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The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has caused the Coronavirus Disease 2019 (COVID-19) worldwide pandemic in 2020. In response, most countries in the world implemented lockdowns, restricting their population's movements, work, education, gatherings, and general activities in attempt to “flatten the curve” of COVID-19 cases. The public health goal of lockdowns was to save the population from COVID-19 cases and deaths, and to prevent overwhelming health care systems with COVID-19 patients. In this narrative review I explain why I changed my mind about supporting lockdowns. The initial modeling predictions induced fear and crowd-effects (i.e., groupthink). Over time, important information emerged relevant to the modeling, including the lower infection fatality rate (median 0.23%), clarification of high-risk groups (specifically, those 70 years of age and older), lower herd immunity thresholds (likely 20–40% population immunity), and the difficult exit strategies. In addition, information emerged on significant collateral damage due to the response to the pandemic, adversely affecting many millions of people with poverty, food insecurity, loneliness, unemployment, school closures, and interrupted healthcare. Raw numbers of COVID-19 cases and deaths were difficult to interpret, and may be tempered by information placing the number of COVID-19 deaths in proper context and perspective relative to background rates. Considering this information, a cost-benefit analysis of the response to COVID-19 finds that lockdowns are far more harmful to public health (at least 5–10 times so in terms of wellbeing years) than COVID-19 can be. Controversies and objections about the main points made are considered and addressed. Progress in the response to COVID-19 depends on considering the trade-offs discussed here that determine the wellbeing of populations. I close with some suggestions for moving forward, including focused protection of those truly at high risk, opening of schools, and building back better with a economy.
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REVIEW
published: 26 February 2021
doi: 10.3389/fpubh.2021.625778
Frontiers in Public Health | www.frontiersin.org 1February 2021 | Volume 9 | Article 625778
Edited by:
Enamul Kabir,
University of Southern
Queensland, Australia
Reviewed by:
Zakir Hossain,
University of Dhaka, Bangladesh
Md Mijanur Rahman,
University of Wollongong, Australia
*Correspondence:
Ari R. Joffe
ari.joffe@ahs.ca
orcid.org/0000-0002-4583-707X
Specialty section:
This article was submitted to
Health Economics,
a section of the journal
Frontiers in Public Health
Received: 09 November 2020
Accepted: 25 January 2021
Published: 26 February 2021
Citation:
Joffe AR (2021) COVID-19: Rethinking
the Lockdown Groupthink.
Front. Public Health 9:625778.
doi: 10.3389/fpubh.2021.625778
COVID-19: Rethinking the Lockdown
Groupthink
Ari R. Joffe 1,2
*
1Division of Critical Care Medicine, Department of Pediatrics, Stollery Children’s Hospital, University of Alberta, Edmonton,
AB, Canada, 2John Dossetor Health Ethics Center, University of Alberta, Edmonton, AB, Canada
The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has caused the
Coronavirus Disease 2019 (COVID-19) worldwide pandemic in 2020. In response, most
countries in the world implemented lockdowns, restricting their population’s movements,
work, education, gatherings, and general activities in attempt to “flatten the curve” of
COVID-19 cases. The public health goal of lockdowns was to save the population from
COVID-19 cases and deaths, and to prevent overwhelming health care systems with
COVID-19 patients. In this narrative review I explain why I changed my mind about
supporting lockdowns. The initial modeling predictions induced fear and crowd-effects
(i.e., groupthink). Over time, important information emerged relevant to the modeling,
including the lower infection fatality rate (median 0.23%), clarification of high-risk groups
(specifically, those 70 years of age and older), lower herd immunity thresholds (likely
20–40% population immunity), and the difficult exit strategies. In addition, information
emerged on significant collateral damage due to the response to the pandemic, adversely
affecting many millions of people with poverty, food insecurity, loneliness, unemployment,
school closures, and interrupted healthcare. Raw numbers of COVID-19 cases and
deaths were difficult to interpret, and may be tempered by information placing the number
of COVID-19 deaths in proper context and perspective relative to background rates.
Considering this information, a cost-benefit analysis of the response to COVID-19 finds
that lockdowns are far more harmful to public health (at least 5–10 times so in terms of
wellbeing years) than COVID-19 can be. Controversies and objections about the main
points made are considered and addressed. Progress in the response to COVID-19
depends on considering the trade-offs discussed here that determine the wellbeing
of populations. I close with some suggestions for moving forward, including focused
protection of those truly at high risk, opening of schools, and building back better with a
green economy.
Keywords: COVID-19, lockdowns, public health, cost-benefit analysis, groupthink
INTRODUCTION
The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) initially caused Coronavirus
Disease 2019 (COVID-19) in China in December 2019, and has caused a worldwide pandemic
in 2020. In response, most countries in the world implemented lockdowns, restricting their
population’s movements, work, education, gatherings, and general activities in attempt to “flatten
Joffe Rethinking the Lockdown Groupthink
the curve” of COVID-19 cases. Even now, as the so-called
“second-wave” of COVID-19 cases is occurring, governments are
considering and some implementing another lockdown to again
“flatten the curve.” The public health goal of lockdowns is to save
the population from COVID-19 cases and deaths, and to prevent
overwhelming health care systems with COVID-19 patients. I
was a strong proponent of lockdowns when the pandemic was
first declared (1).
In this narrative review I explain why I changed my
mind. First, I explain how the initial modeling predictions
induced fear and crowd-effects (i.e., groupthink). Second, I
summarize important information that has emerged relevant
to the modeling. Third, I describe how reality started sinking
in, with information on significant collateral damage from the
response to the pandemic, and on the number of deaths in
context. Fourth, I present a cost-benefit analysis of the response
to COVID-19. I close with some suggestions for moving forward.
An important point must be emphasized. The COVID-
19 pandemic has caused much morbidity and mortality. This
morbidity and mortality have been, and continue to be, tragic.
This narrative review aims to take these tragic outcomes
of the pandemic seriously, and to also consider the tragic
outcomes of the public health response to the pandemic. After
all, lockdowns are a public health response undertaken with
the goal of improving population health outcomes from the
pandemic. Given adverse effects of lockdowns on many millions
of people, with increased poverty, food insecurity, loneliness,
unemployment, school closures, and interrupted healthcare, a
cost-benefit analysis of lockdowns is necessary. We face terrible
choices, but the response of lockdowns can be predicted to cause
far more loss of population wellbeing than COVID-19 itself can.
THE INITIAL PREDICTIONS INDUCE FEAR
How It Started: Modeling
Early modeling made concerning predictions that induced fear
(Table 1). Kissler et al. predicted the need for intermittent
lockdowns occurring for a total of 75% of the time, even after
July 2022, to avoid “overwhelming critical care capacity (page
866 in ref. 2)” (24). In their discussion they wrote that the
response “is likely to have profoundly negative economic, social,
and educational consequences. . . We do not take a position on
the advisability of these scenarios given the economic burden. . .
(page 868)” (2). On March 16, 2020, the Imperial College
COVID-19 Response Team published modeling of the impact
of non-pharmaceutical interventions (NPI) to reduce COVID-
19 mortality and healthcare demand in the United States (US)
and United Kingdom (UK) (5). They wrote that suppression
“needs to be in force for the majority [>2/3 of the time] of
the 2 years of the simulation (page 11),” without which there
would be 510,000 deaths in Great Britain and 2.2 million deaths
Abbreviations: COVID-19, Coronavirus Disease 2019; GDP, Gross Domestic
Product; IFR, Infection Fatality Rate; ICU, Intensive Care Unit; NPI, Non-
pharmaceutical Intervention; QALY, Quality Adjusted Life Years; SARS-CoV-2,
Severe Acute Respiratory Syndrome Coronavirus 2; UK, United Kingdom; US,
United States; WELLBY, Wellbeing Adjusted Life Years.
in the United States by mid-April, surpassing ICU demand by
30 times (5). In their discussion they wrote that “we do not
consider the ethical or economic implications (page 4). . . The
social and economic effects of the measures which are needed
to achieve this policy goal will be profound (page 16). . . ” (5).
The Imperial College COVID-19 Response Team extended this
to the global impact of the pandemic on March 26, 2020, and
estimated that without lockdowns there would be “7.0 billion
infections and 40 million deaths globally this year (page 1)” (6).
In their discussion they wrote “we do not consider the wider
social and economic costs of suppression, which will be high
and may be disproportionately so in lower income settings (page
2)” (6). In a later publication, this group modeled that “across
11 countries [in Europe, since the beginning of the epidemic to
May 4], 3.1 (2.8–3.5) million deaths have been averted owing to
[NPI] interventions. . . (page 260)” (7). Another group similarly
claimed that, in 5 countries (China, South Korea, Iran, France,
US), NPIs “prevented or delayed [to April 6] on the order of 61
million confirmed cases (page 262)” (8).
How It Took Off: Crowd Effects
(Groupthink)
There ensued a contagion of fear and policies across the world (9
12). Social media spread a growing sense of panic (13). Popular
media focused on absolute numbers of COVID-19 cases and
deaths independent of context, with a “sheer one-sided focus
(page 4)” on preventing infection (12). There was an appeal
of group hysteria; “everyone got a break from their ambitions
and other burdens carried in normal life,” and became united
in crowds, which have a numbing effect (9). There was talk of
“acting together against a common threat,” “about seeming to
reduce risks of infection and deaths from this one particular
disease, to the exclusion of all other health risks or other life
concerns,” with virtue signaling to the crowd, of “something
they love to hate and be seen to fight against” (9). A war
effort analogy is apt, with the “unquestioning presumption that
the cause is right, that the fight will be won, that naysayers
and non-combatants [e.g., not wearing a mask] are basically
traitors, and that there are technical solutions [e.g., vaccine and
drugs] that will quickly overcome any apparent problem or
collateral damage” (9). This was associated with a “disregard
and disinterest on the part of individuals in the enormity of
the collateral damage, either to their own kids, people in other
countries, their own futures. . . ” (9). The crisis was framed as a
“war against an invisible enemy (page 5),” presenting the false
choice between “lives and livelihood (page 5),” spreading fear
and anxiety while ignoring the costs of the measures taken -
this resulted in conformity and obedience (12,13). There has
been a strong positive association between new daily and total
confirmed COVID-19 cases in a country and support for the
heads of government, reflecting the “rally ‘round the flag’” effect
[“the perception that one’s group is under attack and hence unity
is required to defend the group (page 25429)”] (14).
