japan contact: kamono.mana@ gmail.c om · 4/17/2020 · d ph. ara, h zu asa a masak 1 1, 5 9 1 0-0...

The effect of BCG vaccination on COVID-19 examined by a statistical

approach: no positive results from the Diamond Princess and cross-national

differences previously reported by world-wide comparisons are flawed in

several ways

Masakazu Asahara, Ph. D.1 1Division of Liberal Arts and Sciences, Aichi Gakuin University, Nisshin, Aichi 470-0195,

Japan

Contact: [email protected]

Abstract

Recently, the controversial hypothesis that past BCG (Bacillus

Calmette–Guérin) vaccination reduces infection or severity of COVID-19 has

been proposed. The present study examined this hypothesis using statistical

approaches based on the public data. Three approaches were utilized: 1)

comparing the infection and mortality ratio of people on the cruise ship

Diamond Princess, 2) comparing the number of mortalities among nations,

and 3) comparing the maximum daily increase rate of total mortalities

among nations. The result of 1) showed that there is no significant difference

in infection per person onboard or mortality-infection between Japanese

citizens vs. US citizens and BCG obligatory nations vs. non-BCG obligatory

nations on the Diamond Princess. The result of 2) showed that the number of

mortalities among nations is similar to the previous studies, but this

analysis also considered the timing of COVID-19 arrival in each nation. After

correcting for arrival time, previously reported effect of BCG vaccination on

decreasing total mortality disappeared. This is because nations that lack

BCG vaccination are concentrated in Western Europe, which is near an

epicenter of COVID-19. Therefore some previous reports are now considered

to be affected by this artifact; the result may have been flawed by dispersal

from an epicenter. However, some results showed weakly significant

differences in the number of deaths at a particular time among BCG

obligatory and non-BCG nations (especially the use of Japanese BCG strain

Tokyo 172). However, these results are affected by the results of three

countries and the effect of BCG vaccination remains inconclusive. The result

of 3) showed that the maximum daily increasing rate in death among nations

. CC-BY-NC-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)

The copyright holder for this preprint this version posted May 22, 2020. ; https://doi.org/10.1101/2020.04.17.20068601doi: medRxiv preprint

NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice.

https://doi.org/10.1101/2020.04.17.20068601http://creativecommons.org/licenses/by-nc-nd/4.0/

showed no significant difference among BCG vaccination policies. In the

present study, although some results showed statistically significant

differences among BCG vaccination policies, they may be affected by the

impact of various other factors, such as national infection-control policies,

social distancing, behavioral changes of people, possible previous local

epidemics of closely related viruses, or inter-population differences in ACE2

or other genetic polymorphism. Further research is needed to better

understand the underlying cause of the observed differences in infection and

mortality of the disease among nations. Nevertheless, our results show that

the effect of past BCG vaccination, if any, can be masked by many other

factors. Therefore, the possible effect might be relatively small. In fact, in

Japan, where almost all citizens have been vaccinated, COVID-19 cases are

constantly increasing. Given the importance of people’s behavior in

preventing viral propagation, the spread of optimism triggered by this

hypothesis would be harmful to BCG vaccination nations.




Introduction

In April 2020, the global pandemic of coronavirus disease-2019

(COVID-19) caused by severe acute respiratory coronavirus 2 (SARS-CoV-2)

is a serious problem all over the world. Recently, several authors have

suggested the hypothesis that past BCG (Bacillus

Calmette-Guérinvaccination) vaccination reduces the morbidity and

mortality of COVID-19. Several authors reported the correlation between

national BCG vaccination policy and infection or mortality rate (or its

increasing rate) in those nations (Akiyama and Ishida 2020; Berg et al. 2020;

Dolgikh 2020; Goswami et al. 2020; Miller et al. 2020; Sala and Miyakawa

2020; Shet et al. 2020), and some have argued that the hypothesis is

supported. However, several authors failed to account for how infectious

diseases spread from one place to another. That is, several authors simply

compared the total number of deaths in each nation without considering the

timing disease arrival in each nation (e.g. Miller et al. 2020; Sala and

Miyakawa 2020), suggesting that past BCG vaccination changes the number

of infection and death by double or triple digits (e.g. they simply compared

16523 deaths until April 6 in Italy which BCG- vs. 47 deaths until April 6 in

Russia which BCG+, where the timing of the pandemic enter to the nation is

different). This shortcoming would produce critically important

misunderstandings of the effect of BCG vaccination on COVID-19. In fact,

mandatory BCG vaccination is discontinued in Western Europe, which is

near a COVID-19 epicenter. This should affect the conclusions of previous

studies. Therefore, the present study attempted to examine the effect of BCG

vaccination while accounting for these biases.

Three approaches were used in the present study. The first approach is a

test in the cruise ship Diamond Princess. In this ship, most patients were

infected before they were aware that the disease was spreading in the ship.

Therefore, the cultural effect of countries (such as wearing masks) or

national policy (such as the “cluster buster” policy in Japan) can be excluded.

The strain of virus on the ship is the same, and the spread occurred

simultaneously on board (Sekizuka et al. 2020). The second approach is a

similar comparison as in many previous studies (e.g. Miller et al. 2020; Sala

and Miyakawa 2020). That is, the number of mortalities in each nation was

compared, but with consideration for the timing of disease arrival. The third

approach is also similar to a previous study (Akiyama and Ishida 2020). That




is, the rate of increase of the number of mortalities in each nation was

compared.

Materials and Methods

Data was obtained from previous publications or public databases. The

number of cases, deaths, and passengers’ nationality on the Diamond

princess was obtained from public data (some districts within the nation

were treated separately) (Ministry of Health, Labour and Welfare, Japan,

2020a; b) and a previous report (Moriarty et al. 2020). BCG vaccination

policies were obtained from The BCG World Atlas (Zwerling et al. 2011;

http://www.bcgatlas.org/). The nationalities of dead passengers were

obtained from each news report.

Data on cases and mortality from each nation was obtained from a public

database (some districts within the nation were treated separately) (Dong et

al. 2020; Johns Hopkins University). The number of international tourist'

arrivals in 2017 was obtained from a previously published report (World

Tourism Organization 2019). Some data (BCG vaccination policy, population,

and life expectancy) were obtained from the supplementary material of a

previous study (Sala and Miyakawa 2020). Some BCG strain information

was obtained from other literature (Akiyama and Ishida 2020; Joung and

Ryoo, 2013).

In the analysis of the Diamond Princess, the effects of BCG policy and

nationality were examined using the Fisher’s exact test. If the BCG

vaccination changes the infection or mortality rate by two or three digits as

previous studies suggested, a power analysis indicated that the sample size

for the analysis of infection rate may be sufficient for 90% power on the

analysis (e.g., n=62 is sufficient to detect a difference between the incidence

rates of 0.2 and 0.02 in each group). With respect to the mortality rate, the

sample size may meet 50 to 70% of the power on the analysis (e.g., 70%:

n=124 is sufficient for 70% power to detect a difference between the

incidence rates of 0.05 and 0.0005; 60%: n=99, 0.05 and 0.0005; 50%: n=394,

0.01 and 0.0001; n=78, 0.05 and 0.0005, respectively).

