COVID-19 Progression: A County-Level Analysis of Vaccination and Case Fatality in Mississippi, USA.

The COVID-19 pandemic has created a severe upheaval in the U.S., with a particular burden on the state of Mississippi, which already has an exhausted healthcare burden. The main objectives of this study are: (1) to analyze the county-level COVID-19 cases, deaths, and vaccine distribution and (2) to determine the correlation between various social determinants of health (SDOH) and COVID-19 vaccination coverage. We analyzed COVID-19-associated data and county-level SDOH factors in 82 counties of Mississippi. The cumulative COVID-19 and socio-demographic data variables were grouped into feature and target variables. The statistical and exploratory data analysis (EDA) was conducted using Python 3.8.5. The correlation between the target and feature variables was performed by Pearson Correlation analysis. The heat Map Correlation Matrix was visually presented to illustrate the correlation between each pair of features and each target variable. Results indicated that people of Asian descent had the highest vaccination coverage of 77% fully vaccinated compared to 52%, 46%, 42% and 25% for African Americans, Whites, Hispanics, and American Indians/Alaska Natives, respectively. The county-level vaccination rate was significantly higher among the minority populations than the White population. It was observed that COVID-19 cases and deaths were positively correlated with per capita income and negatively correlated with the percentage of persons without a high school diploma (age 25+). This study strongly demonstrates that different SDOH factors influence the outcome of the COVID-19 vaccination rate, which also affects the total number of COVID-19 cases and deaths. Vaccine promotion should be given to all populations regardless of race and ethnicity to achieve uniform acceptance. Therefore, statewide policy recommendations focusing on specific community needs should help achieve health equity in COVID-19 vaccination management.

Exploring Unconventional Risk-Factors for Cardiovascular Diseases: Has Opioid Therapy Been Overlooked?

Approximately 2150 adults die every day in the U.S. from Cardiovascular Diseases (CVD) and another 115 deaths are attributed to opioid-related causes. Studies have found conflicting results on the relationship between opioid therapy and the development of cardiovascular diseases. This study examined whether an association exists between the use of prescription opioid medicines and cardiovascular diseases, using secondary data from the National Hospital Ambulatory Medical Care Survey (NAMCS) 2015 survey. Of the 1829 patients, 1147 (63%) were male, 1762 (98%) above 45 years of age, and 54% were overweight. The rate of cardiovascular diseases was higher among women [(p < 0.001), 95% CI: 0.40-0.51]. The covariates were age, race/ethnicity, sex, diabetes mellitus, hyperlipidemia, and hypertension; and were adjusted. Diabetes mellitus, hyperlipidemia, and hypertension were significant predictors of CVD [(p < 0.001, 95% CI: 0.57-0.78); (p < 0.001, 95% CI: 0.34-0.44); (p < 0.001, 95% CI: 0.49-0.59)]. There was no significant association between prescription opioid medication use and coronary artery disease [first opioid group p = 0.34, Prevalence Odds Ratio (POR): 1.39, 95% CI: 0.71-2.75; second opioid group: p = 0.59, POR: 1.20, 95% CI: 0.61-2.37, and third opioid group: p = 0.62, POR: 0.85, 95% CI: 0.45-1.6]. The results of this study further accentuate the conflicting results in literature. Further research is recommended, with a focus on those geographical areas where high prevalence of cardiovascular diseases exists.

Trends in infant mortality in United States: a brief study of the Southeastern states from 2005-2009.

While overall infant mortality rates have declined over the past several decades, the Southeastern states have remained the leading states in high infant death in the United States. In this study, we studied the differences in infant mortality in the southeastern United States from 2005 through 2009 according to mother's characteristics (age of mother, marital status, maternal race, maternal education), birth characteristics (month when maternal prenatal care began, birth weight), and infant's characteristics (age of infant at death). This paper illustrates the significance level of each characteristic of mothers and infants, as well as socioeconomic factors that contribute to significant infant mortality that impacts subgroups within the US population. Descriptive statistics and analysis of variance studies were performed and presented. Statistical analysis of the contribution of causes of infant death to infant mortality at the national and state level was elaborated. Data suggest that mothers with no prenatal care had a very high overall infant death rate (5281.83 and 4262.16 deaths per 100,000 births in Mississippi and Louisiana, respectively, whereas the US average was 3074.82 deaths (p < 0.01)). It is suggested that better education and living quality should be available and improved for the residents in Alabama, Louisiana, and Mississippi.

Geospatial interpolation and mapping of tropospheric ozone pollution using geostatistics.

Tropospheric ozone (O3) pollution is a major problem worldwide, including in the United States of America (USA), particularly during the summer months. Ozone oxidative capacity and its impact on human health have attracted the attention of the scientific community. In the USA, sparse spatial observations for O3 may not provide a reliable source of data over a geo-environmental region. Geostatistical Analyst in ArcGIS has the capability to interpolate values in unmonitored geo-spaces of interest. In this study of eastern Texas O3 pollution, hourly episodes for spring and summer 2012 were selectively identified. To visualize the O3 distribution, geostatistical techniques were employed in ArcMap. Using ordinary Kriging, geostatistical layers of O3 for all the studied hours were predicted and mapped at a spatial resolution of 1 kilometer. A decent level of prediction accuracy was achieved and was confirmed from cross-validation results. The mean prediction error was close to 0, the root mean-standardized-prediction error was close to 1, and the root mean square and average standard errors were small. O3 pollution map data can be further used in analysis and modeling studies. Kriging results and O3 decadal trends indicate that the populace in Houston-Sugar Land-Baytown, Dallas-Fort Worth-Arlington, Beaumont-Port Arthur, San Antonio, and Longview are repeatedly exposed to high levels of O3-related pollution, and are prone to the corresponding respiratory and cardiovascular health effects. Optimization of the monitoring network proves to be an added advantage for the accurate prediction of exposure levels.

HIV and tuberculosis trends in the United States and select Sub-Saharan Africa countries.

Tuberculosis (TB) and Human Immunodeficiency Virus (HIV) are two catastrophic diseases affecting millions of people worldwide every year; and are considered to be pandemic by the World Health Organization. This study aims to compare the recent trends in TB and HIV in the United States and Sub-Saharan African Countries. Data (incidence, prevalence and death rates of HIV and TB) for the United States, Cameroon, Nigeria, and South Africa were collected from The Joint United Nations Programme for HIV/AIDS (UNAIDS), US Census Bureau and World Health Organization (WHO) databases and analyzed using Statistical Analysis Software (SAS v 9.1). Analysis of Variance (ANOVA) was performed to compare the variables of interest between the countries and across time. Results showed that percent rates of TB cases, TB deaths, HIV cases and HIV deaths were significantly different (P<0.001) among these countries from 1993 to 2006. South Africa had the highest rates of HIV and TB; while US had the lowest rates of both diseases. Tuberculosis and HIV rates for Cameroon and Nigeria were significantly higher when compared to the United States, but were significantly lower when compared to South Africa (P<0.001). There were significant differences (P<0.001) in the prevalence of TB and HIV between the United States and the Sub-Saharan African countries, as well as differences within the Sub-Saharan African countries from 1993 to 2006. More analysis needs to be carried out in order to determine the prevalence and incidence of HIV and TB among multiple variables like gender, race, sexual orientation and age to get a comprehensive picture of the trends of HIV and TB.