous years, by a factor that stayed within the narrow range of 1.08 to 1.11 through the seven weeks including the end of, and the easing of lockdown in most states, we can therefore conclude with certainty that lockdown did not reduce deaths in the US.


In fact, free states had decreased deaths from their data in previous years, but locked states on average did not have decreased deaths from their data in previous years.  Therefore, we can conclude with certainty that lockdown did not reduce deaths.  How is this conclusion certain?  Because if a popular hypothesis is that A caused B (lockdowns caused reduced deaths), but we then learn that B never happened, then we can confidently surmise that A definitely did not cause B.  Causation is very hard to prove, but lack of causation is very easy to prove, particularly when the effect never happened.  We can be certain that A did not cause B, if we see that B never happened at all.  Lockdown did happen in most US states, including the states surrounding the free states, which I examined.  However, deaths were not reduced in those locked states, neither in comparison to their own historical mortality data on average, nor in comparison to their free neighbors.  Total deaths from all causes were not reduced in the locked states, as we see from the above data. 


This paper examined CDC data to determine whether reduction in deaths happened in lockdown states.   That did not happen; therefore, there is nothing, including lockdowns, that has caused it to happen.


The conclusion and its supporting data impact future assessments of whether lockdown was an optimal strategy of state governments. A failure of lockdowns to reduce deaths must in the future be considered when weighed against the considerable damage, including political, economic, humanitarian, social and psychological damage, caused directly by lockdowns.  In fact, some of these harmful societal impacts have likely resulted in the deaths that we see from the data shown have been more prevalent in the locked states. 


Society’s response to the phenomenon of COVID-19 led to the loss of 30 million to 40 million jobs in the US alone. (6)  The US unemployment rate rose to 14.7%. (7)  Unemployment’s adverse effects are known to reverberate through families and communities and business sectors, and must be considered in the future, if lockdown is ever proposed again.   The consistently worse (by 8 to 11%) mortality results that I showed in locked states over free states likely reflect the life-threatening consequences of mass unemployment.  In fact, many of the locked states are currently at risk of locking down again, even though the damage that those states have already incurred from lockdown is clear from this study.    


Civil liberties concerns are also paramount to those who value those liberties perhaps as highly as their own lives, aware of wars throughout American history and world history that were fought in defense of or to establish the same.   Those liberties were challenged, curtailed and violated to various degrees throughout the US, as a consequence of lockdowns.  Therefore, lockdowns had historic and far-reaching social, political and economic effects, but they did not reduce deaths, and therefore cannot be justified now or in the future.  The timeframe of this study is limited, however, and a more thorough assessment of lockdown impact on mortality would be obtained by a study of more weeks than the seven examined herein.



This paper shows seven weeks of mortality data during and following the gradual easing of lockdown in most US states during the spring of 2020.  There is a consistent history among those weeks with regard to the following:  States without lockdown, herein “free states,” have had a lower percentage than states with lockdown, herein “locked states,” of total deaths from all causes in these weeks in 2020, compared to the same weeks for each of the states in the years 2017 to 2019.  This difference holds for both of the following comparisons: free vs locked states that are immediately surrounding free states, as well as free states compared to the average results of all locked states in the US.


Each free state had fewer deaths in comparison to its own record of recent years. 

Locked states averaged more deaths compared to their own records of recent years.

These are holding true even after most lockdowns have eased or ended.

This information has implications for the impact of lockdowns on COVID19 deaths in comparison to the impacts of lockdown as a life-threatening event in itself.



US Centers for Disease Control and Prevention (CDC) data from weeks ending May 15, 2020 through June 26, 2020 show consistency over each of those seven weeks in the following data.


Five US states: Arkansas, Iowa, Nebraska, North Dakota and South Dakota, did not lock down, and submitted mortality data to the CDC.  These states are the control group, herein “free states” in the mass human experiment of society-wide lockdown in the United States, in the spring of 2020. 


There are other states that have special situations.  Wyoming also did not lock down, but the CDC had not posted complete mortality data for Wyoming until June 10, 2020, so I exclude Wyoming in most of the following weeks; however, June 12 through 26, 2020 data for Wyoming is included in the June 12 through 26, 2020 tables (Table 5-7).    Also, Utah and Oklahoma did not impose lockdown at the state level; however, lockdown was imposed in their most populous jurisdictions, so I group Utah and Oklahoma with the locked states.  USA Today lists states that locked down, opened up and the dates for each. (1)  That article shows that almost all states locked down during the last 10 days of March, 2020.  Most states began re-opening during the first three weeks of May, 2020.  The CDC shows peak COVID-19 deaths as occurring in mid-April 2020 in this table. (2)


For comparison with the five free states, I also look at CDC mortality data of the immediately neighboring states, with which the free states share long borders.  These are respectively, Mississippi, Louisiana, Missouri, Oklahoma, Minnesota, Wisconsin, Illinois, Kansas, Colorado and Montana.  These are the states in the immediately surrounding experimental group, herein “locked states.”