The NPIs spread to 80% of OECD countries within a 2-
week period in March 2020 (15). A main predictor of a country
implementing NPIs was prior adoptions of a policy among
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Joffe Rethinking the Lockdown Groupthink
TABLE 1 | Initial modeling predictions that induced fear and crowd-effects.
References Statements and predictions from the modeling
Kissler et al. (24) “prolonged or intermittent social distancing may be necessary into 2022 [to avoid overwhelming critical care capacity]… expanded
critical care capacity… would improve the success of intermittent distancing and hasten the acquisition of herd immunity”
“projected that recurrent wintertime outbreaks of SARS-CoV-2 will probably occur after the initial, most severe pandemic wave [if
immunity wanes over 40 weeks]”
With a baseline reproductive number (Ro) 2.5, no seasonality to viral transmission, and the current intensive care capacity of the USA
they projected the need for intermittent lockdowns occurring for a total of 75% of the time, even after July 2022.
Imperial College modeling of
non-pharmaceutical
interventions in USA and UK (5)
“suppression [effective reproductive number (Re)<1] will minimally require a combination of social distancing of the entire population,
home isolation of cases and household quarantine of their family members. This may need to be supplemented by school and
university closures… [and] Will need to be maintained until a vaccine becomes available.”
“we show that intermittent social distancing – triggered by trends in disease surveillance – may allow interventions to be relaxed
temporarily in relative short time windows….[Suppression] needs to be in force for the majority [>2/3 of the time] of the 2 years of the
simulation.”
The modeling assumed an IFR of 0.9%, hospitalization rate of 4.4%, and that 81% of the population would be infected before herd
immunity, resulting in 510,000 deaths in Great Britain and 2.2 million deaths in the United States by mid-April, surpassing ICU
demand by 30X, if lockdowns did not occur.
Imperial College modeling of
non-pharmaceutical
interventions globally (6)
“we estimate that in the absence of interventions, COVID-19 would have resulted in 7.0 billion infections and 40 million deaths
globally this year… healthcare demand can only be kept within manageable levels through the rapid adoption of public health
measures… to suppress transmission… sustained, then 38.7 million lives could be saved.”
“[Suppression] will need to be maintained in some manner until vaccines or effective treatments become available.”
Imperial College estimate of lives
saved so far in Europe (7)
Used a “model [that] calculates backwards [infections] from observed deaths… [and] relies on fixed estimates of some
epidemiological parameters [Ro 3.8; attack rates in different age groups from 60-99%; infection fatality rate in different countries of
0.91–1.26%]….”
Concluded that “we find, across 11 countries [in Europe], since the beginning of the epidemic [to May 4], 3,100,000
(2,800,000–3,500,000) deaths have been averted due to [NPI] interventions….”
Hsiang et al. (8) In 5 countries [China, South Korea, Iran, France, US], using “reduced-form economic methods,” NPIs “prevented or delayed [to April
6] on the order of 62 million confirmed cases, corresponding to averting roughly 530 million total infections… we estimate that all
policies combined slowed the average growth rate of infections [from 43%/day, a doubling time 2 days] by 0.252 per day….”
spatially proximate countries, i.e., the number of earlier adopters
in the same region (15). Variables not predicting adoption of
NPIs included the number of cases or deaths, population >65
years old, or hospital beds per capita in the country (15). It
seems we were all “stuck in this emotional elevation of COVID-
19 deaths and suffering above everything else that could possibly
matter” (16). There was the unquestioned assumption that “there
were and are no alternatives to extreme measures implemented
on entire populations with little consideration of cost and
consequences [externalities] (page 477)” (10). Even now, how
a country “performed” is measured by COVID-19 cases and
deaths without denominators, without other causes of deaths
considered, without considering overall population health trade-
offs “that cannot be wished away” (e.g., the future of our children
from lack of education and social interaction, and “changes to our
wealth-generating capacity that has to pay for future policies”)
(9), and without considering how sustainable current policies are
[protection is temporary and leaves us susceptible; “there is no
exit from the pandemic; there is only an exit from the response to
it (page 479)” (10)].
All of this, even though in October 2019 the WHO
published that for any future Influenza pandemic: travel-related
measures are “unlikely to be successful. . . are likely to have
prohibitive economic consequences (page 2)”; “[measures] not
recommended in any circumstances: contact tracing, quarantine
of exposed individuals, border closure (page 3)”; social distancing
measures (closures of workplace, avoiding crowding and closing
public areas) “can be highly disruptive, and the cost of these
measures must be weighed against their potential impact (page
4)”; and “border closures may be considered only by small
island nations in se vere pandemics. . . but must be weighed
against potentially serious economic consequences (page 4)”
(17). Referring to the 2009 influenza pandemic, Bonneux and
Van Damme wrote that “the culture of fear” meant that
“worst-case thinking replaced balanced risk assessment” on the
part of influenza “experts” (page 539) (18). But “the modern
disease expert knows a lot about the disease in question, but
does not necessarily know much about general public health,
health economics, health policy, or public policy, which are
much more about priority setting and hence resource allocation
between competing priorities [because resources are limited, wise
allocation saves lives]” (19).
Some of this crowd effect is related to cognitive biases,
“the triumph of deeply human instincts over optimal policy”
(page 303 in ref 21) (2022). Identifiable lives bias included the
identifiable victim effect (we ignore hidden “statistical” deaths
reported at the population level), and identifiable cause effect (we
prioritize efforts to save lives from a known cause even if more
lives would be saved through alternative responses). Present bias
made us prefer immediate benefits to even larger benefits in the
future (steps that would prevent more deaths over the longer
term are less attractive) (2022). The proximity and vividness of
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Joffe Rethinking the Lockdown Groupthink
COVID-19 cases (i.e., availability and picture superiority bias),
and anchoring bias (we adhere to our initial hypothesis, and
disregard evidence that disproves our favorite theory) affected
our reasoning (21,23). Superstitious bias, that action is better
than non-action even when evidence is lacking, reduced anxiety
(12). Escalation of commitment bias, investing more resources
into a set course of action even in the face of evidence there are
better options, made us stand by prior decisions (24). We need
to take an “effortful pause,” reflecting on aspects of the pandemic
that do not fit with our first impressions (25). The groupthink
(the tendency for groups to let the desire for harmony and
conformity prevail, resulting in dysfunctional decision-making
processes and becoming less willing to alter their course of
action once they settle on it) needs to be replaced by deliberative
consideration of all the relevant information (24).
IMPORTANT NEW INFORMATION
EMERGING
The Infection Fatality Rate (IFR)
Based on seroprevalence data as of September 9, 2020, including
82 estimates from across 51 locations in the world, Ioannidis
found that the median corrected IFR was 0.23% (range 0.00–
1.54%) (26). Among those <70 years old the median crude
and corrected IFR was 0.05% (range 0.00–0.31%). He estimated
that for those <45 years old the IFR was almost 0%, 45–
70 years old approximately 0.05–0.30%, and 70 years old
1%, rising to up to 25% for some frail older people in
nursing homes (27). He estimated that at that point there
were likely 150–300 million infections that had occurred in the
world, not the reported 13 million, most being asymptomatic
or mildly symptomatic (26,27). The WHO recently estimated
that about 10% of the global population may have been already
infected, which, with a world population of 7.8 billion, and 1.16
million deaths, would make a rough approximation of IFR as
0.15% (28).
Even these numbers are most likely a large over-estimate of
the IFR. First, in serosurveys the vulnerable (e.g., homeless,
imprisoned, institutionalized, disadvantaged people), who have
higher COVID-19 incidence, are more difficult to recruit. Second,
there is likely a healthy volunteer bias in serosurvey studies.
Third, and most importantly, there is a lack of sensitivity of
serology (2934). Many reports now document there is often
a rapid loss of antibody in COVID-19 patients that were less
severely ill (2936). Moreover, at least 10% of COVID-19 patients
never seroconvert, and many more may only develop a mucosal
IgA response (37,38), or only a T-cell response (which may
be the case in up to 50% of mild infections) (39,40). Finally,
most data come from unusual epicenters where infection finds
its way into killing predominantly older citizens in nursing
homes and hospitals (26), and where “[in Italy, Spain, France]
an underfunded, understaffed, overstretched and increasingly
privatized and fractured healthcare system contribute to higher
mortality ra tes.. . [Lombardy] has long been an experimental site
for healthcare privatization (page 474–475)” (10). With “precise
non-pharmacological measures that selectively try to protect
high-risk vulnerable populations and settings, the IFR may be
brought even lower (page 10)” (26).
A serology-informed estimate of the IFR in Geneva,
Switzerland put the IFR at: age 5–9 years 0.0016% (95% Credible
Interval, CrI 0, 0.019), 10–19 years 0.00032% (95% CrI 0, 0.0033),
20–49 years 0.0092% (95% CrI 0.0042, 0.016), 50–64 years 0.14%
(95% CrI 0.096, 0.19), and age 65+outside of assisted care
facilities 2.7% (95% CrI 1.6, 4.6), for an overall population IFR
0.32% (95% CrI 0.17, 0.56) (41). Similarly, a large study from
France found an inflection point in IFR around the age of 70 years
(see their Figure 2D) (42).
High-Risk Groups
Ioannidis et al. analyzed reported deaths from epicenters, in 14
countries and 13 states in the United States, to June 17, 2020 (43).
They found that in those age <65 years the relative risk of death
was 30–100X lower in Europe and Canada, and 16–52X lower in
the USA, compared to those 65 years old (43). They estimated
that those age 40–65 years old have double the risk of the overall
<65 year-old group, and females have 2X lower risk than males
(43). This is compatible with a steep inflection point in the IFR
around the age of 70 years old. Older adults in nursing homes
accounted for at least half of the COVID-19 deaths in Europe
and North America, and over 80% in Canada (44,45). In nursing
homes the usual median survival is 2.2 years, with a yearly
mortality rate >30%, even without COVID-19 (46). Outbreaks of
the seasonal respiratory coronavirus in adults living in long-term
care facilities are common, with case-fatality rates of 8% (47).
Ioannidis et al. estimated that the average daily risk of COVID-
19 death for an individual <65 years old was equivalent to the
risk from driving between 12–82 miles/day during the pandemic
period, higher in the UK and 8 states (106–483 miles/day), and
only 14 miles/day in Canada (43).
