Want to exit Covid-19 confinement? Protect the chronically-ill and the elderly, and let the others work, learn and play! For an immediate, but gradual de-confinement strategy, differentiated per age and chronic health status

(Updated on 13 April 2020)

Executive Summary

The current (in most of Europe) or envisaged (in the Netherlands and Sweden) policies of universal confinement of the population lead to an impasse, and are immensely costly economically, socially – and in terms of lives lost because of generalised poverty and decay of public infrastructure that this crisis will cause as it lengthens and deepens.

Based on public and official data from the European Centre for Disease Prevention and Control, the National Health Commission of the People’s Republic of China, the French Public Health Authority (Santé Publique France), the Italian Epidemiological Institute (Istituto Superiore di Sanità) and Eurostat:

  • The Infection Fatality Rate of Covid-19, i.e. the ratio of the number of people dying from the disease to the number of those infected, is in the range of 1%. This figure is confirmed (with a value of 0.66% and a 95% confidence interval between 0.4 and 1.3%) by a recent article in the reference scientific journal in medicine, The Lancet;
  • This Infection Fatality Rate is enormously differentiated per population groups:
    • it is in the range of 0.007% (7 for 100,000) for people aged 0 to 44 years that are in good health, i.e. with no chronic disease co-morbidity, i.e. 10 times less than the natural mortality rate existing for people of this age class (70 for 100,000);
    • it is between 3 and 8% for people aged 75 years and above, whatever their health condition, a ratio comparable to the natural mortality rate existing for people of this age class (7.63%);

This represents a 1:1,000 ratio in vulnerability between the highest- and lowest-risk populations.

Based on this, I support an exit strategy from the existing universal confinement based on gradual deconfinement, differentiated by age and health status, whereby:

  1. only the vulnerable population (the chronically ill and the elderly above a threshold age to be determined around 65 years of age, e.g. that of legal retirement) remains confined at home until herd immunity is achieved in the rest of the population;
  2. the rest of the population (young people – children, adolescents and adults up to the age threshold defined above, e.g. those of working age – and in good health) is made free to work, learn and play normally, and to be infected with Covid-19 at an extremely low risk (3 to 10 times lower than natural mortality, which is itself very low, of these age groups), in a graduated manner, starting immediately with the healthy population aged 0-44 years, and then gradually extending this measure to age 64 years, for example by 5-year increments every month, at an appropriate rate to maintain an acceptable flow of new serious cases to be treated by hospital emergency departments.

This exit strategy of gradual deconfinement, differentiated by age and health status :

  • can start being implemented immediately because it is based on information that already exists and can be easily monitored, namely age and chronic disease status ;
  • adds an excess mortality that remains low (for France, about 1,000 people between 0 and 44 years old in good health, then about 18,000 people between 45 and 64 years old in good health, compared to the 80,000 of these age groups dying per year, and the 560,000 annual deaths, all causes and ages combined), only once;
  • avoids the saturation of the hospital emergency departments;
  • restarts the productive system quickly and avoids considerable economic, social and therefore human damage: the duration of strict and universal confinement is limited to 1 month, the one that has just elapsed, with a fairly rapid capacity to reconstitute a productive system in apnoea at this stage, whereas the alternatives foresee periods of at best 12 to 18 months of economic shutdown, a period during which no player is able to survive on its reserves ;
  • constitutes herd immunity and therefore avoids the repetition of periods of strict confinement until a vaccine availability that to date remains hypothetical and envisaged at the earliest after 12 to 18 months;
  • protects the vulnerable groups in the population efficiently;
  • is superior to any of the other strategies currently envisaged to exit universal confinement.

The decisions of universal confinement of the population were rational and responsible in the situation of ignorance prevailing when they were taken

The current shutdown of economies and societies around the European Union and the world is grounded on one figure, and one assumption: the Crude FatalityRate (number of reported deaths divided by the reported cases at a given date) is high, in the range of 3-4% (source WHO situation report 06 March 2020), and indiscriminate, killing the whole population more or less evenly, nobody being protected. If this is indeed true, then a simple mathematical extrapolation leads to millions of deaths in the European Union, which is morally unacceptable.