To compare the cases and deaths among nations, the timing of the fifth

death was used to align the timing of disease entry to the nation. Although

Shet et al. (2020) used the timing of the 100th case, this alignment is

considered better because the specific number of the case depends on the




national policy of examination. In addition, the present study focused on the

total number of deaths in each nation, rather than death per population,

because the pandemic was severe in particular cities or particular areas. In

other words, it does not make sense to compensate for the spread of infection

in Hubei province with the population of Beijing and Shanghai. This

relationship is the same in Moscow and Siberia, and the same in Tokyo and

Iwate. Moreover, national political decisions to prevent disease spread,

which is one of the most important factors of disease spread, should be

affected by the total number of victims. Therefore, aligning to the total

national population is irrelevant. Moreover, almost all people are still

considered susceptible to the disease (even in small nations such as San

Marino). In some nations, such as China, the increase in the number of

deaths was stopped or flattened. Therefore, cumulative deaths 30 days after

the date fifth death (this treatment is based on Akiyama and Ishida 2020)

was used. The general linear model was used to test the effect of past BCG

vaccination, the timing of pandemic entry to the nation, and region (e.g.,

East Asia, Europe, etc.). Numbers of death were log-transformed. The region

may serve as rough indexes of social custom, different ratios of genetic

polymorphisms, or the distribution of wildlife. For some results, nations

using the Japanese BCG strain (Tokyo 172) were separated from other BCG

strains because some reports have suggested the Japanese strain is more

effective (Akiyama and Ishida 2020).

To compare the increasing rate of death in each nation, daily increases in

the number of total deaths were calculated. The present study used two

weeks average of the daily rate: Average rates were calculated every two

weeks and the highest value was used as the maximum increase rate per day.

Comparisons were performed using nations where the total number of

deaths was over 25. The effect of BCG policy and region was examined using

the ANOVA-Tukey test. A posthoc power analysis indicated that if the

between-group variance was over 0.0075 (Japanese strain unseparated) and

0.021 (Japanese strain separated), the sample size is sufficient for 90%

power on the analysis. These variances are comparable to within-group

variances. The data of Serbia may not be completed, it was excluded from

this analysis. In this study, all statistical analyses were performed by

Minitab 18 (Minitab Inc, USA) except for the power analyses which were

performed by R (R Core Team, Vienna, Austria). The data and calculations in




the spreadsheet are shown in the supplementary data.

Results and Discussion

The Diamond Princess shows no positive perspective for a personal-level

effect of BCG vaccination

The results of the Diamond Princess are shown in Table 1 and 2. The

case-fatality ratio was not significantly different between people from BCG

mandatory or not mandatory nations even when the analysis was limited to

the elderly (Table 1). The infection and mortality ratio were not significantly

different between Japanese citizens (BCG+) and US citizens (BCG-) (Table 2).

The mortality rate was not significantly different between passengers from

several countries (Table 2).

To discuss the result, Japanese citizens under age 98 should have

received BCG vaccination; in 1951 all infants and citizens under 29 were

inoculated BCG vaccine if their tuberculin test was negative (Ministry of

Health, Labour and Welfare, Japan, 2016). According to the estimated rate of

tuberculosis infection, 12.0% of five year old children and 24.6% of ten year

old children were infected with tuberculosis in 1950 (Omori 2009). Therefore,

80-90% of 70-79 years old people were considered to be inoculated with the

BCG vaccine in Japan. While most Japanese victims on the Diamond

Princess were over 70 years old (except for two victims whose age has not

been announced), most had been inoculated with the BCG vaccination.

However, the infection rate and mortality rate were not different

significantly from that of other people onboard from BCG negative nations.

It should be noted that there was 1045 staff among the 3711 people on the

Diamond Princess (National Institute of Infectious Diseases, 2020). Staff

may be younger than passengers, and the mortality rate should be relatively

low. However, when the analyses focused on older people or passengers only,

the conclusion was not changed (Table 1 and 2). In addition, at that time, the

Diamond Princess traveled from Hong Kong to Japan. Therefore, East Asian

people (from BCG+ countries) could have easily boarded the cruise, even if

they had pre-existing diseases. However, passengers from Western Europe,

the United States, and Australia may have been restricted to individuals

without pre-existing diseases due to the long flight required to reach the

cruise. In addition, 8 people remain in the hospital as of 2020 April 27




(Ministry of Health, Labour and Welfare, Japan, 2020a). These factors may

affect the result. However, it should be emphasized that the Diamond

Princess presented no positive support for the hypothesis that past BCG

vaccination reduces the infection and mortality of COVID-19.

Cross-national comparison showed that previous reports were flawed due to

the timing of spread, yet there is still a weakly significant result in

particular comparisons

The bivariate plots show the results of the cross-national comparison

(Table 3 and 4; Fig. 1, 2, 3, 4, and 5). The result indicated that the number of

deaths is seriously affected by when the disease first spread to the nation (i.e.

date of the fifth death) (Table 3 and 4). In addition, it is also significantly

affected by the region which is used as an index of social custom, different

ratios of genetic polymorphisms, or the distribution of wildlife. For the total

number of deaths, when the period after pandemic entry was fixed, the BCG

effect disappeared (Analysis A and C: Table 3). In contrast, when analyzing

the Japanese BCG strain separately, BCG policy was not significant in

analysis B, but was significant in analysis D (Table 3). This result may be

due to three nations (Japan, Iraq, and South Korea) which showed relatively

lower mortality and use the Japanese BCG strain. Therefore, unique

characteristic effects of those nations may affect the result. For example,

public security problems in Iraq might force people to stay home. The South

Korean government examined many patients and succeeded in controlling

the pandemic. The Japanese government adopted a unique strategy of

“cluster buster” based on the previous result that the “super-spreader” (an

infected person who spreads the virus to many other people) is restricted in

SARS-CoV-2 (Nishiura et al. 2020). In addition, governmental requests for

social distancing may work in Japan (on April 11, the number of train

passengers in Shibuya station, Tokyo reduced 98% from one year ago, except

for those using commuter’s ticket: TBS News 2020). The same metrics

showed 66-89% of passenger reduction at other major stations in Tokyo that

weekend (Cavinet Secretariat, Japan 2020). It should be noted that South

Korea had been using the Danish BCG strain, but later changed to the

Japanese strain Tokyo 172 (Akiyama and Ishida 2020). Among other nations

examined, China and the Philippines, which are BCG+, showed relatively

fewer deaths (Fig. 1 and 2). These nations are known to choose strong




policies to prevent transfer among cities. Australia, which is a BCG- nation,

also showed a similar pattern to Japan, Iraq, and South Korea (Fig. 1 and 2)

although the cause of this is not clear. The pattern of San Marino may be

explained by its smaller population. All nations possess particular factors

that affect their results.

The timing of disease entry seems to correlate to number of tourists (Fig.

3). In addition, political and economic relationships to China might affect

disease entry such as in Iran and South Korea. Therefore, the international

flow of people might affect the timing of pandemic entry and the number of

deaths. However, focusing on nations whose deaths are relatively small,

there seems to be less relationship between the number of tourists and total

deaths (Fig. 5). Some nations using the Japanese BCG strain such as

Thailand, seemed to succeed in preventing transmission despite the number

of tourists. However, some BCG- nations, such as Australia and New Zealand,

also seem successful in preventing the pandemic. In addition, most nations

where the disease spread has so far been prevented are BCG+ nations. These

nations are located outside of Europe, which might flaw previous studies (Fig.

5).

Although previous reports suggested that past BCG vaccination reduces

infection and mortality (e.g. Miller et al. 2020; Sala and Miyakawa 2020), the

present study suggests that these previous results were biased by the route

of pandemic spread and the timing of pandemic entry to the nation. In other

words, the fact that some nations in Western Europe became an epicenter of

the pandemic as a stochastic event is an important factor. This is clearer in

the analysis using only European nations (Table 4; Fig. 4).

The present study did not consider GDP, latitude, or temperature, etc.