By far the most important risk factor is older age (41
43). There is an approximately 1,000-fold difference in death
risk for people >80 years old vs. children (43). In the largest
observational study I am aware of, the OpenSAFELY population
in the UK, including over 17 million people with 10,900
COVID-19 deaths, compared to those age 50–59 years old,
the Hazard Ratio for death from COVID-19 ranged from 0.06
for those age 18–39 years, to >10 for those age >80 years
(48). In comparison, even important co-morbidities such as
severe obesity, uncontrolled diabetes, recent cancer, chronic
respiratory or cardiac or kidney disease, and stroke or dementia
rarely had HR approaching 2 (48). Those co-morbidities
with HR>2, including hematological malignancy, severe chronic
kidney disease, and organ transplant, affected only 0.3, 0.5, and
0.4% of the total population (48).
A rapid systematic review found that only age had a
“consistent and high strength association with hospitalization
and death from COVID-19. . . strongest in people older than 65
years. . . (page 1)” (49). Other risk groups for mortality had either
a low-moderate effect (obesity, diabetes mellites, male biological
sex, ethnicity, hypertension, cardiovascular disease, COPD,
asthma, kidney disease, cancer) and/or were inconsistently
found to have an effect in the literature (obesity, diabetes
mellites, pregnancy, ethnicity, hypertension, cardiovascular
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Joffe Rethinking the Lockdown Groupthink
disease, COPD, kidney disease) (49). Even with these risk factors,
the absolute risk may still be low, given the overall IFR in the
population at that age.
Objection: Is This Age Discrimination?
An objection may be that singling out older people as high
risk is age discrimination. This is false on two counts. First,
pointing out the truly high-risk group is in older people is only
emphasizing that this is the group that requires protection from
severe COVID-19 outcomes. Second, as Singer has pointed out,
“what medical treatment does, if successful, is prolong lives.
Successfully treating a disease that kills children and young
adults is, other things being equal, likely to lead to a greater
prolongation, and thus do more good, than successfully treating
a disease that kills people in the 70’s, 80’s, and 90’s” (50). In fact,
when we try to stay healthy “what we are trying to do is to live
as long as we can, compatibly with having a positive quality of
life for the years that remain to us. If life is a good, then, other
things being equal, it is better to have more of it rather than less”
(50). We should count every quality adjusted life year equally,
whether it is in the life of a teenager or a 90-year old (50,51). This
was also the conclusion of “The Fair Priority Model” for global
vaccine allocation, prioritizing preventing premature death using
a standard expected years of life lost metric (52).
Veil of ignorance reasoning is a widely respected and
transparent standard for adjudicating claims of fairness. A fair
distribution of resources is said to be one that people would
choose out of self-interest, without knowing whom among those
affected they will be: what would I want if I didn’t know who
I was going to be? In an experimental study participants were
asked to decide whether to give the last available ventilator in
their hospital to the 65 year old who arrived first and is already
being prepped for the ventilator, or the 25 year old who arrived
moments later, assuming whoever is saved will live to age 80 years
old. In the veil of ignorance condition, the participant was asked
to “imagine that you have a 50% chance of being the older patient,
and 50% the younger” (53). Asked if “it is morally acceptable
to give the last ventilator to the younger patient,” 67% in the
veil of ignorance condition vs. 53% in control answered “yes”
(odds ratio 1.69; 95% Confidence Interval 1.12, 2.57); compared
to younger age participants (18–30 years), older participants
(odds ratio 3.98) and middle age participants (odds ratio 2.02)
were more likely to agree (53). Asked if “you want the doctor
to give the ventilator to the younger patient,” 77% answered
“yes,” maximizing the number of life-years saved rather than the
number of lives saved (53). Thus, veil of ignorance reasoning
resulted in the participants counting every quality adjusted life
year equally, whether it is in the life of a 25-year old or a
65-year old.
The Herd Immunity Threshold
The classical herd immunity level is calculated based on the basic
reproduction number (Ro) as (1–1/Ro), and is the proportion of
the population that must be immune to a virus before the effective
reproduction number (Re) is <1, and thus the virus cannot
perpetuate itself in the population. This calculation assumes
a homogeneously mixing population, where all are equally
susceptible and infectious. For Ro 2.5, the threshold is 60% of
the population. However, the assumption is not valid, as there is
heterogeneity in social mixing and connectivity, with higher and
lower levels of activity and contacts. One model incorporating
heterogeneity of social mixing found the threshold, for Ro 2.5, to
be 43%, and likely lower as other heterogeneity in the population
was not modeled (e.g., sizes of households, attending school
or big workplaces, metropolitan vs. rural location, protecting
older people, etc.) (54). A model that incorporated variation in
connectivity compatible with other infectious diseases found that
for Ro 3, the threshold is 10–25% of the population developing
immunity (55). Another model that “fit epidemiological models
with inbuilt distributions of susceptibility or exposure to SARS-
CoV-2 outbreaks” calculated “herd immunity thresholds around
10-20% [because]. . . immunity induced by infection. . . [contrary
to random vaccination] is naturally selective (page 2)” (56).
In support of this heterogeneity, it is now known that there
is overdispersion of transmission of SARS-CoV-2, with 80%
of secondary infections arising from just 10% of infected
people (5759).
Objection: Consider Sweden
It has been claimed that Sweden’s strategy of achieving herd
immunity failed, with excess deaths and a suffering economy.
However, that is not clear. First, cases and deaths fell consistently
in later July/August, with deaths continuing at a very low level
into October despite no lockdown (60). Second, serosurveys in
mid-July found 14.4% of the population may be seropositive;
thus, with 5,761 deaths as of August 1, in a population of 10.23
million, the crude IFR may have been 0.39%, and even lower
considering the sensitivity of serology discussed above (61).
Early on, Sweden did not adequately protect those in nursing
homes, a failing that also inflates the IFR (62). The excess
all-cause mortality per 100,000 up to July 25, 2020 in Sweden was
50.8, lower than in England and Wales, Spain, Italy, Scotland,
Belgium, Netherlands, France, and the US (62,63). Third, in a
globalized world, with entangled webs of supply, demand, and
beliefs, what we do here will devastate people not just here, but
also elsewhere and everywhere (64). Compared to Denmark, with
an economy heavily dependent on pharmaceuticals, Sweden’s
recession looks bad. However, compared to the European
Union, Sweden looks good; the European Commission forecasts
a better 2020 economic result for Sweden (GDP5.3%)
than many other comparable European countries (e.g.,
France10.6%, Finland6.3%, Austria7.1%, Germany6.3%,
Netherlands6.8%, Italy11.2%, Denmark5.2%) (65).
The Exit Strategy
Herd immunity appears to be the only exit from the response to
COVID-19. This can be achieved naturally, or through vaccine.
For the reasons given here, it is very possible that the lockdowns
are only delaying the inevitable.
There are problems with the natural herd immunity approach
involving the currently projected and implemented waves of
lockdowns. First, this will take years to occur, causing economic
and social devastation. This also assumes immunity is long-
lasting such that cycles of shutting down can be successful over
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2 or 3 years, and without which it is more likely COVID-19
will be an annual occurrence (2). Second, the less devastating
test-trace-isolation/quarantine strategy seems not feasible. In the
United States it was estimated that there would be a need to train
an extra 100,000 public health workers, and to do >5 million
SARS-CoV-2 tests per day, necessitating the building of many
new very large testing factories (66). Countries would still need
to keep borders closed and maintain physical distancing (e.g., no
large events) in order to make contact tracing feasible; this would
be for years, during which people may become very reluctant
to be tested. Modeling suggests that to be successful, because
asymptomatic and pre-symptomatic individuals may account for
48–62% of transmission (even in nursing home residents) (67),
contact tracing and quarantine would have to occur within 0.5
days for >75% of contacts, necessitating mobile app technology
that has its own feasibility and ethical problems (6870).
Vaccine induced herd immunity involves many assumptions.
First, there will be the discovery of an effective and safe vaccine
that does not cause antibody-dependent (or other immune)
enhancement; this, even though the problem in severe COVID-
19 may be the host response, especially in older people and
children (7173). Second, the immune response will be durable,
not last for only months, and have little immunosenescence
(reduced response to vaccine with rapid decline of antibody
levels) in older people (72,74). Third, that mass production and
delivery of the vaccine will occur very soon, and be done equitably
to all humans on Earth; otherwise, there is the risk of conflict,
war, and terrorism in response to gross inequity in vaccine
distribution (52). In response to the 2009 pandemic of H1N1
Influenza the United States achieved a weekly vaccination rate
of only 1% of the population (72). Vaccine refusers may include
30% of the population in North America and globally (72,75),
and if they have “increased contact rates relative to the rest of
the population, vaccination alone may not be able to prevent an
outbreak (page 817)” (72). There is already competition among
high income countries, and likely crowding out of low-income
countries that represent about half of the human population (76).
The only globally eradicated human disease is smallpox, which
took “30 years to achieve,” and the “fastest historical development
of a [new] vaccine was 4 years (Merck: mumps), while most take
10 years (page 2)” (77).
REALITY SINKING IN
Iatrogenic Collateral Harms: Lockdown as
a “Drug” With Dangerous Side-Effects
When Its Use Is Prolonged
The COVID-19 response has threatened to make, and likely
has already made, several Sustainable Development Goals for
the most vulnerable among us in low-income countries out of
reach (7882). The numbers involved are staggering, and in the
many millions (Table 2). The response has had major detrimental
effects on childhood vaccination programs, education, sexual and
reproductive health services, food security, poverty, maternal and
under five mortality, and infectious disease mortality (7893).
The effect on child and adolescent health will “set the stage for
both individual prosperity and the future human capital of all
societies (page 2)” (94). The destabilizing effects may lead to
chaotic events (e.g., riots, wars, revolutions) (95,96).
In high-income countries, the collateral damage has also been
staggering (Table 3), affecting visits to emergency departments
and primary care for acute (e.g., myocardial infarction, stroke)
and “non-urgent” (“elective” surgery, and cancer diagnosis
and treatment) conditions, intimate partner violence, deaths
of despair, and mental health (12,97112). Of excess deaths
occurring during the pandemic in high-income countries, 20–
50% are not due to COVID-19 (62,113115). There was an
unexplained 83% increase of 10,000 excess deaths from dementia
in England/Wales in April, and an increase in non-COVID-19
Alzheimer disease/dementia deaths in the US, attributed to lack
of social contact causing a deterioration in health and wellbeing
of these patients (115,116).