This paper will examine CDC data to determine whether reduction in deaths happened in US states that locked down. 

Many have asked, Why did governors of certain states choose to lock down, while others chose not to?  Almost all state lockdown orders were imposed by the end of March, 2020, when it was still much too early to know either any data regarding the epidemiology of COVID-19 or to be able to predict the future course of the still unfamiliar phenomenon of this novel coronavirus.


Lockdowns were imposed by many jurisdictions for the stated purpose of limiting movement, activities and commerce of individuals and businesses, for the goal of limiting COVID-19 incidence and mortality.  It was widely hoped this would work for that purpose.  However, outside of the US, it was found that mortality actually increased steeply closely following lockdowns. (3)  Also, it was found that in Europe, “no lives were saved” by lockdown. (4)  In an early analysis in the US also, it was not found that lives were saved by shutdown. (5)  Those last two analyses were relatively early, 4/24 and 4/26/20 respectively, before it was clear that COVID-19 incidence, hospitalizations and deaths had peaked.


This study is likewise of a limited time frame, the seven weeks of the decline of lockdown, the American perestroika, one might say, of re-opening.  Through the seven weeks of this study there is stark and consistent contrast of mortality in free vs. locked states.



In this study, I examine whether lockdowns succeeded in reducing total deaths, and whether that data is consistent over the seven weeks immediately following when most lockdowns through the US began to ease.  In order to answer the question of whether lockdowns succeeded in reducing mortality, it is most helpful to look at all deaths, because total deaths are more precisely enumerated than deaths from any specific cause, due to common multiple co-morbidities.


I chose not to look at COVID-19 deaths in this study for a number of additional reasons, including the following:


  1. The very questionable applicability of the manufacturing technique, the reverse-transcriptase / polymerase chain reaction technique, now used throughout the world as a test for presence of an infectious agent; and

  2. The 80% false positive rate of this “test” in the diagnosis of COVID-19; and

  3. The arbitrary number of iterations of this “test” that have been selected to produce a positive result; and

  4. Instructions given to physicians by the CDC to code cases as COVID-19 deaths including presumptively; and

  5. Controversy regarding higher Medicare reimbursement for COVID-19 patients ($13,000) than for flu patients ($5,000), which may have skewed reported cause of death on death certificates; and

  6. The possibility that there may be emergency aid incentives and/or political influences in altering the true number of deaths from COVID-19; and

  7. If COVID-19 is genuinely the deadly pandemic that it is widely thought to be, then total deaths in any jurisdiction would be greater during the period of its peak incidence and closely following weeks.It is not possible to have a deadly pandemic rage through a population without increasing the total number of all-cause deaths over the weeks of its peak incidence.Therefore, if deaths are not significantly increased above previous years for a given region, then there has been no pandemic, nor even an epidemic there.



Therefore, it is most useful and most accurate to look at total deaths in each state, both in free states, the control group, as well as in locked states, the experimental group.


The CDC shows a percentage of deaths in each state compared with the same week in previous years.  This percentage for each is described by the CDC as follows:


“Percent of expected deaths is the number of deaths for all causes for this week in 2020 compared to the average number across the same week in 2017-2019.”


The CDC compares each of the states, free and locked, to their own mortality history from 2017 through 2019.  Let’s then compare those two groups to each other.


The CDC tables from which the numbers in this study were derived are screen-printed in this endnote.   These tables are from the following Fridays: May 15, May 22, May 29, June 5, June 12, June 19, and June 26, 2020.


The above-mentioned CDC tables are the entire source from which all calculated data in this paper is derived.  No other source is used, and all derived data may be verified by the reader with a simple calculator.


The first five tables may be found in the earlier version of this paper.  The following two tables show data for the remaining weeks ending 6/19/2020 and 6/26/2020 respectively.  Together all seven tables show a comparison of free vs locked states, regarding each state’s mortality for that week as a percentage of the same week in the years 2017 to 2019.  These are shown for each of the last seven weeks.  The tables show comparison of % expected deaths of the total of the free states with the total of their neighboring locked states, control group vs experimental group, over each of those weeks.

Table 1: Week ending 6/19/2020

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