A Bi-lingual chatbot implementation for pandemic response using the transformer-based approach
The COVID-19 pandemic highlighted the critical need for timely and accurate information in effectively managing pandemics. The proliferation of misinformation on public media platforms complicated the management of the pandemic, necessitating a large and constant human resource to meet the demand for trustworthy information. To address this challenge, we developed an intelligent bilingual chatbot that is available 24/7 to provide medically curated up-to-date and approved pandemic management information in English and Luganda. This approach leveraged deep learning to train a chatbot on a growing corpus of curated pandemic-specific information, questions, and answers. Our results demonstrate an implementation of a chatbot that leverages the well-resourced English NLP framework to enable chatting in the Luganda language. They also show that the chatbot is an effective and flexible tool for disseminating accurate information in real-time, while also providing opportunities for continuous improvement through conversation-driven development.
Authors
- Mike Nsubuga (ORCID: https://orcid.org/0009-0004-7668-3917)
- Ronald Galiwango (ORCID: https://orcid.org/0000-0002-5962-151X)
- Ibra Lujumba (ORCID: https://orcid.org/0000-0001-9937-1255)
- Mugume Twinamatsiko Atwine
- Ibrahim Mbabaali
- Byansi David
- Kebirungi Grace
- Timothy Kintu
- Daudi Jjingo
- Richard Serunjogi
Institutions
- University of Bristol (GB)
- Infectious Diseases Institute (UG)
- African Field Epidemiology Network (UG)
- Makerere University (UG)
Publication Details
- Journal
- PLOS Digital Health
- Published
- 2026-04-01
- DOI
- https://doi.org/10.1371/journal.pdig.0001256
- Primary Topic
- AI in Service Interactions
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- International Development Research Centre
- Common Fund
- Grand Challenges in Global Health