COVID-19 “Is a disease of inequality and it also creates even
more inequality (page 3)” (95). Unequal structural determinants
of health meant that disadvantaged minorities have experienced
a greater toll from the COVID-19 “Great Lockdown” (117),
with contributors including lower income (e.g., economic and
job insecurity), homelessness or crowding at home (and in
transportation), worse health care (and pre-existing health
disparities), and inability to work from home (e.g., for essential,
manual, and temporary workers) (45,95,118,119). COVID-
19 policing has involved “racial profiling and violence, crippling
punishments for those living in poverty, and criminalization
of mental health (page E1219)” (120). Refugees are particularly
vulnerable, undertaking “arguably the most essential form of
travel. . . with little access to water, space or health care (page
E1219)” (120). The effect on the health of women and girls
is particularly severe, disproportionately affecting sexual and
reproductive health services, income, and safety (121,122).
Numbers in Context
Numbers without denominators and without context are
deceiving. Some data in this section may put the COVID-19
pandemic numbers in perspective.
Assuming all deaths with COVID-19 are deaths from COVID-
19, in the USA as of August 22, 2020, COVID-19 was the
cause of 9.24% of overall deaths; this means that >90% of
deaths are not a focus of our attention (Supplementary Table 1)
(123). Similarly, in Canada, COVID-19 was the cause of 5.96%
of estimated deaths over the first 6 months of 2020, again
meaning >94% of deaths are not a focus of our attention, and
not being reported daily in the press as are COVID-19 deaths
(Supplementary Table 2) (124,125). By late-November these
relative numbers had changed little (Supplementary Table 3)
(123125). A similar analysis in the UK found that, during 16
weeks of the pandemic, the risk of death was “equivalent to
experiencing around 5 weeks extra ‘normal’ risk for those over
[age] 55, decreasing steadily with age, to just 2 extra days for
schoolchildren. . . [and in t hose] over 55 who are [detected as]
infected with COVID-19, the additional risk of dying is slightly
more than the “normal” risk of death from all other causes over
one year (page 6)” (126).
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TABLE 2 | Some effects of the COVID-19 response that put sustainable development goals out of reach (7893).
Sustainable development goal Effect of COVID-19 response: some details
Childhood vaccination Programs stalled in 70 countries (Measles, Diphtheria, Cholera, Polio)
Education School closures: 90% of students (1.57 Billion) kept out of school
-Early primary grades are most vulnerable, with effects into adulthood: effects on outcomes of intelligence, teen pregnancy, illicit
drug use, graduation rates, employment rates and earnings, arrest rates, hypertension, diabetes mellites, depression
-Not just education affected: school closures have effects on food insecurity, loss of a place of safety, less physical activity, lost
social interactions, lost support services for developmental difficulties, economic effects on families
Sexual and reproductive health
services
Lack of access: estimated 2.7 Million extra unsafe abortions
For every 3 months of lockdown: estimated 2 Million more lack access to contraception, and over 6 months, 7 Million additional
unintended pregnancies
Food security Hunger pandemic: undernourished estimated to increase 83–132 Million (>225,000/day; an 82% increase)
-from disrupted food supply chains (labor mobility, food transport, planting seasons) and access to food (loss of jobs and incomes,
price increases)
End poverty Extreme poverty (living on <US$1.90/day): estimated to increase >70 Million
-Lost “ladders of opportunity” and social determinants of health
Reduce maternal and U5M Estimated increase of 1.16 Million children (U5M) and 56,700 maternal deaths, if essential RMNCH services are disrupted
(coverage reduction 39–52%) for 6 months in 118 LMIC mostly (60%) due to affected childhood interventions (wasting,
antibiotics, ORS for diarrhea); and childbirth interventions (uterotonics, antibiotics, anticonvulsants, clean birth)
Infectious Disease Mortality Tuberculosis: in moderate and severe scenario, projected excess deaths (mostly from reduced timely diagnosis and treatment)
342,000–1.36 Million over 5 years (an increase of 4–16%)
Malaria: in moderate and severe scenario, projected excess deaths (mostly from delayed net campaigns and treatment) 203,000
to 415,000 over 1 year (an increase of 52–107%, with most deaths in children <5 yo).
HIV: in moderate projected excess deaths (mostly due to access to antiretrovirals) 296,000 (range 229,000–420,000) in
Sub-Saharan Africa over 1 year (an increase of 63%). Also would increase mother to child transmission by 1.6 times.
LMIC, low- and middle-income countries; ORS, oral rehydration solution; RMNCH, Reproductive Maternal Newborn and Child Health; U5M, under 5 mortality.
TABLE 3 | Some effects of the COVID-19 response on public health in mostly high-income countries (97119).
Effect of COVID-19 response Some details
Delayed/avoided/disrupted medical
care
Visits to emergency departments for myocardial infarction or stroke declined in USA by 20–48%
Delayed cancer care and “non-urgent” procedures
- weekly presentations with cancer diagnoses down 46% in USA and UK
- 90% reduction in non-cancer surgeries in Ontario in March/April
- surgery backlog in Ontario March 15 to June 13: 148,000; clearance time estimated to take 84 weeks
- in Canada at least $1.3 billion additional funding is required to return to pre-pandemic wait times for six procedures
(CABG, cataract surgeries, hip and knee replacements, MRI and CT scans) within 1 year
Of excess deaths in high-income countries during pandemic, 20-50% are not from COVID-19
Unexplained 83% increase (10,000 excess) deaths from dementia in England/Wales in April (lack of social contact causing a
deterioration in health and wellbeing)
Violence against women (household
stress; disrupted livelihoods,
social/protective networks, support
services)
Intimate Partner Violence: estimated effect from 3 months lockdown is 20% increase (>15 Million additional cases)
Female Genital Mutilation: 2 Million more cases over next decade
Child Marriages: 13 Million more cases over next decade
Increased police reports (France, UK, Ontario) and support line calls (China, Italy, Spain, Vancouver, Alberta) by 20–50%
Deaths of despair (related to
unemployment, and due to drugs,
alcohol, and suicide)
In USA alone: 68,000 (from 27,000–154,000) suicide deaths predicted
Mental Health effects of 3 months (suicide, depression, alcohol use disorder, childhood trauma due to domestic violence,
changes in marital status, social isolation): Years of Life Lost in USA 67.58 Million, Canada 7.79 Million, UK 13.62 Million,
etc.
Surge in Canada in opioid deaths (by 40–50%), alcohol consumption (by 19%), cannabis use (by 8%), tobacco smoking (by
4%), and suicidal thoughts.
Across the world in 2019 there were 58,394,000 deaths, >4.87
million deaths/month and >159,983 deaths/day; COVID-19
deaths are shown relative to these underlying deaths in Table 4
and Supplementary Table 3 (127,128). The number of deaths
is highly unequal, with far more deaths at earlier ages in low-
income countries and Sub-Saharan Africa (127). If all countries
were to achieve the Sustainable Development Goal of Under 5
Mortality Rate <25 deaths/1,000 by 2030, from the year 2015
this would avert 12.8 million deaths (129). From 2000–2017,
if all units had an Under 5 Mortality Rate that matched the
best performing unit in each respective country, this would
have averted 58% of deaths in those under 5 years, that is, 71.8
(68.5–74.9) million deaths (130). A realistic projection was that if
the pandemic takes 5 years for “full cycling,” 60% of the global
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TABLE 4 | World mortality data 2019, with COVID-19 mortality to Sept 4 in 2020 for comparison (127,128).
Region Annual deaths in
thousands (per day)
Infant mortality
Rate/1,000
Under 5 yo mortality
Rate/1,000 (% of
deaths)
Age 15–60 mortality
Rate/1,000 (% of
deaths)
Age 65+(% of deaths)
World 58,394 (160) 28 38 (10%) 140 (32%) (57%)
COVID-19 on Sept 4, 2020 865 (3.5) (0%) (0.06%) (26%) (74%)
High-income 11,161 4 5 (1%) 81 (19%) (80%)
Middle-income 41,551 27 35 (9%) 144 (36%) (55%)
Low-income 5,665 46 68 (31%) 234 (42%) (27%)
Sub-Saharan Africa 9,052 49 74 (31%) 281 (46%) (23%)
Canada 291 4 5 (1%) 62 (17%) (82%)
Effect of COVID-19 is in bold for emphasis.
population is infected, and the IFR is 0.19%, COVID-19 will
account for 2.9% of global deaths. If only 10% of the high-risk
population are infected, COVID-19 will account for 0.6% of
global deaths over 5-years (95).
Some causes of death in the world are given in Table 5;
COVID-19 deaths (3,500/day up to September 4, 2020) are
also shown (131143). For example, there are an estimated
4,110 deaths/day from Tuberculosis (133), 3,699 deaths/day from
motor vehicle collisions (131), 21,918 deaths/day due to use
of tobacco (132), >3,400 deaths/day from Under 5 cases of
pneumonia or diarrhea (137,138), and 30,137 deaths per day
from dietary risk factors (139). The WHO has estimated that
if all people would adopt a vegan diet this would avert 13.7 M
(95% CI 7.9, 19.4) deaths by 2030 (84). Some of these deaths are
preventable if we were to take appropriate action, and some we
as a society have decided we are willing to accept in trade-off for
our freedom and wellbeing.
AN INFORMED COST-BENEFIT ANALYSIS
OF LOCKDOWNS
The Corona Dilemma
The economist Paul Frijters has asked us to consider “The Corona
Dilemma” (Figures 1A,B) modeled after the so-called “Trolley
Problem” in philosophy (144). He asks us to imagine “you are the
decision maker who can pull the lever on the train tracks to avoid
the coming train from going straight” (144). Our options are to
divert the train or not. “If you do not divert the train – you are
letting the virus rage unchecked [i.e., COVID-19 deaths]” (144).
On the other hand, “if you pull the lever – the diverted train will
put whole countries into isolation, destroying many international
industries and thus affecting the livelihood of billions, which
through reduced government services and general prosperity
will cost tens of millions of lives [i.e., COVID-19 reaction]”
(144). The world pulled the lever, and the unintended health
consequences of these measures did not play a part in modeling
or policy.
Cost-Benefit Analysis
Medical and Public Health experts are not expert in this type of
analysis (18,19). Health resources are finite. We all take health
risks to ensure a better future for ourselves, family, children,
and society. “Wellbeing of the population is the ultimate goal
of government (page 6 in ref 146)” (145,146). To compare
outcomes of policies we need a common single metric of
measurement to weigh trade-offs and make rational decisions.
