Describing a National Chatbot Deployed by the Ministry of Health in Malawi During the COVID-19 Pandemic: Retrospective Data Analysis.

BACKGROUND

Malawi was a pioneer among African countries in implementing a coordinated, government-led effort to streamline COVID-19 support using digital health tools. In response to the pandemic, a COVID-19 WhatsApp chatbot was developed to support the public with information, symptom reporting, and service navigation during the pandemic.

OBJECTIVE

This study describes the national deployment, functionality, and use patterns of the WhatsApp chatbot during the COVID-19 pandemic in Malawi.

METHODS

A retrospective descriptive analysis of chatbot interaction data from May 2020 to May 2023 was conducted. User engagement with key chatbot functions was summarized using descriptive statistics, and time-series analysis was used to compare trends in reported COVID-19 cases with access patterns to the chatbot, the emergency operation call center, and Chipatala cha pa Foni (a national hotline initiative).

RESULTS

The chatbot was accessed 347,117 times, with 70.8% (n=245,895) of validated WhatsApp accesses focused on COVID-19 statistics. Chatbot use patterns showed temporal alignment with COVID-19 case trends, particularly during the first and second pandemic waves and increases observed after lockdown events. Throughout the pandemic, chatbot downtime occurred in 38% (407/1070) of days, with the most prolonged period coinciding with the national vaccine rollout in 2021, during which vaccine-related functionalities were introduced. Following this expansion, the chatbot recorded 198 COVID-19 vaccine-related rumors and 644 accesses to vaccine frequently asked questions. Compared with call-based services, the chatbot recorded higher overall interactions, whereas symptoms were more frequently reported through call center platforms.

CONCLUSIONS

This study provides a descriptive account of the development and use of a national COVID-19 WhatsApp chatbot in Malawi. The findings highlight patterns of information-seeking behavior, variation in feature use, and the influence of system availability on engagement. These insights may inform the design, implementation, and sustainability of digital health communication tools in similar settings.