BCG vaccination and COVID-19: Was flattening the curve just an illusion?

Dear Sir,

During the early stages of the ongoing SARS-CoV-2 pandemic, some reports hinted at a “protective” effect of BCG vaccination regarding COVID-19, mainly in terms of avoided mortality [1], [2]. As a result, BCG vaccination emerged as being possibly instrumental in “flattening” the curves of the pandemic.

However, in a previous systematic review, we suggested that initial reports may have been “distorted” by the diachronous nature of the pandemic, of which the early stages strongly depended on the spreading of single outbreaks, which in turn were the eventual consequence of separate, even serendipitous events [3]. While Europe is faced with a sustained resurgence of SARS-CoV-2 infection, it is reasonable to surmise that initial differences may have been leveled out, allowing more consistent comparison between various countries, particularly when dealing with ecological factors such as BCG vaccination rates.

Therefore, with the aim of assessing the actual effect of BCG vaccination rates on SARS-CoV-2 incidence rates and mortality, we retrieved official data on 47 European Countries from the ECDC “COVID-19 situation update for the EU/EEA” (http://ecdc.europa.eu/en/cases-2019-ncov-eueea) in the 01/03/2020–14/12/2020 timeframe. Available data included daily notification rates on new COVID-19 cases and deaths. Respective 7-day moving average for notification of incident cases and 14-day moving average for death cases were calculated accordingly. As BCG vaccination policies across European countries have been and remain quite heterogeneous [4], we utilized 12th month vaccination coverage 1980–2019 from WHO/UNICEF (https://apps.who.int/immunization_monitoring/globalsummary/timeseries/tswucoveragebcg.html) as a proxy, which was then codified as dummy variable: 0 for countries without any previous vaccination policy or discontinuing mass vaccination before 1990; 1 for BCG vaccination rates ≤ 80%, 2 for rates 80% to 89.9%, 3 for rates 90 to 94.9%, 4 for rates ≥ 95%. Eventual estimates were then included as outcome variables of two distinctive regression models that were assumed as explanatory variables: BCG rate, population density, share of the general population aged 60 years or older, and two synthetic indices represented by the Gini coefficient and the Human Development Index (HDI) [5]. The aforementioned factors were retrieved from the Eurostat database (https://ec.europa.eu/eurostat/). Gini Coefficient is a measure of statistical dispersion designed to represent income inequality or wealth inequality within a nation. HDI is a composite statistical index of life expectancy, education, and per capita income. A summary of raw data is reported in Appendix 1.

Notification rates were not correlated with BCG rates or economic and demographic indices, nor, as shown in Table 1 , was BCG rate an effective predictor for either incident cases (Beta 0.074; 95%CI −1.364 to 1512, P  = 0.918) or death cases (Beta −0.016; 95%CI −0.046 to 0.013 P  = 0.271).

Table 1

Effects of Bacillus Calmette-Guerin (BCG) vaccination rate, and demographic factors such as the share of the general population aged 60 years or more, population density, Human Development Index (HDI) and Gini Index on the notification rates of incident and death cases in European countries. The changes in the outcome variables for every 1-unit of change in the predictor variables were reported as beta coefficients with their corresponding 95% confidence intervals (95%CI).

Variable	Notification rate of incident cases(7-day moving average; N#/100,000)				Notification rate of death cases(14-day moving average; N#/100,000)
	R2	Beta	95%CI	P value	R2	Beta	95%CI	P value
BCG vaccination rate1	0.001	0.074	−1.364 to 1512	0.918	0.004	−0.016	−0.046 to 0.013	0.271
Population ≥ 60 yrs (%)	0.002	0.094	−0.279 to 0.467	0.613	0.006	0.006	−0.004 to 0.017	0.205
Population density (inhabitants/km2)	0.007	0.002	−0.005 to 0.009	0.602	0.041	0.002	−0.001 to 0.001	0.693
HDI	0.002	−5.807	−50.557 to 38.943	0.062	0.011	−0.601	−1.523 to 0.322	0.196
Gini Index	0.009	0.094	−0.279 to 0.467	0.796	0.074	0.003	−0.005 to 0.010	0.490

