JMIR Publications

ABSTRACT

Background:

Natural Language Processing (NLP) has significant potential to promote public health by making certain services more accessible, equitable, and efficient. However, applying these technologies in African health systems faces challenges, including limited digital and computational resources to support the continent’s diverse languages and needs. The extent, availability, and challenges of NLP technologies in this context have not been surveyed comprehensively.

Objective:

This scoping review aims to map the current evidence on NLP technologies for public health in Africa. This review addresses the following research questions: (1) What public health needs are currently being addressed by NLP technologies in Africa, and what unmet needs remain? (2) What factors influence the availability of public health NLP technologies across African countries and languages? (3) What stages of deployment have these technologies reached, and to what extent have they been integrated into existing health systems? (4) What measurable impact has these technologies had on public health outcomes, where such data are available? (5) What recommendations have been proposed to enhance the quality, cost, and accessibility of health-related NLP technologies in Africa?

Methods:

This scoping review includes academic studies published between 1 January 2013 and 3 October 2024. A systematic search was conducted across databases including MEDLINE via PubMed, ACL Anthology, Scopus, IEEE Xplore, and ACM Digital Library, supplemented by grey literature searches of preprints, online articles, commercial products, and relevant initiatives. Data were extracted using a standardised template and mapping the NLP technology functions to the World Health Organization’s list of Essential Public Health Functions (EPHFs) and the United Nations’ Sustainable Development Goals (SDGs). The extracted data were analysed to identify trends, gaps, and areas for future research. This scoping review follows the PRISMA reporting guidelines for scoping reviews and its protocol is publicly available.

Results:

Out of 1,782 citations screened, 54 studies were included. While existing NLP technologies show promise in supporting a subset of EPHFs and SDGs, language coverage remains uneven, with limited support for widely spoken African languages such as Kiswahili, Yoruba, Igbo and Zulu and no support for the majority of Africa’s over 2,000 languages. Most technologies are in prototyping phases, with only one fully deployed chatbot addressing vaccine hesitancy. Grey literature reveals industry and NGO-led projects focused on practical and deployable NLP applications, often in collaboration with charitable organisations and international bodies. These projects, however, tend to support only a few major languages and specific use cases, indicating a narrower focus compared to the broader scope of academic research.

Conclusions:

Despite growth in NLP research for public health in Africa, major gaps remain in real-world deployment, linguistic inclusivity, and health outcome evaluation. Future research should prioritise cross-sector and needs-based approaches that engage local communities, align with African health systems, and incorporate rigorous evaluations to enhance public health outcomes across the continent.