In front of this, two strategies are possible in the literature:

  • identify the infected people and put them in quarantine as long as they remain contagious, leaving the others to continue their normal lives. This strategy, called “containment”, requires the availability of tests, and that all infected people be tracked individually to test all the persons that they have been in contact with, so that all infected people be placed in quarantine before contaminating others. Containment is only feasible when the number of infected people is low, i.e. at the start of the epidemic outbreak – it is beyond reach when the figures are in the tens or hundreds of thousands; or
  • confine the whole population, so that the transmission rate falls below the threshold value of 1, and wait for the virus to die out.

The last option, called “suppression” is what the Chinese government and its people have achieved remarkably well, acting with extraordinary courage and clear-sightedness in an emergency situation where nothing was known on the virus. This is also what governments world-wide are doing, starting in Italy and in other Member States of the European Union – but at an immense economic and social cost. In the absence of any information on the lethality of the virus and on the characteristics of the population being killed by it, this option was the only rational and responsible one, and I am grateful to our governments that they have had the courage to take them.

These extremely costly decisions only make sense if the assumptions above hold true: a high, indiscriminate infection mortality rate.

The current policies of universal confinement are an impasse: an exit strategy is urgently needed

The current (or envisaged, as is the case of Sweden) policies of universal confinement were indeed rational and responsible when they were taken. There are however two massive problems to this policy:

  1. the economic and social costs are immense. This confinement prevents most people from working, and shuts down most of the economy, so that the economic survival of vast segments of the productive system is jeopardised. It thus creates massive unemployment and social disruption, and hence massive fatalities, as all deep economic crises do. The only means to limit the damage being massive additional public debt. Roughly speaking, every day of universal confinement is a day of lost GDP, and thus adds 0.3% (1/365) of annual GDP to the public debt;
  2. the solution is only provisional, and requires additional, and equally costly, shutdowns of the economy at each new surge of the pandemic, as it travels round the world and comes back from a location where it hasn’t been suppressed. This is because the population has not been infected, and has thus not developed an immunity to the virus. The Imperial College Covid-19 response team has modelled in its Report n°9 of 16 March 2020 that “social distancing” (= confinement) and the closure of schools and colleges would need to be applied ca. 2/3 of the time after the initial period of universal confinement, until a vaccine is developed, i.e. over 12 to 18 months – if everything goes well.

It is thus important to develop an exit strategy from the current deadlock created by the universal confinement policy.

Recently published data suggest a strategy of “graduated de-confinement, differentiated by age and health status” to exit the current deadlock

Current, official, publicly available data with complementary features from the front-runners China, Italy and France indicate that (fortunately) the assumptions of universal and high fatality rates are not empirically valid, and suggest exiting the existing or envisaged policy of universal confinement in a strategy that I would call “graduated de-confinement, differentiated by age and health status”, which I describe and justify in greater detail at the end of this post, based on the extremely contrasted Infection Fatality Rates of Covid-19 between sub-populations that can be determined ex ante with existing information.

This proposal is based on the following computations that I performed and that I detail hereunder, of:

  • the Infection Fatality Rate of the Covid-19, i.e. the ratio of the number of people dying from the disease to the number of those infected, for the whole population; and, based on this,
  • the Infection Fatality Rate of the Covid-19 per age group and per chronic health condition.

The Infection Fatality Rate estimates the fatality rate among all people having been infected: those where the disease causes visible symptoms (cases) and those with an undetected disease (asymptomatic and not tested group). This is the key figure, as it summarises how dangerous the virus is, and the number of deaths to be anticipated in the population if the epidemic runs freely.

My computation is based on public and official data from the European Centre for Disease Prevention and Control, the National Health Commission of the People’s Republic of China, the French Public Health Authority (Santé Publique France), the Italian Epidemiological Institute (Istituto Superiore di Sanità) and Eurostat.

