Research Article

Lower Incidences and Deaths Due to COVID-19 in Countries with high Deaths Due to Tuberculosis and Flu: a 2021-2022 Update

Sanmoy Pathak, Dipankar Nandi*

Department of Biochemistry, Indian Institute of Science, Bangalore-560012, India

*Corresponding author: Dipankar Nandi, Department of Biochemistry, New Biological Sciences, Indian   Institute of Science, Bangalore-560012, India

Received Date: 22 June, 2023

Accepted Date: 26 June, 2023

Published Date: 28 June, 2023

Citation: Pathak S, Nandi D (2023) Lower Incidences and Deaths Due to COVID-19 in Countries with high Deaths Due to Tuberculosis and Flu: a 2021-2022 Update. J Vaccines Immunol 8: 196. https://doi.org/10.29011/2575-789X.000196

Abstract

Heterogeneity in number of deaths in various countries due to COVID-19 is likely due to multiple factors. Previously, our laboratory has shown, using 2020 epidemiological data, that countries with high deaths due to tuberculosis and flu display less COVID-19 deaths. Also, countries with high BCG but low flu vaccinations display less COVID-19 deaths. It was important to address whether this trend held as the pandemic progressed in 2021-2022 given the rise of SARS-CoV2 variants and COVID-19 vaccinations. In this study, countries with more than 10,000 COVID-19 deaths were selected at four time points and the data was analysed. COVID-19 incidences/million and deaths/million were obtained from various data bases and correlation analysis was performed with tuberculosis deaths, flu deaths, BCG and flu vaccination coverages. The main findings are: First, countries with high tuberculosis deaths show negative correlation with COVID-19 incidences and deaths. This pattern is also true for countries with high BCG vaccinations. Second, countries with high flu deaths display less COVID-19 incidences and deaths. Concomitantly, countries with high flu vaccinations show higher COVID-19 incidences and deaths. Third, countries with high deaths due to tuberculosis and flu display lower COVID-19 incidences and deaths. Finally, countries with high BCG coverage and tuberculosis deaths (e.g. Bangladesh, India, Indonesia, etc) display lower COVID-19 incidences and deaths, compared to countries with high BCG coverage but low tuberculosis deaths (e.g. Brazil, Mexico, Russia etc), demonstrating roles for both. This global study reveals a complex interplay of the roles of other respiratory pathogens in limiting COVID-19.

Keywords: BCG; COVID-19; Flu; Tuberculosis; Vaccinations

Introduction

COVID-19 is a disease that is caused by SARS-COV2, a single stranded positive RNA virus. It is responsible for the recent pandemic leading to widespread deaths and disruption in lives and economies of nations. SARS-CoV2 infects the respiratory tract causing mild symptoms or, in severe cases, causes damage to the lungs [1]. The SARS family of viruses have a similar mechanism of entry in host cells using multiple mechanisms. The spike glycoprotein present in the virus plays important roles and interacts with the receptor angiotensin converting enzyme (ACE)2 on host cells. In addition, several other viral as well as host proteins such as cellular transmembrane proteases (e.g TMPRSS2), furin proteases etc are involved in aiding the replication of SARS-CoV2 viral particles [2]. A better understating of the viral replication cycle will be the key to the development of inhibitors some of which are likely to act as drugs.

The economic damage and loss of lives due to COVID-19 has been immense with official world- wide deaths in the range of 1.88 million in 2020, 3.58 million in 2021 and 1.22 million in 2022.  Mortality due to COVID-19 is variable across different countries and there may be several reasons for this heterogeneity: population age, sex, temperature, cultural norms such as the use of masks, better health care infrastructure, comorbidities such as hypertension, obesity, etc [3-5]. Recent studies have demonstrated the critical roles of host derived autoimmune antibodies to Interferons, polymorphisms in Toll-like receptors in protection against SARS-CoV2 infections [6]. Additionally, prior exposure to infectious pathogens may boost cross-reactive immunity to pathogens. For example, H. pylori infections may lower tuberculosis incidences [7]. Also, pre-existing infections with HIV or tuberculosis can also lead to COVID-19 severity [8]. On the other hand, malaria incidences are known to lower COVID-19 [9]. It is well known that previous exposure to family members of coronaviruses that cause common cold leads to better T cell immunity against SARS-Cov2 [10]. Another important aspect is vaccinations, which are an established public safety shield as well as a highly cost-effective strategy. They are a key factor in enhancing immunity against a vast number of pathogens, especially in protecting children [11,12]. Interestingly, immunizations with oral polio vaccine, measles vaccine, hepatitis vaccine [13-15] are known to reduce COVID-19 cases and these are likely due to boost non-specific immunity, resulting in heterologous protection.

