Once something becomes a habit, it can be hard to break. So it has been with the array of restrictions governments imposed in response to the Covid-19 pandemic. What were initially billed as short-term measures to “flatten the curve” morphed into something much bigger and longer-term: comprehensive policies altering nearly every aspect of our lives, imposed by the local premier, governor, or top health official with little reflection and only the barest legislative oversight. “Lockdowns” quickly became conventional wisdom and the accepted ideology of nearly every societal elite. And with many lockdowns or key elements lingering even today, they proved anything but short term.
While aimed at fighting the virus’s spread, the interventions imposed a massive toll in areas including global hunger, domestic abuse, mental and physical health problems, suicides and bankruptcies. Despite these grim consequences and, more recently, the accelerating pace of vaccinations and the gratifying reduction in deaths from Covid-19, many North American governments remain reluctant to ease the restrictions. Prime Minister Justin Trudeau mused lately that the Canada-U.S. land border would reopen “eventually,” while some public health figures are now calling for a third lockdown.
Before we – again – do anything that drastic, we need to pose an important question: Did the lockdowns actually work? Not merely in the sense of keeping people at home and convinced that their governments were doing something; but in actually altering the course of the virus through the population. This should be a crucial matter of interest to every citizen and politician. It is key to rationally assessing the costs and benefits of imposing similar social and economic policies during the next serious epidemic.
So, just how effective have all these restrictions been in containing the Covid-19 pandemic?
Given the nature of the pandemic and the political response to it, no controlled experiment can be conducted to determine the causal impact of different governmental interventions. We are limited to drawing inferences exclusively from observational analyses. The collected data must be reviewed on a post hoc basis with a few rough checks in place. The following review is, accordingly, not a strict scientific analysis. Nevertheless, being cautious in its conclusions, it seeks insights into the relationship between differing governmental regulations in selected U.S. states and the spread of Covid-19 infections and deaths.
Covid-19-related state-level regulations and measures were gathered and examined in their temporal relationship to the pandemic’s development, reflected in the case and death statistics (daily and total) in two pairs of U.S. states. Each pair of states is broadly comparable in climate, population, urbanization and economic characteristics, but is contrasted in the degree of severity of its statewide rules.
Minnesota’s first lockdown was justified by an epidemiological model from the University of Minnesota School of Public Health and the state Department of Health which anticipated, even with significant mitigation, a death toll of 50,000-55,000 by the end of June 2020.
Two are mid-sized, adjoining Midwest states: Minnesota and Wisconsin. Minnesota had a hard and extended lockdown (many schools are still not open, for example), while Wisconsin had a short lockdown followed by moderate restrictions. The other two are southerly coastal states – California and Florida. California has had a hard and ongoing lockdown, while Florida has sought every opportunity to ease restrictions and reopen. Two other seemingly suitable cases were omitted: New York, a hard-lockdown state, because of its unique circumstances (including heavy mass-transit use in its largest city, and its deadly nursing home scandal), and South Dakota, North America’s only jurisdiction to remain fully open throughout the pandemic, because of its small and non-urbanized population.
There is an array of uncontrollable or unmeasurable variables related to the pandemic’s course, the public health response, the political response and the nature of the studied states that further complicates state-by-state comparison, increases uncertainty and, hence, lowers the confidence of conclusions. The process requires making a number of important assumptions. Among these are the accuracy of Covid-19 testing, the accuracy of case and fatality counts, and the state-to-state and temporal consistency of lockdown enforcement. The key assumptions are discussed in the Appendix.
Because the pandemic is ongoing, the observed trends are accurate to mid-March 2021. There is no intention to forecast the pandemic’s future course.
Timeline
With the assumptions in mind, and with due respect for uncontrollable and/or unknown factors, the foundation for the four-state comparison is a summary timeline of the critical Covid-19-related decisions made in each state, along with a snapshot view of each state’s key characteristics, presented in pairs. Following the timeline are graphs depicting the daily change in Covid-19 cases and deaths, along with the timing of key state orders. The first pair of states examined is Minnesota and Wisconsin, followed by California and Florida.
