THE FIRST THIRTY DAYS1COMPARATIVE LESSONS FROM THE COVID PANDEMIC
Paul-André Rosental
CHSP-Sciences Po (Paris)rosental@sciencespo.fr
14 July 2020

To be available on the website of the
Joint Centre for History and Economics, Harvard-Cambridge
https://www.histecon.magd.cam.ac.uk/seminar_hec.htm

This paper aims to compare the effectiveness of national responses to the covid-19 epidemic in 24
countries, mostly in Western Europe, but also covering North America and Central Europe; Russia,
Turkey, and South Africa; and the Middle East and Asia. The question is whether we can say
anything about the effectiveness of responses to the pandemic, including:1) “reactive” measures immediately taken by public authorities, and the population’s
behavior in response to them;2) “proactive” measures, consisting of regular health spending and the state of healthinfrastructures.
To this end, the study focuses on available mortality data. First, it recalculates national mortality
rates by controlling for national demographic parameters that might prevent any direct comparison
between them. Second, it compares these corrected and now comparable mortality rates with somemajor public health parameters. The goal is to observe the extent to which the combination of
structural (proactive) health efforts and immediate (reactive) measures tempered the severity of thescourge.

1 This paper is based on a report published in French in May 2020, and available at http://tnova.fr/notes/un-balcon-

en-foret-2020-essai-comparatif-sur-l-epidemie-de-covid.

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I.

Controlling mortality rates for structural demographic parameters

The comparisons currently found in the media and scholarly debate on the epidemic are at best
limited to reporting the number of recorded deaths in relation to the total population of eachcountry. This overlooks the fact that a number of structural parameters prevent an immediate
comparison between countries.
Americans would not expect epidemic hazards to equally strike New Jersey (almost 400 inhabitants
per km²) and Wyoming (2.22)… By comparing the US to Belgium, President Trump forgot thatthe same holds true at the international level. Europeans have not always hit the mark either.
Sweden has been widely envied for combining low mortality and very light collective restrictions,whereas Italy and Spain were blamed for their high mortality and severe lockdowns. But given its
low density (15 times lower than Belgium), which “naturally” distances residents, Sweden’s ability
to contain mortality should be placed in perspective.
Other parameters stand in the way of straightforward international comparisons. The pandemic isless likely to affect a dense population evenly distributed across a national territory than less densecountries where the population is concentrated in one region. Intense human mobility (be itinternal, or to and from other countries) is also conducive to the dissemination of the virus. Age
structure penalizes countries that have the highest shares of senior citizens. We now know, throughthe largest epidemiological survey available to date, that this is by far the greatest risk factor, much
more so than known comorbidities or socio-environmental variables2.
In this paper (see Table 1, Appendix 1) I control for all these variables in order to harmonize
comparisons between “corrected” mortality rates.
Another preliminary condition for any comparison is the chronology of a disease that tends toinitially emerge as an avalanche. Since each country has its own timeline, international comparison
requires consideration of mortality data covering comparable phases of the epidemic. To this end,
I captured the 24 countries in my sample at a comparable point in time in the epidemic, startingwith the day when 50 cases of covid-19 were recorded – bearing in mind that this also happens tocorrespond to when the first deaths were recorded3. I then followed the development of theepidemic for 30 days.
This was the maximum timeframe available when I began the study and accounts for why certain
geographical areas (South America and Central Africa) are excluded. This period is long enough toobserve what I call "the first cycle of epidemic maturity". It is also highly relevant for my purposes.
Given that mortality results from an infection that may have occurred a few weeks earlier, it is a"strategic" period that captures public authorities’ attitude towards an unexpected shock as it hit either
the national territory for "pioneer" countries such as South Korea, Japan, and Italy, neighboring
countries, or the rest of the world.

2 Elizabeth Williamson et al., OpenSAFELY: factors associated with COVID-19-related hospital death in the linked electronic

health records of 17 million adult NHS patients, preprint doi: https://doi.org/10.1101/2020.05.06.20092999, 7 May 2020.
3 I increased this observation threshold for the most populous countries in the sample, namely Russia, Japan and theUnited States, which in their cases shifts the starting point of the analysis by a few days.

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Over this one-month period, starting between February 19 (South Korea) and March 17 (Hungary),
I determined the observed mortality rate for each of the countries in the sample by relating thenumber of deaths to the total population. I then calculated a "corrected" mortality rate bycontrolling for the raw data on the demographic variables previously mentioned: population
density, geographical concentration, percentage of elderly people, and internal and external
mobility.
The results are provided in Table 1 (Appendix). It significantly changes the ranking of countries.
However, with the exception of Iran, which is discussed below, the order of magnitude of thedifferences between the countries least affected and most affected by mortality remains the sameas it was at the outset, i.e. very high. Gross mortality varies from 0.00286% (Japan) to 1.65225%(Spain), and corrected mortality, from 0.00483% (Japan) to 3,69662% (Turkey).
Table 1, and the resulting graph 14, show three jumps in the order of magnitude: first between
Sweden and Portugal, then between the United Kingdom and South Africa, and finally between
Spain and Belgium. By aggregating the nations most severely affected by the pandemic (i.e.
starting with South Africa), three comparably sized groups of countries become apparent (9, 6,
and 9 respectively).
Group 1 with “low mortality”: Japan, South Korea, Israel, Norway, Greece, Austria, Hungary,
Germany, Sweden;Group 2 with “average mortality”: Portugal, France, Netherlands, Canada, Poland, United
Kingdom;Group 3 with “high mortality”: South Africa, United States, Russia, Switzerland, Spain, Belgium,
Italy, Turkey, Iran.
Graph 1
Corrected mortality
4,00%
3,50%
3,00%
2,50%
2,00%
1,50%
1,00%
0,50%

Japan
South Korea
Israel
NorwayGreeceAustria
Hungary
Germany
SwedenPortugal
FranceNetherlands
CanadaPolandUnited Kingdom
South Africa
USA
RussiaSwitzerland
Spain
Belgium
Italy
Turkey0,00%

4 For graphic reasons this leaves out Iran, which has an overly large mortality gap.

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Having established these groupings, the idea is to relate the corrected mortality data that can now
be compared, "all demographic structures being equal", with the public health variables objectifying
the responses to the epidemic.

