medRxiv preprint doi: https://doi.org/10.1101/2020.04.07.20056994; this version posted April 10, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . Further Evidence of a Possible Correlation Between the Severity of Covid-19 and BCG Immunization Serge Dolgikh1[0000-0001-5929-8954] Abstract. In this work we observe a number of cases supporting the possible correlation between the administration of BCG tuberculosis vaccine and the se- verity of Covid-19 effects in the population proposed in the earlier works [1]. Based on the early preliminary analysis of the publicly available data we propose a number of arguments and observations providing further support for the corre- lation hypothesis and make an observation that the effectiveness of the protection effect of BCG immunization, if confirmed, may depend to a significant extent on the age of administration, with the early age inoculation more effective for the lasting protection. Keywords: Infectious epidemiology, Covid-19 1 Introduction 1.1 Purpose A significant variation in the patterns of onset of Covid-19 epidemics across jurisdic- tions has been noticed previously. Quite pronounced is the difference between the “av- alanche” scenario seen in Italy, Spain, France and USA on one hand, and the “mild” one (Taiwan, Germany, many East European jurisdictions and others) on the other. While multiple factors certainly play role in these variations, some can be more influ- ential on the overall dynamics of the impacts of the epidemics. A possible link between the effects of Covid-19 pandemics such as the rate of spread and the severity of cases; and a universal immunization program against tuberculosis with BCG vaccine (UIP, hereinafter) was suggested in [1]. In this work we provide several additional arguments supporting the case for such correlation based on the avail- able data in the public domain. Further analysis of statistical data is needed to achieve a confident conclusion. Based on the preliminary analysis of the data we make an important observation that the effectiveness of the protection provided by BCG vaccination against Covid-19 may extend more or substantially more to the cases where it is provided at birth or young age. NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. medRxiv preprint doi: https://doi.org/10.1101/2020.04.07.20056994; this version posted April 10, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . 2 2 Data 2.1 Terminology Time aspect is critically important in this analysis. We propose to define the beginning moment of the developments related to Covid-19 globally as the date of the first official release of information about Covid-19 on the 31.12.2019 [2], though the first cases of the epidemics including the zero event of possible animal to human crossover almost certainly happened earlier. 푇푍 = 31.12.2019 Along with the global Time Zero we also suggest to define the local Time Zero (LTZ) indicating the time of arrival of the epidemics in the given locality. It can be sensibly defined as the date of the first confirmed case in the area. Two common measures of the epidemics impact on the human population used throughout: Cases per capita (c.p.c.) and Mortality per capita (m.p.c): 푐. 푝. 푐 = 푇표푡푎푙 푐푎푠푒푠 / 푇표푡푎푙 푝표푝푢푙푎푡표푛 (푚푙푙표푛푠) 푚. 푝. 푐 = 푇표푡푎푙 푙푒푡ℎ푎푙 푐푎푠푒푠 / 푇표푡푎푙 푝표푝푢푙푎푡표푛 (푚푙푙표푛푠) Note that the former measure strongly depends on the methods and policies in the re- porting jurisdiction such as testing strategy, verification of reported cases and so on. Also, it’s not always possible to verify the difference between suspected or reported cases, and those that were later confirmed as Covid-19. For that reason, we suggest it to be used as a trend indicative parameter and more often used m.p.c. as the current and more accurate measure of the epidemics impact, on the assumption that policies and protocols in the selected administration allow more accurate identification of cause and reporting. 