Minnesota | Wisconsin | |
Population | 5,639,632 | 5,822,434 |
Location (centre of state) | 46.7° N, 94.7° W | 43.8° N, 88.8° W |
Climate | Humid continental 19.3°C; -10.9°C | Humid continental 19.3°C; -8.2°C |
2019 total GDP (US$ billion) GDP per capita (US$) | $332 $60,066 | $299 $52,534 |
Type of economy | Agricultural | Agricultural |
Largest cities | Minneapolis – 439,012 St. Paul – 310,368 Rochester – 122,711 Duluth – 85,142 | Milwaukee – 587,721 Madison – 263,332 Green Bay – 104,068 Kenosha – 100,016 |
Governor’s party | Democratic | Democratic |
Table 1: Minnesota vs. Wisconsin: Key geographical and economic characteristics.
Minnesota
March 15, 2020: Governor Tim Walz issues order (20-02) shutting down schools, which is extended (20-19 on March 25, 20-41 on April 23) to keep schools closed for the rest of the school year.
March 25, 2020: Walz issues a stay-at-home order (20-20) – a lockdown – requiring all workers who can do so to work from home and to close down non-essential business. It is justified by an epidemiological model presented by the University of Minnesota School of Public Health and the state Department of Health. This model anticipates, even with significant mitigation, a death toll of 50,000-55,000 by the end of June. The stay-at-home order is reissued on April 13 (20-35) and April 30 with modifications (20-48) to last through May 17.
May 13, May 23, May 27 and June 5, 2020: Walz signs several executive orders (20-56, 20-62, 20-63, and 20-74) aimed at gradually re-opening non-critical businesses. Specifically, order 20-62 allows places of worship to open at 25 percent capacity.
July 22, 2020: A statewide mask mandate (20-81) is announced requiring face masks in all indoor spaces where people congregate.
July 30, 2020: Safe Learning Plan for the 2020-21 School Year is implemented, allowing families to choose between in-person and distance learning.
November 19, 2020: Walz initiates a Four Week Dial Back plan (akin to a lockdown) banning social gatherings by members of different households. All restaurants, pubs, gyms, studios, cinemas and other public buildings are closed for in-person service. Places of worship are “encouraged” to offer virtual alternatives.
December 14, 2020: Walz signs executive order 20-103 easing the extreme restrictions and allowing indoor social gatherings of up to 10 people with no more than two households. Outdoor social gatherings of up to 15 people and three households are also permitted. The subsequent two executive orders (21-01 on January 6 and 21-07 on February 12) further relax restrictions so that gyms, public pools, restaurants and bars would also open with various capacities.
February 12, 2021: Stay Safe Plan is announced reinforcing Walz’s previous orders on gathering restrictions and partial business operations.
March 15, 2021: Stay Safe Plan is modified, easing the restrictions: 15 people are allowed indoors, 50 people outdoors; limits on business operations are lifted further, but not fully.
Wisconsin
March 13, 2020: Governor Tony Evers instructs all schools to close for public instruction. According to the order issued on April 16, they are to remain closed for the rest of the year and through the summer.
March 20: 2020: Evers issues an order banning social gatherings of any size.
March 24, 2020: Evers signs the Safer-at-Home (stay-at-home) order permitting only essential activities and operations in the state. This order is reissued on April 16 to last through May 26 and modified on April 20 to begin easing the restrictions (Badger Bounce Back plan).
May 13, 2020: Evers’ Safer-at-Home order is overturned by the Wisconsin Supreme Court, which calls it “unlawful, invalid, and unenforceable,” allowing businesses to reopen immediately. Henceforth, decisions regarding lockdowns and limits on social gatherings are made regionally. Some counties, like Dane County, choose to extend the lockdown through May 26.