II.

Public health indicators

II.1 Indicator selection
Let us now turn to the public health indicators, both proactive (national public health policy prior
to the epidemic) and reactive (measures to control the epidemic).
With regard to the first group of factors, the first two variables cover national public and private
funding for health – an essential distinction to test since it corresponds to different structures of"medical goods and care"5.
The third variable, from the same source, is the number of hospital beds per 1,000 inhabitants.
This indicator has the disadvantage of aggregating very heterogeneous types of care. I supplement
it with two quality indicators for intensive care units (ICUs). The number of ICU beds would not
be a very good parameter because it aggregates highly specialized and heterogeneous medical
services6. Moreover, some countries have adapted their hospital structures in response to theepidemic. I therefore chose a measure of the quality of intensive care, which is decisive given theseriousness of coronavirus complications: the case fatality rate in the 30 days following serious
interventions – "a rate that reflects care procedures (e.g. timely transport of patients) and effective
medical interventions"7.
This measure is reliable and comparatively available for all OECD member countries, albeit
unfortunately for these countries alone. Its other limitation is its specificity: each type of medical
incident has its own measure that cannot be combined into a general indicator. Two different rates
best suited my purposes: the case fatality rate within 30 days of hospital admission for ischemic
stroke and for acute myocardial infarction (AMI). To ensure sufficient comparative data, I used themortality measure for patients who remained in a single hospital8.
These two indicators also have the advantage of implicitly incorporating information on the healthstatus of populations with respect to the coronavirus. Both strokes and AMI depend on people’s
overall vascular condition, and their effects are aggravated in diabetic and obese patients – twocovid-19 risk factors.
Let's now turn to "reactive" data. The first variable concerns the stringency of responses to theepidemic: the severity of containment measures, understood in the broadest sense (closings ofschools, workplaces, and borders; cancellation of public events; and restrictions on public
transportation), as well as contact tracing, testing, and the magnitude of awareness campaigns. The
Coronavirus Government Response Tracker (CGRT) of the Blavatnik School of Government at
5 The data is for the year 2017, and provided in 2017 $ per inhabitant. Source: WHO, Global Health Expenditure Database,https://apps.who.int/nha/database/Select/Indicators/en.
6 Meghan Prin and Hannah Wunsch, “International comparisons of intensive care: informing outcomes and improving
standards”, Current Opinion in Critical Care, 18, 6, 2012, p. 700-706, doi: 10.1097/MCC.0b013e32835914d5
7 Health at a Glance 2019, OECD, p. 134.
8 The coupled rate, which also includes patients who changed institutions during their care, is more accurate but
unfortunately it is not available for all OECD countries.

4Oxford University has reported all this data daily and globally9. By recording government
provisions on a daily basis and weighting them in terms of strictness, the CGRT has produced an"Oxford Stringency Index" (OSI).
Although it has the weaknesses of any indicator that combines heterogeneous dimensions, thisparameter is of major interest to me. Its daily cadence completely aligns with my objective ofmonitoring the reactions of States in a comparable 30-day epidemic timeframe. I incorporated the"Stringency Index" on three different dates for each country: on the first day of the 50 declaredcases (D1), ten days later (D10), and on the 30th and last day (D30).
The second "reactive" data relates to disease testing. This variable is not continuously available forall the countries, but can be approximated, more or less precisely depending on the case, for the
30-day observation period. It is tenuous data. Performed testing is uneven. In addition, somecountries count the number of people tested, while others count the number of tests. The US datain particular is questionable10. I add this parameter to the OSI, of which it is but one of thecomponents, in order to approximate its specific effect.

II.2 Public health and anti-epidemic measures
II.2.1 Proactive measures
When corrected mortality is related to public health data, the first observation is the heterogeneityof country profiles and the apparent inconsistency of the results. Switzerland and the United States
respectively rank 22nd and 23rd out of 24 for mortality, while both countries have by far the highest
health spending in the sample, and high-quality ICUs. Hungary, Greece, and Israel, ranked between
15th and 20th in health spending, are among the six countries with the lowest corrected mortality,
alongside affluent Norway.
Aggregating the countries into three blocks according to their corrected mortality (above) allows
for an initial organization of the data, without assuming a priori that each of the three blocks ishomogeneous.
To highlight and facilitate discussion of apparent consistencies, I have each time indicated the country’s
rank for the relevant variable rather than the absolute data itself (Tables 2 to 4). This shift from thecardinal to the ordinal is also better suited to the often fragile nature of the data: it is better in thisheuristic approach to elevate the data’s main strength, which is its comparativeness, than to exaggerate
the legitimacy of the basic data by objectivizing them with sophisticated statistical measurements.

9 https://www.bsg.ox.ac.uk/research/research-projects/coronavirus-government-response-tracker
10 “States currently report testing figures in a range of different ways: some report the number of tests performed,

others the number of people tested; some include private labs, others not; some report negative test results, others
only positive test results; some include pending tests, others do not (below we show figures that exclude explicitly
pending results). Moreover, many states do not explicitly provide details about these important factors needed tointerpret the data they provide. There are issues in comparing the figures over time. The totals given for early on in
the outbreak do not include all states. One significant uncertainty is the extent to which the rapid rise in tests seenfrom the mid-March in part reflects states beginning to report private lab tests” (https://ourworldindata.org/covidtesting).