The Infection Fatality Rate of Covid-19 is in the range of 1%

The first question to answer is: What is the Infection Fatality Rate of Covid-19?

One first clear observation is that the Crude Fatality Rates differ enormously from one country to the next (from 0.4% in Germany – 149 deaths for 31,554 confirmed cases as of 25 March 2020, source WHO Situation report – to 9.85% in Italy– 6,820 deaths for 69,176 cases, same source – a 1 to 24 ratio, between two countries of comparable development levels, specifically when considering the North of Italy where most cases happen), or even between the Chinese city of Wuhan (5.8%) and other locations (0.7%) – source Report of the WHO-China Joint Mission on Coronavirus Disease 2019.

This Crude Fatality Rate is the ratio of two figures: the number of deaths due to COVID-19 at a given date and the number of cases of infection at the same date. The number of deaths relies on hard evidence, and is well-documented, because the registration of the cause of death is mandatory in the European Union and in many other jurisdictions. It can thus be considered as reliable. The number of cases of infection can be very strongly under-estimated because of under-reporting of mild or asymptomatic cases, of the unavailability of tests, and of national testing policies. A recently-published review of national health policies in the European Union regarding the attribution of Covid-19 tests by the well-recognised Robert Schuman Foundation illustrates this heterogeneity in the detection of cases: in Austria or Germany, screening tests are performed on any person having symptoms or having been in contact with an infected person (which has good chances of detecting a large fraction of the infected people), whereas in Spain, Italy or France tests are reserved to people with severe symptoms (and thus miss the bulk of infected, but mildly affected, people). The reported number of infected people is thus very unreliable, way below reality. As a conclusion, the most reliable figures for fatality rates are the lower ones, because they compare the (reliable) number of deaths to a number of cases of infection that is the less under-estimated.

The main flaw of calculating the Crude Fatality Rate is that it compares the number of deaths of a given day with the number of infected people of that same day – which makes the unrealistic assumption that a person infected dies on the same day, whereas in general a few days elapse between the two. This is problematic when these numbers grow at the currently observed high daily rates of ca. 25% / day. This is why the recommended method is to compare he number of deaths of a day with the number of infection cases of a number of days before, corresponding to the delay between infection and death.

The delay between infection and death is the sum of: (1) the incubation time, between infection and first symptoms, currently estimated by the WHO at 5 days, and (2) the time between first symptoms and death (when it occurs), currently estimated at 9 days by the Italian Epidemiological Institute (Istituto Superiore di Sanità). The delay between infection and death can thus be estimated at 14 days in total.

I have performed this calculation on the data collected and updated daily by the European Centre for Disease Prevention and Control on the cases and deaths reported by each country, in the attached file. For China, I have collected the daily briefings provided by the National Health Commission of the People’s Republic of China for the province of Hubei, the first and hardest hit of all Chinese provinces. I then subtracted the figures for Hubei from the total figures for all of China to obtain figures for all provinces and territories except Hubei. These are territories where a very stringent, accurate and detailed tracking of all infected persons was performed, as described in the Report of the WHO-China Joint Mission on Coronavirus Disease 2019 (COVID-19).

I estimated the Infection Fatality Rate as the ratio between the total number of deaths recorded in a territory at date T to the total number of infected cases at date (T – 14 days), in order to compare the number of deaths to the population of infected people among which these deaths can have developed. The results are detailed in the spreadsheet file downloadable here and summarised in this table, in which I only placed the countries with a reliable policy for tracking infections.

