Data Management and Biostatistics Core (DMBC)

The DMBC is a Data Coordinating Center (DCC) with capacity to support optimal design, conduct, and analysis of malaria research performed under the aegis of the Malawi ICEMR.

Using a secure network, we:

  • Assist with study planning and management, and protocol development
  • Develop data capture tools using electronic data capture (eDC)
  • Customize and develop optimal Data Management Systems
  • Track samples
  • Assure data quality and adherence to study protocols

Key Personnel of Core


Alfred Matengeni (DMBC Leader)

Kamuzu University of Health Sciences - COM MACCDAC

Before joining the Malawi ICEMR, Alfred had led teams of Data Managers in different Clinical Research Organizations (CROs) in Malawi. At the Malawi ICEMR, Alfred oversees the operations of the DMBC while coordinating and collaborating with different data advisors and consultants from the US and other countries.


Clarissa Valim 
Boston University School of Public Health
(DMBC Advisor)


Ernest Matola
Kamuzu University of Health Sciences - COM MACCDAC
(Data Manager)


Samson Gowa
Kamuzu University of Health Sciences – COM MACCDAC
(Data Officer)


Jonathan Babbage
Michigan State University
(Data Core Consultant)


Paulo Filimone
Philimone’s Group Mozambique
(Data Core Consultant)

Key Personnel of Core

Study Planning and Management

  • We support research projects with study design, sampling, protocol development, planning of logistics, development of Data Management Plans and producing material for data and sample capture including: forms and devices for electronic data capture (EDC) with real time data validation based on range and logic checks within and across forms; pre-populated logs and study packages

Electronic Data Capture

  • We support projects with a Health Surveillance systems that assist the field team with identifying study subjects and eCRFs to be filled at each follow-up visit and tracking forms. Using an in house developed system (DCS), we can synchronize and automatically integrate different types and sources of data collected at different locations and automatically synchronize data into REDCap for easy access by investigators. Through this system, we can easily generate sample identification numbers (IDs) for printing sample barcodes and Pre-populated logs

Data Integration through a Web-based Data Management System

  • Using an in house developed system (DCS), we can collect data offline. Different types and sources of data from varied locations are synchronized and automatically integrated into REDCap for easy access by investigators. Through this system, we can easily generate sample identification numbers (IDs) for printing sample barcodes .

Sample Tracking

  • Our systems Track samples from the collection through temporary storage in the site offices to their permanent storage in the biobank of the Molecular Laboratory in Blantyre.

Quality Assurance and Control (QA/QC)

  • We support investigators with QA of data and monitoring of study are conducted in several ways, including issuing automated reports with frequent data analysis. Furthermore, we periodically conduct data cleaning analysis. Our developer team also created a Web-based system for automatic, real-time QA/QC of PCR assays.

Training and Capacity Building

  • We recruit and train professionals to support Investigators with project management, data collection, and data entry, processing, storage and retrieval. Furthermore, for all research projects supported by the DMBC, we recruit and train Data Managers, Data Officers, and Interns in the use of our systems and in all processes and procedures.

Data Storage

  • Data is uploaded and synchronized into a cloud server and backed up both on premise and on cloud. Working jointly with the Information Technology Core, we make sure research data is secure and protected from unauthorized access.


  • The staff of the DMBC writes health informatics publications.

DMBC Locations


  • The central office is located in Blantyre at MAC-DAC, where the majority of data management, analysis, and systems development takes place and local and cloud servers are managed in a Data Center. Additionally, DMBC operates in two satellite offices in rural Malawi: Namanolo and Balaka, connected to cloud servers and to the central office through the Web. In these offices, a Data Officer performs the first data quality assurance by reviewing daily collected eCRFs. Furthermore, collection, centrifuging, and storage of samples are carefully monitored through our sample tracking systems. Because these staff are close to field operations, they can provide immediate assistance and better oversee on the ground activities.


  • The DMBC works with investigators to develop a plan detailing the processes and procedures for data capture, flow, quality assurance and control, and analysis, specifically tailored for the project needs.

  • Through our DCS, we can automate pre-populated study logs to assist the filed team with tracking participant study visits. These logs contain information about participants to be visited. They can be easily updated at each participant visit and shared with the study sites by email. They are fast to be completed. 

  • Our data capture system is based on a health surveillance system in tablets integrated to Open Data Kit. The system allow verifying whether a participant is part of a study by providing several search paths: 1) individual ID, 2) participant full, first, or last name; 3) any fragment of participant’s names; 4) names of members in participant households. In the case of cohort studies, the system can also display a list of all participants with a visit due.

  • With sample barcodes pre-linked to study identification numbers, we support preparation of packages including all necessary material for data (e.g., consent forms) and sample capture of each study participant. These study packages help shortening interactions with each study participant.

  • Working with investigators, we develop and program electronic case report forms including complex validation rules to prevent mistakes at data entry. Real-time queries within and across forms are produced, allowing for instance, to check information about weight and height within a visit using Z-scores or across visits. Our eCRFs can also carry information from one visit to the other. For instance, when collecting information about vaccines in a cohort study, our system “knows” at each visit which childhood vaccines are still pending for a given participant.

  • For each project, visit and type of sample, we use our customized system to generate barcodes

  1. When samples arrive from the field into our offices, using an offline in-house developed system barcodes each sample barcode is scanned and the time is automatically recorded. This system allows capturing additional sample information.

  2. When samples are ready to be transported, the system automatically prints a change of custody log recording date and time that samples leave the temporary biobank and arrive in the second
  3. In the central laboratory, we customized a commercial sample tracking Web based system for tracking dry blood spots, plasma, and other types of samples. This system records sample arrival, storage, movement. Furthermore, maps of plates used to extract genetic material and qPCR are automatically recorded.
  1. Checks are conducted by Data Officers at the end of the day before eCRFs are uploaded from tablets to the cloud. At data synchronization in the cloud, SQL scripts check for existing of repeated or missing forms. After that, lists are distributed weekly during study visits to investigators and query reports are automatically produced.

We developed a Web-based system that allows: importing data directly from qPCR machines

  • QA PCR plates using pre-established criteria and flag plates for repetition
  • detects and remove outliers in standard controls based on pre-defined thresholds, refitting standard curves and re-estimating parasite counts
  • automatically detects individual wells that need to be repeated based on sample duplicate disparity
  • has a friendly customer interface to allow technicians to immediately see the performance of their work
  • produces statistical reports to monitor assay conduct