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On that basis, it appears that the higher the national investment in public health infrastructure, thelower the mortality (table 2, Appendix). This effect is both linear and very strong. Between the first
and the third group in terms of mortality, the ratio, in terms of rank, of total health spending per
capita is 1.38. It reaches 1.63 for public health spending, and even 1.70 for the number of beds.
As with any retrospective evidence, it is tempting to take this result for granted in the case of an
epidemic: having a reserve of beds enables treatment of a greater number of seriously ill patients,
and probably adjustments to the supply of care by devoting some – or all, in the case of some
Italian regions – of the hospitals to covid-19 care, provided they have the necessary equipment and,above all, specialized staff. But this retrospective evidence overlooks the fact that the average
number of beds is "in normal times" considered to be a problematic variable in health economics:
high numbers are seen as a sign of suboptimal management, as international organizations such as
the OECD impressed upon its members. Countries that bucked the advice had greater strategic
leeway to fight the disease.
Covid-19 pandemic thereby raises a fundamental question that will remain well beyond the current
crisis. Does the pandemic call into question "regular" health policies? Or is it just an
exceptional case arising from the combination of two aspects of covid-19:
1) The length of intensive care needed by the most affected patients – often
three weeks or more;
2) The influx of sick people in a very short period of time, linked to thecontagiousness of the virus (and the unpreparedness of most states).
It is this double bind – unheard of for decades in most of the countries considered here –of suddenly having to treat a mass of patients for a long period of intensive care – thatmakes this disease unique from a public health perspective.
The final set of "proactive" variables relates to the quality of critical care. The results differ
depending on whether the care follows a heart attack or ischemic stroke: no significant effect wasobserved for the former – in fact, it was a slightly negative effect (0.92) – but a ratio of 1.6 wasobserved for stroke between the ranks of extreme groups of countries in terms of correctedmortality. These two gaps are probably actually higher, since the data is only available for OECD
countries and is incomplete for the states in the high mortality group, 4 out of 9 of which are notmembers.
Why is the ability to fight ischemic stroke more discriminating than that for AMI? First, with acomparable level of information in the population through prevention campaigns, it is easier to
identify the chest pain associated with AMI than signs of stroke. The difference between the two
indicators is thus an indirect marker of the health system's efforts to raise public awareness, or of
the public's greater openness to it – an advantage that may also be relevant to covid-19. Second,
stroke management requires a highly specialized staff. It is an indicator of a country's ability toallocate teams of “hyper specialists”, reflecting a particularly high level of investment in thehealthcare system.

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II.2.2 Reactive measures
Let us now turn to reactive measures (Table 3, Appendix). That the number of tests per 1 M.
inhabitants is positively correlated with the difference in corrected mortality between the first groupand the next two – a difference of around 15% - is quite remarkable considering the fragility of thevariable. Even if its measurement is too imperfect to serve as absolute proof, the results for thisvariable confirm the generally shared assumption about the protective role of tests.
By contrast, the three sets of data on lockdown severity produce what appears to be acounterintuitive result. J30 shows an inverse relationship between the severity of measures taken
against the epidemic and the effectiveness of the fight against mortality. Countries with low
corrected mortality adopted less stringent provisions than moderately affected countries,
which in turn adopted less severe measures than the most affected countries.
Of course, this does not mean that lockdowns failed to contain the epidemic, or that they helped
it. It has been much noted that lockdowns were often palliative, serving as a catch-up policy
for countries where a weak health infrastructure and/or lack of preparedness forced adefault response that was costly in human, social and economic terms. Thus underresourced South Africa falls within the group of countries with high corrected mortality, but is inan honorable position that places it ahead of the United States. Hungary, which ranks 19 th out of
24 on health spending but 1st at D1 for stringency measures, ranks among the group of countries
least affected by covid-19 mortality.
What the results for stringency actually reveal is that, unlike the previous parameters, it is notstrictly speaking a variable. Rather, it is a kind of residual reflection of all the parameters– a crude indicator of the authorities' response to the pandemic based on initially available
resources.
Even if one focuses on the health dimension, ignoring the liberticidal uses of epidemic control
measures11 by authoritarian governments, their intensity and severity, which rapidly changed overthe 30-day observation period, are primarily indicative of contextual public policy decisions. As ahistorian, I would need specific sources to understand the rationale for these measures from theperspective of governments. However, it is possible to identify general patterns that are valid forseveral countries. They guide the following conclusions and hypotheses.
III.

CONFRONTING THE VIRUS: CONCLUSIONS AND HYPOTHÈSES

1. The general scale and quality of public health investment and infrastructure were amajor factor in the effectiveness of the fight against mortality
For countries leading the way in the fight against mortality, regular health efforts and/or the ability
to test during the epidemic have proven valuable in limiting the loss of human life among their
populations, and by the same token the strictness of anti-epidemic measures.
Let’s remove information on the severity of lockdowns, and simplify the data in tables 2 and 3 byretaining only the cases where a given country is in the top 5 of the sample for a given criterion, or isranked between 6th and 10th (Table 4, Appendix). For the remaining six criteria (proactive measures
11 For an analysis of Hungary's instrumental use of the health situation, compared to other countries in the Visegrad

group, see Jacques Rupnik, « Orbán and rhe European Right », Esprit, 4, 2020, p. 33-37, https://www.cairnint.info/abstract-E_ESPRI_2004_0033--orban-and-the-european-right.htm#

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+ tests), the nine countries with the lowest corrected mortality (37.5% of the total) alone account foralmost two thirds (19 out of 30) of the possible spots in the top five. This compares with only 13% for
the countries in the middle group, which is admittedly smaller (25%), and 23% for the high-mortality
countries.
Countries with intermediate mortality – including Canada, France and the United Kingdom – arealso around the average for the selected indicators. They dominate in the ranks between 5th and 10thplace, accounting for 40% of the items in each of these ranks, compared with 30% for each of the othertwo groups, even though this middle group is smaller.

