Projected health workforce requirements and shortage for addressing the disease burden in the WHO Africa Region, 2022-2030: a needs-based modelling study.

Introduction: An adequate health workforce (HWF) is essential to achieving the targets of the Sustainable Development Goals (SDG), including universal health coverage. However, weak HWF planning and constrained fiscal space for health, among other factors in the WHO Africa Region, has consistently resulted in underinvestment in HWF development, shortages of the HWF at the frontlines of service delivery and unemployment of qualified and trained health workers. This is further compounded by the ever-evolving disease burden and reduced access to essential health services along the continuum of health promotion, disease prevention, diagnostics, curative care, rehabilitation and palliative care.

Molecular modelling and fragment-based design of potential inhibitors of beta-tubulin gene of from natural products.

The emergence of drug resistance against the known hookworm drugs namely albendazole and mebendazole and their reduced efficacies necessitate the need for new drugs. Chemically diverse natural products present plausible templates to augment hookworm drug discovery. The present work utilized pharmacoinformatics techniques to predict African natural compounds ZINC95486082, ZINC95486052 and euphohelionon as potential inhibitory molecules of the hookworm β tubulin gene.

Evaluation of the soil and water assessment tool (SWAT) for simulating E. coli concentrations at the watershed-scale.

Water quality management at the watershed level requires a framework to identify sources, apportion water quality risks and develop mitigation strategies to reduce health risks. Watershed-scale models have been used as a support tool to understand the sources, fate and transport of fecal bacteria and pathogens in the environment. The Soil and Water Assessment Tool (SWAT) model was applied in this study to understand the sources and drivers of microbial water quality in the Clouds Creek watershed in Georgia, USA.

Design and Development of Diabetes Management System Using Machine Learning.

This paper describes the design and implementation of a software system to improve the management of diabetes using a machine learning approach and to demonstrate and evaluate its effectiveness in controlling diabetes. The proposed approach for this management system handles the various factors that affect the health of people with diabetes by combining multiple artificial intelligence algorithms. The proposed framework factors the diabetes management problem into subgoals: building a Tensorflow neural network model for food classification; thus, it allows users to upload an image to determine if a meal is recommended for consumption; implementing K-Nearest Neighbour (KNN) algorithm to recommend meals; using cognitive sciences to build a diabetes question and answer chatbot; tracking user activity, user geolocation, and generating pdfs of logged blood sugar readings.

Isolating the impact of septic systems on fecal pollution in streams of suburban watersheds in Georgia, United States.

The presence of multiple sources of fecal pollution at the watershed level presents challenges to efforts aimed at identifying the influence of septic systems. In this study multiple approaches including targeted sampling and monitoring of host-specific Bacteroidales markers were used to identify the impact of septic systems on microbial water quality. Twenty four watersheds with septic density ranging from 8 to 373 septic units/km were monitored for water quality under baseflow conditions over a 3-year period.

Evaluating the influence of septic systems and watershed characteristics on stream faecal pollution in suburban watersheds in Georgia, USA.

Aims: To determine the impact of septic systems on water quality and in so doing identify watershed level characteristics that influence septic system impact.

Methods And Results: Water samples were collected from streams in 24 well-characterized watersheds during baseflow to analyse for the levels of faecal indicators Escherichia coli and enterococci. The watersheds represent a gradient of land-use conditions from low to high density of septic systems, as well as developed to undeveloped uses.