However, the results indicate that even if past BCG vaccination may have an

effect on COVID-19, it can be easily masked by other factors. In fact, the

timing of pandemic entry had much larger effect on the observed

cross-national difference than the BCG policy did (Table 3 and 4). Therefore,

the author considers that the effect of BCG, if any, may not be potent as

previous reports suggested; the result does not support that the past BCG

vaccination reduces the number of infection and death changes by double or

triple digits (e.g. Miller et al. 2020; Sala and Miyakawa 2020).

BCG may possess little or no effect on the increase rate of deaths in countries




where the disease spreading

The result of the increase rate of deaths is shown in Fig. 6. The real

increase graph is shown in Fig. 7. There is no significant difference between

BCG+ or – nations (Fig. 6). However, when analyzing the Japanese BCG

strain separately, the result was weakly significant (Fig. 6). The result may

be affected by sample size (the comparison was performed on 55 nations).

The increase rate decreases from BCG –, BCG – (past +), BCG +, and BCG +

(Japanese strain) nations. However, there are several outliers and large

regional differences. In addition, few nations affected the result.

Furthermore, the timing of the pandemic entry may affect because people’s

behavior may have gradually changed. Therefore, the effect of BCG

vaccination is not clear. It should be noted that another study reported a

highly significant correlation between BCG vaccination and the increasing

rate (Akiyama and Ishida 2020). This difference may be attributed to the

previous study focusing on the average increase rate whereas the present

study is focused on the maximum increase rate. The author considers that

the maximum increase rate indicates potential of disease increase and may

be more critical to pandemic control.

Possible factors affecting the results and the remaining possibility of the

BCG hypothesis

The hypothesis that past BCG vaccination affects COVID-19 can be

separated into three. The first hypothesis is regarding reducing personal risk

of infection or mortality. The present study partially tested this using the

data of 1) the Diamond Princess and did not show positive result. Another

study also reported a negative result by comparing infection rate of BCG+

and BCG- age people in several nations (Fukui et al. 2020). The second

hypothesis is regarding reducing the total morbidity and mortality in the

population (e.g. Miller et al. 2020; Sala and Miyakawa 2020). The present

study did not show a positive perspective regarding this aspect, as seen by

the result of 2) the cross-national comparisons. The third hypothesis is about

reducing the rate of propagation in the population (e.g. Akiyama and Ishida

2020). The present study did not show clear results about this. As discussed

above, although the possibility of undetectable effect cannot be ruled out,

none of the hypothetical effects of past BCG vaccination on COVID-19 are

supported in this study.




The hypotheses of BCG have emerged from previous reports that BCG

has non-specific provocation of natural immunity (termed “trained

immunity”; reviewed by e.g. Covián et al. 2019; Angelidou et al. 2020). This

mechanism is very attractive, although the present study did not show a

positive result. However, if this mechanism is effective, then the effects of

BCG on COVID-19 may not differ in high magnitude among BCG strains.

T-cell epitopes of BCG have been estimated previously (Zhang et al. 2013).

According to the previous study (Zhang et al. 2013), the Japanese BCG

strain possesses more epitopes than other strains. The author preliminary

examined whether SARS-CoV-2 possesses homologous amino acid sequences

of these BCG epitopes using BLAST. However, no homologous sequence was

observed (Personal Observations; Fig. 8). If the Japanese strain had a larger

effect on the disease, it would not be due to affinity to T-cell receptors. A

possible mechanism could be that a domain or constituent unique to the

Japanese strain has a high affinity to Toll-like receptors or some other

receptors for innate immunity and leads to strong trained immunity (Fig. 8).

However, according to the results of the Diamond Princess, this is rather

unlikely.

The cross-national difference of morbidity and mortality can be

influenced by many factors. A schematic illustration is shown in Fig. 8. A

possibility explained above is that several nations have unique reasons that

reduce disease propagation. Each nation’s policy in response to the pandemic,

cultural differences, or lifestyle differences should be considered.

Additionally, as our cross-national comparisons showed the region

significantly affected the result (Table 3), there can be other hypotheses.

The author could suggest another possible hypothesis that several

nations already experienced local epidemics of similar viruses. Wild bats and

civets possess viruses related to SARS-CoV-2 (e.g., bat/ civet SARS

coronaviruses) (e.g. Guan et al. 2003; Lau et al. 2005; Li et al. 2005; Song et

al. 2005; Wu et al. 2016; Luk et al. 2019; Lam et al. 2020). Epitopes of

SARS-CoV-2 were suggested by a previous study (Ahmed et al. 2020). The

author preliminarily examined whether SARS-related viruses possess

homologous amino acid sequences of these SARS-CoV-2 epitopes using

BLAST. There are many homologous sequences in bat and civet SARS

coronaviruses (Personal Observations). Rhinolophus bats are one of the wild

hosts of these viruses and distribute in South Europe, Middle East, South




Asia, South East Asia, East Asia, and Oceania. Another host is the masked

palm civet (Paguma larvata) distributes in East Asia. If there were local

epidemics of these related viruses manifested as a slight cold in several

particular nations, many people may have acquired immunity to these

viruses, hence explaining the different morbidity and mortality patterns

between nations. A large scale antibody test may address these hypotheses.

In addition, cross-immunity to normal colds should also be considered. In

Japan, there is a culture that people go to work even if they have a cold.

Therefore, a high percentage of the working generation may have already

contracted the common cold. This may have an impact on the situation in

Japan. However, this effect will not work for the second wave predicted in

the near future, as immunity of normal cold does not last long.

The author could suggest one more possible hypothesis being that human

genetic variation caused the difference between nations. As other SARS-like

coronaviruses, SARS-CoV-2 may use the angiotensin-converting enzyme II

(ACE2) protein (Ge et al., 2013; Hoffman et al. 2020) and the

transmembrane serine protease (TMPRSS2) protein (Matsuyama et al. 2010;

Glowacka et al. 2011; Shulla et al. 2011) for infection. Some reports have

suggested that ACE2 variants (Elisa et al. 2020) or TMPRSS2 variants

(Asselta et al. 2020) can affect the severity of COVID-19. A previous report

suggested that the proportion of ACE2 polymorphisms is different among

populations; the ratio of some allele variant gradually decreases from Europe

> America > Africa, South Asia> East Asia (including China) (Cao et al. 2020).

Geographic variation of MHC class I (HLA) gene whose susceptibility the

COVID-19 may be different was also reported (Nguyen et al. 2020). These

patterns may explain the relatively low mortality and increase rate in East

Asian nations. Perhaps this geographic pattern may have been caused

through natural selection by a possible historical epidemic of SARS related

viruses in East Asia or other regions. Given that historical contact with

livestock may have been important to resistance to some kind of infectious

disease (Diamond 1997), increased resistance to another kind of zoonosis can

be observed in areas where are close to biodiversity hotspots. Perhaps the

resistance could be a cultural or political propensity.

The author could suggest another possible hypothesis of polymorphisms

affecting the genetic ability of disease spread. Although many studies focus

on susceptibility of the disease, ability of disease transmission to others




would be necessary to examine as a factor on the regional difference. In fact,

several results suggest relatively low difference of susceptibility among

human populations (Table 1 and 2). Previous studies have suggested that

almost all infected persons do not spread COVID-19, but rather only a

selected few people spread the disease (Nishiura et al. 2020; Endo 2020). In

addition, a previous study reported that viral load in the saliva correlated

with age (To et al., 2020), but their result seems to show high variance

among individuals. If the ability of disease spread varies among individuals

and the proportion of “super-spreaders” is different among nations, the

previously reported spread pattern (Nishiura et al. 2020) and the different

increase rates of victims among nations can be explained. The author

suggests two patterns of hypothetical causation. The first is that the degree

of expression of ACE2 or other related genes in the salivary gland or

intraoral organs varies. If the expression is high, the number of viruses

increases in the saliva. COVID-19 may infect through droplets (Lai et al.