2. However, if one focuses on the single criterion of mortality control, there is no one
path to effective mortality control. A comparison of countries with low epidemic
mortality suggests three profiles and three strategies.
Within the group of low-mortality countries, the first subgroup includes those that focused on
hospitals prior to the current crisis, with a large number of beds and high-quality intensive care.
Japan and South Korea are the leading countries in this regard, while their performance is modest
on the other criteria. This selectivity confirms the extent to which the first variable in addressing
the epidemic is the number of available hospital beds. It could only be strengthened by variables
that are unobservable here, such as hygiene in private and public spaces, especially public
transportation, and the habit of wearing masks as well as following government instructions oreven strict social control12. It is difficult to mention these variables here without being able toobjectify them, and thus risk falling into the trap of culturalism. But it is equally difficult to ignore
the role of the populations themselves in the dynamics of the epidemic.
A second type of low-mortality country includes Germany and Austria, which are akin to
excellent decathletes, ranking highly across virtually the whole range of indicators: level ofhealth spending, number of beds, quality of intensive care, and number of tests. It also includes
the Scandinavian countries Norway and Sweden, which were able to make up for their low numberof beds with the scale of their overall health investments, the quality of their intensive care, and for
Norway, the number of performed tests.
Because they proved to be both lavish in their public health investments and far-sighted in termsof hospital capacity, all these states with low corrected mortality rates were able to spare their
populations from overly drastic measures. The only exception, albeit a moderate one, is South
Korea. Undoubtedly bearing in mind the SARS precedent, it adopted stricter measures than averagein the first days of the epidemic, unlike the first European countries affected.
Finally, among the countries with the highest corrected mortality, a third sub-group
includes countries – Hungary, Israel, and Greece – that compensated for a more limited initiallevel of health resources with strict and immediate measures.
These States made up for their initial disadvantage through comparable means deployed to various
extents. Hungary and Israel, and to a lesser extent Greece, adopted drastic measures (close to maximal
OSI). Greece sought to compensate for its relatively weak health infrastructure in the aftermath of the2015 crisis by speeding measures to limit the epidemic to reflect lessons learned from the Italian overflow:
it imposed early restrictions on mobility from and to foreign countries, facilitated by its insular position
12 For a statistical simulation of the braking effect on the current epidemic that the availability of masks would have

had in France, see Hugues Lagrange Masques et bergamasques… Contradictions des démocraties, 30 March 2020
https://www.sciencespo.fr/osc/sites/sciencespo.fr.osc/files/masques_et_bergamasques_V6.pdf

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in the Schengen area and therefore its greater border control; closed schools and universities; prohibitedlarge gatherings; and also attempted to double its intensive care unit capacity. Israel, which shared therecord with South Africa in our sample for strictness, limited its citizens' authorized mobility area to
100 meters. It also partly entrusted the army with ensuring that rules were followed – in order toaddress the real internal threat of some "ultra-Orthodox" communities that placed religious rules forcollective worship above public health rules.

These strategies were all the more effective that they could draw on public health assets(quality of intensive care for Israel, and number of beds for Hungary) and, where applicable, on
the high adaptability of the health care system.
Moreover, Israel is a special case with respect to the range of means it deployed – a wider range thanthat of Austria, with which it shares a large number of features. In addition to the policy ofsystematically testing people likely to be contaminated, either because they were showing symptoms or
because they came from abroad (as in the case of Greece, it had the advantage of insularity), Israel
deployed intrusive individual tracing techniques, the non-parliamentary adoption of which has given rise
to much debate. Israel was also one of the first countries to (as early as February) adopt a policy of"dedicated quarantines"13, using different tools to follow the same strategy as Japan. While the latter
used its reserve of beds to confine covid-19 patients within hospitals, thus limiting contamination of
their social circles, Israel did the same by using the hotels deserted by tourists.
Another strategy was to call for hospital volunteers to relieve healthcare workers – a variable that would
be interesting to quantify for all countries, since it is indicative of the direct mobilization of populations.
It was central in Italy, where the Civil Protection played a key role, to which I will return below.

The Hebrew state’s responsiveness, which reflects the political and institutional organization of acountry at war, was one of the indirectly measurable but essential variables in limiting theepidemic, as was "preparedness" for East Asian countries, which unlike Western states hadlearned the lessons from previous epidemics over the past 20 years. Despite its initially limited
resources, Israel is ultimately the only OECD nation to have come close to containing mortality to
an extent that only the latter have achieved, but at an incomparable social and economic cost.
3. While each country's situation is unique, an examination of the patterns that are
effective in limiting mortality enables, via comparison, a better understanding of
the heterogeneity of countries with the highest mortality. The combination of
preparedness/responsiveness/stringency of measures is also central here.
The presence in this group of countries with a relatively weak healthcare infrastructure,such as Russia, and especially South Africa, Turkey, and Iran, confirms the crucial nature of thisparameter. To compensate for limited public health capabilities, the most immediate
remedy is to adopt drastic lockdown measures. South Africa most stringently did this,deploying the military to enforce them. The particular plight of Iran, which has a significantly higher
corrected mortality rate than any other country, is an experimental confirmation of sorts, bycontrast, that for poorly equipped countries the lack of a response, or a late response, has disastrous
consequences in the first phase of the epidemic’s maturity.

