Lockdowns failed to reduce deaths in the US
May 27, 2020
The COVID19 era is characterized among other things by lockdowns in countries around the world and in US states, imposed by their governments, attempting to limit movement, activities and commerce of individuals and businesses, for the stated goal of limiting COVID19 incidence and mortality.
In this paper, I examine CDC data regarding the COVID19 deaths in US states that did not have lockdowns (the control group), herein “free states,” compared to neighboring states that did have lockdowns (the experimental group), herein “locked states.” I examined neighboring states that share long borders, rather than touching at only corners or short segments, and then I examine neighboring states, free vs lockdown, that have similar population density.
The control group showed a lower percentage of COVID19 deaths compared to total deaths than the experimental group. This finding was consistent over the week prior to and including the date of this writing, May 18 to 27, 2020. CDC states’ data was updated daily over this time, except on the weekend. The data in this paper reflects the latest data as of the date of this writing: 5/27/2020.
Moreover, deaths from all causes, as percent of expected deaths for this time of year, are lower in free states than in neighboring lockdown states.
Effectiveness of universal quarantine in disease control is apart from questions of grave concern regarding civil liberties violations, as well as breaking with the historical precedent of quarantining only sick people. Any “quarantine” of well people, in fact all of a given population, was previously known only by its more familiar name, martial law.
Political events created a control group of free US states, as well as an experimental group of US states that did lock down. I compare these two groups in this study with respect to COVID19 mortality and overall mortality.
For the purpose of working with CDC data, this paper does not challenge the popular assumption that COVID19 is a unique infectious agent, even though researchers have not agreed on distinct features of this particular coronavirus. Nor have researchers yet satisfied Koch’s postulates for isolation, purification and verification of this virus.
The COVID19 Case Fatality Rate (CFR) = 0.26% in the US. That is, approximately one of every 385 individuals who are infected with COVID19 die of the same disease. Data from the CDC in late May 2020 show that COVID19 cases and fatalities peaked in mid-April 2020. Thereafter, daily COVID19 deaths and hospitalizations declined steadily through the first three weeks of May 2020, by 2.7% and 3.2% per day respectively. 
All of this information must be strongly tempered by the nature of what is commonly called “the COVID19 test.” It has been assumed, almost with religious certainty, that this reverse transcriptase, polymerase chain reaction manufacturing technique is the only or best way to test for COVID19 infection. In fact, that technique was not designed for diagnostic purposes at all, and its designer, Dr. Kary Mullis, had specifically cautioned not to use it to diagnose infectious disease. A further problem with the COVID19 test has been the assigning of an arbitrary number of iterations to produce a positive result. This has led to magnified errors with each iteration, such that the RT-PCR test applied to COVID19 has been found to have an 80% false positive rate, making it nearly useless for this application. Despite these problems, “the COVID19 test” was adopted quickly in the US and around the world. Suspicion of test results have been rife since the beginning, famously highlighted when the President of Tanzania and Chemistry PhD John Magufuli submitted specimens from a goat and a piece of fruit, each submitted for testing with human names. Both samples were then declared positive for COVID19 infection.
Much criticism has been made of testing methods and declared values for incidence and mortality. Notably, many microbiologists and physicians have publicly criticized the daily US COVID19 death counts announced by a portion of the US media, which have exceeded the CDC’s daily US COVID19 death counts by over 20,000 deaths on each day (76,874 by the CDC, but “nearly 100,000” by CNN, both updated today, 5/27/2020).
Much concern has focused on the economic devastation of lockdown, a unique historical experience, unprecedented and unlike any of our ancestors’ approach to disease. Never in human history have well people been quarantined on a large scale, for the purpose of disease prevention. Martial law had in the past been acknowledged as politically, not medically, motivated.
As a result of this quarantine, in the United States, 11.1% of Americans lost their jobs in only 7 weeks, now 14.7% of the active US labor force. By comparison, in the Great Depression, 10.4% of Americans lost their jobs over a 4-year time span, 1929 to 1933, 25.6% of the then active labor force.   Unemployment is known to have public health consequences.
There were, remarkably, six US states in this COVID19 era where lockdown was not ordered by the governors. The other 44 states had lockdown. I examine the differences in COVID19 mortality among them. The 6 free states provide a useful control group. Their neighboring states that did have lockdown provide a useful experimental group for us to study.
The states that did not have lockdown imposed by their state governors in early 2020, while the rest of the US did, herein, “free states,” are:
Arkansas, Iowa, Nebraska, North Dakota, South Dakota and Wyoming, herein AR, IA, NE, ND, SD and WY.
Data for Wyoming is not updated at the CDC at this writing, so I will exclude WY.
The free states share long borders with the following lockdown states respectively:
Mississippi, Louisiana, Oklahoma, Missouri, Minnesota, Wisconsin, Illinois, Kansas, Colorado, and Montana, herein MS, LA, OK, MO, MN, WI, IL, KS, CO, MT.
