PNNL

Abstract

Infectious disease surveillance is crucial for early detection and situational awareness of potential disease outbreaks. Digital biosurveillance monitors large volumes of open-source internet data to flag potential health threats. This study was aimed to investigate the role of digital surveillance in the detection of the five important zoonotic diseases of Kenya: Rift Valley fever (RVF), anthrax, rabies, brucellosis and trypanosomiasis. Open-source disease events reported between August 2016 and October 2020 were collected and key event-specific information was extracted using a newly developed disease event taxonomy. A total of 424 disease reports en-compassing 55 unique events belonging to anthrax (43.64%), RVF (34.55%), and rabies (21.82%) were identified. Most events were first reported by news media (78.18%) followed by international health organizations (16.36%). The results show a positive association between official re-porting and RVF disease events (odds ratio [OR] 195.50, 95% confidence interval [CI]; 24.01–4756.43, p