“Israel said planning for coronavirus with isolation units”, Times of Israel, 20 February 2020,
https://www.timesofisrael.com/israel-said-planning-for-coronavirus-with-isolation-units-tourist-site-closures/. On
the notion of “dedicated quarantine”, see James Wael and V. Elrayes Lawler, “Quarantine Unit Operations”, in
Theodore J. Cieslak et al., Nebraska Isolation and Quarantine Manual, University of Nebraska Press, 2020, p. 33-38.
13

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The second confirmed criterion is the responsiveness and adaptability of healthcare
systems. Their inadequacy translated into a very high corrected mortality in Spain and Italy. The
latter was heavily and enduringly penalized by epidemic progression among the major European
countries (D1 to 22 February).
Spain (D1 to 29 February) was affected at the same time as France and Germany (28 February),
but had a weaker healthcare system (the rank for cumulative indicators of "proactive" measures is
38 for Germany and 48 for France, compared to 60 for Italy and 75 for Spain). It is not Spain's
early timeline that explains its high mortality per se, but rather the fact that it lacked adequate
healthcare infrastructure, starting with the number of beds and the quality of intensive care services,to allow for any fumbling. As the gap with its Portuguese neighbor suggests, Spain lagged incompensating for its modest health rank with sufficiently rapid reactive measures.
The notion of "preparedness", which is central to public health14, is not universally applicable.
Poorly ranked Switzerland was one of the first countries to follow the WHO's recommendation,at the end of the 20th century, to develop a pandemic plan – one that it revised in 201815. Although
it prefaced its plan with Benjamin Franklin's motto, "If you fail to plan, you are planning to fail",
Switzerland’s update was based on an influenza control model that fell short of addressing thespecificities of the coronavirus. The plan had maintained a post-Cold War legacy policy of sourcing
medical goods from abroad; emphasized vaccination; and limited containment measures to public
spaces. These elements combined with the practical difficulty of responsibility sharing between the
Confederation and the cantons, particularly with regard to statistical information. As a result, thecountry was not able to capitalize on its "anticipation". It is therefore a combination of
preparation and responsiveness that is decisive, and all the more so when the healthcare
infrastructure is inadequate. The Swiss case also illustrates the possible discrepancy between
private and public health spending, and the importance of the latter in combating a collective healthscourge.
4. The cohesiveness of the group of countries with intermediate mortality
demonstrates the importance of political variables in fighting the epidemic. The
group includes wealthy countries with a strong democratic culture16 but a healthinfrastructure that, high quality aside, did not have a sufficient reserve of beds toaddress an epidemic overflow, thus tightly constraining authorities from the outset.
Unlike the other two groups, the trajectories of these countries converged. During
the observation period, authorities constantly juggled conflicting demands from
populations for freedom of movement and activity on the one hand, and forprotection against the virus on the other.
The procrastination of the countries in the intermediate group is reflected in the rapidly growing
stringency of their anti-epidemic measures. During the 30-day observation period, the OSI of
countries in this group increased 3.7 times, compared with 2.6 times for low-mortality countries.
Unlike comparable Human Development Index countries, their healthcare structures exposed
them to risk in the event of an epidemic outbreak linked to insufficient compliance withprecautionary measures, and of a sudden influx of seriously ill people in hospitals (the cumulative
14 Andrew Lakoff, Unprepared: Global Health in a Time of Emergency, Berkeley, University of California Press, 2017.

15 Federal Office of Public Health, Swiss Pandemic Plan Influenza 2018. See also Marc Guillaume, “Sur le papier, la Suisseétait prête” [On paper, Switzerland was ready], Le Temps, 13 April 2020.
16 In the sense that their governments are subject to continuous evaluation by citizens who are free to be represented
and to organize themselves as they wish, and who receive information from a media whose journalists can exercise
their profession without risking their freedom, let alone their lives.

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rank of this group on health policy variables was 61, compared to 38 for low mortality countries).
The fact that the Netherlands, although highly ranked in this area (34), was slow to impose
lockdown measures in the name of a herd immunity strategy, probably cost it a higher mortality
level than that of countries in the first group.
The comparison between Portugal and the United Kingdom confirms the need for lockdowns incountries with modest healthcare systems in relation to their wealth (the cumulative rank on"proactive" variables is 82 for Portugal and 73 for the United Kingdom17). While Portugal
compensated for this initial handicap with a strict lockdown on D1 and D10, and with abundanttesting (ranked 3rd in the whole sample), the United Kingdom pursued a moderate lockdown, andmediocre testing (ranked 16th). This passivity translated into a much higher corrected mortality rate
than Portugal (over 60%) and France (over 50%) – a rate that I expect to see reassessed as moreaccurate death figures are published.

5. The relatively homogenous group of countries with intermediate mortality
illustrates the centrality, to understanding anti-epidemic measures, of authorities'
anticipation of the population’s attitudes towards measures restricting theirfreedom of movement and activity.
This real or assumed attitude is far from being universal and reflects each country’s
different way of dividing political responsibility for managing the epidemic acrossnational and local governments, individuals, and civil society.
Every day since the beginning of the epidemic, a Ministry of Health official has announced thedeath statistics in France, whereas in Italy this has been the purview of the head of Civil Protection,
an association that centralizes data from hospitals. This contrast illustrates national variations in
the way responsibility for fighting the epidemic is shared between authorities and citizens.
France exemplifies countries where the authorities rightly or wrongly believed that they could notcount on the population to adhere to "qualitative" containment measures that would have been
limited to "social distancing" in public spaces, as in Germany. The official form that citizens wererequired to fulfill for each daily one-hour outing within a one-kilometer radius officially placed
epidemic responsibility on the shoulders of political and administrative authorities.
Herein lies the key to the French paradox: the population is all the more critical of the state, because
it expects the state to take charge of all aspects of epidemic management, including the provisionof masks – unlike Germany, which stands in sharp contrast on this point. At the same time, France
idealized the Swedish example of simply appealing to civic values, even though Sweden’s so-called"light" strategy is based on both moral and legal accountability. Under a "law on communicablediseases", Swedish citizens are co-responsible for not spreading the epidemic: failure to heed this
responsibility can lead to prison sentences18 - a historical legacy of the powerful hold of "reformeugenics" in mid-20th century Sweden19.
17 In concrete terms, for example, the United Kingdom has poor public health statistics, ranking 12 th out of 24 inoverall public health spending, 21st on the number of beds, around 16th on the quality of intensive care, and 17th on
the number of performed tests.
18 Cf. Marta Paterlini, “Interview with Anders Tegnell”, Nature, 580, 574, 21 April 2020, doi: 10.1038/d41586-02001098-x and, for the legal content, Legal Responses to Health Emergencies, https://www.loc.gov/law/help/healthemergencies/sweden.php
19 May I refer you to Paul-André Rosental, A Human Garden: French Policy and the Transatlantic Legacies of Eugenic
Experimentation, New York, Berghahn Books (2020).

