Data Management and Analysis Core (DMAC)

Data Management and Analysis Core (DMAC)

D-SINE Africa’s Data Management and Analysis Core (DMAC) facilitates and supports effective data collection, management and analysis across D-SINE Africa for both existing data and the development of new datasets.  The DMAC will also help to foster good data collection, data management, and reproducible and transparent research practices among junior investigators within D-SINE Africa.

The DMAC activities include:

i. Working closely with Hub researchers to develop standardized, data quality protocols to ensure collection of high-quality data and to ensure timely identification and resolution of problems

ii. Overseeing the implementation of a Research Electronic Data Capture (REDCap) system that creates secure data inputting from our two major projects (Project 1 – Health Equity Surveillance and Project 2 – Trauma Follow Up Prediction), creating de-identified analysis-ready data and metadata for the Hub network, and making data available via appropriate credentials

iii. Providing expert support for complex machine learning methodology for both prediction and causal inferences, research focus areas for junior investigators who may apply for seed grants

Leadership: The Data Management and Analysis Core is co-led by Georges Nguefack-Tsague, PhD, Associate Professor of Statistics at the University of Yaoundé I in Cameroon, with affiliate faculty positions at AIMS-Cameroon and at the University of Buea, and Alan Hubbard, PhD, Professor of Biostatistics at the University of California, Berkeley.