Policy brief · June 2025

The use of public health analytics in developing Nigeria's national health sector strategy

A landscape analysis by Applied Health Analytics for Delivery and Innovation (AHADI), with CGHII as implementing partner, supported by the Harvard T.H. Chan School of Public Health.

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Fieldwork
Abuja, June to August 2024
Method
Mixed methods
Recommendations
11 for government

Why it matters now

Health planning has never depended more on good data. Nigeria, one of the largest recipients of US health aid, has lost around a fifth of its external support for the health sector, funding that largely backed work on malaria, HIV and vaccines.

The Ministry of Health and its agencies have recognised the importance of public health analytics, using it in the Second National Strategic Health Development Plan, the National Malaria Strategic Plan and a new national strategic blueprint. This analysis asks how well that is working, and what would make it sustainable.

What we did

The study combined a systematic desktop review of government reports, health policy documents and peer-reviewed research with qualitative fieldwork in Abuja.

6
in-depth interviews with key informants, five in person and one virtual
3
national bodies: the Ministry of Health, NCDC and the National Malaria Elimination Programme
4
themes: infrastructure, capacity, data quality and timeliness, and partnerships

What we found

Real progress

  • Analytics now informs situational analysis and priority setting in national and malaria strategic plans.
  • The 2014 HMIS policy sets a clear intent for a unified system, recommending at least 2% of health budgets for HMIS and a further 1% for data governance.
  • The Sector-Wide Approach unit is centralising priorities and reducing duplication from uncoordinated donor efforts.

Where it is fragile

  • Analytics infrastructure and people depend heavily on donors, leaving them exposed to shifting priorities.
  • DHIS2 is the central hub, but disease-specific repositories create silos and older systems do not integrate well.
  • Varied reporting standards, late facility data and outdated surveys limit real-time insight, especially below national level.
  • Skilled analysts are scarce and hard to retain, so overstretched health workers carry data work alongside care.

Eleven recommendations

Sequenced so government and partners can act now while laying foundations for the long term.

Immediate to short term

  1. 1Update the HMIS policy and digitisation strategy. A unified data framework with interoperability, privacy and security built in.
  2. 2Increase and sustain investment in data infrastructure. A dedicated budget line to reduce reliance on donors.
  3. 3Agree a unified national partnership framework. Align donor support with national priorities and end duplication.
  4. 4Run regular needs assessments. Keep tools, systems and training aligned with the planning cycle.
  5. 5Strengthen data integration and visualisation. Expand the MSDAT dashboard and connect SORMAS and NLIMS to DHIS2 through standard APIs.

Long term

  1. 6Institutionalise the Sector-Wide Approach. Protect it across administrations through regulation or legislation.
  2. 7Create a Medical Research Council. Direct government funding for research aligned with national needs.
  3. 8Enhance digital infrastructure and data security. Secure, scalable cloud infrastructure kept up to date.
  4. 9Build a government-funded analytics workforce. Competitive pay, training and career paths to retain skilled analysts.
  5. 10Establish a national health data hub. One source of truth for surveillance, laboratory, research and logistics data.
  6. 11Legislate for health data governance. Clear responsibilities, standards and privacy requirements across the sector.