11

Besides the state and private individuals, another type of actor has played a key role in somecountries, complementing and sometimes virtually replacing state action. All kinds of NGO andvolunteer activities – such as the aforementioned Italian civil protection system – were mobilized,
be it to replace hospital staff, bolster prevention policies, address impoverishment and even foodshortages for people deprived of income, and even take over a large part of the actual medical
control of the epidemic, particularly in sub-Saharan Africa, by drawing on precedents20. The Iraniancase of "managing disorder rather than disposing order" is a good example of this use of
subsidiarity, which has since appeared mutatis mutandis in countries that were affected by the
pandemic later.
In Iran, “virtual debate on social media and the news outlets, grassroots organisations, charities, social
workers and medical professionals worked strenuously to create a mobilisation web of intervention aimed
at informing, safe-guarding, and reducing the risks of the viral outbreak. These networks of mobilisation
are organised through local groups of citizens, in NGOs, charities and also mosques. They supply foodand personal protective equipment to citizens in need. They also act as a safety net against extreme
poverty for those workers which have been most affected by the economic impact of Covid-19, inparticular informal workers who number in several hundred thousand” 21.

6. Beyond the apparent naturalness of the death figures, and of the legal measurestaken to address them, all aspects of the covid-19 epidemic involve a significant role
for the social sciences as a prerequisite for any comparative interpretation. Suchfundamental notions as people’s perception of risk, containment, and the
distribution of institutional powers, call for national contextualization in each case.
Consider the seemingly obvious notion of "confinement", the most dramatic embodiment of
restrictions on individual liberty. It appears simple to characterize since it has a legal definition. But
this administrative and legal concept only accounts for part of people's behavioral adjustment inresponse to the epidemic. Measurements of proxy variables, which I will delve into during thepresentation, indicate that even in nations and regions that maintained full freedom of movement,
populations often took it upon themselves to limit their movements, and this self-confinement
may have been as impactful as imposed strict lockdowns.
These more abstract concepts are especially tricky. Two of the dimensions I mentioned above –responsiveness and subsidiarity – reflect a relationship between institutions that exists across allcases: that between the state, regions, NGOs, and healthcare systems. The interplay between thesefour dimensions, complicated by the wide range of elements and logics at work in the "state"(especially if regional authorities, Parliament22, etc. are also considered), unfolds in both a purely
national context and according to dynamics that call for comparisons. For example, the central
government placed responsibility on regional authorities in Russia, and even happened to directly
oppose them in the United States.

Florence Bernault, “Some lessons from the history of epidemics in Africa”, African Arguments, 5 June
2020, https://africanarguments.org/2020/06/05/some-lessons-from-the-history-of-epidemics-in-africa/
21 Maziyar Ghiabi, Managing Disorder: Iran's Governance Amidst the COVID-19 Pandemic, Istituto per gli studi di politica
internazionale (ISPI), 12 May 2020, https://www.ispionline.it/it/pubblicazione/managing-disorder-irans-governanceamidst-covid-19-pandemic-26080
22 Olivier Rozenberg, Inquiries by Parliaments The political use of a democratic right, Report to the European Parliament's
Committee
on
Citizens'
RightsandConstitutional
Affairs,
March
2020,
https://www.europarl.europa.eu/RegData/etudes/STUD/2020/648709/IPOL_STU(2020)648709_EN.pdf
20

12

Similarly, the very perception of the risk associated with the epidemic calls for comparison. As wehave seen, it was particularly extreme in countries that sensed their healthcare systems would fallshort of meeting their citizens’ expectations, and anticipatorily closed their borders and adopted
various measures to limit mobility and collective activities. Some cases were specific: South Africa
adopted particularly severe measures because it considered its population to be at very high risk,
with approximately 8 million people suffering from HIV, tuberculosis, and/or pneumoconiosis
linked to mining activity. Still reeling from the economic embargo, the Iranian government
deliberately chose to preserve economic activity to the greatest extent possible rather than minimize
the number of deaths23.

7. The social state plays a decisive role here. It acts as a real hidden variable at work
behind the great apparent heterogeneity of anti-epidemic strategies.
A crucial comparative variable that is too often omitted in analyses is the role of the social state,
and more specifically, of the interrelated formal sector of the labor market and full-benefit
employment. The contrast between Europe and the United States is exemplary here. It reveals thestrength of this hidden double variable. The strength of the welfare state, or in any event states’
readiness to implement massive emergency social policies in the form of wage substitution, gave
European states the ability (but also the terrible responsibility) to determine the balance between
paying for lives and paying in lives24.
It is feared that this tradeoff could prove less favorable to preserving human life in the UnitedStates. Despite its wealth and democracy, its working population does not enjoy the same level ofcollective social protection and full-benefit jobs. In addition to ideological hostility to any public
intervention, the population’s at times violent reactions to measures limiting freedom are reflected
in independent professions’ fear of being deprived of income, with knock-on effects given theindebtedness rates of individuals and the mortgage system.
From this perspective, the American situation shares similarities with emerging countries
threatened by the virus but dominated by the "informal" sector of the labor market, making theattempt to strike a balance even more tragic. While the case of India perhaps best illustrates thisreasoning25, to stick to the countries in my sample, the same applies to South Africa, where thepopulation has expressed its opposition to stringent lockdowns and their economic consequences.

8. More speculatively, it appears that the statistical results produced in this paper
suggest the need to reflect on the morphological limits of international
epidemiological comparisons. Three state entities should probably be consideredin further studies: the Empire, the State, and the City.

