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Leveraging AI-Powered Conversational Agents to Mitigate Vaccine Hesitancy in Low-Resource African Contexts: A Public Health Framework

Domaine:

healthcarenatural language processing

Type de record:

paper
Créateur:
UzoC. Chu
Éditeur:
Dep
Éditeur:
CCSD
Hôte:avatar
International audience Vaccine hesitancy remains a major public health concern across Africa, driven by misinformation, cultural beliefs, and limited access to accurate health communication. With growing mobile and internet access, AI-powered conversational agents (chatbots) offer a promising means of improving vaccine literacy and trust in low-resource settings such as Nigeria. A qualitative review of studies from PubMed, Scopus, and IEEE Xplore, along with WHO and Africa CDC reports, was conducted to examine chatbot applications in healthcare. Findings informed the design of a multimodal framework that integrates text, voice, and visuals in indigenous languages (Igbo, Yoruba, Hausa) for inclusive communication. A pilot design covering urban (Lagos) and rural (Abia) populations was proposed to evaluate comprehension, engagement, and accessibility. The review shows that culturally localized chatbots can substantially enhance vaccine literacy. Projected outcomes indicate up to a 70% improvement in comprehension and a 60% increase in engagement when multimodal features and linguistic adaptation are incorporated. Ethical and infrastructural considerations remain key for sustainable deployment. AI-driven conversational agents provide a scalable, low-cost solution to vaccine hesitancy in Africa. By aligning technology with cultural and linguistic diversity, they can bridge communication gaps, counter misinformation, and strengthen public health awareness. This study contributes a context-driven framework for integrating AI into community-based vaccine education.

Visit

hal.science

Languages

HausaYoruba

Tags

[INFO]Computer Science [cs]

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