About the instructor:
Mohamed Sillah Kanu is a data scientist, statistician and software engineer with deep expertise in DHIS2 system administration, metadata configuration, app development and API integration. He holds an MSc in Data Science from The George Washington University and an MSc in Statistics from the University of Sierra Leone, along with degrees in Software Engineering and in Mathematics and Statistics.
He served as a consultant Malaria Epidemiologist with the World Health Organization, supporting the subnational tailoring of malaria interventions that informed Sierra Leone's National Strategic Plan 2026 to 2030. He then joined Northwestern University as a Research Data Analyst Associate, where he handled complex data analytics for national malaria programmes. Today, as Chief Executive Officer of Informatics Consultancy Firm, Sierra Leone (ICF-SL), he leads the primary technical partner to Sierra Leone's National Malaria Control Programme, where he designed the Sierra Leone National Malaria Data Repository, an analytical platform that brings routine health, logistics and surveillance data into one place for decision making from national down to facility level.
The overall objective of his work is to put reliable, timely health data in the hands of the people who make programme decisions. He is a member of AMMnet and the American Society of Tropical Medicine and Hygiene, and has taught mathematics and statistics at the University of Sierra Leone.
Event Summary
This AMMnet Hackathon provided a hands-on introduction to building a complete health reporting system in DHIS2, starting with an empty instance and ending with a working dashboard that could support program decision-making.Participants set up DHIS2 on their own laptops using Docker and worked through the full configuration workflow, including building organizational unit hierarchies manually and through CSV import; creating data elements and category combinations; designing data sets and data entry forms; entering and validating aggregate data; and constructing indicators that transformed raw counts into comparable rates.Using malaria routine data—including suspected cases, testing, confirmed cases, and treatment—as the worked example, the training demonstrated how different components of DHIS2 fit together and how configuration choices shaped what a program could ultimately see and use.Participants also explored case-based data entry through event programs, custom form design using HTML, CSS, and JavaScript, analysis using the Data Visualizer and Maps apps, and the assembly of a two-column program dashboard. Additional topics included user management, data export, system customization, and extending DHIS2 through the App Hub.All topics were taught through hands-on exercises, allowing participants to practice each step before moving on to the next.
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