23 Maziyar Ghiabi, Managing Disorder…, op cit.
24 For more on this distinction, cf. Ariel Colonomos, Evaluer le prix de la vie en temps de pandémie, [Assessing the cost oflife in pandemic times], 22 April 2020, https://www.sciencespo.fr/fr/actualites/actualités/evaluer-le-prix-de-la-vieen-temps-de-pandemie/4730
25 Amartya Sen, “Overcoming a pandemic may look like fighting a war, but the real need is far from that”, Indian
Express, 8 April 2020, https://indianexpress.com/article/opinion/columns/coronavirus-india-lockdown-amartyasen-economy-migrants-6352132/

13

I will conclude with the limitations of my approach, pertaining to the very definition of statisticaladjustment. In the initial version of this work, published in French, I underscored the limitationsof the demographic and public health indicators I had chosen. Another problem needs to beaddressed here because it points to possible paths forward for this study: its geographical level ofobservation. Dictated by the national statistical framework, it actually covers three types of entities:
the Empire, the State, and the City.
Some of the states studied in this paper are in fact too large to be fully compared with the others:
vast Russia, sparsely populated Canada, and the United States with its diverse healthcare systems(not to mention the diverse social conditions) are therefore included here only for the sake of global
comparison, to set orders of magnitude. It would be interesting to duplicate the analysis on a few
states in the United States, comparing them with European nations; as it would be to go down to
the macro-regional level for the largest nations: India, Russia, Brazil, and China. The latter was
excluded from this analysis due to great uncertainties about the quality of its sources. Note that thereverse approach would also be possible: to compare these empire states with the European Union
as a whole.
But the problem doesn't end here. Some authors erroneously object that the national framework
obscures the understanding of epidemic dissemination, which follows a primarily geographicallogic. This observation is indeed applicable to some of the countries in the sample. The mosteloquent case is perhaps that of Switzerland. Its very high corrected mortality in fact consists ofthree different levels that reflect the country's three linguistic zones. Each of these zones reflects
the mortality of its respective border country: the highly affected, Italian-speaking Ticino is close
to Italy; the mortality in French-speaking Switzerland is akin to that of France; and Germanspeaking Switzerland is much less affected, in alignment with Germany and Austria26. Similarly, theresults of many countries with very high national mortality actually reflect one or two particularly
affected regions: Lombardy in Italy, the regions of Madrid and Barcelona in Spain, or the Moscow
region in Russia.
But besides my attempt to mitigate this effect by including population concentration among thevariables for correcting mortality, it would be fallacious to dissolve states by reducing them to one
or two martyr regions. The purpose of this paper was to better compare political responses to theepidemic. From this perspective the national framework plays a major role in terms of legislationand institutions; of regional comparison (fundamental in Italy); of the decision, deemed necessary
or not depending on the state, to close internal borders; and above all of resources. France mostly
succeeded in eschewing overrun hospitals, because when the epidemic peaked, the State transferredpatients suffering from the most serious complications to healthcare institutions located in the least
affected regions. This confirms both the centrality of national indicators on hospital infrastructure
and their limitation, since the parameter of the number of beds available in intensive care units
across the country was only operational insofar as political authorities gave themselves the means
to activate it. France was also able to evacuate patients to neighboring Germany, again
demonstrating a variable of state action: diplomatic relations.

26 Reto Fehr, “So stark wirkt sich Covid-19 auf die Todesfall-Statistik in den Kantonen aus”, Watson, 26 April 2020,

https://www.watson.ch/schweiz/coronavirus/973207961-covid-19-die-todesfaelle-in-den-drei-schweizersprachregionen

14But after Empires and States remains the case of Cities, or more precisely quasi City-States. For
both Belgium and Switzerland, the internal circulation indicators that I selected, based on citizens’
number of overnight stays, probably overestimated the corrected mortality: given the density of
the urban fabric, which is very well connected by road and rail infrastructure, daily round trips arecommon. In the Swiss case, an additional mechanism may be at play. Between its border cantons
with heavy circulation with foreign countries and its small mountain cantons, the Confederation
embodies the two processes that are comparatively conducive to the spread of the epidemic.
These few remarks show how relevant the current pandemic is to a well-known methodologicalquestion: the conditions enabling international comparisons.

SOURCES
Population and density: https://www.populationdata.net/palmares/population/
Population concentration: https://www.populationdata.net/palmares/villes/
Share of people aged 65 and older:
https://donnees.banquemondiale.org/indicator/SP.POP.65UP.TO.ZS
Mobility flows (internal, from and to foreign countries): World Tourism Organization,
Compendium of Tourism Statistics dataset, Madrid, 7 November 2019 (data used: 2018 or the mostrecent available ones). http://statistics.unwto.org/method_notes_tourism_stat_database_2019ed
Oxford Stringency Index J1, J10, J30: https://www.bsg.ox.ac.uk/research/researchprojects/oxford-covid-19-government-response-tracker
Tests: number of tests per inhabitant during the D1-D30 period.
https://ourworldindata.org/covid-testing, or failing thathttps://www.worldometers.info/coronavirus/
AMI (resp. Ischemic stroke): mortality rate after a month of intensive care in a given hospitalfor acute myocardial infarction (resp. ischemic stroke). Source : Panorama de la santé 2019, OCDE.
Number of hospital beds per inhabitant:
https://donnees.banquemondiale.org/indicateur/SH.MED.BEDS.ZS
Health spending: WHO https://apps.who.int/nha/database/ViewData/Indicators/en(2017, in $).