The goal is to maximize the sum of years lived by the population
(52), weighted by the health quality of those years (i.e., Quality
Adjusted Life Years, QALY) or the wellbeing quality of those
years (i.e., Wellbeing Years, WELLBY). The QALY misses some
important things that are valued by individuals, including joy,
status, and things that give fulfillment like jobs. The WELLBY
measures the value of anything that makes life enjoyable, and
captures almost everything that is important to people. It is
measured by life satisfaction, asking “overall, how satisfied are
you with your life nowadays?” and rated on a Likert Scale from
0 (“not at all”) to 10 (“completely”); the usual healthy level is
“8,” and those indifferent between living on or not at all score
“2” – 1 regular year of happy life (1 QALY) is worth 6 WELLBY
(145,146). Despite some limitations, cost and benefit should
be measured in terms of human welfare in the form of length,
quality, and wellbeing of lives, and “to make no assessment is just
to make policy in a vacuum (page 9)” (147).
First, consider the benefits of lockdown, preventing COVID-
19 deaths. Using the age distribution of deaths and comorbidities,
in the UK the average person who died due to COVID-19 had 3–
5 healthy years left to live; that is, 3–5 QALY, or 18–30 WELLBY
(95,144,147). This number was even lower in Italy (144). We
can calculate the QALY and WELLBY that lockdowns “saved” by
multiplying the following factors:
50% of the population will be infected to achieve herd
immunity ×
0.3% IFR in the population ×
7.8 Billion people in the world population
=11.7 million deaths ×
5 QALY lost per death =58.5 million QALY ×
6 WELLBY per QALY =360 million WELLBY.
The number is likely much lower than this for several reasons:
it is likely <40% to achieve herd immunity, the IFR is likely
<0.24%, some deaths would occur even with lockdowns (that
might prevent at most 70% of deaths; in Sweden it was estimated
lockdown could have prevented one-third of deaths) (148), with
focus on retirement and nursing homes we might avoid many
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TABLE 5 | Selected causes of death in the world, with deaths per year and day, compared to COVID-19 in 2020 (131143).
Cause of death Deaths/year (/day) Case fatality rate Age group predominant
COVID-19 on Sept 4, 2020 864,618 (3,500) 0.24% 65–70 years old
Malaria 405,000 (1,110) 0.2% Children
Tuberculosis 1,500,000 (4,110) <15% –
Measles 140,000 (384) 1.46% Children
Influenza 389,213 (range 294–518 K)a0.01–0.02% for pH1N1 Children 34,800 (13–97 K), and 65 years old.
Respiratory deaths only
HIV 690,000 (1,890) Access to treatment for 67%
Motor Vehicle Collisions 1,350,000 (3,699) Young 5–29 years old, mostly in Low- to
Middle-Income Countries
Tobacco >8,000,000 (21,918)
Childhood (U5M) pneumonia 808,920 (2,216) <5 years old
Childhood (U5M) diarrhea 533,768 (1,462) 0.08% U5M <5 years old
Dietary risk factors 11,000,000 (30,137)
aThe 1957–1959 Influenza pandemic, when the world population was 2.87 billion, was estimated to cause 4 deaths/10,000 population totaling 1.1 million excess deaths due to
respiratory disease, with the greatest excess mortality in school-aged children and young adults. If COVID-19 is of similar severity, given the world population of 7.8 billion, we would
expect 3 Million deaths, mostly in older people (143).
K, thousands; U5M, under 5 mortality. Effect of COVID-19 in bold for emphasis.
of the excess deaths, and we cannot stay locked down forever [if
no “exit strategy” exists, then lockdown is not really a “strategy”
(10)]. A more realistic number is at least 2X lower, well fewer
than 5.2 million deaths “saved.” It is also worth mentioning that
the efficacy of lockdown has been questioned in several studies,
reducing the benefit of lockdown potentially markedly further
(Supplementary Table 4) (149155).
Second, consider the costs of lockdown (144,156158). An
important point must be made here. We are not comparing
COVID-19 deaths vs. economy as prosperity. Rather, it is
COVID-19 deaths vs. recession deaths – it’s lives vs. lives, as
the economy is about lives. “It’s horrible either way. . . [we’re]
advocating for the least people to die as possible” (159).
Expected costs of the recession in lives can be calculated
based on two methods. One uses historical evidence of
a strong long-run relation between government spending
(economic development) and life expectancy (144,156158).
Government expenditures on healthcare, education, roads,
sanitation, housing, nutrition, vaccines, safety, social security
nets, clean energy, and other services determines the population
wellbeing and life-expectancy (144). If the public system is
forced to spend less money on our children’s future, there
are statistical lives lost (people will die in the years to come).
The social determinants of health, including conditions of
early childhood, education, work, social circumstances of elders,
community resilience (transportation, housing, security), and
fairness (economic security) determine lifespan (160). As a
general rule, US$10K/year GDP buys an additional 10 years of
life, so in a life of 75 years, US$10K/year X 75 years =US$750K
buys 10 years in life expectancy =US$75K/QALY (144, 156158).
This is a maximum cost; in India US$25K/QALY is appropriate
(most effect occurs for vulnerable and marginalized groups)
(144). The other method is based on government numbers that
are used to estimate how much health and life expenditures
buy. Since the lockdown is a government public health policy,
“it is saving of lives which is what the lockdown was for. . . we
are treating decisions on how to face COVID-19 in the same
way as decisions. . . are made about resources to apply to the
treatment of cancer, heart disease, dementia, and diabetes (page
11)” (147). Based on research on how costly it is to save people
from illness (how government services maintain health), in the
UK it is US$20K/QALY, and using consumer willingness to pay
it is US$80K/QALY (144146). This again is a maximum cost,
as this is for Western countries, who are at least 3X wealthier
than the average country in the world; you can save a life in
poor countries with US$2-3K, and lives are saved more cheaply
with the first few billions spent (144,161). It is estimated that
in 2020–2021 the world economy will shrink by at least US$8-
9 trillion (about 6% of GDP), and this will take many years to
recover (Figure 2) (144,156,157,162,163). The loss in terms
of GDP will be “easily US$50 trillion over the coming decade”
(144,156), with lockdowns ordering businesses and workplaces
to stop functioning, ports closed, business bankruptcies, and
resultant disrupted supply and demand chains (64,164,165). We
can calculate what the recession resulting from lockdowns “cost”
as follows:
US$50 trillion loss in GDP ×
40% of GDP as government expenditure ÷
US$100K/QALY =200 million QALY ×
6 WELLBY per QALY =1.2 billion WELLBY.
This is an underestimate, and the actual figure is likely at least
12X higher for several reasons: the number US$100K/QALY was
used when it is far less than this for half the world population
residing in low-income countries and may be much lower even
in high-income countries, and a conservative estimate of world
GDP loss during the pandemic was used, particularly if there is
another prolonged period of lockdown.
Another cost of lockdown is the loneliness and anxiety effect
on individuals. It is estimated that loneliness from isolation costs
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FIGURE 1 | (A) The Trolley Dilemma using numbers compatible with the Corona Dilemma. Modified with permission from Frijters (144). (B) The Corona Dilemma
choices explicitly explained. Modified with permission from Frijters (144).
0.5 WELLBY/person/year (145,146). If lockdowns last for 2
months to 4 billion people, this results in a cost of 333 million
WELLBY (156). The cost is likely far higher, as this assumes
only 2 months of lockdown, and does not include the effect
of loneliness on lifespan (i.e., early mortality) and disease that
occurs particularly to young people (166172).
The last cost considered here is the effect of unemployment. It
is estimated that unemployment costs 0.7 WELLBY/unemployed
person/year (145,146). Since it is estimated there will be 400
million additional unemployment years due to the lockdowns,
the cost is 280 million WELLBY/year (156,173). The cost is likely
at least 3X higher, as recovery from unemployment will occur
over several years, we do not consider the effect on wellbeing
to the families of the unemployed, and we do not consider
the effect on deaths of despair in young people or on loss of
health insurance.
The effects of loneliness and unemployment on life-
expectancy are not considered in the costs above, only the
loss of life-satisfaction in WELLBYs. Recent literature has
summarized the major effect of individual income, social
network index (i.e., integration in a social network), and
adverse childhood experiences on life-span, early mortality, risk
of chronic diseases (including heart disease, diabetes, kidney
disease, stroke, cancer, lung disease, Alzheimer’s, substance
use, depression), and suicide rates (166172). Recent financial
difficulties, history of unemployment, lower life satisfaction,
and history of food insecurity are associated with mortality in
the United States (167). Actual or perceived social isolation
is one of the top three risk factors for death due to
cardiovascular disease, increases risk of death in the next
decade by 25–30%, and “risks creating cohorts of individuals
who are less socially functional (page 729)” (168,174).
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FIGURE 2 | Explanation of how acute GDP loss of 6-7% will accumulate over the decade to a loss of at least US$50 trillion. Reproduced with permission from Frijters
(Personal Communication).
Unemployment is associated with a mean adjusted hazard
ratio for mortality of 1.63 (175). Life stress is associated
with development and exacerbation of asthma, rheumatoid
arthritis, anxiety disorders, depression, cardiovascular disease,
chronic pain, HIV/AIDS, stroke, certain types of cancer, and
premature mortality (176). Especially concerning are the effects
on children during “the early years” of life, increasingly
recognized as the period of greatest vulnerability to, and
greatest return on investment from, preventing adverse long-
term outcomes that can have lasting and profound impacts
on future quality of life, education, earning potential, lifespan,
and healthcare utilization (169172). The early years of
life are a critical period when a child’s brain develops
from social interaction and experiences, thus providing the
foundation for their entire future life potential. During the
pandemic children are being exposed to increased intimate
partner violence, family financial crises, disrupted education,
an increasing achievement gap (i.e., low-income families
who do not have access to computer, internet, space, food,
and parental support cannot participate in online learning),
loneliness, physical inactivity, and lack of support services
(e.g., school lunches, access to early childhood services and
aids for those with disability) (87,88,104,107,177179).
These adverse childhood experiences have permanent impacts
that cannot be compensated for by later improvements in
social situations.
The cost-benefit analysis is shown in Table 6, finding on
balance the lockdowns cost a minimum of 5X more WELLBY
than they save, and more realistically, cost 50–87X more.
