Africa’s public health is at a critical juncture, facing a paradigm shift in funding and strategy. Learning how to improve African health systems is paramount as external donor reliance fades, giving way to nationally owned, intelligence-driven, and accountable models. The recent US decision to channel billions directly to African governments isn’t merely a financial adjustment; it’s an invitation to forge resilient, equitable, and data-centric health infrastructures. This pivotal moment demands a fundamental re-evaluation of existing approaches to healthcare delivery and management.
For decades, African health systems have grappled with chronic under-resourcing, fragmentation, and dependence on external actors, despite significant donor investment. The COVID-19 pandemic starkly illuminated these vulnerabilities, forcing ministries to make critical decisions with outdated data and fragmented reporting tools. Africa, home to 17% of the world’s population, accounts for only 3% of global health spending, with a disproportionate 37% of health expenditure coming from out-of-pocket payments, double the global average.
A quiet revolution began in 2025 with the US restructuring its global health engagement, directly funding African governments. Kenya secured $1.5 billion, Côte d’Ivoire $480 million, and Ethiopia, Botswana, Sierra Leone, and Madagascar collectively received $2.3 billion. Nigeria, with its vast population, has now joined this wave of direct partnerships. Crucially, this funding bypasses NGOs, flowing through national government systems, signifying a profound governance revolution in public health.
What is intelligence driven governance in public health? Intelligence-driven governance in public health refers to the discipline of using real-time data and actionable insights to inform decision-making, detect service disruptions early, allocate resources effectively, and hold managers accountable. It moves beyond lagging indicators to enable quick, evidence-based responses to health challenges across the continent.
African health systems often struggle not from a lack of commitment or money, but from a deficit of real-time health intelligence. Ministries frequently rely on reports that are 30 to 90 days late, fragmented donor systems, and manual aggregation that obscures local realities. This leads to delayed outbreak detection, preventable stock-outs, and misallocated budgets. Africa takes 10 days longer than the global average to detect disease outbreaks, a delay that directly costs lives and financial resources.
Intelligence-driven governance is not just about technology; it’s about the discipline to see, decide, and act swiftly. By integrating facility-level data, supply chain visibility, workforce deployment, disease surveillance, citizen feedback, and budget execution, governments can pinpoint service disruptions early and allocate resources based on evidence. Predictive analytics can reduce outbreak response times by up to 40%, while smarter procurement could save billions annually. Every dollar invested in health intelligence can yield ten dollars in efficiency gains, a crucial step for how to improve African health systems.
This shift, however, is a political disruption. Real-time visibility threatens actors who benefit from opacity, fragmentation, and slow decision cycles. Bureaucratic gatekeepers often control information flows to maintain influence, negotiate budgets, or shield underperformance. Opaque procurement systems are ripe for manipulation, with stock-out manipulation and inflated tenders thriving in environments where real-time visibility is absent. Resistance will manifest as procedural delays, endless “pilots,” and calls for “further consultation,” all designed to slow down critical change.
For decades, donor and INGO incentives favored parallel systems, justified as efficient but often sidelining national governments. Direct funding changes this dynamic entirely. Donors must now align with national systems, and INGOs must transition from implementers to enablers. This demands a redesign of business models, focusing on strengthening government capacity, supporting data integration, and transferring skills to local organizations, rather than simply aiming for project volume.
An efficient health system can still be unjust. Women, who constitute 70% of the health workforce, hold only 25% of leadership roles. Maternal mortality remains tragically high at 533 per 100,000 births, compared to 12 in high-income countries. Rural communities and informal settlements often lack skilled providers and face frequent service disruptions. Intelligence systems must illuminate these disparities, making the invisible visible: the poor, rural populations, and those far from political power. Achieving equity requires partners who understand their evolving role in this new governance landscape.
To fully seize this moment, African governments must establish national health intelligence labs and subnational decision rooms. Integrating citizen feedback, strengthening data governance and privacy, aligning donor reporting with national systems, and training leaders in intelligence-driven governance are crucial steps. Technology alone is insufficient; strong, visionary leadership is the ultimate determinant of success in transforming public health outcomes.
Africa stands at a profound crossroads, moving from a reactive, donor-driven past to a future defined by national ownership and intelligence. The US investment is an opportunity, not just a handout, to build systems that are resilient, equitable, and politically credible. If governments, donors, and INGOs collaboratively rise to this challenge, Africa can transition from perpetual crisis response to a future founded on dignity, shared prosperity, and genuinely resilient health systems. This is the definitive path to understanding how to improve African health systems for generations to come.
