Artificial intelligence in vaccine coverage in Africa: predictive analytics and innovations for immunization equity

Abstract Vaccination coverage in Africa is currently suboptimal, with a decline in some countries. The prevalence of non-vaccination rates for certain vaccine-preventable diseases varies from 2 to 32% in countries across the continent. This decline has increased due to the COVID-19 pandemic and armed conflicts in some regions. Hence, routine immunization campaigns are not as effective. A literature review of studies published from 2000 to 2025 was conducted to examine the current use of AI in optimizing vaccine coverage in Africa and future directions tailored to Africa’s unique context. The findings highlight that AI is significantly improving vaccine coverage and public health outcomes in Africa by enhancing predictive capabilities and improving operational efficiency. The transport time for vaccines and samples has reduced significantly due to the use of AI-powered drone technology systems, improving emergency response outcomes. AI-driven disease surveillance systems are being used to predict early outbreak detection and response, and predictive analytics is helping to identify vaccine coverage gaps, thereby informing targeted interventions. In vaccine development, AI-guided vaccinology approaches are improving antigen selection and immunogenicity testing. Integrating AI into large-scale vaccination programs requires addressing ethical concerns, strengthening data infrastructure, and ensuring model adaptability to diverse healthcare settings in the short, medium, and long term.