August 1, 2020: Evers declares a statewide mask mandate. It is extended on September 22 to November 21, receiving harsh criticism from Senate Republicans.
October 6, 2020: The Department of Health Services, with Tony Evers and Andrea Palm as the Secretary-designee, announces a statewide order to limit indoor gatherings to 25 percent of capacity or 10 people in places without an occupancy limit. The Tavern League of Wisconsin files a lawsuit against this order, and the 3rd District Court of Appeals blocks the order on October 23, ceasing its effect on November 6.
November 20, 2020, January 19 and February 4, 2021: Evers re-issues the statewide mask mandate.
Minnesota-Wisconsin Summary: Since the beginning of the pandemic, Minnesota imposed stay-at-home orders for 54 days, social gathering restrictions for nearly 300 days, severe social and business restrictions for 29 days and school closure from March 15, 2020 through the end of that academic year, with only kindergarten through grade 2 reopening in September. A complete return to in-person learning was not authorized by the state until mid-January.
In contrast, at a state level Wisconsin implemented a stay-at-home order for 28 days and social and business restrictions to various degrees for 61 days. The strictest order on social gatherings (akin to stay-at-home rules) lasted for 31 days. Similar to Minnesota, Wisconsin’s schools were closed from March 13 until the end of the academic year. Since September, local authorities have been authorized to choose between virtual and in-person learning for all grades; the Legislature’s state budget committee plan of February 10 intends to penalize schools that continue to stay closed by limiting funding.
Altogether, throughout the past year Walz has issued 112 executive orders related to Covid-19, while Evers’ cabinet issued 46 orders. As noted above, Evers’ authority to impose statewide measures was limited by the Republican Legislature majority following the Wisconsin Supreme Court’s ruling of May 2020.
California | Florida | |
Population | 39,512,223 | 21,477,737 |
Location (centre of state) | 36.8° N, 119.4° W | 27.7° N, 81.5° W |
Climate | Ranges from polar to subtropical 23.0°C; 7.9°C | Ranges from humid subtropical to tropical 27.2°C; 15.2°C |
2019 total GDP (US$ billion) GDP per capita (US$) | $2,743 $70,662 | $946 $44,267 |
Type of economy | Industrial | Industrial |
Largest cities | Los Angeles – 3,983,540 San Diego – 1,427,720 San Jose – 1,009,340 San Francisco – 883,255 | Jacksonville – 929,647 Miami – 478,251 Tampa – 404,636 Orlando – 290,520 |
Governor’s party | Democratic | Republican |
Table 2: California vs. Florida: Key geographical and economic characteristics.
California
March 11, 2020: Governor Gavin Newsom introduces limits on social gathering and cancels large events (N-25-20).
March 19, 2020: Statewide stay-at-home order (N-33-20) is issued, enforced by a US$1,000 fine, up to six months’ imprisonment or both. Statewide, schools are closed starting March 23 until year-end. Churches are closed.
May 8, 2020: Restrictions are partially lifted, allowing Stage 2 “lower-risk” workplaces (e.g., bookstores, clothing stores, florists) to open, in accordance with State Report Card. On May 18, Stage 3 businesses (e.g., office spaces, counselling services in places of worship, curbside libraries) begin to open.
July 13, 2020: Newsom signs a new order (akin to stay-at-home) that demands all counties close indoor operations of restaurants, bars, wineries, museums, zoos, movie theatres and other entertainment businesses. In 80 percent of counties, representing the state’s “targeted engagement list,” places of worship, indoor malls, fitness centres, hair salons and offices for non-critical sectors are also closed.
June 18, 2020: California begins following the universal masking guidance announced by the federal Department of Public Health.
August 28, 2020: Newsom initiates Blueprint for a Safer Economy, a plan for ostensibly lifting restrictions. Under this plan, however, 80 percent of California falls within a “Widespread” (highest-risk) zone, which implies that the most severe restrictions are still to be followed.
