Early Detection and Surveillance of Infectious Disease Outbreaks in Nigeria: Integrating Nigerian Pidgin English (Npe) Into the Epiwatch® Platform

Background This study aimed to integrate Nigerian Pidgin English (NPE) into the Artificial Intelligence software the EPIWATCH® with the aim of providing early detection and enhanced surveillance of infectious disease outbreaks in Nigeria. The widespread use of NPE as a national language with over 75 million speakers in Africa improves interaction and communication with communities across Nigeria. Methods For the study, key search terms were converted into NPE and then integrated into the EPIWATCH® for monitoring. A descriptive analysis was performed on publicly available data on outbreaks reported between 2018 and 2023 in Nigeria (a 5-year retrospective dataset) obtained from the EPIWATCH® to conduct descriptive analysed to compare outbreaks before and after NPE integration. Results The results showed a 166.7% increase in frequency of reported outbreaks after language integration. Conclusion This study demonstrates the potential of leveraging technology and linguistic diversity to improve disease surveillance using open source intelligence (OSINT) and response efforts in Nigeria.