Importantly, this cost does not include the collateral damage
discussed above (from disrupted healthcare services, disrupted
education, famine, social unrest, violence, and suicide) nor
the major effect of loneliness and unemployment on lifespan
and disease. Frijters and Krekel have estimated that “the
[infection] fatality rate should be about 7.8% to break-even and
make a radical containment and eradication policy worthwhile,
presuming that would actually eliminate the disease (page 422)”
(180). A similar cost-benefit analysis for Canada is shown in
Supplementary Table 5, with the cost at least 10X higher for
lockdowns than the benefit. A different analysis for Australia is
shown in Table 7, estimating the minimum cost is 6.6X higher
than the benefit of lockdown (181,182). Another cost-benefit
analysis for the UK used National Institute for Health and Care
Excellence guidelines for resource decisions, that 1 QALY should
cost no more than US$38.4K. Assuming lockdown could save
up to 440 K people (although more likely at most: 66.65 million
population ×40% to herd immunity ×0.24% IFR =64 K
people) of 5 QALY each, and a minimum GDP loss of 9% (i.e.,
assuming lost output comes back quickly, and not including
any health costs of unemployment or disrupted education), “the
economic costs of t he lockdown. . . is far larger than annual tot al
expenditure on the UK national health service. . . the benefits of
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TABLE 6 | Cost-Benefit analysis in WELLBYs for the world’s response to
COVID-19.
Factor in World Benefit Cost
COVID-19 deaths 360M WELLBY
Recession 1.2B WELLBY
Unemployment 280M WELLBY
Loneliness 333M WELLBY
Disrupted health
services, disrupted
education, famine, social
unrest, violence, suicide
Not counted
TOTAL 360M WELLBY 1.813B WELLBY
BALANCE 5X (minimum)87X
(maximum)
B, Billion; M, Million; WELLBY, wellbeing years. See text for details of the calculations.
Maximum: benefit reduced in half; recession effect increased 12X, unemployment effect
increased 3X, and still not counting the disruption of health services, education, life-span
effects of loneliness, etc.
that level of resources applied to health. . . would be expected
to generate far more lives saved than is plausibly attributable
to the lockdown in the UK... The cost per QALY saved of the
lockdown looks to be far in excess... (often by a factor of 10
and more) of that considered acceptable for health treatments
in the UK (page 9–10)” (147). The authors estimated the benefit
of easing restrictions for over the next 3 months outweighs the
cost by 7.3–14.6X (147). “A cost-benefit analysis of 5 extra days
at COVID-19 alert level 4” for New Zealand found that the cost
in QALY was 94.9X higher than the benefit (183). Finally, a cost-
benefit analysis for the US is shown in Table 8, finding the cost of
lockdown would be at least 5.2X the benefit (184,185).
Objection: The Economic Recession Would
Happen Without Lockdown
This is unlikely, particularly if the fear is appropriately controlled
with clear communication on risk, numbers with denominators
and context, and important trade-offs, as this information
becomes available. The resources and attention should be
directed toward protecting the most vulnerable (i.e., older people,
especially those with multiple co-morbidities). The evidence for
policy impact on total human welfare should be based on a
wide range of expertise, including economists, and not only
health experts. The CIDRAP group published suggestions for
communication during a crisis, which included advice to not
over-reassure (i.e., be realistic about the course post-lockdown
– cases and deaths will climb), to express uncertainty (i.e.,
explain the difficult dilemmas and trade-offs, and why we choose
which course; explain that the initial reaction was temporary,
buying time to figure out next steps); to validate emotions (i.e.,
admit waves of disease will occur and there may be economic
devastation); and to admit and apologize for errors (i.e., we must
resurrect a devastated economy in order to save lives) (186).
The severity of mandated lockdowns was directly linked with
the severity of the economic collapse (147,181,187191). These
were direct commands to halt work, restrict travel, restrict the
number of people inside dwellings, close factory floors, stay at
home, etc. Economic activity, GDP loss, and unemployment
were temporally, within weeks, related to lockdown orders
(181). There was a dramatic decline in employment, consumer
spending, and economic outcomes largely accounted for by
different degrees of restrictions in different countries (181,188,
189). The consensus, for example by the Bank of England, the
Reserve Bank of Australia, the Organization for Economic Co-
operation and Development, the International Monetary Fund
(e.g., the “calamitous Great Lockdown”), and the Chief Medical
Officer of Health in Canada (e.g., “the extensive slowdown in
the Canadian economy as a result of public health emergency
measures” (page 29), is that the economic recession is a result of
the lockdowns (45,117,190192).
Objection: Consider the “Long-Haulers”
The long-term effects of COVID-19 illness need to be studied and
clarified. Much of the current information is based on anecdotes
(i.e., single cases) in the press. It may be expected that survivors
of ARDS due to COVID-19 will have significant quality of life
sequelae similar to ICU survivors from other causes of ARDS, or
even lower given the lower cytokine levels in COVID-19 (193,
194). It may also be expected that some survivors of COVID-
19 that did not require hospitalization will have significant
lingering symptoms for months similar to what occurs with other
causes of community acquired pneumonia (195). The few studies
reported to date do not well quantify the severity and duration
of long-term symptoms such as fatigue, breathlessness, “foggy
thinking,” etc., making it difficult to interpret the impact on cost-
benefit analyses (196200). The highest rates of “long-COVID-
19” are from crowdsourced online data where there is likely
a strong selection bias in participation (201203). In addition,
most of these reports do not compare to contemporary controls
during the pandemic, controls who are often experiencing
social isolation, unemployment, and loneliness. For example,
one survey of people without COVID-19 in the United States
found a high prevalence of anxiety (25.5%), depressive (24.3%),
and trauma and stressor related (26.3%) disorders, with 13.3%
who started or increased substance use to cope, and 10.7% who
seriously contemplated suicide in the last 30 days (204). The
Household Pulse Survey in the US found that in 2019 11% of
adults had symptoms of anxiety or depressive disorder, while
in April-August 2020 35–40% did (205). Another survey in US
adults found the prevalence of depression symptoms was more
than 3-fold higher during COVID-19 than before, and worse for
those with lower social and economic resources (206). A survey in
Australia found worse exercise (47.1%), mental wellbeing (41%),
weight gain (38.9%), screen time (40–50%), and life satisfaction
(down by an average of 13.9%) during the pandemic (207).
In Canada, 57% of children 15–17 years old reported their
mental health was “somewhat worse” or “much worse” than it
was prior to physical distancing measures during the pandemic,
and Canadians 15 years old had a 23% decrease in reported
“excellent or very good self-perceived mental health” (177,208).
Although there will likely be many “long-haulers,” the incidence,
severity, and duration of long-term symptoms would need to
be very high to change the cost-benefit balance. Given that at a
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TABLE 7 | Cost-benefit analysis in quality adjusted life years for Australia’s response to COVID-19 (181,182).
Consideration Cost/month Benefit overall Comment
Wellbeing (immediate) 83,333 QALY Attributes half of reduction (of 0.5 WELLBY) to lockdown
Reduced economic activity
(government services)
25,812 QALY Attributes half of yearly 6% loss in GDP to lockdown, and only government
expenditure (not private) buys welfare (36% of GDP), at $100,000/QALY
Increased suicides 600 QALY Expected to rise 25% over next 5 years, and attributes only 40% of this to lockdown
Disrupted non-university schooling 740 QALY Foregone wages of children: each year of schooling yields approximately 9% more
future earnings; assumes 80–90% equivalence of disrupted to normal school days
Disrupted health services, future
mental stress and violence
Not included. Also does not consider bad habits inculcated (reduced physical
activity, increased weight gain (for 40%), increased alcohol intake)
Reduced COVID-19 deaths 50,000 QALY This is for lockdown “ad infinitum” (not per month); 0.04% of population saved
Total over 3 months of lockdown 331,485 QALY 50,000 QALY Minimum cost is 6.6X any benefit
QALY, Quality Adjusted Life Years; WELLBY, Wellbeing Years.
TABLE 8 | A cost-benefit analysis for lockdown in the US, modified from Cutler and Summer (184,185).
Factor Quoted (184)Revised Explanation of revision
Cost
GDP loss $7.592 Trillion $7.592 TrillionaNo revision made. Note that, as the US accounts for 15% of world GDP, this translates to the
global loss of $50.6 Trillion (as estimated in Table 6).
Mental health 0 $0.8 Trillion Assuming that 50% of the mental health effect is from lockdowns
Benefit
Deaths avoided $4.4 Trillion $0.3125 Trillion Assuming the 625,000 deaths lose 5 QALY each at $100,000 per QALY. This is better than
assuming each death, regardless of age or comorbidity, is the loss of the entire value of a
statistical life. This is also how the cost on mental health was calculated.
Health impairment $2.6 Trillion $0.4875 Trillion Assuming 35% of quality of life is lost for the remaining years left (likely 15 remaining years of
80 on average in a statistical life).
Mental Health $1.6 Trillion $0.8 Trillion Assuming 50% of the mental health effects are due to not having lockdowns to prevent
COVID-19 cases.
Cost-benefit balance Benefit 1.3X cost Cost 5.2X benefit A minimal estimate: the GDP loss will likely be higher; willingness to pay for QALY is usually
<$100,000/QALY, and NICE uses $30,000/QALY; not all deaths could be avoided by
lockdown; at least 20% of excess deaths are not due to COVID-19 (i.e., are more likely from
the response); severe cases (i.e., those that do not need intensive care, and may only need
oxygen) likely have lower risk for health impairment of the severity modeled.
aIf the Value of a Statistical Life is accepted as used in the reference at $7 million, and the US economy will lose $7.592 Trillion in GDP over the decade, that is equivalent to the loss of
1,084,571 whole (statistical 80-year duration) lives =86,765,680 years of lost life; that is equivalent to (assuming 5 QALY lost per COVID-19 death) 17,353,136 COVID-19 deaths.
generous minimum the cost-benefit balance is at least 5X against
lockdowns, the sequelae of COVID-19 would need to cost well
over 200 million QALY worldwide, and likely >10X that number,
to make the cost-benefit analysis in need of reconsideration.