September 29, 2020: Most of California’s counties shift to a “Substantial” (second-highest risk) zone of restrictions. Public schools are permitted to open for some on-site classes, under guidelines. Restaurants, gyms, movie theatres and churches are also allowed to open at 25 percent capacity.
November 10, 2020: Newsom re-imposes the “Widespread” regulations in most counties. This coincides with the infamous French Laundry incident when, flouting his own regulations, Newsom joins a party of 12 from six different households for an indoor birthday celebration at a luxurious Napa Valley restaurant.
November 21, 2020: Newsom introduces a nighttime curfew for counties under the “Widespread” regulations.
January 25, 2021: Nighttime curfew and stay-at-home orders are lifted.
March 12, 2021: Most of the state’s counties shift to “Substantial” restrictions, allowing business operation at 25 percent capacity.
Florida
March 17, 2020: Governor Ron DeSantis issues an order (20-68) directing all bars and nightclubs selling alcoholic beverages to close, beaches to have no more than 10 people per party and restaurants to limit occupancy to 50 percent.
April 3, 2020: Safer at Home (i.e., stay-at-home) rules (20-91) are introduced directing Floridians to limit their travel to essential activities. “Essential” activities are specified to include attending religious services, participating in recreational activities, caring for loved ones and taking care of pets. Florida’s schools are ordered to close, switching to distance learning and remaining closed to the end of the academic year, with the subsequent reopening in August 2020. This order excludes Miami-Dade, Broward and Palm Beach counties, where decisions are left to be negotiated locally.
April 29, 2020: DeSantis initiates Phase 1 of the Safe. Smart. Step-by-Step. Plan for Florida’s Recovery (20-112). This order is subsequently modified several times, lifting restrictions in stages for barbershops and hair salons (20-120) and allowing restaurants, retail stores, museums and gyms to open with 50 percent capacity (20-123). Miami-Dade, Broward and Palm Beach counties, representing approximately 30 percent of Florida’s population, are excluded.
June 3, 2020: DeSantis signs the order to begin Phase 2 of the Safe. Smart. Step-by-Step. Plan for Florida’s Recovery (20-139), again excluding Miami-Dade, Broward and Palm Beach counties. Bars selling alcohol and movie theatres are allowed to resume operation at 50 percent of capacity.
September 25, 2020: DeSantis continues with the Safe. Smart. Step-by-Step. Plan for Florida’s Recovery, announcing the start of the final Phase 3 (20-244). This order states: “No COVID-19 emergency ordinance may prevent an individual from working or from operating a business.” Any restrictions on restaurants and other businesses are lifted, allowing full capacity. In Miami-Dade, Broward, Palm Beach and a few other counties, local restrictions continue. Nonetheless, DeSantis’ order prohibits locally-imposed penalties for non-compliance with mandatory masking and social distancing.
California-Florida Summary: Overall, California experienced the severest statewide restrictions, staying in lockdown for 51 days, in near-lockdown for over 120 days and under nighttime curfew for approximately 75 days. Less restrictive rules lasted for about 50 days in total. Schools have not been open consistently in the new year given the state’s shift to the strictest restrictions in November and December.
Florida’s state-at-home rules lasted for less than one month, its definition of “essential” activities was the broadest, and the state has been continuously opening up since late April 2020, although some cities and counties have resisted state policies.
Altogether, Newsom issued 92 Covid-19-related executive orders, in contrast to DeSantis who signed 42 orders. By mid-March 2021, a drive to trigger a recall election of Newsom had generated 2.1 million signatures.
In September 2020, Governor DeSantis announced Phase 3 of the ‘Safe. Smart. Step-by-Step. Plan for Florida’s Recover.’ This order states: ‘No COVID-19 emergency ordinance may prevent an individual from working or from operating a business.’