Country of fraction of countryLine in tableComputed Infection Fatality Rate
Austria38015,0%
China except Hubei14630,9%
Germany256210,0%
South Korea58431,6%
Japan35458,0%

Based on the previous reasoning, the most reliable figures are those where the number of reported infections underestimates reality the least, i.e. the lowest figures: South Korea and China except Hubei. Considering the geopolitical tensions existing between China and South Korea, the hypothesis of these two governments cooperating to mislead the public is very unlikely. Based on this, the Infection Fatality Rate for the whole population is in the range of 1%, i.e. ca. 10 times more than that of the seasonal flu. This estimation is fully in line with the computations performed by Robert Verity and colleagues of the MRC Centre for Global Infectious Disease Analysis, Imperial College London and published on 30 March 2020 in this article of The Lancet, which is the world-wide reference journal for medicine, where an Infection Fatality Ratio of 0.66% is estimated (with lower and upper bounds of uncertainty 0.39% and 1.33% respectively), based on Chinese data (44,672 cases), on that of the cruise ship “Diamond Princess” quarantined off Japan and of people repatriated from Wuhan, China.

The Infection Fatality Rate varies immensely with age and chronic health condition

The Chinese CDC Infectious Disease Information System has been excellent at tracking all infection cases in the provinces other than Hubei, but has a major limitation in that it does not require data on the health condition of Covid-19 patients (what is known as “co-morbidity”), nor on the age of patients.

Reciprocally, the French public health system has been very poor at tracking the infections (notably by restricting the usage of tests to the people with severe symptoms only), but has followed the co-morbidity condition and the age of the patients deceased from Covid-19. In its weekly report of 09 April 2020, it provides the breakdown of the existence of co-morbidities and of the age of deceased persons in the 3,975 deaths where the information was available among the 10,328 registered deaths in the country between 01 March and 07 April 2020. The information on the age and the existence (and nature) of co-morbidity is available if the institution recording the death is equipped with the relevant software and equipment – which is a variable independent from either the age of patients or their health condition. This sample can thus reasonably be considered as representative of the overall population of people deceased in France from Covid-19 during the period considered.6

Among these 3,975 deceased persons, 97% were either above 65 years of age or had at least one chronic health condition (mainly a cardio-vascular disease, but also diabetes, chronic obstructive pulmonary disease, kidney condition, neurologic diseases, immunodeficiency). This means that the Infection Fatality Rate differs very strongly between people with no chronic health condition and those with at least one, and with age.

The Infection Fatality Rate for persons people aged above 75 years is between 3 and 8%, comparable to the natural death rate per year – but only 0.007% for those below 45 years and in good condition, 10 times below the natural death rate

Based on this data, and making the reasonable assumption that the infected people are a random representative sample of the whole French population, I have computed the Infection Fatality Rates of the sub-populations determined by their age group and co-morbidity condition.

A simple calculation, detailed in the box below, results in the Infection Fatality Rate of Covid-19 for a sub-population being equal to the Infection Fatality Rate for the whole population, multiplied by the fraction of all deceased people from that sub-population, divided by the fraction of the total population represented by that sub-population.

Eurostat provides the following tables:

The last table provides, for each chronic disease, the fraction of people in a given age group reporting suffering from it. It does not provide the fraction X of the population having at least one of the chronic conditions increasing the probability of dying from Covid-19 (Heart attack or chronic consequences of heart attack, Coronary heart disease or angina pectoris, High blood pressure, Kidney problems, Diabetes), considering (which is unfortunately often the case, specifically for diabetes and high blood pressure in the case of overweight and obese people, in a condition sometimes described as “metabolic syndrome”) that a given person may suffer from several such conditions simultaneously. The highest possible value for X is based on the assumption that people only have one chronic condition, so that the figures for all conditions add up. The lowest possible value is based on the assumption that all persons with at least one of these conditions have the chronic health condition with the largest prevalence, namely high blood pressure, so that the figures don’t add up and are equal to the largest among them. I have performed the calculations for both the maximum and the minimum possible values for X, knowing that the real value lies in between.