2020) possibly including those blown out during conversation. Therefore, this

hypothesis is feasible. In addition, the amount or viscidity of saliva, and

morphological character of oral organs might affect disease spread. However,

to prove this hypothesis, an intensive examination of the route of infection

and disease spread would be needed.

As discussed above, there can be many hypotheses explaining the

differences of COVID-19 morbidity, mortality, and how those increase among

nations. Given that the effect of the region was significant in analysis 2,

simple comparisons among nations may fail to address these

problems/hypotheses.

Although there are many things to do before proving the BCG hypothesis,

many mass media outlets are reporting the hypothesis, causing people to

gradually consider the hypothesis to be true (especially in BCG+ nations

such as Japan). Some people even suggested that no special protective

measure is needed in Japan. The author seriously worries about this

problem because the change in people’s behavior is the most important

avenue to prevent viral spread (Flaxman et al. 2020; Ministry of Health,

Labour and Welfare, Japan, 2020a; Zhang et al. 2020). Optimism caused by

the spread of this hypothesis is a serious problem. We should be cautious

that in Japan, even though almost all citizens received BCG vaccination

(using the Japanese strain, which may be most effective), cases and deaths




are constantly increasing at the beginning of April, 2020.

The effect of past and recent vaccination should not be confused

The present study focuses on past vaccination (such as that in many

decades ago) as in the previous cross-national comparative studies. In the

meantime, clinical studies examining the effects of recent vaccination to

adults are currently being conducted (e.g. reported by Vrieze, 2020). However,

it is dangerous to confuse the effects of recent vaccination with the past

vaccination (Asahara, submitted). Even if the cross-national comparison

results were positive, it cannot prove the effect of recent vaccination because

inoculation to infants may be necessary for effectiveness (e.g. low efficacy of

adult inoculation for tuberculosis resistance: Mangtani et al. 2014). Of course,

the cross-national comparisons have too many factors to consider, and that

alone is not sufficient to prove the BCG effect. On the other hand, even if the

results of a clinical study are positive, it cannot prove that the effects will

last for decades. In other words, the result of the clinical trials cannot prove

that past BCG vaccination is responsible for the cross-national differences in

cases and deaths. Other studies would be required such as examining the

previous vaccination history of infected people in a country where

vaccination is optional. However, clinical studies would provide more reliable

data on the effect of BCG vaccination on the COVID-19 than cross-national

comparisons.

Conclusions

The hypothesis that BCG vaccination reduces the infection and mortality

of COVID-19 is attractive. However, previous international comparative

reports may not prove the hypothesis because many other possibilities can

explain the observed pattern. In addition, the present study did not show a

positive result. Clinical researches are currently being conducted (e.g.

reported by Vrieze, 2020). These ongoing clinical studies should provide a

better understanding of this hypothesis. Until then, we should be careful

about patterns observed in the statistical data. Moreover, spreading the

optimistic view triggered by the hypothesis is rather harmful.




Acknowledgement

The author thanks anonymous readers who commented on the

preprint version of the manuscript (published in April 22, 2020). English of

the some part of the manuscript have been corrected by courtesy of Editage

service.

References

Ahmed S. F. et al. 2020. Preliminary identification of potential vaccine targets for the

COVID-19 coronavirus (SARS-CoV-2) based on SARS-CoV immunological studies.

Viruses 12: 254.

doi:10.3390/v12030254

Akiyama Y. and Ishida T. 2020. Relationship between COVID-19 death toll doubling

time

and national BCG vaccination policy. (preprint)

http://www.bi.cs.titech.ac.jp/COVID-19/Death_vs_BCGpolicy.html?fbclid=IwAR1-3au

eH73F0HIBZeWLsJXXNVKQ56P7DaX5a20iO1eCNbjPBWoHC7q%E2%80%A6

Angelidou A. et al. 2020. BCG as a Case study for precision vaccine

development: lessons from vaccine heterogeneity, trained immunity, and

immune ontogeny. Frontiers in Immunology 11: 332.

doi: 10.3389/fmicb.2020.00332

Asselta R. et al. 2020. ACE2 and TMPRSS2 variants and expression as candidates to

sex and

country differences in COVID-19 severity in Italy.

medRxiv preprint doi: https://doi.org/10.1101/2020.03.30.20047878

Berg M. K. et al. 2020. Mandated Bacillus Calmette-Guérin (BCG) vaccination predicts

flattened curves for the spread of COVID-19.

MedRxiv preprint doi: https://doi.org/10.1101/2020.04.05.20054163.

Cabinet Secretariat. 2020. 駅の改札通過�数の推移（対前年�）[in Japanese]

https://corona.go.jp/toppage/pdf/area-transition/20200414_station.pdf

Cao Y. et al. 2020. Comparative genetic analysis of the novel coronavirus

(2019-nCoV/SARS-CoV-2) receptor ACE2 in different populations. Cell

Descovery 6: 11.

https://doi.org/10.1038/s41421-020-0147-1

Covián C. et al. 2019. BCG-induced cross-protection and development of




trained immunity: implication for vaccine design. Frontiers in

Immunology 10: 2806.

doi: 10.3389/fimmu.2019.02806

Diamond J. 1997. Guns, Germs, and Steel. W. W. Norton & Company inc., New York.

Dolgikh S. 2020. Further Evidence of a Possible Correlation Between the Severity of

Covid-19 and BCG Immunization.


Dong E., Du H., Gardner L. 2020. An interactive web-based dashboard to track

COVID-19 in real time. The Lancet.

https://doi.org/10.1016/S1473-3099(20)30120-1

Endo A. 2020. Estimating the overdispersion in COVID-19 transmission using outbreak

sizes outside China. Wellcome Open Research 5:67. (preprint)

https://doi.org/10.12688/wellcomeopenres.15842.1

Elisa B. et al. 2020. ACE2 variants underlie interindividual variability and

susceptibility to

COVID-19 in Italian population.


Flaxman S. et al. 2020. Estimating the number of infections and the impact of

nonpharmaceutical interventions on COVID-19 in 11 European countries. Imperial

College London (30-03-2020)

doi: https://doi.org/10.25561/77731.

Fukui M. et al. Does TB vaccination reduce COVID-19 infection? No evidence from a

regression discontinuity analysis. JEL I18: I15. (preprint)

Ge X.-Y. et al. 2013. Isolation and characterization of a bat SARS-like coronavirus that

uses the ACE2 receptor. Nature 503: 535-538.

Glowacka I. et al. 2011. Evidence that TMPRSS2 activates the severe acute respiratory

syndrome coronavirus spike protein for membrane fusion and reduces viral control by

the humoral immune response. Journal of Virology 85: 4122-4134.

Goswami R. P. et al. 2020. Interaction between malarial transmission and BCG

vaccination with COVID-19 incidence in the world map: A cross-sectional study.


Guan Y. et al. 2003. Isolation and characterization of viruses related to the SARS

coronavirus from animals in southern China. Science 302: 276-278.

Hoffmann M. et al. 2020. The novel coronavirus 2019 (2019-nCoV) uses the

SARS-coronavirus receptor ACE2 and the cellular protease TMPRSS2 for entry into

target cells.




bioRxiv preprint doi: https://doi.org/10.1101/2020.01.31.929042

Lai C.-C. et al. 2020. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)

and coronavirus disease-2019 (COVID-19): The epidemic and the challenges.