Summary of Four-State Timeline
The timeline above demonstrates that California implemented the harshest restrictions, including statewide mask mandates, prolonged lockdowns, closure of schools, closure of churches and nighttime curfews. Minnesota is the next most restricted state, with a mask mandate and a stay-at-home order lasting for an extended period of time. The least restricted state is Florida, which only had brief periods of stay-at-home rules and some limits on social assemblies at the state level. Wisconsin is the second-least restricted state, with a statewide mask mandate, but short-term stay-at-home rules and selected limits on gatherings.
Trends in Daily Covid-19 Statistics and Relationship to Statewide Restrictions
Despite the obvious differences in Covid-19-related policies among the four states with respect to severity, specific measures taken and timing of the related orders, a general trend can be identified based on the graphs presented in Figures 1a-d below. Discussion follows the graphs.
Figure 1 (a through d): Daily Covid-19 cases (top) and deaths (bottom) in four U.S. states. Note that scale of Y-axis is different between the four states. (Source of graphs: The New York Times. Source of information in text bubbles: Author)
First, across the four states, there was a relatively stable count of daily cases from March through September – a weak “first wave” that was highest in Florida. This was followed in all states by a substantial climb in early autumn, typically steepening in October, with a successive peak between late November and January. The fall/winter peak was eventually followed by a steep decline through mid-March.
In Minnesota, the peak occurred on November 28 with 9,022 daily cases registered. In Wisconsin, the apex was reached on November 18 with a comparable magnitude – 8,510 registered cases. In much larger California, a record number of cases was registered twice, 60,941 on December 16 and 64,987 on December 26. In Florida, the peak occurred on January 8, although with fewer cases recorded – 19,530 (leaving aside January 2, which reflected two days’ results as 0 cases were recorded on New Year’s Day). Note, however, that there had been an earlier (though lower) peak in Florida’s daily cases, with 15,300 new infections registered on July 12.
Florida’s daily fatality count never exceeded 300 and its seven-day moving average peaked at 185, while California, with less than twice Florida’s overall population, recorded more than 700 daily deaths on numerous occasions and had a seven-day average of more than 500 daily deaths for much of January.
Second, the observed trend of daily deaths is very similar: Relatively flat from March to September (except in Florida), with a notable increase occurring in all four states between October and late January. In Minnesota the daily record of deaths reached 101 on November 27 (leaving aside an outlier in early March) and in Wisconsin it reached 135 on January 16. In California 724 deaths were registered on January 12, with the absolute record of 1,084 deaths being registered on February 24. Florida shows a slightly different trend, having the majority of deaths stretched over a longer period, from July through February, with two peaks, on August 11 with 276 deaths and on January 26 with 272 deaths. Interestingly, Florida’s daily fatality count never exceeded 300 and its seven-day moving average peaked at 185, while California, with less than twice Florida’s overall population, recorded more than 700 daily deaths on numerous occasions and had a seven-day average of more than 500 daily deaths for much of January.
Overall, the following relationships between the state rules and daily Covid-19 statistics are apparent:
- The stay-at-home orders, which varied greatly in intensity and duration (and, anecdotally, in enforcement severity) seem to have made no observable tangible impact on the daily Covid-19 cases and deaths. Further, the most severe restrictions, such as a prolonged lockdown and nighttime curfew implemented in California in November, did not prevent the subsequent December-January spike in cases or fatalities.
- Following imposition of statewide mask mandates, there was no observable change in the daily infections or deaths in Minnesota, California or Wisconsin, nor in Florida, which never imposed this regulation statewide.
- In contrast to the three other states, Florida experienced two distinct Covid-19 waves, while its daily Covid-19 cases and deaths grew less sharply during its cooler season and were distributed more evenly throughout the year. But does this trajectory translate into greater infection and/or death rates in Florida than in California or the other states? A review of the general statistics on Covid-19 cases and deaths might help answer this question.
