Africa: What Digital Transformation Means for Malaria Control Programmes

Across health programme delivery, digital transformation is often discussed in terms of tools. But its real test is whether it helps people make better decisions, faster, in the places where lives are at risk.

In May 2026, more than 500 delegates from 61 countries gathered in Nairobi, Kenya, for the Information and Communication Technologies for Development (ICT4D) conference. The meeting explored how digital innovation and data-driven solutions can transform humanitarian relief and development. The discussions centred on artificial intelligence (AI), digital public infrastructure (DPI), interoperability, predictive analytics, responsible digital development and local innovation.

In partnership with Catholic Relief Services (CRS) and eGov Foundation, Malaria Consortium's representatives hosted a session that focused on transitioning from fragmented campaign tools to digital public infrastructure that could be reused.

Malaria Consortium showcased the Digital Immunisation and Geospatial Tool for Health Campaigns Management (DIGIT HCM), and presented a use case on how to strategically leverage the DPI approach to strengthen and scale campaign digitisation across multiple public health interventions in Nigeria. For our malaria work, particularly seasonal malaria chemoprevention (SMC), the conference reinforced a clear message: digital transformation is not about introducing more platforms, dashboards or AI tools, but about improving decisions, systems and accountability in real-world operating environments.

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"The real value of digital transformation in health systems is not the tools themselves, but whether they strengthen decision-making in the environments where services are delivered," says Peter Otieno, Senior Digital Health Specialist, Malaria Consortium. "Technology can accelerate impact, but only when it is designed around people, systems and the decisions that ultimately determine programme success."

Below are five key takeaways from ICT4D 2026 that are particularly relevant for malaria control and wider health programmes.

Start with decisions, not tools

A consistent message across ICT4D was 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. This has implications for what decisions need to be made, who makes them, what information they need and how quickly they need it.

The value of digital systems is not in data collection or visualisation alone, but in whether they improve timeliness, accountability, coverage and equity. This includes whether such systems improve decisions related to campaign readiness, stock movement, hard-to-reach populations, adverse event follow-up and supervision planning.

Digital health should make it easier to act, not just easier to report.

Interoperability is now a core implementation requirement

ICT4D reinforced that interoperability is no longer a technical 'nice to have', but a core implementation requirement for programme performance, national ownership and sustainability.

Across malaria and community health systems, data often sits in multiple platforms, including routine health information systems, campaign tools, stock systems, training databases, supervision forms, spreadsheets and partner dashboards. When these systems are not connected, programmes rely on manual workarounds, delayed reporting and inconsistent datasets.

This fragmentation reduces the speed and reliability of decision-making. The DPI approach presented at the conference emphasised the importance of reusable, connected systems that can link workflows across campaigns, logistics and national reporting.

Interoperability must be designed into systems from the beginning, not added afterwards. Clean, governed data pipelines are the foundation for any advanced analytics or AI use.

AI readiness depends on data quality, governance and trust

While AI featured prominently at ICT4D, the most grounded discussions highlighted that AI is only as strong as the systems that underpin it.

Key enablers include structured and high-quality data, clear governance frameworks and accountability, cybersecurity safeguards, leadership understanding and staff confidence in using outputs appropriately. Without these, AI risks introducing more uncertainty than value.

In malaria programmes, potential AI applications include summarising trends or identifying anomalies in routine data; flagging abnormal data patterns or potential data quality issues; identifying hard-to-reach areas or operational bottlenecks; alerting stock-out risks; supporting campaign readiness checks and helping interpret complex datasets. However, these must remain decision-support tools, not substitutes for accountability.

AI should support human judgement, not outsource responsibility. If governance and data readiness are weak, scaling AI is not appropriate.

Predictive analytics must be linked to clear action pathways

ICT4D highlighted the growing potential of predictive analytics to anticipate risk and improve preparedness in complex operating environments. This is highly relevant for malaria programmes facing a changing climate, shifting malaria transmission patterns and supply chain constraints.

However, forecasting alone has limited value. The effectiveness of predictive tools depends on whether they trigger timely and defined action. For example, a malaria risk alert only matters if it leads to pre-positioning of commodities, targeted supervision or early response planning. Similarly, stock-out predictions must be linked to redistribution or procurement decisions.

For programmes like SMC, predictive analytics could help identify areas likely to have access, denominator, staffing, supply or adherence challenges before a cycle begins. In surveillance, it could help flag abnormal trends that need review. In climate-sensitive malaria programming, it could connect rainfall, temperature, flooding, vegetation, vector risk and routine malaria data to early planning decisions.

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Predictive analytics must be designed with clear operational protocols from the start: who acts, at what threshold, using which resources and how outcomes are tracked or documented. A forecast without an action pathway may only serve to delay.

Design digital systems for the last mile

A key reflection from ICT4D was that the most 'advanced' digital solution is not always the most effective. In many implementation contexts, the most successful systems are those that work offline, align with government workflows and can be supported locally.

Malaria campaigns and community health systems operate in environments with limited connectivity, constrained infrastructure and high workload. Tools that perform well in pilots may fail at scale if they are not designed for these realities.

Usability, reliability and local support systems are not optional features but core design requirements. Digital solutions are more likely to be adopted if they are useful and reliable. They must reduce workload, not add to it.

ICT4D 2026 reinforced a clear shift in thinking: digitalisation need to move from mere tool deployment to digitalisation as decision-making infrastructure. For malaria control and wider health programmes, this means focusing less on what is built and more on what is improved.