High real-time reporting of domestic and wild animal diseases following rollout of mobile phone reporting system in Kenya

M Kariuki Njenga, Naomi Kemunto, Samuel Kahariri, Lindsey Holmstrom, Harry Oyas, Keith Biggers, Austin Riddle, John Gachohi, Mathew Muturi, Athman Mwatondo, Francis Gakuya, Isaac Lekolool, Rinah Sitawa, Michael Apamaku, Eric Osoro, Marc-Alain Widdowson, Peninah Munyua

Research output: Contribution to journalA1: Web of Science-article

Abstract

BACKGROUND: To improve early detection of emerging infectious diseases in sub-Saharan Africa (SSA), many of them zoonotic, numerous electronic animal disease-reporting systems have been piloted but not implemented because of cost, lack of user friendliness, and data insecurity. In Kenya, we developed and rolled out an open-source mobile phone-based domestic and wild animal disease reporting system and collected data over two years to investigate its robustness and ability to track disease trends.

METHODS: The Kenya Animal Biosurveillance System (KABS) application was built on the Java® platform, freely downloadable for android compatible mobile phones, and supported by web-based account management, form editing and data monitoring. The application was integrated into the surveillance systems of Kenya's domestic and wild animal sectors by adopting their existing data collection tools, and targeting disease syndromes prioritized by national, regional and international animal and human health agencies. Smartphone-owning government and private domestic and wild animal health officers were recruited and trained on the application, and reports received and analyzed by Kenya Directorate of Veterinary Services. The KABS application performed automatic basic analyses (frequencies, spatial distribution), which were immediately relayed to reporting officers as feedback.

RESULTS: Of 697 trained domestic animal officers, 662 (95%) downloaded the application, and >72% of them started reporting using the application within three months. Introduction of the application resulted in 2- to 14-fold increase in number of disease reports when compared to the previous year (relative risk = 14, CI 13.8-14.2, p<0.001), and reports were more widely distributed. Among domestic animals, food animals (cattle, sheep, goats, camels, and chicken) accounted for >90% of the reports, with respiratory, gastrointestinal and skin diseases constituting >85% of the reports. Herbivore wildlife (zebra, buffalo, elephant, giraffe, antelopes) accounted for >60% of the wildlife disease reports, followed by carnivores (lions, cheetah, hyenas, jackals, and wild dogs). Deaths, traumatic injuries, and skin diseases were most reported in wildlife.

CONCLUSIONS: This open-source system was user friendly and secure, ideal for rolling out in other countries in SSA to improve disease reporting and enhance preparedness for epidemics of zoonotic diseases.

Original languageEnglish
Article numbere0244119
JournalPLoS ONE
Volume16
Issue number9
Number of pages13
ISSN1932-6203
DOIs
Publication statusPublished - 2021

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