ArticlePathogens (Basel, Switzerland)2021
Digital Biosurveillance for Zoonotic Disease Detection in Kenya.
Article in Pathogens (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 14 citations in OpenAlex.
- Epidemic status of echinococcosis, brucellosis, and tuberculosis among rural residents in three counties of Wuzhong City, Ningxia, China in 2023.Parasite epidemiology and control · 2025Article
- Advance Warning and Response Systems in Kenya: A Scoping Review.medRxiv : the preprint server for health sciences · 2025Article
- The evolution of Kenya's animal health surveillance system and its potential for efficient detection of zoonoses.Frontiers in veterinary science · 2024Article
- Predicting Kyasanur forest disease in resource-limited settings using event-based surveillance and transfer learning.Scientific reports · 2023Article
- Predicting infectious disease for biopreparedness and response: A systematic review of machine learning and deep learning approaches.One health (Amsterdam, Netherlands) · 2022Review
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Infectious disease surveillance is crucial for early detection and situational awareness of disease outbreaks. Digital biosurveillance monitors large volumes of open-source data to flag potential health threats. This study investigates the potential of digital surveillance in the detection of the top five priority zoonotic diseases in 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 encompassing 55 unique events belonging to anthrax (43.6%), RVF (34.6%), and rabies (21.8%) were identified. Most events were first reported by news media (78.2%) followed by international health organizations (16.4%). News media reported the events 4.1 (±4.7) days faster than the official reports. There was a positive association between official reporting and RVF events (odds ratio (OR) 195.5, 95% confidence interval (CI); 24.01-4756.43,
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Registered trials
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