15

APPENDIXTABLE 1 Corrected vs gross mortality (Day30)27
Gross
Corrected
Countries
Day30 Total deaths mortality
mortality
Austria
5/4
204 0,23182% 0,10726%
Belgium
4/4
1283 1,12544% 2,27444%
Canada5/4
280 0,07388% 0,50492%
France29/32606 0,38896% 0,39153%
Germany
29/3
541 0,06518% 0,11393%
Greece5/4
73 0,06822% 0,09221%
Hungary
16/4
77 0,14898% 0,11037%
Iran
25/3
2077 0,25360%
82,14%
Israel8/4
73 0,08022% 0,05909%
Italy
23/3
6077 1,00446% 3,20919%
Japan
21/3
36 0,00286% 0,00483%
Netherlands
4/4
1651 0,95988% 0,48300%
Norway3/4
59 0,10926% 0,07885%
Poland11/4
208 0,05417% 0,58300%
Portugal
10/4
435 0,42233% 0,37573%
Russia15/4
198 0,01350% 1,36744%
South Africa
14/4
27 0,00468% 1,11910%
South Korea
20/3
94 0,01815% 0,01360%
Spain
30/3
7716 1,65225% 1,48736%
Sweden3/4
358 0,34757% 0,18958%
Switzerland
2/4
536 0,63059% 1,42316%
Turkey15/41006 0,18512% 3,69662%
United Kingdom 2/4
2921 0,43925% 0,60208%
United States
5/49616 0,29113% 1,13234%

Rank
6
21
13
11
8
5
7
24
3
22
1
12
4
14
10
18
16
2
20
9
19
23
15
17

Legend:Countries ranked by decreasing corrected mortality rate.
In red: countries that improved their position by more than 3 ranks from the initial crude mortality data.
In blue: countries that fell by three ranks according to the same criterion.
16

TABLE 2 Proactive measures: health policies and corrected mortality

Countries
Japan
South Korea
Israel
NorwayGreeceAustria
Hungary
Germany
SwedenTotal
PublicHospital beds Quality of ICUs Quality of ICUs
health spendings health spendings
AMI
Ischemic stroke
11
6
1
18
1
16
16
2
17
2
13
14
16
8
9
3
1
13
1
3
18
18
12
n.a.
n.a.
6
5
5
10
11
19
19
6
n.a.
n.a.
5
4
3
16
10
4
3
23
3
8

Average rank
low mortality countries

10,6

9,6

9,0

10,4

6,3

17
10
7
8
20
12

17
9
10
7
20
11

15
7
10
21
8
20

15
9
1
5
4
14

18
13
6
14
19
16

Average rank
12,3intermediate mortality countries

12,3

13,5

8,0

14,3

22
1
21
2
15
9
14
24
23

23
2
22
12
15
8
13
21
24

19
18
4
11
17
9
14
22
24

14,6

15,6

15,3

Portugal
FranceNetherlan.a.s
CanadaPolan.a.
United Kingdom

South Africa
United States
RussiaSwitzerlan.a.
Spain
Belgium
Italy
TurkeyIran

Average rank
high mortality countries

17

n.a.

n.a.
6

n.a.
n.a.

5
n.a.
7
17
15
12
4

11
12
7
12
n.a.

n.a.

9,6

10,0

TABLE 3 Reactive measures: policy stringency and corrected mortality

Countries
Japan
South Korea
Israel
NorwayGreeceAustria
Hungary
Germany
SwedenSTRINGENCY
Day1
Day10
Day30
9
18
22
6
9
18
7
2
1
23
16
15
11
2
18
17
1
3
1
5
8
14
18
17
23
24
24

Average rank
12,3
low mortality countries

Tests
24
11
4
1
22
5
18
6
12

10,6

14,0

11,4

6
20
9
23
9
20

12
6
8
12
15
17

3
19
14
7
19
16

Average rank
13,3
14,5
intermediate mortality countries

11,7

13,0

Portugal
FranceNetherlands
CanadaPolandUnited Kingdom

South Africa
United States
RussiaSwitzerland
Spain
Belgium
Italy
Turkey
Iran

9
11
20
20
3
17

4
14
4
11
17
14
7
2
20

6
20
8
17
13
13
15
2
9

1
18
8
12
6
8
3
3
23

23
12
7
2
9
10
15
17
21

Average rank
10,3high mortality countries

11,4

9,1

12,9

18

TABLEAU 4
Summary representation of the public health and testing of each block of countries

Countries
Japan
South Korea
Israel
NorwayGreeceAustria
Hungary
Germany
SwedenTotal
PublicHospital Quality of ICUs Quality of ICUs
Tests
Rank health spendings health spendings beds
AMI
Ischemic stroke
1
6
1
1
2
2
2
4
8
9
4
5
3
1
1
3
1
6
7
6
5
5
10
5
3
6
8
5
4
3
10
6
9
4
3
3
8

Portugal
FranceNetherlands
CanadaPolandUnited Kingdom

10
11
12
13
14
15

South Africa
United States
RussiaSwitzerland
Spain
Belgium
Italy
Turkey
Iran

17
18
16
19
21
22
24
23
25

3
10
7
8

9
10
7

7
10
8

1

2

9
1
5
4

6

6
7

5

4
2
9

7
8

9

7
2
9
10

7
4

Legend: For each indicator, the top five countries (rank shown in red) and those ranked between 6th and10th place are selected.

19

TABLEAU 5 Stringency of anti-epidemic measures in D1, D10 & D30(Oxford Stringency Index)

Countries
Japan
South Korea
Israel
NorwayGreeceAustria
Hungary
Germany
SwedenAverage

D1 D10 D30
29
48
62
48
67
67
38
90 100
0
55
76
24
90
67
14
95
95
90
86
86
19
48
71
0
29
43
29
67
74

Portugal
FranceNetherlands
CanadaPolandUnited Kingdom
Average

29
24
5
5
57
14
20

81
43
67
38
67
43
54

81
90
86
81
76
71
75

South Africa
United States
RussiaSwitzerland
Spain
Belgium
Italy
TurkeyIran
Average

52
19
52
24
14
19
38
67
5
32

81
43
71
52
62
62
62
90
67
66

100
67
86
81
90
86
95
95
57
84

20