International Journal of Antimicrobial Agents 55: 105924.

https://doi.org/10.1016/j.ijantimicag.2020.105924

Lam T. T.-Y. et al. 2020. Identifying SARS-CoV-2 related coronaviruses in Malayan

pangolins. Nature (online)

https://doi.org/10.1038/s41586-020-2169-0

Lau S. K. P. et al. 2005. Severe acute respiratory syndrome coronavirus-like virus in

Chinese horseshoe bats. PNAS 102: 14040-14045.

Li W. et al. 2005. Bats are natural reservoirs of SARS-like coronaviruses. Science 310:

676-679.

Luk H. K. H. 2019. Molecular epidemiology, evolution and phylogeny of SARS

coronavirus. Infection, Genetics and Evolution 71: 21-30.

Johns Hopkins University. Mapping 2019-nCoV.

https://github.com/CSSEGISandData/COVID-19

Mangtani P. et al. 2014. Protection by BCG vaccine against tuberculosis: a systematic

review of randomized controlled trials. Clinical Infectious Diseases 58: 470-480.

https://doi.org/10.1093/cid/cit790

Matsuyama S. et al. 2010. Efficient activation of the severe acute respiratory syndrome

coronavirus spike protein by the transmembrane protease TMPRSS2. Journal of

Virology 84: 12658-12664.

Moriarty L. F. et al. 2020. Public Health Responses to COVID-19 outbreakes of cruise

ships — Worldwide, February–March 2020. Morbidity and Mortality Weekly Report

69: 347-352.

https://www.cdc.gov/mmwr/volumes/69/wr/pdfs/mm6912e3-H.pdf

Miller A. et al. 2020. Correlation between universal BCG vaccination policy and reduced

morbidity and mortality for COVID-19: an epidemiological study.


Ministry of Health, Labour and Welfare, Japan, 2020a. About the new coronavirus

infection. (accessed in 2020 April 27)

https://www.mhlw.go.jp/stf/seisakunitsuite/bunya/0000164708_00001.html

Ministry of Health, Labour and Welfare, Japan, 2020b. Diamond Princess Cases.

(accessed in 2020 April 27)

https://www.mhlw.go.jp/content/000598727.pdf

Ministry of Health, Labour and Welfare, Japan, 2016. Kekkaku ni kausuru tokutei




kansensyo yobo shishin ni Tsuite (結核に関する特定感染症予防指針について). [in

Japanese]

https://www.mhlw.go.jp/stf/shingi2/0000110066.html

National Institute of Infectious Diseases. 2020. Field Briefing: Diamond

Princess COVID-19 Cases.

https://www.niid.go.jp/niid/en/2019-ncov-e/9407-covid-dp-fe-01.html

Nguyen A. et al. 2020. Human leukocyte antigen susceptibility map for

SARS-CoV-2. Journal of Virology

DOI: 10.1128/JVI.00510-20

Nishiura H. et al. 2020. Closed environments facilitate secondary

transmission of coronavirus disease 2019 (COVID-19).

medRxiv preprint doi: https://doi.org/10.1101/2020.02.28.20029272.

Joung S. M. and Ryoo S. 2013. BCG vaccine in Korea. Clinical and

Experimental Vaccine Research 2: 83.

http://dx.doi.org/10.7774/cevr.2013.2.2.83

Omori M., 2009. Kekkaku kikansensya suu no suikei (結核既感染者数の推計).

The Research Institute of Tuverculosis, Japan. [in Japanese]

http://www.jata.or.jp/rit/ekigaku/

Sala G. and Miyakawa T. 2020. Association of BCG vaccination policy with prevalence

and mortality of COVID-19.

medRxiv preprint doi: https://doi.org/10.1101/2020.03.30.20048165.

Sekizuka T et al. 2020. Haplotype networks of SARS-CoV-2 infections in the Diamond

Princess cruise ship outbreak. MedRxiv preprint

https://doi.org/10.1101/2020.03.23.20041970.

Shet A. et al. 2020. Differential COVID-19-attributable mortality and BCG vaccine use

in countries.


Shulla A. et al. 2011. A transmembrane serine protease is linked to the severe acute

respiratory syndrome coronavirus receptor and activates virus entry. Journal of

Virology 85: 873-882.

TBS News. 2002. Passengers 98% reduction in Shibuya station on the first Saturday

after the announcement of state emergency. (「緊急事態宣言」後の土曜日、ＪＲ渋谷駅

利用客９８％減) [in Japanese]

https://news.tbs.co.jp/newseye/tbs_newseye3955068.html

To et al. 2020. Temporal profiles of viral load in posterior oropharyngeal saliva samples

and serum antibody responses during infection by SARS-CoV-2: an observational




cohort study. The Lancet Infectious Diseases (published online)

https://doi.org/10.1016/S1473-3099(20)30196-1

Wourld Tourism Organization. 2019. International Tourism Highlights.

https://www.e-unwto.org/doi/book/10.18111/9789284421152

Wu Z. et al. 2016. Deciphering the bat virome catalog to better understand the

ecological diversity of bat viruses and the bat origin of emerging infectious diseases.

The ISME Journal 10: 609-620.

de Vrieze J. 2020. Can a century-old TB vaccine steel the immune system against the

new coronavirus? Science (online) doi:10.1126/science.abb8297

Zhang W. et al. 2013. Genome sequencing and analysis of BCG vaccine strains. PLoS

ONE 8: e71243.

doi:10.1371/journal.pone.0071243

Zhang J. et al. 2020. Changes in contact patterns shape the dynamics of the COVID-19

outbreak in China. Science. DOI: 10.1126/science.abb8001

Zhou P. et al. 2020. A pneumonia outbreak associated with a new coronavirus of

probable bat origin. Nature 579: 270-273.

https://doi.org/10.1038/s41586-020-2012-7

Zwerling A. et al. 2011. The BCG World atlas: a database of global BCG vaccination

policies and practices. Plos Medicine 8: e1001012.

doi:10.1371/journal.pmed.1001012




Table and Figure Legends

Table 1. Case fatality ratio between the nationality of different BCG vaccination policies

in the Diamond Princess (April 27, 2020).

Both past and current implementing of vaccination are categorized to +

Current implementing of vaccination is categorized to +

*There are still 6 people in the hospital whose nationality is undisclosed.

Table 2. Infection and mortality ratio between citizens of Japan and other countries in

the Diamond Princess (April 27, 2020)

Table 3. The result of general linear model testing for the effect of BCG vaccination and

other factors using all available nations around the world (Fig. 1 and 2)

Table 4. The result of general linear model testing for the effect of BCG vaccination and

other factors using European nations (Fig. 4)

Fig. 1. Bivariate plots of the Date of fifth Death (as an index of the timing of pandemic

entry into the nation) vs. Log (Total deaths up to April 6). Most nations showed

exponential increases in the number. However, some nations plotted lower than other

nations. It should be noted that BCG – countries are mainly located in Europe, there is

an epicenter of the pandemic.

Fig. 2. Bivariate plots of Days from fifth Death to April 6 or 30 (as an index of the time

from the entry of the pandemic to the nation/the time until the number of deaths has

flattened) vs. Log (Total deaths or sum of deaths at 30 days after the fifth death, i.e. the

number of deaths during the time X axis). Most nations showed exponential growth in

the number. However, some nations plotted lower than the other nations.

Fig. 3. Bivariate plots of international tourist arrivals in 2017 vs. Date fifth Death.

Pandemic propagation may be affected by tourist arrivals.

Fig. 4. Bivariate plots using only European nations. The plots clearly show that high

number of deaths are affected by when the pandemic enter the nation. The pandemic

explosion occurred in Western Europe where BCG – nations are located, and then

spread to the peripheral of Europe where BCG + nations are located.




