Hypertension in Bangladesh is a leading cause of cardiovascular diseases, stroke, and kidney failure, resulting in significant morbidity and mortality. Preventive measures and simple health practices can effectively reduce hypertension and its complications. This study utilizes machine learning algorithms (Naive Bayes, support vector machine, logistic regression, random forest) to predict hypertension in high-risk individuals. The proposed hybrid model achieves a prediction accuracy of 78.17%, surpassing other machine learning methods. Random forest has the highest accuracy among the individual algorithms at 73.86%. Classification performance is evaluated using sensitivity, specificity, precision, and F-score, along with receiver operating characteristic analyses and confusion matrices through 10-fold cross-validation. These findings emphasize the importance of managing risk factors for better population health and highlight the efficacy of the hybrid model in hypertension prediction. The study underscores the significance of preventive measures in reducing the burden of hypertension-related diseases and improving overall well-being.

Background: COVID-19 vaccination uptake is associated with demographic characteristics such as age, sex, and ethnicity-race in the United States (U.S.). Prior research predominantly analyzed COVID-19 vaccination uptake unidimensionally, limiting insights into multidimensional demographic inequalities. Multidimensional studies provide a closer insight into vaccination inequality and assist in designing more effective vaccination strategies. Objectives: Review descriptive studies of the COVID-19 vaccination uptake across combinations of at least two of the three key demographic characteristics: age, sex, and ethnicity-race in the U.S. Methods: A systematic review was performed using the Joanna Briggs Institute methodology and adhering to the PRISMA-ScR principles for reporting. Six impartial reviewers examined all of the papers. The data were obtained using a tailored data extraction template. Results: A total of 2793 records were initially downloaded, 461 of them were dropped for duplication, and 2332 were reviewed. Based on the title and abstract reviews, 2115 records were excluded. After reviewing the full text of the remaining records, 212 more records were excluded. The remaining six records were reviewed to identify and compare their population, study period, data, the studied dose number, methodology, and results. Conclusions: Multidimensional COVID-19 vaccine uptake analyses are rare and mostly focused on the dose-one vaccination. Improving researchers’ access to immunization registry data while preserving data security is a prerequisite for such analyses.

Background: Although children can contract COVID-19, their typically lower immune reactivity appears to shield them from the intense hyperinflammatory response observed in other age groups, leading to milder disease symptoms. Nonetheless, children’s infection raises the possibility of unwanted transmission of the coronavirus to others, especially because most infected children are asymptomatic. Objectives: This study examines the uptake of the first and second doses of the COVID-19 vaccine among children by combinations of age, race, ethnicity, and sex. Methods: Data from the immunization registry were utilized to assess changes over time in COVID-19 vaccine uptake among children in Jefferson County, Kentucky’s most populous county. The analysis examined trends by age, race, ethnicity, and combinations of age-race, age-ethnicity, age-race-sex, and age-ethnicity-sex during the first six quarters of the COVID-19 vaccination rollout. Results: By May 2022, in 16–17-year-olds, the highest and lowest COVID-19 vaccination rates were observed among White and Black children (64.8% versus 41.2%, respectively, for dose two). The highest two-dose vaccination rate at ages 12–15 years was among Multiracial and White children (63.3% and 62.9%, respectively), the lowest among Black children (38.8%). The highest two-dose vaccination rate at ages 5–11 years was among children of Some Other Races, Asian, and White children (37.0%, 36.7%, and 35.5%, respectively), and the lowest among Black children (17.2%). Conclusions: Inequalities in COVID-19 vaccination based on race, ethnicity, and sex persisted throughout the study period. Efforts in vaccine distribution and promotional initiatives should focus on increasing vaccination rates among children from racial and ethnic minority groups and males.

Adults face a higher risk of exposure to COVID-19 than older adults and children due to their labor force participation. This study investigated the uptake of the initial and second doses of the COVID-19 vaccine among adults, stratified by age, race, ethnicity, sex, and their combinations. Data from the Kentucky Immunization Registry were employed to evaluate temporal changes in COVID-19 vaccine uptake among adults in three age groups (college age: 18–24, prime working age: 25–44, and middle age: 45–64) in Jefferson County, Kentucky (2020 population: 782,969). The analysis explored trends by age, race, and ethnicity; intersections of age with race and ethnicity; and interactions of age–race and age–ethnicity with sex. By May 2022, the highest and lowest COVID-19 vaccination rates were observed among White and Black 45–64-year-old adults: 74.8% and 64.0%, respectively, for dose two. The highest and lowest two-dose vaccination rates at ages 25–44 and 18–24 were also among White and Black residents: 67.9% versus 46.0% and 55.2% versus 35.4%, respectively. Disparities in COVID-19 vaccination by race, ethnicity, sex, and their intersections remained evident during the study period. Efforts in vaccine distribution and promotional initiatives should focus on demographically appropriate strategies.

Background: While disparities in vaccine uptake have been well documented, few studies have evaluated the impact of local vaccine programs on COVID-19 outcomes, namely cases, hospitalizations, and deaths. Objectives: Evaluate the impact of COVID-19 vaccine doses coordinated by the Louisville Metro Department of Public Health and Wellness (LMPHW) on COVID-19 outcomes by race across ZIP codes from December 2020 to May 2022 in Jefferson County, Kentucky. Methods: Fixed-effects longitudinal models with ZIP codes as ecological time-series units were estimated to measure the association between COVID-19 vaccine doses and outcomes with time lags of one week, two weeks, three weeks, four weeks, and one month. Models were adjusted for time (week or month of the year) and its interaction with ZIP code. Results: In the one-week lag model, significant negative associations were observed between LMPHW-coordinated vaccine doses and COVID-19 outcomes, indicating reductions of 11.6 cases, 0.4 hospitalizations, and 0.3 deaths per 100 doses administered. Vaccine doses were consistently associated with fewer deaths among White residents across all lags, with an average reduction of 0.2 deaths per 100 doses. No significant associations were found for Black residents. Temporal trends also indicated declines in COVID-19 outcomes when LMPHW’s vaccine administration program peaked, between March and May 2021. Conclusions: Timely uptake of COVID-19 vaccines remains critical in avoiding severe outcomes, especially with emerging variants. Racial disparities in vaccine–outcome associations emphasize the potential need for equitable, community-driven vaccine campaigns to improve population health outcomes.