The novel coronavirus outbreak was declared a pandemic in March 2020. We are reviewing the COVID-19 vaccines authorized for use in the United States by discussing the mechanisms of action, administration, side effects, and efficacy of vaccines developed by Pfizer, Moderna, and Johnson & Johnson. Pfizer and Moderna developed mRNA vaccines, encoding the spike protein of SARS-CoV-2, whereas Johnson & Johnson developed an adenovirus vector-based vaccine. Safety has been shown in a large cohort of participants in clinical trials as well as the general population since emergency approval of vaccine administration in the US. Clinical trial results showed the Pfizer and Moderna vaccines to be 95.0%, and the Johnson & Johnson vaccine to be 66.0% effective in protecting against moderate and symptomatic SARS-CoV-2 infection. It is important to keep medical literature updated with the ongoing trials of these vaccinations, especially as they are tested among different age groups and upon the emergence of novel variants of the SARS-CoV-2 coronavirus.

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Body mass index (BMI), a measurement based on a person's height and weight, allows the classification of individuals into categories such as obese or overweight. With these classifications, we can assess risk for hypertension, diabetes, cancer, hypercholesterolemia, and other chronic diseases. Furthermore, childhood BMI serves as a prediction method for health and disease later in life. Along with BMI, researchers also study waist circumference and waist-to-hip ratio in correlation with the above-mentioned chronic illnesses. This brief review explores the associations between body mass index, waist circumference, and the waist-hip ratio as measurements and their capability as predictors for persistent conditions like diabetes and hypertension.

Background. The purpose of this study was to examine occupation-, education-, and gender-specific patterns of tobacco use and knowledge of its health effects among 23,953 rural Asian Indians ≥18 years in Gujarat. Methodology. A statewide, community-based, cross-sectional survey was conducted in 26 districts of Gujarat (December 2010–May 2015), using face-to-face interviews by trained community health workers called SEVAKS. Results. Mean age was 39.8 ± 15.2 years. Eighteen percent of respondents used tobacco in various forms. Tobacco consumption was significantly higher among males (32%), 18–34 years' age group (35%), those who were self-employed (72%), and those with elementary education (40%). The prevalence was 11 times higher among males than females (95% CI = 9.78, 13.13). Adjusted ORs for tobacco use showed strong gradient by age and educational level; consumption was lower among the illiterates and higher for older participants (≥55 years). Tobacco consumption also varied by occupation; that is, those who were self-employed and employed for wages were more likely to use tobacco than those who were unemployed. Knowledge of health effects of tobacco lowered the odds of consumption by 30–40%. Conclusions. Effective educational programs should be tailored by gender, to improve knowledge of health risks and dispel myths on perceived benefits of tobacco.

A wide variety of social determinants of health have been associated with various risks and impacts on quality of life. Specifically, poverty, lack of insurance coverage, large household sizes, and social vulnerability are all factors implicated in incidence and mortality rates of infectious disease. However, no studies have examined the relationship of these factors to the COVID-19 pandemic on a state-wide level in Florida. Thereby, the objective of this study is to examine the relationship between average household size, poverty, uninsured populations, social vulnerability index (SVI), and rates of COVID-19 cases and deaths in Florida counties.The objective was accomplished by analyzing the cumulative case and death reports from state and local health departments in Florida. The data was compiled into a single dataset by the CDC COVID-19 Task Force. Using US Census Bureau data, all Florida counties were classified into tertiles of the separate categories of poverty rate, average household size, uninsured rates, and SVI (Social Vulnerability Index). The poverty level was classified as low (0-12.3%), moderate (12.3-17.3%), and high (>17.3% below the federal poverty line). The uninsured population proportion was classified as low (0-7.1%), moderate (7.1-11.4%), and high (>11.4% uninsured residents). Average county household size was classified as low (0-2.4), moderate (2.4-2.6), and high (>2.6). The Centers for Disease Control and Prevention (CDC)/Agency for Toxic Substances and Disease Registry (ATSDR) Social Vulnerability Index (SVI) used US census data on 15 social determinants of vulnerability to evaluate and assist disadvantaged communities. SVI tertiles were low (0-0.333), moderate (0.334-0.666), and high (0.667-1) on a range of 0-1, with higher numbers signifying communities with many factors of social vulnerability. The mean cumulative cases and deaths per 100,000 inhabitants were calculated in each tertile for each category.Analysis of the data revealed that case and mortality rates due to COVID-19 in the high poverty counties were markedly higher in Florida than the national average. In contrast, moderate and low poverty rates were below average. Similarly, counties with a high SVI had case and mortality rates greatly above state and national averages. Counties with a high proportion of uninsured displayed the highest case rates. However, mortality rates were the highest in counties with a low proportion of uninsured individuals. No clear correlation was observed between COVID-19 rates and household size.It was concluded that compiled CDC and US census data suggests a significant correlation between poverty, social vulnerability, lack of insurance coverage, and increased incidence and mortality from COVID-19. Future research should statistically analyze the correlations and examine the individual factors of SVI as potential COVID-19 predictors.