Relationship between Statewide Restrictions and Total Case and Death Counts
This section examines the overall case and death counts as proportions of each studied state’s total population and its population of older people. The latter is particularly important because the Covid-19 mortality rate among people aged 65 and over is more than 62 times higher than among younger groups, and over 85 percent of deaths attributed to Covid-19 have occurred in the older population. The estimate of the risk of the disease, therefore, becomes more accurate if it is considered in relation to this most vulnerable group. The following table provides overall figures as well as rates by population and rates by population 65 and over.
Minnesota | Wisconsin | California | Florida | |
Total population (estimate as of July 2019) | 5,639,632 | 5,822,434 | 39,512,223 | 21,477,737 |
Cases | ||||
6,935 | 7,687 | 57,575 | 29,974 | |
Case rate by population (%) | 8.87 | 9.79 | 8.95 | 9.26 |
Death rate by population (%) | 0.12 | 0.13 | 0.15 | 0.14 |
Death rate (% of cases) | 1.39 | 1.35 | 1.63 | 1.51 |
Population aged 65+ (% of total population) | 919,260 (16.3) | 1,018,926 (17.5) | 5,847,809 (14.8) | 4,488,847 (20.9) |
6,205 | 6,735 | 42,608 | 24,760 | |
Death rate among people 65+ (%) | 0.67 | 0.66 | 0.73 | 0.55 |
Table 3: Total Covid-19 cases and deaths through March 17, 2021. Proportions of cases and deaths of total population and of older population. (Source of calculations: Author)
At first glance it appears that Minnesota, which implemented harder statewide restrictions than Wisconsin, did slightly better at flattening the case curve. As of March 17, 8.9 percent of the state’s population had been diagnosed with Covid-19 in Minnesota versus 9.8 percent in Wisconsin – about a 9 percent difference in the relative rates. Minnesota’s lower number of cases does not, however, correspond to a similarly lower death rate. In fact, the Covid-19 death rates of the total population in Minnesota and Wisconsin are nearly the same: 0.12 percent and 0.13 percent, respectively.
For the second pair of states, California and Florida, the percentage of the registered cases per total population is comparable – 9.0 percent in California, with more restrictions in place, and 9.3 percent in Florida, with fewer restrictions, which is a 3 percent difference. There is also a very similar proportion of Covid-19 attributed deaths: 0.15 percent of California’s population and 0.14 percent of Florida’s population succumbed to the disease.
The number of deaths can be translated into the fatality rate, which reflects the proportion of people who died having been diagnosed with Covid-19. In harder-lockdown Minnesota, deaths per registered cases have been virtually identical to less restricted Wisconsin (1.39 percent vs. 1.35 percent), while California is slightly higher at 1.63 percent than Florida at 1.51 percent.
In proportion to the total number of people aged 65 and older in each state, nearly 33 percent more people died in California than in Florida. This is remarkable given there is a significantly greater percentage of older people living in Florida than in California.
As for the older population, note first that across the four states, the percentage of Covid-19-attributed deaths among people over 65 is well below 1 percent. Minnesota and Wisconsin are nearly identical at 0.67 percent and 0.66 percent, respectively. In California and Florida, however, a key difference is apparent. In proportion to the total number of people aged 65 and older in each state, nearly 33 percent more people died in California than in Florida. This is especially remarkable given there is a greater percentage of older people living in Florida (21 percent of the total population) than in California (15 percent).
Taken together, this evidence suggests that:
- Despite restrictions of differing severity and duration, there is little difference in the total number of Covid-19 infections and deaths across the four states, respectively, averaging around 9.22 percent and 0.14 percent of each state’s total population. The fatality rate is also comparable, although it is somewhat greater in California and Florida than in Minnesota and Wisconsin. This difference does not seem to be related to the regulations that were imposed.
- Regardless of the state-by-state restrictions, the percentage of deaths of people 65 and older is under 1 percent in each of the four states, with Florida having the lowest rate. As well, the two least-restricted states had the two lowest death rates in this category.
- Regarding the original rationale for imposing lockdowns – to “flatten the curve” – the least restricted state, Florida, experienced an overall rate of cases and deaths comparable to the other three states. Paradoxically, Florida’s double-hump pandemic also forms the flattest trajectory of the four states.