Fig. 5. Bivariate plots of International tourist arrivals in 2017 vs. Total deaths up to

April 6 using non-European nations with total deaths less than 200. Most nations are

BCG +, but some BCG - nations seem to succeed in suppressing COVID-19. Most

non-European nations are BCG + and are located where COVID-19 has not yet entered

at full scale. This fact would flaw the results of previous studies.

Fig. 6. Box plots of maximum increase rate per day (two week average). Nations where

deaths are more than 25 were illustrated. Boxes indicate quartiles, central-lateral bars

indicate medians, vertical bars indicate the range of the specimens, and asterisks

indicate outliers. The increase rate seems to higher in BCG – nations. However, only

one pair was weakly statistically significant, but most are not (ANOVA/ Tukey’s test).

Fig. 7. Cumulative deaths of nations in which total deaths over 25. Although the

increase rate in Iraq, Korea, and Japan seem to low, at the beginning of the increase,

the rate is not particularly low. Malaysia which uses Japanese strain shows a similar

pattern to the other nations.

Fig. 8. Schematic illustration of how cross-national statistical analysis (“ecological

study”) can be influenced. Many factors influence the results. The author’s idea of the

remaining possibility of BCG vaccination is also illustrated. The map is modified based

on the map provided by the Geospatial Information Authority of Japan.

https://maps.gsi.go.jp/development/ichiran.html




Both past and current implementing of vaccination are categorized to +BCG Cases Deaths Mortaliry rate (%)

+ 493 13 2.64- 141 1 0.71

No significant differencep=0.325 (Fisher's exact test)

Current implementing of vaccination is categorized to +BCG Cases Deaths Mortaliry rate (%)

+ 422 11 2.61- 212 3 1.42


Analysis on people over 60 years old (age-indeterminate deaths included)Both past and current implementing of vaccination are categorized to +

BCG Cases Deaths Mortaliry rate (%)+ 350 13 3.71- 126 1 0.79



+ 301 11 3.65- 175 3 1.71


Analysis on people over 70 years old (age-indeterminate deaths included)Both past and current implementing of vaccination are categorized to +

BCG Cases Deaths Mortaliry rate (%)+ 227 13 5.73- 71 1 1.41



+ 198 11 5.56- 100 3 3.00


*There are still 8 people in hospital whose nationality is undisclosed

Table 1. Case fatality ratio between nationality of different BCG vaccinationpolicies in the Diamond Princess (April 27, 2020)




Infection rate in the Diamond Princess (*2)Nationality Number on board Cases Infection rate (%)

Japan (BCG +) 1341 270 20.13USA (BCG -) 428 107 25.00


Mortality rate in the Diamond Princess (*2)Nationality Number on board Deaths Mortality rate (%)

Japan (BCG +) 1341 9 0.67USA (BCG -) 428 0 0.00


Mortality rate in the Diamond Princess passengers (*3)Nationality Number on board Deaths Mortality rate (%)

Japan (BCG +) 1281 9 0.70Hong Kong (BCG +) 260 2 0.77

USA (BCG -) 416 0 0.00Canada (BCG -) 251 1 0.40

Australia (BCG - / past+) 223 1 0.45UK (BCG - / past+) 57 1 1.75

No significant differenceJapan + Hong Kong vs Others; Others vs USA + Canada: p > 0.05 (Fisher's exact test)

*1 There are still 8 people in hospital whose nationality is undisclosed*2 US data was obrained from Moriarty et al. (2020)*3 Passengers data was obrained from Moriarty et al. (2020)

Table 2. Infection and mortality ratio between citizens of Japan and other countries in theDiamond Princess (April 27, 2020)




Table 3. The result of general linear model testing for the effect of BCG vaccination and other factors using all available nations aroud the world (Fig. 1 and 2)

Analysis A Analysis B

Adj SS Adj MS F P Adj SS Adj MS F PBCG policy 0.4857 0.2429 1.730 0.184 BCG policy (Japanese strain separated) 0.4895 0.1632 1.150 0.336Date 5th death 29.1332 29.1332 207.920 0.000 Date 5th death 29.006 29.006 204.210 0.000Region 8.1498 1.0187 7.270 0.000 Region 7.0906 0.8863 6.240 0.000

R^2=0.8367 R^2=0.8091Analysis C Analysis D

Adj SS Adj MS F P Adj SS Adj MS F PBCG policy 0.0821 0.0411 0.280 0.760 BCG policy (Japanese strain separated) 1.5887 0.5296 4.110 0.010Days from 5th death 25.005 25.005 168.160 0.000 Days from 5th death 26.353 26.353 204.720 0.000Region 3.6858 0.4607 3.100 0.005 Region 2.4454 0.3057 2.370 0.026

R^2=0.8080 R^2=0.8362*Period Death: Total deaths or sum of deaths 30th days from 5th death

Log Total Death = BCG polocy + Date 5th death + Region Log Total Death = BCG polocy (J strain separated) + Date 5th death + Region

Log Period Death = BCG polocy + Days from 5th death + Region Log Period Death = BCG polocy (J strain separated) + Days from 5th death + Region

. C

C-B

Y-N

C-N

D 4.0 International license

It is made available under a

is the author/funder, who has granted m

edRxiv a license to display the preprint in perpetuity.

(wh

ich w

as no

t certified b

y peer review

)T

he copyright holder for this preprint this version posted M

ay 22, 2020. ;

https://doi.org/10.1101/2020.04.17.20068601doi:

medR

xiv preprint


Analysis E

Adj SS Adj MS F PBCG policy 0.7688 0.3844 2.850 0.072Date 5th death 17.3209 17.3209 128.450 0.000

R^2=0.8582Analysis F

Adj SS Adj MS F PBCG policy 0.36 0.18 1.270 0.295Days from 5th death 16.118 16.118 113.400 0.000

R^2=0.8427*Period Death: Total deaths or sum of deaths 30th days from 5th death

Log Period Death = BCG polocy + Days from 5th death

Table 4. The result of general linear model testing for the effect of BCGvaccination and other factors using European nations (Fig. 4)

Log Total Death = BCG polocy + Date 5th death




2020/04/012020/03/012020/02/01

4.5

4.0

3.5

3.0

2.5

2.0

1.5

1.0 Venezuela

US

Uruguay

United Kingdom

Channel Islands

United Arab Emirates

Ukraine

Turkey

Tunisia

Trinidad and Tobago

Thailand

Switzerland

Sweden

Spain

South Africa

Slovenia

Singapore

Serbia

Saudi ArabiaSan Marino

Russia

Romania

Portugal

Poland

Philippines

Peru

PanamaPakistan

Norway

North Macedonia

Niger

Netherlands

Sint Maarten

Morocco

Moldova

Mexico

Mauritius

Malaysia

Luxembourg

LithuaniaLebanon

Korea, South

KenyaKazakhstanJordan

Japan

Italy

Israel

Ireland

Iraq

Iran

Indonesia

India

Iceland

Hungary

Honduras

Greece

Germany

France

Guadeloupe

Finland

Estonia

Egypt

Ecuador

Dominican Republic

Denmark

Czechia

CyprusCuba

CroatiaCongo (Kinshasa)

Colombia

China

Chile

Canada

Cameroon

Burkina FasoBulgaria

Brazil

Bosnia and Herzegovina

Bolivia

Belgium

BelarusBangladesh

Azerbaijan

Austria

Australia

Armenia

Argentina

Andorra

Algeria

Albania

Afghanistan

BCG +

BCG - (past BCG +)BCG -

BCG + (using Japanese strain)

Date 5th Death

Date 5th Death

Log (Total deaths to April 6)


A

B

Fig. 1. Bivariate plots of the Date of fifth Death (as an index of the timing of pandemic entry into the nation) vs. Log (Total deaths up

to April 6). Most nations showed exponential increases in the number. However, some nations plotted lower than other nations. It

should be noted that BCG – countries are mainly located in Europe, there is an epicenter of the pandemic.

