There are many public health challenges in the so-called global south that are tackled through literacy-focused interventions by nonprofits and public health agencies. However, it is extremely challenging to scale such interventions to large populations in countries that speak multiple languages, and have complex sociocultural norms. We leverage large language models (LLMs) to demonstrate a scaling of successful literacy interventions to improve menstrual health and hygiene among adolescent females in Bangladesh. Our system is deployed as a WhatsApp chatbot that generates responses grounded in accurate, verified knowledge from international health agencies and domain-specific knowledge from local health organizations. We discuss the considerations for the development and deployment of consumer-facing LLM chatbots to be accessible in low-resource communities without a large English-speaking population.

Key Contributions

• Study in Low-Resource Regions
• LLM-Based Chatbot Development
• Multilingual Support
• Grounded Responses
• Deployment on WhatsApp