Objection: Low-Income Countries Are
Particularly Susceptible and Need
Protection
The Imperial College COVID-19 Response Team modeled the
effect on low-income countries (209). These countries were
hypothesized to be more susceptible to COVID-19 deaths, even
with markedly lower population over age 65 years (about 3%),
due to several factors: larger size of households (i.e., more
homogeneous contact patterns), far fewer hospital and ICU beds,
lower quality of health care, and unique co-morbidities (e.g., HIV
in >1%, tuberculosis in >25%, and malnutrition in >30% of
the population) (209). For suppression to have benefit, it was
estimated to need to be in force 77% of the time (compared to
66% in high-income countries) over the 18 months of modeling
[and “well beyond the time window of our simulations (page
421)”] (209). However, modeling inputs were overestimated,
with >90% of the population infected, and baseline IFR in
high-income countries 1.03%. Moreover, low-income countries
are more vulnerable to lockdown adverse effects for several
reasons: lower ability to work from home, more household based
transmission (when confined to home), economic vulnerability
(a higher degree of informal labor markets, and marginal capacity
to provide support for ensuring livelihoods), slower build-up of
herd immunity (given limited health care capacity), little testing
capacity, wider health risks from diverting all attention to a
single disease, and future health system failure once suppression
measures are lifted (also see Table 1) (209,210). The effects
of a recession on government spending is magnified when
this spending was already insufficient to improve the social
determinants of health. In India, the desperation is leading to
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an increase in child trafficking (211). Surveys in Africa indicate
a very low IFR; for example, in Kenyan blood donors 5% were
seropositive yet the country reported only 100 deaths, in Bantyre,
Malawi, a serosurvey found 12.3% of healthcare workers were
seropositive yet only 17 deaths were reported, and in two cities
in Mozambique seropositivity was 3 and 10% yet only 16 deaths
were reported (212). It is extremely likely the cost-benefit analysis
is even more against lockdown in low-income countries for
these reasons.
DISCUSSION
What to Do Now: Change the Trolley Track
Other Calls for a Change in Response Priorities
Several other groups and individuals have made calls for a
change in COVID-19 response priorities (Table 9) (213220).
In an open letter on July 6, 2020, to the Prime Minister and
Premiers of Canada signed by many former deputy ministers of
health, chief public health officers, and medical deans, the authors
called for “A Balanced Response” (213). They write that the
current approach “carries significant risks to overall population
health and threatens to increase inequalities. . . Aiming to
prevent or contain every case of COVID-19 is simply no longer
sustainable. . . ” (213). In an open letter to the National Cabinet in
Australia signed by many economists and medical experts with
the Australian Institute for Progress, the authors make similar
points (214). They write that “to analyze the COVID-19 effect it is
necessary to understand it as shortening life. But the lockdowns
and the panic have also had a cost in shortening life for others”
(214). Ioannidis called for evidence to guide policy, noting many
of the collateral and recession effects discussed above (215219).
“Shutdowns are an extreme measure. We know very well that
they cause tremendous harm” (216). A resignation letter by an
economist in the Australian Treasury wrote that “the pandemic
policies being pursued in Australia. . . are having hugely adverse
economic, social and health effects. . . The need for good policy
process does not disappear just because we face a public health
crisis. . . ” (220). The “Great Barrington Declaration” written on
October 4, 2020, by infectious disease epidemiologists and public
health scientists recommends “Focused Protection” (221). The
declaration writes that “current lockdown policies are producing
devastating effects on short and long-term public health. . .
leading to greater excess mortality in years to come. . . ” (221).
A caveat to quoting these open letters is that “petitions
should not be used to prove that the positions of the signatories
are scientifically correct (page 1),” as this would be based
on the fallacies of “argument ad populum” and “invoking
authority,” and have other drawbacks (222). These open letters
are used only to show that many have expressed views similar
to those expressed here, and this might open the door to
serious consideration of the empirical evidence and arguments
presented above.
Objection: Herd Immunity Is a Dangerous Idea
There are several objections that have been made to the idea of
opening up society to achieve natural herd immunity (223226).
First, an objection is that natural herd immunity assumes the
immunity is long lasting, and this may not be the case (223
226). If immunity is short-lived, then COVID-19 may become an
endemic and likely yearly viral infection as predicted by Kissler
et al. (2). In the event of short-lived immunity it may still be
important to achieve natural herd immunity to protect the high-
risk groups (i.e., older people) now and yearly (until a vaccine
is widely available) without recurrent and prolonged lockdowns
that devastate the economy and thus population life-expectancy
and wellbeing. Notably, if immunity is not long-lasting this will
be a problem for possible vaccine induced herd immunity as well,
as the world population will need vaccines to be produced and
delivered everywhere at least each year.
Second, another objection is that the costs in deaths, mental
and physical health and suffering, socioeconomic inequities, and
harming the economy will be too high (223,224). This objection
ignores the discussion above of the trade-offs involved that
include not only COVID-19 direct effects, but also indirect effects
of the response to COVID-19, the collateral damage and cost-
benefit analysis where it was shown that the costs of all these
effects is in fact much higher with lockdowns.
Third is the objection that uncontrolled transmission in
younger people would inevitably result in infections in high-risk
groups with high mortality (223226). The ability to successfully
shield continuing care facilities and hospitals from COVID-19 is
questioned (223,224). Prolonged isolation of high-risk groups is
said to be “unethical (page e71)” (223). The objection is odd, as
if we cannot protect those in nursing homes nor hospitals, why
are we using personal protective equipment at all? In addition,
prolonged isolation of all groups is what has occurred now,
and based on the cost-benefit analysis this is what is unethical
by causing far more harm to all, including the high-risk older
population. Of course, infection can still spread to high-mortality
populations; however, the goal is to reduce this risk. Moreover,
<10% of the population is at high-risk, accounting for >90% of
potential deaths; surely we can focus on protecting this subgroup
of people (219). Early monitoring in Europe shows that despite
increasing COVID-19 cases, excess mortality has only shown
a slight increase, suggesting protection of the most vulnerable
may be feasible (227). Modeling has also suggested that social
distancing of those over 70 years of age would prevent more
deaths than a fixed duration of social distancing of the entire
population (228).
Fourth is the objection that healthcare systems will be
overwhelmed by uncontrolled spread (223,224). This is a
worrisome possibility, as health-care providers may be forced
to make painful rationing decisions. If a healthcare system is
overwhelmed, the effects would have to be extreme to make
the benefit of lockdowns to save ICU capacity comparable to
the long-term costs. There are several ways to minimize this
possibility, including a focus on protecting those at high-risk
(see below), information dissemination to cause fast awareness
of voluntary sensible self-imposed use of handwashing and (in
crowded areas) masks (229,230), limiting very large gatherings,
and expanding critical care capacity when necessary. Forecasting
of healthcare capacity needs in the short or medium term,
even when built directly on data and for next day predictions,
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TABLE 9 | Other calls for a change in COVID-19 response priorities.
References Content of the call for adjusting COVID-19 response priorities
Open letter on July 6, 2020, to the
Prime Minister and Premiers of Canada
(213)
The current approach “carries significant risks to overall population health and threatens to increase inequalities… Aiming to
prevent or contain every case of COVID-19 is simply no longer sustainable… We need to accept that COVID-19 will be with
us for some time and to find ways to deal with it.”
The response risks “significantly harming our children, particularly the very young, by affecting their development, with
life-long consequences in terms of education, skills development, income and overall health.”
Suggest that we need “to focus on preventing deaths and serious illness by protecting the vulnerable while enabling society
to function and thrive… While there is hope for a vaccine to be developed soon, we must be realistic about the time… We
need to accept that there will be cases and outbreaks of COVID-19.”
“Canadians have developed a fear of COVID-19. Going forward they have to be supported in understanding their true level
of risk… while getting on with their lives – back to work, back to school, back to healthy lives and vibrant, active
communities….”
COVID-19 “is not the only nor the most important challenge to the health of people in Canada… The fundamental
determinants of health – education, employment, social connection and medical and dental care – must take priority…”
Open letter to National Cabinet of
Australia (214)
“exposure to COVID-19 is only temporarily avoidable”; “to analyze the COVID-19 effect it is necessary to understand it as
shortening life. But the lockdowns and the panic have also had a cost in shortening life for others.”
Some of these costs include that the lockdown: “will decrease national income… and this will have a measurable effect on
the length of the average lifespan,” “[has] disrupted normal health services… estimated an increase in cancer deaths over
the next 12 months of 20%,” [and will cause] future suicides by the unemployed and others whose lives have been ruined.”
Urge for “a cost-benefit analysis, including lives saved versus lives lost, both directly and consequentially… [and] weekly or
daily non-epidemic death figures should be posted as well as deaths from the epidemic…”
Ioannidis, JPA (95,215219) Called for evidence to guide policy, noting many of the collateral and recession effects discussed above.
“Shutdowns are an extreme measure. We know very well that they cause tremendous harm.”
“the excess deaths from the measures taken is likely to be much larger than the COVID-19 deaths… learning to live with
COVID-19 and using effective, precise, least disruptive measures is essential to avoid such disasters and to help minimize
the adverse impact of the pandemic” (95).
“When major decisions (e.g., draconian lockdowns) are based on forecasts, the harms (in terms of health, economy, and
society at large) and the asymmetry of risks need to be approached in a holistic fashion, considering the totality of the
evidence” (219).
Resignation letter by economist in
Victorian Treasury (220)
“the pandemic policies being pursued in Australia… are having hugely adverse economic, social and health effects… The
need for good policy process does not disappear just because we face a public health crisis… the elderly are many times
more vulnerable to a serious outcome than the young. It was necessary, therefore, to work out a targeted age-based
strategy… The direct and indirect costs imposed by regulatory approaches may not be… immediately obvious. Risk
regulation that is poorly targeted or costly will divert resources from other priorities… needed to commission a cost-benefit
analysis of alternative policy options….”
Governments should have realized “they are hostage to chronic groupthink and actively sought alternative advice… instead
of performing its taxpayer-funded duty of providing forthright analysis of alternatives… can (even now) be managed by
isolating the elderly and taking a range of voluntary, innovative measures.”
The Great Barrington Declaration (221) “current lockdown policies are producing devastating effects on short and long-term public health… leading to greater
excess mortality in years to come… keeping students out of school is a grave injustice… The most compassionate
approach that balances the risks and benefits of reaching herd immunity, is to allow those who are at minimal risk of death
to live their lives normally to build up immunity to the virus through natural infection, while better protecting those who are at
highest risk.”
has consistently failed, and most healthcare systems were not
overwhelmed despite sometimes being stressed with high peaks
of cases (219,231). Forecasting failure led to frail older patients
being discharged to nursing homes (where there was high
mortality), and largely empty wards (unnecessarily affecting
hospital utilization for other serious conditions); in Canada
“overall ICU occupancy rates did not exceed 65% (page 12)”
(45,219). Lockdowns in anticipation of forecast healthcare
incapacity should not be done, especially if based on forecasting
that is not released for public scrutiny nor repeatedly fit to
real-time data to verify accuracy. In addition, if there are
insufficient ICU beds for the population due to underfunding,
the effects of the recession on government healthcare spending
in the future will markedly adversely worsen this situation in
the long-term.