Box: computation of the Infection Fatality Rate of a sub-population Let: R be the Infection Fatality Rate for the total population D be the total number of deaths recorded at the date of observation I be the total number of people infected at the number of days before the observation sufficient for the Covid-19 to evolve from infection to death r be the Infection Fatality Rate for the sub-population being considered d be the number of deaths recorded at the date of observation belonging to the sub-population being considered x be the fraction of the total population belonging to the sub-population
We have the following equations: R = D / I, by definition of the Infection Fatality Rate R, which is the ratio of the total number of deaths by the total number of people infected r = d / (I.x), by definition of the Infection Fatality Rate r in the sub-population, which is the ratio of the number of deaths of that sub-population by the number of people infected belonging to that sub-population, with the reasonable assumption that this number of infected persons belonging to the sub-population equals I.x, i.e. that the infection touches all sub-populations considered evenly (“uniform attack rate”).
Based on these equations, a simple resolution leads to the rather intuitive result: r = R . (d/D) . (1/x) meaning that the Infection Fatality Rate for a sub-population is equal to the Infection Fatality Rate of the total population, multiplied by the ratio of deceased people belonging to that sub-population to the total number of deceased people, and divided by the fraction of the total population belonging to that sub-population.

Numerically, the computation performed in the spreadsheet file available here leads to the following results.


Computed Infection Fatality Rates for Covid-19
Age bandWithout co-morbidity (min)Without co-morbidity (MAX)With one comorbidity or more (min)With one comorbidity or more (MAX)Existing death rate France (2016)
0-14 years0,00%0,00%0,00%0,00%0,03 %
15-44 years0,0066%0,0069%0,206%0,373%0,07 %
45-64 years0,127%0,155%0,724%1,35%0,48 %
65-74 years0,75%1,36%1,59%3,00%1,60 %
75 years +2,82%6,87%4,06%8,20%7,63 %

Computations performed with a value for the Infection Fatality Rate of the whole population R = 1%

These values are again fully coherent with the results published by Robert Verity and colleagues (2020), in their table 1, where they compute the Infection Fatality Rate per age groups – but not per chronic health condition.

From this table, we can see that:

  • the Infection Fatality Rate of Covid-19 for the people studying or of working age (i.e. 64 years or younger) and in good health (having no chronic health condition) is 3 to 10 times inferior to the existing mortality rate of the same age groups. This implies that they can be infected by the virus at a risk level that is extremely low, and should be fully acceptable;
  • the Infection Fatality Rate of Covid-19 for retired people (i.e. 65 years or older) or having at least one chronic health condition is superior to the existing mortality rate of the same age groups, up to a factor of 5. This implies that, should this population be infected, a number of deaths due to Covid-19 comparable or greater than the usual number of deaths for these age groups during a whole year would happen, partly in addition to this normal number of deaths, and concentrated in the few months of the epidemic – clearly a situation to be avoided.

Considering the immense economic, social andhuman costs of a prolonged universal confinement, I support a fast exit strategy by gradual deconfinement, differentiated by age and health status

The current policy of universal confinement of the population aims at suppressing the propagation of the virus causing Covid-19, so that the virus dies out with most of the population left uninfected – and thus vulnerable to new infection cases coming from other regions of the world. As mentioned above, it leads to an succession of periods with and without confinement (or of relaxed confinement), with 2/3 of the time in strict confinement, until a vaccine is developed, manufactured and distributed – which is planned to last 12 to 18 months at best, and can be delayed for any unforeseeable reason (work on the AIDS vaccine has been ongoing for the last 35 years with no industrial-scale production result so far). The economic, and thus social and human costs (also in terms of deaths), and the resulting deterioration of our democracy, of such a “stop and go” confinement policy are immense.

It is thus urgent to define an exit strategy from this dreadful deadlock. For this, I support, based on the quantitative estimations made above, an exit strategy from the existing universal confinement by a gradual deconfinement, differentiated by age and health status, based on the extremely fortunate circumstance that the Infection Fatality Rates of Covid-19 are so massively different between sub-populations that are easy to identify ex ante and to verify.