1 = In order to take into account heterogenous reporting and inconsistent BCG vaccination policies, BCG vaccination rate was modelled as a dummy variable (i.e. 0 for countries without any previous vaccination policy or discontinuing mass vaccination rates before 1990; 1 for BCG vaccination rates ≤ 80%, 2 for rates 80% to 89.9%, 3 for rates 90 to 94.9%, 4 for rates ≥ 95%).

Our estimates are affected by significant limits. First, not only are European policies on BCG heterogenous, but also, the reporting of corresponding vaccination rates is often inconsistent [4]. As a result, we were forced to approximate, referring to a proxy rather than to actual vaccination rates. Second, notification rates on COVID-19 are characterized by significant heterogeneities, with resultingly uncertain estimates [6]. Third, different European countries applied mitigation measures that were heterogenous in terms of timing, scope and means [3], [6]. Such factors are essentially qualitative, and decidedly elusive in terms of statistical modelling. Lastly, European countries are highly variable in terms of ethnographic composition; as a result, background genetic factors can hardly be ruled out by means of ecological study [3].

To conclude, our analyses suggest that the effects of BCG on the ongoing dynamics of the SARS-CoV-2 pandemic are very difficult, if not impossible to ascertain. Even though the role of BCG-elicited “trained immunity” (i.e., enhanced reactivity of the innate immune system by means of increased secretion of pro-inflammatory cytokines) in COVID-19 has not been clearly ruled out, there is no evidence that BCG may protect people against SARS-CoV-2 infection [1], [2], [3], and there is no evidence justifying recommendation of BCG vaccination as a means of preventing COVID-19.

Human and animal rights

The authors declare that the work described has not involved experimentation on humans or animals.

Informed consent and patient details

The authors declare that the work described does not involve patients or volunteers.

Disclosure of interest

The authors declare that they have no competing interest.

Funding

This work did not receive any grant from funding agencies in the public, commercial, or not-for-profit sectors.

Author contributions

All authors attest that they meet the current International Committee of Medical Journal Editors (ICMJE) criteria for Authorship.