2020/04/012020/03/012020/02/01

4.5

4.0

3.5

3.0

2.5

2.0

1.5

1.0 South Asia

Africa

America

Central AsiaEast Asia

Europe

Middle EastPacific

SE AsiaVenezuela

US

Uruguay

United Kingdom

Channel Islands


Ukraine

Turkey

Tunisia

Trinidad and Tobago

Thailand

Switzerland

Sweden

Spain

South Africa

Slovenia

Singapore

Serbia


Russia

Romania

Portugal

Poland

Philippines

Peru

PanamaPakistan

Norway

North Macedonia

Niger

Netherlands

Sint Maarten

Morocco

Moldova

Mexico

Mauritius

Malaysia

Luxembourg

LithuaniaLebanon

South Korea

KenyaKazakhstanJordan

Japan

Italy

Israel

Ireland

Iraq

Iran

Indonesia

India

Iceland

Hungary

Honduras

Greece

Germany

France

Guadeloupe

Finland

Estonia

Egypt

Ecuador

Dominican Republic

Denmark

Czech

CyprusCuba


Colombia

China

Chile

Canada

Cameroon


Brazil


Bolivia

Belgium

BelarusBangladesh

Azerbaijan

Austria

Australia

Armenia

Argentina

Andorra

Algeria

Albania

Afghanistan




302520151050

4.5

4.0

3.5

3.0

2.5

2.0

1.5

1.0 Venezuela

USUnited Kingdom

Channel Islands


Ukraine

Turkey

Tunisia

Trinidad and Tobago

Thailand

Switzerland

Sweden

Spain

South Africa

Slovenia

Singapore

Serbia


Russia

Romania

Portugal

Poland

Philippines

Peru

PanamaPakistan

Norway

North Macedonia

Niger

Netherlands

Morocco

Moldova

Mexico

Mauritius

Malaysia

Luxembourg

LithuaniaLebanon

Korea, South

Kazakhstan

Japan

Italy

Israel

Ireland

Iraq

Iran

Indonesia

India

Hungary

Honduras

Greece

Germany

France

Guadeloupe

Finland

Estonia

Egypt

Ecuador

Dominican Republic

Denmark

Czechia

CyprusCuba


Colombia

China

Chile

Canada

Cameroon


Brazil


Bolivia

Belgium

Belarus Bangladesh

Azerbaijan

Austria

Australia

Armenia

Argentina

Andorra

Algeria

Albania

Afghanistan

BCG +



Days from 5th death to April 6 (-30)

Days from 5th death to April 6 (-30)Log (Total deaths or sum of deaths 30th days from 5th death)

Log (Total deaths or sum of deaths 30th days from 5th death)

A

B

Fig. 2. Bivariate plots of Days from fifth Death to April 6 or 30 (as an index of the time from the entry of the pandemic to the

nation/the time until the number of deaths has flattened) vs. Log (Total deaths or sum of deaths at 30 days after the fifth death, i.e.

the number of deaths during the time X axis). Most nations showed exponential growth in the number. However, some nations

plotted lower than the other nations.

302520151050

4.5

4.0

3.5

3.0

2.5

2.0

1.5

1.0

South Asia

Africa

America


Europe

Middle EastPacific

SE Asia

Venezuela

USUnited Kingdom

Channel Islands


Ukraine

Turkey

Tunisia

Trinidad and Tobago

Thailand

Switzerland

Sweden

Spain

South Africa

Slovenia

Singapore

Serbia


Russia

Romania

Portugal

Poland

Philippines

Peru

PanamaPakistan

Norway

North Macedonia

Niger

Netherlands

Morocco

Moldova

Mexico

Mauritius

Malaysia

Luxembourg

LithuaniaLebanon

South Korea

Kazakhstan

Japan

Italy

Israel

Ireland

Iraq

Iran

Indonesia

India

Hungary

Honduras

Greece

Germany

France

Guadeloupe

Finland

Estonia

Egypt

Ecuador

Dominican Republic

Denmark

Czech

CyprusCuba


Colombia

China

Chile

Canada

Cameroon


Brazil


Bolivia

Belgium

Belarus Bangladesh

Azerbaijan

Austria

Australia

Armenia

Argentina

Andorra

Algeria

Albania

Afghanistan




100000100001000100

2020/04/01

2020/03/01

2020/02/01

Venezuela

US

Uruguay

United Kingdom


Ukraine

Turkey

TunisiaThailand

Switzerland

Sweden

Spain

Slovenia

Singapore

Saudi Arabia

San Marino

Russia

Romania

PortugalPoland

Philippines

PeruPanama

Norway

North Macedonia

Niger

Netherlands

Morocco

Moldova

Mexico

Mauritius

MalaysiaLuxembourg

Lithuania

Lebanon

Korea, South

Kenya Jordan

Japan

Italy

Israel

Ireland

Iran

Indonesia

IndiaHungary

Greece

Germany

France

Finland

Estonia

Egypt

Ecuador

Dominican Republic

Denmark

Czechia

CubaCroatia

Colombia

China

Chile

Canada


Brazil

Bosnia and HerzegovinaBolivia

Belgium

Belarus

Bangladesh

Azerbaijan

AustriaAustralia

Armenia

Argentina

Andorra

Algeria

Albania

BCG +



Date 5th Death

International tourist arrivals 2017

Date 5th Death

International tourist arrivals 2017

A

B

Fig. 3. Bivariate plots of international tourist arrivals in 2017 vs. Date fifth Death. Pandemic propagation may be affected by tourist

arrivals.

100000100001000100

2020/04/01

2020/03/01

2020/02/01

South Asia

Africa

America


Europe

Middle EastPacific

SE Asia

Venezuela

US

Uruguay

United Kingdom


Ukraine

Turkey

TunisiaThailand

Switzerland

Sweden

Spain

Slovenia

Singapore

Saudi Arabia

San Marino

Russia

Romania

PortugalPoland

Philippines

PeruPanama

Norway

North Macedonia

Niger

Netherlands

Morocco

Moldova

Mexico

Mauritius

MalaysiaLuxembourg

Lithuania

Lebanon

South Korea

Kenya Jordan

Japan

Italy

Israel

Ireland

Iran

Indonesia

IndiaHungary

Greece

Germany

France

Finland

Estonia

Egypt

Ecuador

Dominican Republic

Denmark

Czech

CubaCroatia

Colombia

China

Chile

Canada


Brazil

Bosnia and HerzegovinaBolivia

Belgium

Belarus

Bangladesh

Azerbaijan

AustriaAustralia

Armenia

Argentina

Andorra

Algeria

Albania




302520151050

4.5

4.0

3.5

3.0

2.5

2.0

1.5

1.0

United Kingdom

Ukraine

TurkeySwitzerland

Sweden

Spain

Slovenia San Marino

Russia

Romania

Portugal

Poland

Norway

North Macedonia

Netherlands

Moldova

Luxembourg

Lithuania

Italy

Ireland

Hungary

Greece

Germany

France

Finland

Estonia

Denmark

Czechia

Croatia

BulgariaBosnia and Herzegovina

Belgium

Belarus

Azerbaijan

Austria

Armenia

Andorra Albania

2020

/04/

07

2020

/04/

01

2020

/03/

25

2020

/03/

19

2020

/03/

13

2020

/03/

07

2020

/03/

01

2020

/02/

25

4.5

4.0

3.5

3.0

2.5

2.0

1.5

1.0

United Kingdom

Ukraine

TurkeySwitzerland

Sweden

Spain

SloveniaSan Marino

Russia

Romania

Portugal

Poland

Norway

North Macedonia

Netherlands

Moldova

Luxembourg

Lithuania

Italy

Ireland

Hungary

Greece

Germany

France

Finland

Estonia

Denmark

Czechia

Croatia

BulgariaBosnia and Herzegovina

Belgium

Belarus

Azerbaijan

Austria

Armenia

AndorraAlbania

BCG +




Days from 5th death to April 6 (-30)

Date 5th Death

Log (Total deaths or sum of deaths 30th days from 5th death)

A

B

Number of total deathsmay reflect the route of propagation

Fig. 4. Bivariate plots using only European nations. The plots clearly show that high number of deaths are affected by when the

pandemic enter the nation. The pandemic explosion occurred in Western Europe where BCG – nations are located, and then spread

to the peripheral of Europe where BCG + nations are located.