So I compare data from:
AR with MS, LA, OK & MO,
IA with MN, WI, MO & IL,
NE with KS & CO, and
ND & SD with MT & MN.
And then, because they have exactly the same population density, 57 people per square mile as of 2018, I separately compare Arkansas with its neighbor Oklahoma, as well as another comparison of states with similar population density.
Because of the inappropriate nature of “the COVID19 test,” it is especially important to also compare all deaths in free states vs lockdown states. I include that analysis as well.
Table 1 below shows percentages derived from CDC data, updated as of the day of this writing.
We can see that COVID19 deaths, as a percentage of total deaths, are over 3 times higher, on average, in locked down states than in free states.
Table 2, is the May 27, 2020 CDC table of state-by-state mortality, in 3 parts, https://www.cdc.gov/nchs/nvss/vsrr/COVID19/ from which the calculations in Table 1 were derived. Those calculations may be verified by simple division, Column 2 / Column 3 of this CDC table.
Some variation in mortality data among states may be expected due to varying population density among the various states studied. However, all states considered have rural, suburban and urban areas and populations.
We will compare below free states vs locked states of similar population density.
Table 3 shows population density for all of the states studied, as of 2018.
The above states have wide variation in population density, both within states and from one state to its neighboring state, as with most states. However, of the states considered, two have the same population density. Both Arkansas and Oklahoma have 57 people per square mile, and share a long border. The former is free, and the latter is locked.
Table 4 compares Arkansas and Oklahoma data.
Table 5 compares data among states with population density between 53 and 57. The remaining states studied are widely divergent in population density, from 7 to 231.
Of the states with comparable population density in the mid-50’s, the free states Arkansas and Iowa averaged 1.95% COVID19 deaths of all deaths. Whereas, the lockdown states of Oklahoma and Colorado averaged 5.1% COVID19 deaths of all deaths. So these two lockdown states had more than twice the COVID19 portion of total deaths of the two comparable free states, in fact 260% higher.
Let’s also address the problem of the inappropriate test that was discussed above used to certify cases and deaths as COVID19. To eliminate this problem, let’s look at total deaths in the free states vs the neighboring lockdown states.
Table 6 compares the percent of expected deaths the past week for this time of year in the free states with that of their neighboring lockdown states. All of the free states show lower than expected deaths (<100%) for the past week for this time of year. These figures are taken from the 4th column of Table 2 at the same CDC website, https://www.cdc.gov/nchs/nvss/vsrr/COVID19/ 
The factor by which % of all expected deaths over the reported period are higher in the locked states than in the free states is 1.1. That is, locked states’ percentage of all expected deaths averages 10% higher than in the free states.
The proportion of COVID19 deaths to all deaths is lower on average in the states without lockdown, the control group, than in the states with lockdown, the experimental group. This held true also in states with the same population density.
Also, the percent of expected deaths, for the COVID19 period compared to previous years of the same season, from all causes, is as of this time lower in the free states than in the lockdown states after about two months of lockdown.
Quarantine of an entire state population, for disease control purpose, is an experiment without historical precedent. The stated goal of quarantine of the well population was purportedly to reduce mortality from COVID19.
CDC data proved the experiment failed. Both COVID19 death rates were lower, and overall deaths were lower than expected in the free states than in neighboring lockdown states.
Further damage from society-wide quarantine, commonly known as martial law, is economic devastation from loss of employment and loss of small and medium-sized businesses. The collateral damage of suicides, alcoholism and other substance abuse, anxiety and depression from this debacle are not yet measured, nor yet measurable in full.
Therefore, having failed in its stated goal, and having caused widespread violations of civil liberties and human rights, as well as economic and social havoc and widespread suffering, universal quarantine against infectious disease should not ever be repeated.
Corresponding author: Colleen Huber, NMD
Mail to: 1250 E. Baseline Rd., Suite 205, Tempe, AZ, USA 85283
Objective: As the prevention and control of COVID-19 continues to advance, the active nucleic acid test screening in the close contacts of the patients has been carrying out in many parts of China. However, the false-positive rate of positive results in the screening has not been reported up to now. But to clearify the false-positive rate during screening is important in COVID-19 control and prevention. Methods: Point values and reasonable ranges of the indicators which impact the false-positive rate of positive results were estimated based on the information available to us at present. The false-positive rate of positive results in the active screening was deduced, and univariate and multivariate-probabilistic sensitivity analyses were performed to understand the robustness of the findings. Results: When the infection rate of the close contacts and the sensitivity and specificity of reported results were taken as the point estimates, the positive predictive value of the active screening was only 19.67%, in contrast, the false-positive rate of positive results was 80.33%. The multivariate-probabilistic sensitivity analysis results supported the base-case findings, with a 75% probability for the false-positive rate of positive results over 47%. Conclusions: In the close contacts of COVID-19 patients, nearly half or even more of the ‘asymptomatic infected individuals’ reported in the active nucleic acid test screening might be false positives.