Whatever policy choices Florida’s government made, or whatever luck the state benefited from, the least-restricted state, with the highest proportion of elderly, had arguably the greatest success in preventing the overwhelming of its hospitals as well as limiting deaths among its most vulnerable age group.
Implications and Conclusions
First, the trends do not show that the implemented regulations had no effect on the number of Covid-19 cases and deaths. To make such a definite claim would require a complex analysis with more controlled variables in place.
As well, the results do not insinuate that there is no relationship between reduced social activity and the pandemic’s course. There is evidence suggesting that reductions in social activities restrained Covid-19 case expansion and that those behavioural changes began prior to the state-issued orders. Apparently, people were willing to adopt safer habits on their own initiative and to cooperate in curbing the transmission of the virus even before state governors imposed regulations by decree. Hence, there is no reason to question social distancing, improved hygiene and other related practices as ways to control this virus’s spread.
Given the great hopes placed in lockdowns, and the lavish claims as to their benefits, one should expect the more restrictive states to have achieved decisively better performance by nearly any Covid-19-related metric – not the ambiguous, marginal, contradictory or even inferior results shown in this analysis.
The question is whether these benefits were significantly amplified through government restrictions or could have been achieved through voluntary measures, public information and local ordinances. In blunt terms: Did the lockdowns work, were they necessary and were they worth the staggering cost?
Clearly, Minnesota’s Walz was remiss to brag about his stay-at-home decrees, claiming in spring 2020 that “our actions have saved lives.” At that time, he had no evidence to support this claim, nor did other lockdown jurisdictions. Scientific evidence showing that such severe governmental interventions have made a significant difference in controlling this pandemic is not conclusive, and the debate remains open (see, for example, here vs. here and here). It is unlikely that the scientific community will be able to present a more decisive conclusion until after this crisis is over.
Overall, there is serious doubt whether such harsh statewide interventions, including stay-at-home orders and curfews in places like California, were effective or necessary from a public health standpoint or, viewed as political acts, were prudent and justifiable. For example, the ban on sitting and sunbathing on California’s beaches (while exercising on the same beaches was permitted), enforced through fines and even imprisonment, seems to fail both tests: it looks unnecessary and ineffective, as well as irrational and oppressive.
In Florida, with no lockdowns and not even a statewide mask mandate, the Covid-19 case and death rates were comparable and actually better with regard to the most vulnerable group, older people. Given the great hopes placed in lockdowns, and the lavish and ceaselessly repeated claims as to their benefits, one should expect the more restrictive states to have achieved decisively better performance by nearly any Covid-19-related metric – not the ambiguous, marginal, contradictory or even inferior results shown in this analysis.
Well-informed citizens are likely the real key to containing the pandemic. Enabling people to exercise responsibility for keeping themselves and those around them safe, rather than relying on an ever-metastasizing multitude of draconian or, in some cases, almost totalitarian governmental policies, could be the better way forward.
In search of more solid evidence, it is helpful to examine a recent U.S. study, entitled What Drives the Effectiveness of Social Distancing in Combating COVID-19 across U.S. States? comparing the life-saving effectiveness of lockdowns to voluntary social distancing. The four authors from the University of Utah argue that over the course of the pandemic, people’s own mobility choices have saved three times more lives than their respective state’s lockdown policies. The study also stresses that voluntary reduction in mobility is especially effective when people are given accurate information about the spreading of the virus instead of being told what they can and cannot do.
In short, well-informed citizens are likely the real key to containing the pandemic. Enabling people to exercise responsibility for keeping themselves and those around them safe, rather than relying on an ever-metastasizing multitude of draconian or, in some cases, almost totalitarian governmental policies, could be the better way forward. When informed, people tend to cooperate and act sensibly. Such news is particularly encouraging to those living in a free society. One of the basic principles of democracies such as the U.S. and Canada is that citizenship means exercising both rights and responsibilities, with the least governmental intervention possible.
