Scholarlink

<p>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.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

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

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月12日

查看全文
  • Toluwase Oluwajomiloju Ogundipe,
  • Oloruntoba Joshua Ajayi,
  • Michael Ayodele Olawale,
  • Toluwalope Adekunle Faleye

摘要

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.