Predictive analysis on the factors associated with birth Outcomes: A machine learning perspective.

Background: Recent studies reveal that around 1.9 million stillbirths occur annually worldwide, with Sub-Saharan Africa having among the highest cases. Some Sub-Saharan African countries, including Ghana, failed to meet Millennium Development Goal 5 (MDG5) by 2015 and may struggle to meet Sustainable Development Goal 3 (SDG3) despite maternal healthcare interventions.

Assessment of Neonatal Mortality and Associated Hospital-Related Factors in Healthcare Facilities Within Sunyani and Sunyani West Municipal Assemblies in Bono Region, Ghana.

Objectives: Ghana's quest to reduce neonatal mortality, in hospital facilities and communities, continues to be a nightmare. The pursuit of achieving healthy lives and well-being for neonates as enshrined in Sustainable Development Goal three lingered in challenging hospital facilities and communities. Notwithstanding that, there have been increasing efforts in that direction.

Generalization of Odd Ramos-Louzada generated family of distributions: Properties, characterizations, and applications to diabetes and cancer survival datasets.

Probability distributions offer the best description of survival data and as a result, various lifetime models have been proposed. However, some of these survival datasets are not followed or sufficiently fitted by the existing proposed probability distributions. This paper presents a novel Kumaraswamy Odd Ramos-Louzada-G (KumORL-G) family of distributions together with its statistical features, including the quantile function, moments, probability-weighted moments, order statistics, and entropy measures.

Gait speed and its associated factors among older black adults in Sub-Saharan Africa: Evidence from the WHO study on Global AGEing in older adults (SAGE).

Gait speed is an essential predictor of functional and cognitive decline in older adults. The study aimed to investigate the gait speed of older adults in Ghana and South Africa and to determine its associated factors, as the Sub-Saharan representatives in the World Health Organization's Study on Global AGEing in Older Adults (SAGE). A secondary analysis of data from the SAGE study which consists of nationally representative data involving participants aged ≥50+ years with smaller samples of younger adults aged 18-49 years in Ghana and South Africa was conducted.

Application of Hierarchical/Multilevel Models and Quality of Reporting (2010-2020): A Systematic Review.

Introduction: Multilevel models have gained immense popularity across almost every discipline due to the presence of hierarchy in most data and phenomena. In this paper, we present a systematic review on the adoption and application of multilevel models and the important information reported on the results generated from the use of these models.

Methods: The review was performed by searching Google Scholar for original research articles on the application of multilevel models published between 2010 and 2020.

Examining the risk factors for overweight and obesity among women in Ghana: A multilevel perspective.

Overweight/obesity prevalence is on the increase in epidemic proportions across Low- and Middle-Income countries (LMICs). The public health burden associated with obesity/overweight cannot be underestimated due to its association with chronic health outcomes. This study investigated the individual- and community level risk factors for obesity/overweight among reproductive women.

Structural equation modeling of pedestrian behavior at footbridges in Ghana.

This study was undertaken to fill the information gap by exploring pedestrian behavior at footbridges in the Greater Accra and Kumasi Metropolitan areas of Ghana. Further, the study modelled the behavior of 69,840 pedestrians at the footbridges using Structural Equation Modeling (SEM). Pedestrians were observed as users and non-users of seven selected footbridges in the morning (7:00 am-9:00 am), afternoon (11:00 am-1:00 pm), and evening (3:00 pm-5:00 pm) periods for seven consecutive days (Monday to Sunday).

Modelling COVID-19 incidence in the African sub-region using smooth transition autoregressive model.

Prediction of COVID-19 incidence and transmissibility rates are essential to inform disease control policy and allocation of limited resources (especially to hotspots), and also to prepare towards healthcare facilities demand. This study demonstrates the capabilities of nonlinear smooth transition autoregressive (STAR) model for improved forecasting of COVID-19 incidence in the Africa sub-region were investigated. Data used in the study were daily confirmed new cases of COVID-19 from February 25 to August 31, 2020.

The effects of weather on the spread of COVID-19: evidence from Ghana.

Background: Climatic factors have been shown to influence communicable disease dynamics especially in tropical regions where temperature could swing from extreme heat and dryness to wet and cold within a short period of time. This is more pronounced in the spread of airborne diseases. In this study, the effect of some local weather variables (average temperature, average relative humidity, average wind speed and average atmospheric pressure) on the risk of Severe Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in Ghana is investigated.

Spatial analysis of the prevalence of obesity and overweight among women in Ghana.

Objective: Identifying hot spots for the overweight aids in effective public health interventions due to the associated public health burden and morbidities. This study, therefore aimed to explore and determine the spatial disparities in the overweight/obesity prevalence among women in Ghana. The study also aims at modelling the average body mass index (BMI) values using the spatial regression and the performance compared with the standard regression model.

Discriminant analysis of farmers adoption of improved maize varieties in Wa Municipality, Upper West Region of Ghana.

This study employed the quadratic classification function analysis to examine the influence of farmer's socio-demographic and varietal characteristics of maize on adoption of improved maize varieties (IMVs) in the Wa Municipality of the Upper West region of Ghana. The results showed that, farm labour, information availability about the variety, weed resistance, low yielding variety, early maturity and water stress resistance are the major discriminating variables in classifying farmers in the Municipality. The study however revealed that maize experience, low yield, information availability and cost of variety were the most influential discriminating variables between adopters and non-adopters of IMVs.