Digital transformation can improve malaria control programmes by enhancing decision-making and accountability.
Key facts
- •Digital transformation should begin with deciding what needs improving, not with the technology itself.
- •Interoperability is a core implementation requirement for programme performance, national ownership and sustainability.
- •AI is only as strong as the systems that underpin it, and requires structured and high-quality data, clear governance frameworks and accountability.
- •Predictive analytics can help anticipate risk and improve preparedness in complex operating environments.
- •Digital systems should improve timeliness, accountability, coverage and equity, not just data collection or visualisation.
The Information and Communication Technologies for Development conference in Nairobi, Kenya, discussed how digital innovation can transform humanitarian relief and development. Malaria Consortium showcased the Digital Immunisation and Geospatial Tool for Health Campaigns Management, highlighting the importance of digital transformation in improving decisions and accountability in real-world operating environments.
Digital Transformation
The conference emphasized that digital transformation should begin with deciding what needs improving, not with the technology itself. For malaria programmes, this means shifting how we frame digital health: from system deployment to decision support. The value of digital systems is not in data collection or visualisation alone, but in whether they improve timeliness, accountability, coverage and equity.
Interoperability and AI
ICT4D reinforced that interoperability is no longer a technical 'nice to have', but a core implementation requirement for programme performance, national ownership and sustainability. AI is only as strong as the systems that underpin it, and key enablers include structured and high-quality data, clear governance frameworks and accountability, cybersecurity safeguards, leadership understanding and staff confidence in using outputs appropriately.
Predictive Analytics
ICT4D highlighted the growing potential of predictive analytics to anticipate risk and improve preparedness in complex operating environments. Predictive analytics could help identify areas likely to have access, denominator, staffing, supply or adherence challenges before a cycle begins, and connect rainfall, temperature, flooding, vegetation, vector risk and routine malaria data to early planning decisions.
This article was independently rewritten by ManyPress editorial AI from reporting originally published by AllAfrica.
