RESUMO
The impact of vaccine hesitancy on global health is one that carries dire consequences. This was evident during the outbreak of the COVID-19 pandemic, where numerous theories and rumours emerged. To facilitate targeted actions aimed at increasing vaccine acceptance, it is essential to identify and understand the barriers that hinder vaccine uptake, particularly regarding the COVID-19 vaccine in Ghana, one year after its introduction in the country. We conducted a cross-sectional study utilizing self-administered questionnaires to determine factors, including barriers, that predict COVID-19 vaccine uptake among clients visiting a tertiary and quaternary hospital using some machine learning algorithms. Among the findings, machine learning models were developed and compared, with the best model employed to predict and guide interventions tailored to specific populations and contexts. A random forest model was utilized for prediction, revealing that the type of facility respondents visited and the presence of underlying medical conditions were significant factors in determining an individual's likelihood of receiving the COVID-19 vaccine. The results showed that machine learning algorithms can be of great use in determining COVID-19 vaccine uptake.
RESUMO
Hypertensive disorders in pregnancy (HDPs) are no longer seen as "transitory diseases cured by delivery." It accounts for up to 50% of maternal deaths. Information concerning HDPs is less in developing countries like Ghana. This study was conducted to find out the prevalence, awareness, risk factors, control, and the birth outcomes of HDPs. This was a retrospective cohort study conducted among pregnant women seeking care in selected health facilities in the Ashanti Region. Data on demographics, HDPs, and its associated birth outcomes were collected. Logistic regression models were used to examine the association of the independent variables with HDPs. The burden of HDPs was 37.2% among the 500 mothers enrolled with chronic hypertension superimposed with preeclampsia accounting for 17.6%, chronic hypertension, 10.2%, and preeclampsia 6.8% whilst gestational hypertension was 2.6%. It was observed that 44% (220) of the mothers had excellent knowledge on HDPs. Oral nifedipine and methyldopa were frequently used for HDP management, and it resulted in a significant reduction in HDP burden from 37.2% to 26.6%. Factors that influenced the increased risk of HDPs were grand multigravida (AOR = 4.53; CI = 1.42-14.42), family history of hypertension (AOR = 3.61; CI = 1.89-6.90), and the consumption of herbal preparations (AOR = 2.92; CI = 1.15-7.41) and alcohol (AOR = 4.10; CI = 1.34-12.62) during pregnancy. HDPs increased the risk of preterm delivery (AOR = 2.66; CI = 1.29-5.89), stillbirth (AOR = 12.47; CI = 2.72-57.24), and undergoing caesarean section (AOR = 1.70; CI = 1.10-2.61) amongst mothers during delivery. The burden of HDPs is high amongst pregnant mothers seeking care in selected facilities. There is the need for intensified campaign on HDPs in the Ashanti Region of Ghana.
