Comorbidity defines asthmatic patients' risk of COVID-19 hospitalization: A global perspective.

BACKGROUND: The global epidemiology of asthma among patients with coronavirus disease 2019 (COVID-19) presents striking geographic differences, defining prevalence zones of high and low co-occurrence of asthma and COVID-19. OBJECTIVE: We aimed to compare asthma prevalence among hospitalized patients with COVID-19 in major global hubs across the world by applying common inclusion criteria and definitions. METHODS: We built a network of 6 academic hospitals in Stanford (Stanford University)/the United States; Frankfurt (Goethe University), Giessen (Justus Liebig University), and Marburg (Philipps University)/Germany; and Moscow (Clinical Hospital 52 in collaboration with Sechenov University)/Russia. We collected clinical and laboratory data for patients hospitalized due to COVID-19. RESULTS: Asthmatic individuals were overrepresented among hospitalized patients with COVID-19 in Stanford and underrepresented in Moscow and Germany as compared with their prevalence among adults in the local community. Asthma prevalence was similar among patients hospitalized in an intensive care unit and patients hospitalized in other than an intensive care unit, which implied that the risk for development of severe COVID-19 was not higher among asthmatic patients. The numbers of males and comorbidities were higher among patients with COVID-19 in the Stanford cohort, and the most frequent comorbidities among these patients with asthma were other chronic inflammatory airway disorders such as chronic obstructive pulmonary disease. CONCLUSION: The observed disparity in COVID-19-associated risk among asthmatic patients across countries and continents is connected to the varying prevalence of underlying comorbidities, particularly chronic obstructive pulmonary disease.

Predicting the Kinetic Coordination of Immune Response Dynamics in SARS-CoV-2 Infection: Implications for Disease Pathogenesis

A calibrated mathematical model of antiviral immune response to SARS-CoV-2 infection is developed. The model considers the innate and antigen-specific responses to SARS-CoV-2 infection. Recently published data sets from human challenge studies with SARS-CoV-2 were used for parameter evaluation. The calibration of the mathematical model of SARS-CoV-2 infection is based on combining the parameter guesses from our earlier study of influenza A virus infection, some recent quantitative models of SARS-CoV-2 infection and clinical data-based parameter estimation of a subset of the model parameters. Hence, the calibrated mathematical model represents a theoretical exploration type of study, i.e., 'in silico patient' with mild-to-moderate severity phenotype, rather than a completely validated quantitative model of COVID-19 with respect to all its state-space variables. Understanding the regulation of multiple intertwined reaction components of the immune system is necessary for linking the kinetics of immune responses with the clinical phenotypes of COVID-19. Consideration of multiple immune reaction components in a single calibrated mathematical model allowed us to address some fundamental issues related to the pathogenesis of COVID-19, i.e., the sensitivity of the peak viral load to the parameters characterizing the antiviral specific response components, the kinetic coordination of the individual innate and adaptive immune responses, and the factors favoring a prolonged viral persistence. The model provides a tool for predicting the infectivity of patients, i.e., the amount of virus which is transmitted via droplets from the person infected with SARS-CoV-2, depending on the time of infection. The thresholds for variations of the innate and adaptive response parameters which lead to a prolonged persistence of SARS-CoV-2 due to the loss of a kinetic response synchrony/coordination between them were identified.

Intracellular Life Cycle Kinetics of SARS-CoV-2 Predicted Using Mathematical Modelling.

SARS-CoV-2 infection represents a global threat to human health. Various approaches were employed to reveal the pathogenetic mechanisms of COVID-19. Mathematical and computational modelling is a powerful tool to describe and analyze the infection dynamics in relation to a plethora of processes contributing to the observed disease phenotypes. In our study here, we formulate and calibrate a deterministic model of the SARS-CoV-2 life cycle. It provides a kinetic description of the major replication stages of SARS-CoV-2. Sensitivity analysis of the net viral progeny with respect to model parameters enables the identification of the life cycle stages that have the strongest impact on viral replication. These three most influential parameters are (i) degradation rate of positive sense vRNAs in cytoplasm (negative effect), (ii) threshold number of non-structural proteins enhancing vRNA transcription (negative effect), and (iii) translation rate of non-structural proteins (positive effect). The results of our analysis could be used for guiding the search for antiviral drug targets to combat SARS-CoV-2 infection.

Asthma-associated risk for COVID-19 development.

The newly described severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for a pandemic (coronavirus disease 2019 [COVID-19]). It is now well established that certain comorbidities define high-risk patients. They include hypertension, diabetes, and coronary artery disease. In contrast, the context with bronchial asthma is controversial and shows marked regional differences. Because asthma is the most prevalent chronic inflammatory lung disease worldwide and SARS-CoV-2 primarily affects the upper and lower airways leading to marked inflammation, the question arises about the possible clinical and pathophysiological association between asthma and SARS-CoV-2/COVID-19. Here, we analyze the global epidemiology of asthma among patients with COVID-19 and propose the concept that patients suffering from different asthma endotypes (type 2 asthma vs non-type 2 asthma) present with a different risk profile in terms of SARS-CoV-2 infection, development of COVID-19, and progression to severe COVID-19 outcomes. This concept may have important implications for future COVID-19 diagnostics and immune-based therapy developments.