In the “gradual deconfinement, differentiated by age and health status”:

  1. only the vulnerable population remains confined at home. The vulnerable population can be defined as the elderly above a threshold to be determined around 65 years of age, e.g. that of legal retirement, or the persons having at least one of the chronic health conditions increasing the fatality rate of Covid-19. Thereby, the number of vulnerable people being infected by Covid-19 – and thus also that of fatalities and of Intensive Care Units being used – is minimised. Since this vulnerable population is essentially composed of retirees, their absence from the productive system does not compromise its operation. This confinement lasts until a herd immunity” is reached by the less vulnerable population, i.e. when 60 to 70% of the total population has been infected and is subsequently immunised;
  2. the rest of the population (young people – children, adolescents and adults up to the age threshold defined above, e.g. those of working age – and in good health) is made free to work, learn and play normally, and to be infected with Covid-19 at an extremely low risk (3 to 10 times lower than natural mortality, which is itself very low, of these age groups), in a graduated manner, starting immediately with the healthy population aged 0-44 years, and then gradually extending this measure to age 64 years, for example by 5-year increments every month, at an appropriate rate to maintain an acceptable flow of new serious cases to be treated by hospital emergency departments.

This exit strategy of gradual deconfinement, differentiated by age and health status, which I support thus:

  • can start being implemented immediately because it is based on information that already exists and can be easily monitored, namely age and chronic disease status ;
  • adds an excess mortality that remains low (for France, about 1,000 people between 0 and 44 years old in good health, then about 18,000 people between 45 and 64 years old in good health, compared to the 80,000 of these age groups dying per year, and the 560,000 annual deaths, all causes and ages combined), only once;
  • avoids the saturation of the hospital emergency departments;
  • restarts the productive system quickly and avoids considerable economic, social and therefore human damage: the duration of strict and universal confinement is limited to 1 month, the one that has just elapsed, with a fairly rapid capacity to reconstitute a productive system in apnoea at this stage, whereas the alternatives foresee periods of at best 12 to 18 months of economic shutdown, a period during which no player is able to survive on its reserves ;
  • constitutes herd immunity and therefore avoids the repetition of periods of strict confinement until a vaccine availability that to date remains hypothetical and envisaged at the earliest after 12 to 18 months;
  • protects the vulnerable groups in the population efficiently;
  • may be felt as discriminatory against some categories of the population.

The exit strategy by gradual deconfinement, differentiated by age and health status, is superior to any of the alternatives currently envisaged

The strategies currently foreseen for the exit from universal confinement, in addition to that of “gradual deconfinement, differentiated by age and health status” that I support, are the following:

  • an universal testing of the whole population, whereby only the non-infected and those having been infected and thus being immunised are released from confinement, followed by a permanent tracking of this population to trace back from any newly infected person to all its contacts during the incubation period, so as to re-test and quarantine those infected;
  • universal deconfinement by gradually relaxing the constraints of social distancing (gradual re-opening of shops, re-authorisation of gatherings, etc.)
  • a regionally-based universal de-confinement of the regions where the number of cases and fatalities has started decreasing.

All three strategies have very significant drawbacks:

  • the universal testing supposes that the whole population be tested simultaneously, within the same hour or less, with immediate result of the test and immediate enforcement of the consequences (confinement or release) of its outcome. If any of these conditions is not met, then there is no means to prevent a person having been tested at date T from being infected subsequently by a person planned to be tested at T + several days. None of these conditions are met: (1) the number of available tests is far below that of the whole population: even front-runner Germany only produces only 160,000 tests per week, meaning that it would still require 500 weeks (more than 9 years!) to test its whole population of ca. 80 million; (2) test results are at best available after 2.5 hours (same source) and (3) the enforcement would require a disproportionate police force (which itself would need to be subject to the same testing and face its own internal discipline problems);
  • if the universal testing were to be performed gradually, as per the availability of tests (and not on one single day), and even under the highly unlikely hypothesis that the tested population would be able to remain strictly separate from the untested one, this gradual testing would lead to massive political and social conflicts around the order of people being tested. If being tested is the key to start one’s work or economic activity again, with prospects of having to wait months (or even years) before being tested if unlucky, then this order of testing creates enormous social and economic inequalities – and conflicts – in itself;
  • the universal and permanent tracking of the whole population for the sake of disease control is a massive breach of basic civil liberties and human rights, which is problematic in itself and may also lead to political unrest or civil disobedience or both;
  • the relaxation of the constraints of social distancing makes the mistake of considering the slowing down of the spread of the epidemic as a given, and forgets the very unstable character, with a very strong threshold effect, of the exponential function: if the rate of reproduction of infections is strictly less than 1 (exponential with a negative coefficient), their number rapidly decreases, if it is strictly higher (exponential with a positive coefficient), it explodes. It is almost impossible to stabilize at a value strictly equal to 1. The relaxation of the constraints can therefore only be very temporary, with a resumption of strict confinement as soon as the inevitable spread of the epidemic begins again;
  • the fact of breaking up the de-confinement per region supposes that regions can remain air-tightly separated – whereas the existing movement of people for work or leisure takes no consideration of administrative boundaries. It also does not prevent the resurgence of infection in the “released” regions, and hence only makes the confinement – de-confinement cycle more complex – but in no way more effective;
  • in these three strategies, no care is taken of the specific vulnerability of the elderly and of those with chronic health conditions (a condition that they often are barely responsible of).

I would summarise the comparison between exit strategies from universal confinement in the following table.

Exit strategyAdvantagesDrawbacks
gradual deconfinement, differentiated by age and health statusImmediate start
Limited economic, social and human damage
No saturation of emergency units in hospitals
Protection of the vulnerable population
Build-up of herd immunity, with only one confinement period Differentiation along clear and visible criteria
Potential feeling of discrimination by the vulnerable, confined population
Additional fatalities among the young and healthy, 3 to 10 times below the natural mortality rate, happening once only
Universal testing + trackingExact medical knowledge of the infection situation of each person
No saturation of emergency units in hospitals
Only possible when tests are available for the whole population Massive economic, social and human damage
Based on unrealistic assumptions regarding the availability of tests and the enforceability of decisions No build-up of herd immunity: repeated confinement periods until vaccine
Additional fatalities among the whole population at each epidemic wave, with high mortality rates in the vulnerable population
No protection of the vulnerable population
Massive breach of human rights
Relaxing of constraintsEasy and fast implementation Temporary re-start of economic activityFast succession of periods of relaxing and of tightening of constraints
Massive economic, social and human damage
Probable saturation of hospital emergency services at each new surge of the epidemic
No build-up of herd immunity: repeated confinement periods until vaccine
Additional fatalities among the whole population at each epidemic wave, with high mortality rates in the vulnerable population
No protection of the vulnerable population
Regionally-based de-confinementAdaptation to the local situation of the disease diffusionOnly possible when the number of cases has significantly decreased Massive economic, social and human damage
No build-up of herd immunity: repeated confinement periods until vaccine
Additional fatalities among the whole population at each epidemic wave, with high mortality rates in the vulnerable population
No protection of the vulnerable population
Based on unrealistic assumptions regarding movement of persons across administrative boundaries Increased complexity of the management of confinement

I conclude from this table that the “gradual deconfinement, differentiated by age and health status” exit strategy is superior to any of the other strategies currently envisaged to exit universal confinement.

Conclusion

I strongly encourage governments, in the European Union and beyond, to consider exiting the current universal confinement via this strategy of “gradual deconfinement, differentiated by age and health status”.

I also wish that governments will display the same capacity to act with speed, boldness, determination and sense of priorities between economic interests and survival of our human societies, when taking measures on climate and biodiversity for the sake of the younger and future generations, as what they have recently done on Covid-19 to save the single generation of those currently at the end of their lives.

Author: Sergio Arbarviro

My competences are originally those of an engineer – but I have been making incursions, for quite some time now, into several other fields, such as economics, politics, psychology, social sciences and history. I am the initator of the CosmoPolitical Cooperative, a cooperative for social, economic and political transformation, supporting the transition to a just, sustainable and happy society.