2.2 Case Data Here we attempted to collect data from a number of jurisdictions as an input to the analysis of the significance of the correlation hypothesis. A comprehensive statistical study to this effect should be undertaken, for which the presented data can provide a convincing rationale, but hardly a replacement. Vaccination level is measured in the following bands as defined in [3]: A: has universal or near-universal BCG coverage B: had BCG vaccination in the past covering significant part of population (> 50%) B2: never had a universal program, but some coverage (e.g. regional, specific groups) C: never had a UIP/BCG We define three groups of countries, by the reported impact of Covid-19 on the popu- lation: Very Low (VL), m.p.c. < 1 or near Low (L): 2 < m.p.c. < 10 or near High (H): m.p.c. near or greater than 100 medRxiv preprint doi: https://doi.org/10.1101/2020.04.07.20056994; this version posted April 10, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . 3 The data was not selected to fit the hypothesis. Rather, several common sense criteria were applied such as: certain expectation of reliability and consistency of the reporting jurisdiction; a reasonable level of exposure to Covid-19 e.g. certain minimum number of reported cases; geographical and development level variation; and the well-known cases that already received attention. A comprehensive and more formal statistical anal- ysis will be the subject of a future study. Cautions: 1. Consistency and reliability of data reported by the national, regional and local health administrations. 2. Alignment in time of beginning of epidemics: the situation is developing quickly and the phases of epidemics development may not be aligned. 3. Alignment in the time of reporting may be an issue due to reporting practices of jurisdictions. 4. Especially the availability, consistency and reliability of historical data and statistics on the administration of immunization programs in the national, regional and so on, jurisdictions can be an issue. Table 1 Covid-19 Impacts by Jurisdiction (updated 07.04.2020) Case Popula- Start (1) Cases, Mort., Cases, Mort., BCG tion (M) tot tot cap cap level VLow Slovakia 5.5 06.03 534 2 85.2 0.37 A Taiwan 23.8 21.01 373 5 15.04 0.21 A Japan 126.8 16.01 3664 73 23.3 0.58 A Ukraine 42.2 29.02 1467 46 29.0 1.10 A Kyiv 3.8 16.03 267 4 64.5 1.05 A Singapore 5.6 23.01 1375 6 208.5 1.10 A Low Chile 18.1 03.03 4815 37 252 2.0 A Australia 24.6 25.01 5899 48 216.2 1.95 B South Ko- 51.5 20.01 10331 192 196.1 3.7 A rea Moldova 3.6 07.03 965 19 280.4 5.3 A Ukraine, 2.1 03.03 380 8 162.4 3.8 A west (2) Israel 8.7 21.02 8904 57 826.7 6.6 B Poland 38.0 04.03 4413 107 2.8 A Czechia 10.7 01.03 4362 78 407.9 7.3 A Croatia 4.1 25.02 1222 16 299 3.9 Albania 2.9 08.03 377 21 117 7.2 A Greece 10.5 28.02 1755 79 167.1 7.5 A Jordan 10.1 02.03 349 6 32.8 0.59 Finland 5.5 29.01 1875 47 407.6 4.6 B Canada 37.6 25.01 16663 323 369.8 8.6 B2 Prairies 2.6 12.03 425 5 163.5 1.92 B2(4) (Can) (3) medRxiv preprint doi: https://doi.org/10.1101/2020.04.07.20056994; this version posted April 10, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . 4 Ontario 14.6 25.01 4347 132 248.6 9.0 B2(4) (Can) Quebec 8.5 28.02 8580 121 823.2 14.2 B2(4,5) (Can) Argentina 45.2 03.03 1554 46 1.0 A Mid Norway 5.4 26.02 5551 77 1028.0 14.3 B Denmark 5.6 27.02 4681 187 85.2 33.4 B Sweden 10.1 31.01 6558 506 654.6 50.1 B Austria 8.8 25.02 12297 220 25 B Germany 82.8 27.01 103375 1810 1113 21.9 B Portugal 10.3 02.03 11730 311 1024 30.2 A Ireland 4.9 29.02 5364 174 35.5 A High Italy 60.5 31.01 124632 16523 2069 273.1 C Spain (5) 46.7 31.01 124736 11814 2648 253.0 B2 UK (6) 66.4 29.01 51608 5373 630.7 80.9 B Nether- 17.2 27.02 18803 1867 952.8 108.5 C lands Belgium 11.4 18431 1632 1600 143.1 C France (6,7) 67.0 24.01 74390 8911 959.2 133.0 B New York 8.6 01.03 60850 2254 7075.6 262.1 C Other USA 327.2 21.01 367461 10910 909.9 33.3 C 1 The first confirmed case of Covid-19, LTZ (2) Ternopilska, Chernovitska regions (oblast) (3) Manitoba, Saskatchewan provinces (4) Used in targeted communities with higher incidence (5) Limited age cohort (Quebec: 19 years, Spain: 16 years) (6) Immunization started at later age (not at birth) (7) Contradictory data on immunization practice (at birth or later age).