Country	Total population (2019)	Share of population aged 60 years or older (2019)	Population density (inhabitants/km2)	Sum total of cases	Sum total of Deaths	7-day mobile average for case notification rate per 100,000 inhabitants (01/03/2020–14/12/2020)	14-day mobile average for death notification rate per 100,000 inhabitants (01/03/2020–14/12/2020)	BCG vaccination rates at 12th month of age (%; average 1980–2019)	HDI (2019)	Gini Index (2019)
Albania	2862427	20.40%	98.00	48530	1003	5.57	.11	93.88	.80	33.20
Armenia	2957728	18.10%	101.50	148682	2503	17.09	.28	93.39	.78	34.40
Austria	8858775	25.00%	106.00	320029	4400	12.16	.15	90.00	.92	27.50
Azerbaijan	10047719	11.50%	115.00	175874	1922	5.66	.06	87.18	.76	26.60
Belarus	9452409	22.10%	45.80	160295	1263	5.66	.04	97.82	.82	25.20
Belgium	11455519	25.10%	376.00	607998	17945	18.24	.53	N/A	.92	25.60
Bosnia and Herzegovina	3300998	N/A	69.00	101117	3336	10.30	.31	88.29	.85	29.70
Bulgaria	7000039	28.20%	63.00	179449	5688	8.58	.24	98.05	.82	40.80
Croatia	4076246	27.80%	73.00	175885	7130	13.91	.19	98.07	.85	29.70
Cyprus	875899	21.70%	123.40	15101	78	5.54	.02	N/A	.89	29.10
Czechia	10649800	26.00%	134.00	581079	9609	18.46	.29	97.71	.90	24.00
Denmark	5806081	25.40%	137.65	109756	941	6.01	.05	N/A	.94	27.50
Estonia	1324820	26.10%	29.22	18055	149	4.33	.03	97.37	.89	30.50
Finland	5517919	28.40%	16.00	30809	453	1.84	.03	94.81	.94	26.20
France	67012883	26.20%	116.00	2376795	57909	12.07	.29	81.18	.90	28.50
Georgia	3996762	21.00%	57.60	191063	1839	15.76	.14	86.68	.81	36.40
Germany	83019213	28.20%	232.00	1337021	22011	5.29	.08	N/A	.95	29.70
Greece	10724599	28.30%	82.00	124533	3625	3.90	.10	74.33	.89	31.00
Hungary	9772756	26.40%	105.00	283870	2640	9.57	.21	99.00	.85	28.00
Iceland	356991	19.80%	3.50	5556	28	5.36	.03	N/A	.95	24.10
Ireland	4904240	19.20%	70.80	76185	2124	5.31	.15	68.50	.96	28.90
Italy	60359546	29.20%	201.30	1842824	64499	10.26	.35	N/A	.89	33.40
Kosovo	1798506	12.40%	159.00	46580	1198	10.74	.17	99.00	.74	29.00
Latvia	1919968	27.00%	29.60	25675	349	4.25	.05	96.04	.87	35.20
Liechtenstein	38378	24.50%	237.00	1514	18	13.33	.15	N/A	.93	N/A
Lithuania	2794184	26.50%	43.00	95021	825	10.74	.08	98.04	.88	35.40
Luxembourg	613894	20.70%	242.00	41272	396	22.26	.20	N/A	.92	33.20
Malta	493559	24.90%	1633.00	11101	166	7.63	.11	76.64	.90	28.00
Moldova	4043258	17.20%	86.20	126518	2572	10.48	.21	96.96	.75	26.80
Monaco	33085	N/A	18713.00	668	2	6.87	.02	93.08	N/A	N/A
Montenegro	622182	21.70%	45.00	41426	582	22.28	.30	93.00	.83	37.70
Netherlands	17282163	25.50%	521.00	612744	10034	11.74	.19	N/A	.94	26.60
Northern Macedonia	2077132	20.20%	80.10	73638	2121	11.84	.32	95.22	.77	31.90
Norway	5328212	22.90%	14.20	40016	387	2.56	.02	N/A	.96	24.80
Poland	37972812	24.90%	123.00	1135676	22864	10.04	.18	94.30	.88	28.50
Portugal	10276617	28.30%	114.50	348744	5559	11.32	.17	86.00	.86	31.90
Romania	19414458	25.50%	84.40	556334	13385	9.59	.22	97.21	.83	34.80
Russian Federation	145872260	19.30%	8.40	2653926	46941	6.10	.17	94.89	.82	37.50
Serbia	6963764	27.80%	89.00	266432	2331	12.32	.17	95.68	.81	33.30
Slovakia	5450421	22.80%	111.00	132984	1175	7.89	.17	96.05	.86	20.90
Slovenia	2080908	26.80%	102.00	96314	1459	15.24	.17	97.31	.92	23.90
Spain	46937060	25.30%	94.00	1730540	47624	12.67	.34	N/A	.90	33.00
Sweden	10230185	25.40%	25.00	320087	7514	10.62	.17	17.23	.95	27.60
Switzerland	8544527	24.40%	207.00	372317	5378	14.79	.20	N/A	.96	29.70
Turkey	82003882	13.00%	105.00	995471	16199	3.89	.17	88.21	.82	43.00
Ukraine	43993643	23.40%	73.80	900666	15247	6.76	.17	89.71	.78	26.10
United Kingdom	66647112	24.00%	270.70	1849373	64170	9.30	.32	N/A	.93	33.50