Data Management and Analysis Core (DMAC):

Project summary

The greatest challenge facing healthcare systems in many low and middle-income countries (LMICs), including South Africa and Kenya is how to maintain the health and well-being of the population with increasingly scarce healthcare resources. This is especially important as levels of multimorbidity, commonly defined as the co-existence of two or more long-term health conditions are rising. Therefore, valid, reliable, well-curated and documented data as well as use of appropriate and efficient modern analytic techniques are critical to investigating the burden of multimorbidity and improving its management in under resourced settings in sub-Saharan Africa. The Data Management and Analysis Core (DMAC) will serve as a fundamental resource to the hub’s investigative team, projects, and the scientific community by developing and providing the technical skills, infrastructure, analytic techniques and tools to manage, integrate, transform, analyze, visualize and distribute the complex heterogeneous data that would support a varied portfolio of work of the hub. The DMAC will directly support and contribute to project 1 on data integration and development of data visualization platforms and interactive web portal, project 2 on development of the data visualization platform to display results from prediction and modeling processes, and core 3 (pilot projects and scientific/technical capacity strengthening) on ensuring effective data management and analyses in order to fulfil their aims. Specific aims of the DMAC are:

Aim 1

Develop and implement a comprehensive data management plan for the hub and quality assurance of heterogeneous population-level data (sociodemographic, behavioural, mortality, morbidity, risk factor) and clinical, laboratory, genomic and treatment data to support enquiry into the burden of multimorbidity, demand for care and evidence-informed management.

Aim 2

Support development and implementation of analytic techniques and data visualization tools to enable studies on the burden of multimorbidity, demand for care and evidence-informed management.

Aim 1

Build capacity for data management and analysis.

Public Health Relevance

A comprehensive assessment of the burden of multimorbidity and strategies for improving its management requires integration and joint analysis of vast quantities of socio-demographic, behavioural, clinical, laboratory, genomic and treatment data from disparate sources. The DMAC will provide the primary data management and analytic services needed to achieve these goals. The integration of the data from the various sources and utilisation of modern analytic techniques will enable the assessment of causal relationships and testing of hypotheses that may not otherwise be possible from each data source independently.