Tuberculosis and COVID-19: Lessons from the Past Viral Outbreaks and Possible Future Outcomes.

Radu Crisan-Dabija,Cristina-Alice Pavel,Andrei Cernomaz,Cristina Grigorescu,Alexandru Burlacu,Bogdan Artene,Iolanda Valentina Popa

doi:10.1155/2020/1401053

Radu Crisan-Dabija, Cristina-Alice Pavel + Show 5 more

Open Access

https://doi.org/10.1155/2020/1401053

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Abstract

Background The threat of contagious infectious diseases is constantly evolving as demographic explosion, travel globalization, and changes in human lifestyle increase the risk of spreading pathogens, leading to accelerated changes in disease landscape. Of particular interest is the aftermath of superimposing viral epidemics (especially SARS-CoV-2) over long-standing diseases, such as tuberculosis (TB), which remains a significant disease for public health worldwide and especially in emerging economies. Methods and Results The PubMed electronic database was systematically searched for relevant articles linking TB, influenza, and SARS-CoV viruses and subsequently assessed eligibility according to inclusion criteria. Using a data mining approach, we also queried the COVID-19 Open Research Dataset (CORD-19). We aimed to answer the following questions: What can be learned from other coronavirus outbreaks (focusing on TB patients)? Is coinfection (TB and SARS-CoV-2) more severe? Is there a vaccine for SARS-CoV-2? How does the TB vaccine affect COVID-19? How does one diagnosis affect the other? Discussions. Few essential elements about TB and SARS-CoV coinfections were discussed. First, lessons from past outbreaks (other coronaviruses) and influenza pandemic/seasonal outbreaks have taught the importance of infection control to avoid the severe impact on TB patients. Second, although challenging due to data scarcity, investigating the pathological pathways linking TB and SARS-CoV-2 leads to the idea that their coexistence might yield a more severe clinical evolution. Finally, we addressed the issues of vaccination and diagnostic reliability in the context of coinfection. Conclusions Because viral respiratory infections and TB impede the host's immune responses, it can be assumed that their lethal synergism may contribute to more severe clinical evolution. Despite the rapidly growing number of cases, the data needed to predict the impact of the COVID-19 pandemic on patients with latent TB and TB sequelae still lies ahead. The trial is registered with NCT04327206, NCT01829490, and NCT04121494.

Highlights

ObjectivesIndividuals with chronic respiratory infections, including TB, are first to experience the adverse effects of a pneumotropic pandemic, especially in the healthcare setting [11, 12]
Despite the rapidly growing number of cases, the data needed to predict the impact of the COVID-19 pandemic on patients with latent TB and TB sequelae still lies ahead. e trial is registered with NCT04327206, NCT01829490, and NCT04121494
Articles of interest were retrieved by administering the query “COVID” OR “COVID-19” OR “2019-nCoV” OR “severe acute respiratory syndrome (SARS)-CoV-2” OR “Novel coronavirus” OR “Tuberculosis” OR “Mycobacterium tuberculosis” OR “Flu” OR “Influenza” OR “Coinfection” OR “Vaccine” OR “Immunization.” Data mining was further applied to select only articles that met our topics of interest about coinfections between particular pathogens stated earlier and COVID-19 developing vaccines. e study selection process and number of papers identified in each phase are illustrated in the flowchart (Figure 1)

Summary

Objectives

Individuals with chronic respiratory infections, including TB, are first to experience the adverse effects of a pneumotropic pandemic, especially in the healthcare setting [11, 12]. In order to identify emerging coinfection particularities of novel coronavirus SARS-CoV-1, we queried the COVID19 Open Research Dataset (CORD-19), the current largest open dataset available with over 47000 scholarly articles, including over 36000 with full text about COVID-19, SARSCoV-2, and other coronaviruses. Articles of interest were retrieved by administering the query “COVID” OR “COVID-19” OR “2019-nCoV” OR “SARS-CoV-2” OR “Novel coronavirus” OR “Tuberculosis” OR “Mycobacterium tuberculosis” OR “Flu” OR “Influenza” OR “Coinfection” OR “Vaccine” OR “Immunization.” Data mining was further applied to select only articles that met our topics of interest about coinfections between particular pathogens stated earlier and COVID-19 developing vaccines. Articles of interest were retrieved by administering the query “COVID” OR “COVID-19” OR “2019-nCoV” OR “SARS-CoV-2” OR “Novel coronavirus” OR “Tuberculosis” OR “Mycobacterium tuberculosis” OR “Flu” OR “Influenza” OR “Coinfection” OR “Vaccine” OR “Immunization.” Data mining was further applied to select only articles that met our topics of interest about coinfections between particular pathogens stated earlier and COVID-19 developing vaccines. e study selection process and number of papers identified in each phase are illustrated in the flowchart (Figure 1)

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Disclosure