The vast differences in the number of COVID-19 deaths in various countries led us to investigate the correlation between COVID-19 incidences or deaths with the prevalence of various diseases using data available in the public domain. Previously, we had shown that countries with high amounts of deaths due to flu or tuberculosis display less COVID-19 deaths in 2020 [16]. Also, countries with high amounts of flu vaccination led to higher COVID-19 deaths. On the other hand, countries with high BCG vaccine coverage led to lower COVID-19 deaths [16]. An important question to address is whether this trend was observed as the pandemic spread in 2021 and 2022. This aspect is important as there was a rise in variants as well as an increase in vaccinations. We find that the trends observed initially in 2020 are sustained and even better now in 2021-2022 as COVID-19 incidences as well as deaths correlate well with time. The implications of our findings are discussed in detail in this study.

Methods

Study design

Countries with more than 10,000 COVID-19 deaths were selected at four time points and the data was analysed: 24th May 2021, 31st December 2021, 14th April 2022 and 31st December 2022.

Selection of Samples

A set of 62 countries were selected on the criteria of deaths that are more than 10,000 by 14th April 2022 (Figure 1). These countries were arranged and tables were constructed where COVID-19 incidences/million and deaths/million were obtained from: https://www.worldometers.info/coronavirus/ and https:// ourworldindata.org/coronavirus#explore-the-global-situation. These factors were initially correlated with pathogen exposure. TB deaths/100,000 and Flu deaths/100,000 and this data was obtained from: https://www.worldlifeexpectancy.com/worldhealth-rankings. Next, correlation analysis was performed with different vaccination programs. BCG coverage for different countries were obtained from http://www.bcgatlas.org/. BCG Atlas uses three distinct methods of obtaining data: First, it uses a questionnaire method which is sent to at least two individuals in each country based on their expertise on TB research, TB control programs and public health/vaccination programs. It includes data regarding any changes that have occurred in the last 25 years. It also includes criteria such as tuberculin skin testing, effect of HIV and different vaccine strains playing a role in affecting extent of TB infection. Secondly, case reports, published papers and policy documents from the government are also included as a part of the overall database. Finally, it uses the immunization data from the World Health Organization Vaccine Preventable Diseases Monitoring System as mentioned in http://apps.who. int/immunization_monitoring/en/globalsummary/ScheduleSelect. cfm [17]. Flu vaccination coverage data was obtained from various sources: https://www.statista.com/chart/16575/global-fluimmunization-rates-vary/, https://www.oecd.org/health/graph-ofthe-month.htm and published manuscripts [18-20]. The COVID-19 vaccination coverage in each country was extracted from: https:// ourworldindata.org/covid-vaccinations. These factors were compared to COVID-19 deaths/million and incidences/million at the four time points.

COVID variant kinetics data was obtained from: https:// covariants.org/variants which helped to confirm the dominant COVID-19 strains responsible for infection and deaths in each country at mentioned time points. The early 2020 time points suggested that a dominant strain wasn’t identified and was therefore labelled as “others” (Table 1).


Table 1: Dominant COVID-19 variants in countries with high COVID-19 deaths from 17th May 2020-31st December 2022.

Statistical Analysis

Correlation analysis was performed by using Spearman’s correlation analysis and the Spearman’s correlation coefficient (Rs) and p values were calculated using a Spearman’s correlation calculator: https://www.socscistatistics.com/tests/spearman/default2.aspx. Correlation was considered significant if p<0.1. Bar graphs were constructed for countries grouped either by using extent of TB and Flu deaths or using BCG and Flu vaccination coverages. Statistical analysis was done using One way ANOVA to calculate the statistical significance. Statistical analysis was considered significant if p<0.1.

Results

To perform the epidemiological study, a subset of 62 countries were selected based on the criteria in which the total deaths due to COVID-19 were greater than 10000 by 14th April 2022. To evaluate changes with time, the cluster of countries were arranged on the basis of four distinct time points (Table 2-5): 24th May 2021, 31st December 2021, 14th April 2022 and 31st December 2022 and compared to four conditions (Figure 1): Flu deaths/100,000, TB deaths/100,000, Flu vaccination coverage and BCG coverage.


Figure 1: Flow chart describing the methodology used to perform the mentioned epidemiological study.


Table 2: List of countries with COVID-19 deaths/million and COVID-19 incidences/million, BCG, Flu Vac coverage, TB and Flu deaths/100,000 on 24th May 2021.