400003000020000100000

10

8

6

4

2

0

BCG +



VietnamFijiChadBhutan

Benin

Costa RicaBarbados

Bahrain

UgandaSeychellesNamibiaMadagascar

ZimbabweZambiaTanzaniaGambia

SudanSenegalEthiopiaAngola

Togo

GhanaCongo (Brazzaville)

Kenya

Mauritius

Niger

Saint Vincent and the Grenadines

NicaraguaHaiti

JamaicaGuatemala

GuyanaEl Salvador

Paraguay

Uruguay

Venezuela

Cuba

Uzbekistan

Mongolia

Hong Kong

Taiwan

Oman

Qatar

Jordan

Papua New Guinea

New Zealand

VietnamCambodia

Singapore

NepalMaldives

Sri Lanka

400003000020000100000

200

150

100

50

0VietnamFijiChadBhutanBenin

Costa R icaBarbadosBahrain

UgandaSeychellesNamibiaMadagascar ZimbabweZambiaTanzaniaGambiaSudanSenegalEthiopiaAngola

TogoGhanaCongo (Brazzaville)

KenyaMauritiusNiger

Burkina Faso

Tunisia

Morocco

Egypt

A lgeria

Saint V incent and the GrenadinesNicaraguaHaitiJamaicaGuatemalaGuyanaEl Salvador

ParaguayUruguayVenezuela

CubaBolivia

Chile

ColombiaArgentina

Panama

Dominican Republic

PeruMexico

Ecuador

UzbekistanMongolia

Hong KongTaiwan

Japan

Korea, South

OmanQatar

Jordan


Lebanon

Saudi Arabia

Israel

Papua New Guinea New Zealand

Australia

V ietnamCambodia

Singapore

Thailand

Malaysia

Philippines

NepalMaldives

Sri Lanka

Bangladesh

India

Total death to April 6

Total death to April 6

International tourist arrivals 2017 (1000)

Fig. 5. Bivariate plots of International tourist arrivals in 2017 vs. Total deaths up to April 6 using non-European nations with total

deaths less than 200. Most nations are BCG +, but some BCG - nations seem to succeed in suppressing COVID-19. Most

non-European nations are BCG + and are located where COVID-19 has not yet entered at full scale. This fact would flaw the results

of previous studies.




1.6

1.5

1.4

1.3

1.2

1.1

Region

1.6

1.5

1.4

1.3

1.2

1.1

+ (Japanese strain)

-- (past +)

+

1.6

1.5

1.4

1.3

1.2

1.1

-- (past +)

+

Nations where deaths are more than 25

Maximum increase rate per day (two week average)

BCG policy

BCG policy (Japanese strain separated)

No significant difference (P = 0.128)

No significant difference (P = 0.055)

Weakly significant difference (P = 0.037)

South AsiaSE AsiaPacificMiddle EastEuropeEast AsiaAmericaAfrica

(P = 0.043)

Fig. 6. Box plots of maximum increase rate per day (two week average). Nations where deaths are more than 100 and 25 were

separately illustrated. Boxes indicate quartiles, central-lateral bars indicate medians, vertical bars indicate the range of the

specimens, and asterisks indicate outliers. The increase rate seems to higher in BCG – nations. However, only one pair was weakly

statistically significant, but most are not (ANOVA/ Tukey’ s test).

N = 33

N = 18 N = 4

N = 27N = 18 N = 4

N = 6




0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

2020

/1/2

220

20/1

/23

2020

/1/2

420

20/1

/25

2020

/1/2

620

20/1

/27

2020

/1/2

820

20/1

/29

2020

/1/3

020

20/1

/31

2020

/2/1

2020

/2/2

2020

/2/3

2020

/2/4

2020

/2/5

2020

/2/6

2020

/2/7

2020

/2/8

2020

/2/9

2020

/2/1

020

20/2

/11

2020

/2/1

220

20/2

/13

2020

/2/1

420

20/2

/15

2020

/2/1

620

20/2

/17

2020

/2/1

820

20/2

/19

2020

/2/2

020

20/2

/21

2020

/2/2

220

20/2

/23

2020

/2/2

420

20/2

/25

2020

/2/2

620

20/2

/27

2020

/2/2

820

20/2

/29

2020

/3/1

2020

/3/2

2020

/3/3

2020

/3/4

2020

/3/5

2 020

/3/6

2020

/3/7

2020

/3/8

2020

/3/9

2020

/3/1

020

20/3

/11

2020

/3/1

220

20/3

/13

2020

/3/1

420

20/3

/15

2020

/3/1

620

20/3

/17

2020

/3/1

820

20/3

/19

2020

/3/2

020

20/3

/21

2020

/3/2

220

20/3

/23

2020

/3/2

420

20/3

/25

2020

/3/2

620

20/3

/27

2020

/3/2

820

20/3

/29

2020

/3/3

020

20/3

/31

2020

/4/1

2020

/4/2

2020

/4/3

2020

/4/4

2020

/4/5

Italy

Spain

US

France

United Kingdom

Iran

China

Netherlands

Germany

Belgium

Switzerland

Turkey

Brazil

Sweden

Portugal

Canada

Austria

Indonesia

Korea, South

Ecuador

Denmark

Ireland

Algeria

Philippines

Romania

India

Poland

Peru

Dominican Republic

Mexico

Egypt

Japan

Greece

Norway

Morocco

Czechia

Iraq

Malaysia

Serbia

Log (Cumulative Deaths)

Date

BCG -

BCG - (previously +)

BCG +

BCG + (Japanese strain)

Fig. 7. Cumulative deaths of nations in which total deaths over 25. Although the increase rate in Iraq, Korea, and Japan seem to low, at the beginning of the increase, the rate is not particularly

low. Malaysia which uses Japanese strain shows a similar pattern to the other nations.




Toll-likereceptor

Epitopes

Specific domain of the Japanese strain

No homologous amino acid sequences

High affinity?

SARS-CoV-2

A protein of BCG

ACE2

Polymorphism?

Difference of ACE2 expression in salivary gland?

Polymorphism of salivaor oral morphology?

Difference in susceptibility?

Culture, national politicy etc.

Rhinolophus bat distribution

Paguma larveta distribution

Geographic variation inratio of the variant?

Epidemic?

Cross-national difference in morbidity and mortality of COVID-19

BCG vaccination?

Malaria mosquito distribution

Fig. 8. Schematic illustration of how cross-national statistical analysis ( “ecological study” ) can be influenced. Many factors

influence the results. The author’ s idea of the remaining possibility of BCG vaccination is also illustrated. The map is modified

based on the map provided by the Geospatial Information Authority of Japan. https://maps.gsi.go.jp/development/ichiran.html



japan contact: kamono.mana@ gmail.c om · 4/17/2020 · d ph. ara, h zu asa a masak 1 1, 5 9 1 0-0...

Documents