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.

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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

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article

A Bi-lingual chatbot implementation for pandemic response using the transformer-based approach

Mike Nsubuga, Ronald Galiwango, Ibra Lujumba, Mugume Twinamatsiko Atwine et al.
PLOS Digital Health
AI in Service Interactions
article

A Bi-lingual chatbot implementation for pandemic response using the transformer-based approach

Mike Nsubuga, Ronald Galiwango, Ibra Lujumba, Mugume Twinamatsiko Atwine, Ibrahim Mbabaali, Byansi David, Kebirungi Grace, Timothy Kintu, Daudi Jjingo, Richard Serunjogi
article en

Abstract

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.

PLOS Digital HealthVol. 5(4)
University of Bristol (GB), Infectious Diseases Institute (UG), African Field Epidemiology Network (UG), Makerere University (UG)
International Development Research Centre, Common Fund, Grand Challenges in Global Health
Good health and well-being
Openalex Percentile: Top 34%
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A Bi-lingual chatbot implementation for pandemic response using the transformer-based approach — Mike Nsubuga, Ronald Galiwango, et al. · PLOS Digital Health (2026) | TGRS Research Map | TGRS