When faced with Covid-19, unfortunately, virtually all state and provincial governments threw this principle overboard, if they ever adhered to it at all. The first round of widespread lockdowns and other extreme governmental interventions could have been considered just a “mistake,” and perhaps would have caused less popular angst, if not for their catastrophic economic and social consequences. These largely foreseeable effects were among the factors that policymakers and bureaucrats were supposed to carefully evaluate prior to taking the drastic steps in locking down entire communities, including hundreds of millions of perfectly healthy people.
It is devastating to realize what price humanity will have to pay for the policy excesses and errors of the unprecedented Covid-19 response. Governments and public health elites cannot afford to make similar mistakes again. The experience gained by the grave errors of the pandemic policy response to date must guide our efforts in the future. Otherwise, it will all have been in vain.
Appendix – Assumptions
- It was assumed that the number of people diagnosed with Covid-19 and the number who died, as obtained from the official U.S. Covid-19 statistical reports, represents the actual course of the pandemic. This assumption rests on the accuracy of the polymerase chain reaction (PCR) test, a commonly used tool to diagnose people with the corona virus. This test’s accuracy is questionable.
As Kary Mullis, the PCR test inventor, said, “[PCR] is the process that is used to make a whole a lot of something out of something. It does not tell you if you are sick and it does not tell you that the thing you ended up with is gonna hurt you.” Internet searches typically generate a list of “fact-checked” websites that debunk the claim that the PCR test may be unreliable and controversial. But to hold a debate on the accuracy of a test – any test – usually involves reviewing its reliability and validity coefficients which, in case of the PCR test, could not be found. In any event, the accuracy of the PCR test is assumed.
- It was assumed that people who had been documented as “Covid-19 deaths” indeed died from the disease and not from other frequently diagnosed comorbid conditions such as lung, heart, kidney and liver diseases, as well as diabetes, stroke, and cancer. The validity of this assumption is dependent on health care systems in the four states being diligent in recording deaths accurately and being unaffected by financial or political incentives.
It was further assumed that the same diagnostic criteria have been used for cases in all four states. From a practical point of view, however, this is doubtful, simply because the official Covid-19 symptomology has been changing as the pandemic has progressed. In addition, there have been reports suggesting attribution of Covid-19 as cause of death to Covid-19-positive individuals who, for example, fell from ladders or were shot to death. Nonetheless, this study assumes the accuracy of Covid-19 case diagnoses and cause-of-death attribution.
In comparing the course of the Covid-19 crisis in the four states, it was assumed that the role of other factors potentially affecting the official statistics had been negligible. In other words, if there were errors in recording instances of the virus and deaths from it, these errors are random.
It was beyond the scope of the study to determine the consistency and severity of the enforcement of lockdowns and other restrictions. It cannot be known how variations between states in this important area influenced popular adherence to government measures.
There are, nonetheless, at least two critical and observable factors that vary systematically across the states: population and climate. The importance of roughly comparable population is self-evident. Comparable climate is important because Covid-19 was quickly recognized as a seasonal virus that especially thrives in colder and drier environments and that succumbs under UV radiation (including sunlight). This suggested the importance of comparing states with similar seasonality and latitude.
Additional important observable factors can also be broadly compared from state to state: demographics, economic structure and degree of urbanization. These factors were taken into consideration in this analysis, while other potentially influential but research-intensive factors, such as degree of mass transit use, hygiene practices and household living arrangements, were left aside.
Selecting pairs of states that are similar in as many of these factors as could be found among the 50 states enabled commenting on the temporal relationships between the state measures and the Covid-19 data and to make comparisons regarding the impact of those interventions.
Maria (Masha) V. Krylova is a Social Psychologist and writer based in Calgary, Alberta who has a particular interest in the role of psychological factors affecting the socio-political climate in Russia and Western countries.
