ABSTRACT
We investigated the influence of Bacillus Calmette-Guérin (BCG) vaccination on the unstimulated plasma levels of a wide panel of cytokines, chemokines, acute-phase proteins (APPs), matrix metalloproteinases (MMPs), and growth factors in a group of healthy elderly individuals (age, 60 to 80 years) at baseline (before vaccination) and 1 month after vaccination as part of our clinical study to examine the effect of BCG on COVID-19. Our results demonstrated that BCG vaccination resulted in diminished plasma levels of types 1, 2, and 17 and other proinflammatory cytokines and type 1 interferons. BCG vaccination also resulted in decreased plasma levels of CC, CXC chemokines, APPs, MMPs, and growth factors. Plasma levels of the aforementioned parameters were significantly lower in vaccinated individuals when compared to unvaccinated control individuals. Thus, our study demonstrates the immunomodulatory properties of BCG vaccination and suggests its potential utility in nonspecific vaccination of COVID-19 by down-modulating pathogenic inflammatory responses.
Subject(s)
BCG Vaccine/administration & dosage , COVID-19/immunology , Cytokines/metabolism , Inflammation Mediators/metabolism , Inflammation/prevention & control , Vaccination/methods , Aged , Aged, 80 and over , BCG Vaccine/immunology , COVID-19/epidemiology , COVID-19/virology , Case-Control Studies , Female , Humans , India/epidemiology , Inflammation/immunology , Inflammation/metabolism , Inflammation/pathology , Male , Middle Aged , SARS-CoV-2/immunologyABSTRACT
Aim: This study explored the knowledge, attitude and practices (KAP) of higher education students towards COVID-19. In addition, this study analysed the association of socio-demographic variables with KAP apart from finding the relationship between KAP. Subject and methods: This is a cross-sectional study conducted in India. Study participants were selected using a convenient sampling method from various higher educational institutions across 22 states in India. Data was collected using self-administered close-ended questionnaires via Google forms. The data were analysed using frequencies and percentage for descriptive purposes. A chi-square test was used to determine the association between groups, and correlation analysis was used to illustrate the significant relationship between KAP. Results: The majority, that is, 65.5% of students possess a high level of knowledge about the disease. It was noteworthy that 71.0% of them had a positive attitude towards COVID-19 and 66.7% of them exhibited desirable practices to mitigate COVID-19. Furthermore, the results showed a significant association between KAP and some of the socio-demographic variables studied. Social media emerged as a vital source of information regarding COVID-19 for the majority (81.0%) of students. Also, a strong significant positive correlation was observed between KAP variables. Conclusion: One-fourth of the students demonstrated only low and moderate levels of knowledge, negative attitude and undesirable practices in preventing COVID-19. The implications suggesting various approaches to enhance KAP to moderate the spread of COVID-19 among the students were recommended to aid the higher educational institutions.
ABSTRACT
BACKGROUND: Most of the countries are affected with the pandemic outbreak of the coronavirus infection. Understanding the severity and distribution in various regions will help in planning the controlling measures. OBJECTIVES: The objective was to assess the distribution and growth rate of COVID-19 infection in Tamil Nadu, India. METHODS: The data on the number of infections of COVID-19 have been obtained from the media reports released by the Government of Tamil Nadu. The data contain information on the incidence of the disease for the first 41 days of the outbreak started on March 7, 2020. Log-linear model has been used to estimate the progression of the COVID-19 infection in Tamil Nadu. Separate models were employed to model the growth rate and decay rate of the disease. Spatial Poisson regression was used to identify the high-risk areas in the state. RESULTS: : The models estimated the doubling time for the number of cases in growth phase as 3.96 (95% confidence interval [CI]: 2.70, 9.42) days and halving time in the decay phase as 12.08 (95% CI: 6.79, 54.78) days. The estimated median reproduction numbers were 1.88 (min = 1.09, max = 2.51) and 0.76 (min = 0.56, max = 0.99) in the growth and decay phases, respectively. The spatial Poisson regression identified 11 districts as high risk. CONCLUSION: The results indicate that the outbreak is showing decay in the number of infections of the disease which highlights the effectiveness of controlling measures.