Fifth is the objection that natural herd immunity is not
achievable (223226). This is based on the few case reports
of re-infection, the Brazilian city of Manaus where adjusted
seroprevalence was up to 66% yet there is currently a resurgence
of COVID-19 cases, and the claim that natural herd-immunity
has never occurred. The seven published case reports of re-
infection, four with symptoms (one requiring hospitalization,
and one death in an immunocompromised 89 year-old with
few details reported), when 10% of the world population has
likely been infected over the past 10 months cannot yet provide
evidence that severe reinfection and contagion is at all common
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(232237). This also applies to a more recent review finding 17
cases of reinfection reported of whom 3 were hospitalized and
the one died (238). Regarding Manaus, the high seroprevalence
likely reflected the special situation of a relatively homogeneous
cohort of people in overcrowded low socioeconomic urban
situations, with reliance on crowded long riverboat travel; now
there seems to be a different demographic cohort of young
wealthy individuals being exposed (239241). The resurgence of
cases in Manaus was described as follows: “from the second week
of August there has been a small increase in the number of cases
which, at the time of writing, has begun to decline (page 3)”
(241). In addition, the peak seroprevalence in blood donors in
Manaus was 51.8% in June, while another study of household
seroprevalence in Manaus on May 14–21 found this to be 12.7%
(the respective numbers for São Paulo were closer, at 6.9 and 3.3%
in the two serosurveys) (241,242). Even correcting for a possible
lower sensitivity of capillary blood used in the household survey
does not explain the difference, as the corrected seroprevalence
might be up to 19.3% (243). Regarding historical natural herd-
immunity, it is likely that this was achieved for several infections,
with outbreaks that occurred as births added sufficient numbers
of new susceptible young individuals (e.g., for Measles, Mumps,
Rubella, Pertussis, Chickenpox, Polio) (244,245). The current
vaccines are given intramuscular, and thus do not induce mucosal
IgA responses thought necessary to prevent upper respiratory
tract SARS-CoV-2 infection (246). These vaccines have unknown
efficacy on infection and infectiousness of SARS-CoV-2 in
those protected from COVID-19 symptoms (246248). Herd
immunity is premised on the efficacy of immunity in preventing
transmission (244), and it is possible that current vaccines will
have little effect on this.
Finally, an important point to emphasize is that the
information in this review does not depend on natural herd
immunity being achieved. The collateral damage, and the cost-
benefit analysis showed that lockdowns are far more harmful than
a risk-tailored population specific response. “Public health is the
science and action of promoting health, preventing disease, and
prolonging life. . . ensuring that Canadians can live healthy and
happier lives (page 59–60)” (45); some suggestions for how to do
this are discussed below.
Some Suggestions: What Can We Do?
Focus on Protecting Those at High Risk
A risk-tailored, population-specific response (249). This starts
with better public understanding of the risks and trade-offs
involved (186). Protection should focus on high-risk groups:
those hospitalized (e.g., prevent nosocomial infection) (216), in
nursing homes (e.g., staff work in only one facility, adequate
personal protective equipment supply, more staff, equitable pay)
(250), prisons, homeless shelters, and certain demographics
(e.g., age 70 years, especially those with multiple severe co-
morbidities) (249). There should be investment in improving
the social determinants of health [e.g., “invest in strategies that
address health inequities and better serve the elderly, people
experiencing homelessness, and those living with limited means
(page E685)” (249)] (45,160,251). That this is so important
is demonstrated by the sobering fact that “Black disadvantage
operates every year on the scale [in terms of age-adjusted
mortality and life-expectancy in the United States] of White’s
experience with COVID-19 (page 21854)” (252). Do not lock
everyone down, regardless of their individual risk, as this will
cause more harm than benefit (216). It is not true that “no one
is protected until everyone is protected (page 2)” (45).
Open Schools for Children (87,253)
School provides essential educational, social, and developmental
benefits to children (254). Children have very low morbidity and
mortality from COVID-19 (174), and, especially those 10 years
old, are less likely to be infected by SARS-CoV-2 (57,255258),
and have a low likelihood to be the source of transmission of
SARS-CoV-2 (178,258). Children account for 1.9% of confirmed
cases worldwide (259). School closures don’t seem to have an
impact on community outbreaks (178,260). Modeling predicted
that school and university closures and isolation of younger
people would increase the total number of deaths (postponed to
a second and subsequent waves) (228). Modeling also predicted
that school closures alone would prevent only 2–4% of deaths
(261). The infection mortality risk from influenza is higher than
from COVID-19 for people age <50-years, and about 2.9X
lower for those 50–64-years (still, 99.86% survived SARS-CoV-2
infection) (see Supplementary Table 6) (41,262,263). We need
to educate parents and teachers regarding their low risk, and
focus teachers with greater vulnerability due to age and multiple
co-morbidity on remote learning. Until schools open, education
is lacking especially for those with the fewest opportunities,
worsening social disparities that education systems are intended
to level. Similarly, allow visitation in children’s hospitals and
pediatric long-term care facilities, where the risk even with co-
morbidities is so low as to not warrant the tragedy of sacrificing
our most vulnerable in the false hope of protecting them (43,48,
49,178).
Consider Increasing Health Care Surge Capacity
If forecasting, accurately calibrated repeatedly to real-time data
[up to now, forecasting, even short-term, has repeatedly failed
(219,231)], suggests it is needed, health care surge capacity
should be increased. With universal masking in hospitals,
asymptomatic health care workers can continue to work as their
transmission risk, even if infected, is very low, and this can
preserve staff coverage (264,265).
Build Back Better
Maybe we have learned that the “government can intervene
decisively once the scale of an emergency is [or seems] clear
and public support is present (page 4)” (266). Maybe we can
“recalibrate our sense of omnipotence” seeing “the ability of
‘natural’ forces to shock the global economy” (page 4) (266).
Maybe we can tip “energy and industrial systems toward
newer, cleaner, and ultimately cheaper modes of production
that become impossible to outcompete (page 4)” (266). This
would involve investment in clean technologies (e.g., renewable
energy, green construction, natural capital, carbon capture and
storage technologies), and conditional (on measurable transition)
bailouts. This is because climate change, like the COVID-19
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response, will involve market failures, externalities, international
cooperation, and political leadership: the devastation is just in
slow motion and far graver. The aggregate fiscal stimuli aimed
at alleviating the consequences of the COVID-19 crisis for 149
countries amount to US$12.2 trillion (267). Climate experts
have estimated that “the additional investment needed to shift
low-carbon energy investment onto a Paris-compatible pathway
thus amounts to about US$300 billion per year globally over
the coming 5 years. . . 12% [of total pledged stimulus to date]
when considered over the entire 2020-2024 period. . . (page 299)”
(267). Moreover, “subtracting divestments from high-carbon
fossil fuels. . . indicates that the overall increase in net annual
investments to achieve an ambitious low-carbon transformation
in the energy se ctor are notably small. . . 1% [of the total
announced stimulus to date] over the 2020-2024 period (page
299)” (267). A green recovery may be a driver of employment,
spur innovation and diffusion of technologies, reduce stranded
assets, and result in a more sustainable and resilient society
(117,267).
Some Research Priorities
More information will help to optimize responses to the
pandemic. This particularly applies to possible prevention,
prophylaxis, and treatment of COVID-19. How effective cloth
masks are at preventing infection, or at reducing severity of
infection needs more study (268,269). The safety, efficacy
(including for interrupting infectiousness, necessary to achieve
herd immunity), and durability of protection from vaccines,
particularly in high-risk groups, must be determined in large
Phase III randomized controlled trials (246). Novel treatments
are in clinical trials, with dexamethasone having benefit on
mortality in those with severe COVID-19 requiring oxygen
treatment (270). Research is also required to determine the
frequency and severity of reinfections (271). The frequency,
duration, and severity of “long-COVID” requires better study.
The impact of influenza on COVID-19 morbidity and mortality
requires study, as both viruses may compete for the same
susceptible individuals (271). Importantly, research on “the
impending authoritarian pandemic. . . [the] toll being inflicted
on democracy, civil liberties, fundamental freedoms, [and]
healthcare ethics. . . (page 1)” [e.g., due to those responses that
were not strictly necessary nor proportionate, largely copied from
the “authoritarian example of others (page 5)”] is required to
prevent regression and “erosion of rights-protective democratic
ideals and institutions (page 1)” (272) across the globe (272275).
CONCLUSION
The lockdowns implemented in the name of public health
entailed trade-offs that were not adequately considered (275).
Lockdowns may prevent some COVID-19 deaths by flattening
the curve of cases and preventing stress on hospitals. At the same
time, lockdowns cause severe adverse effects for many millions
of people, disproportionately for those already disadvantaged
among us. The collateral damage included severe losses to
current and future wellbeing from unemployment, poverty, food
insecurity, interrupted preventive, diagnostic, and therapeutic
healthcare, interrupted education, loneliness and deterioration
of mental health, and intimate partner violence. The economic
recession has been framed as the economy vs. saving lives
from COVID-19, but this is a false dichotomy. The economic
recession, through austerity in government spending on the
social determinants of health, can be expected to cause far more
loss of life and wellbeing over the long-run than COVID-19
can. We must open up society to save many more lives than we
can by attempting to avoid every case (or even most cases) of
COVID-19. It is past time to take an effortful pause, calibrate our
response to the true risk, make rational cost-benefit analyses of
the trade-offs, and end the lockdown groupthink.
AUTHOR CONTRIBUTIONS
AJ wrote the manuscript, and approved the final version.
ACKNOWLEDGMENTS
A version of this paper appeared in a Preprint as: Ari
R. Joffe. COVID-19: Rethinking the Lockdown Groupthink
(Preprint) (2020). Available online at: https://www.preprints.org/
manuscript/202010.0330/v2 (accessed January 4, 2021).
SUPPLEMENTARY MATERIAL
The Supplementary Material for this article can be found
online at: https://www.frontiersin.org/articles/10.3389/fpubh.
2021.625778/full#supplementary-material
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