A smartphone-based application improves the accuracy, completeness, and timeliness of cattle disease reporting and surveillance in Ethiopia
Beyene, Tariku Jibat and Asfaw, Fentahun and Getachew, Yitbarek and Tufa, Takele Beyene and Collins, Iain and Beyi, Ashenafi Feyisa and Revie, Crawford W. (2018) A smartphone-based application improves the accuracy, completeness, and timeliness of cattle disease reporting and surveillance in Ethiopia. Frontiers in Veterinary Science, 5. ISSN 2297-1769 (https://doi.org/10.3389/fvets.2018.00002)
Preview |
Text.
Filename: Beyene_etal_FVS_2018_A_smartphone_based_application_improves_the_accuracy_completeness_and_timeliness_of_cattle_disease_reporting.pdf
Final Published Version License: Download (455kB)| Preview |
Abstract
Accurate disease reporting, ideally in near real time, is a prerequisite to detecting disease outbreaks and implementing appropriate measures for their control. This study compared the performance of the traditional paper-based approach to animal disease reporting in Ethiopia to one using an application running on smartphones. In the traditional approach, the total number of cases for each disease or syndrome was aggregated by animal species and reported to each administrative level at monthly intervals; while in the case of the smartphone application demographic information, a detailed list of presenting signs, in addition to the putative disease diagnosis were immediately available to all administrative levels via a Cloud-based server. While the smartphone-based approach resulted in much more timely reporting, there were delays due to limited connectivity; these ranged on average from 2 days (in well-connected areas) up to 13 days (in more rural locations). We outline the challenges that would likely be associated with any widespread rollout of a smartphone-based approach such as the one described in this study but demonstrate that in the long run the approach offers significant benefits in terms of timeliness of disease reporting, improved data integrity and greatly improved animal disease surveillance.
ORCID iDs
Beyene, Tariku Jibat, Asfaw, Fentahun, Getachew, Yitbarek, Tufa, Takele Beyene, Collins, Iain, Beyi, Ashenafi Feyisa and Revie, Crawford W. ORCID: https://orcid.org/0000-0002-5018-0340;-
-
Item type: Article ID code: 64222 Dates: DateEvent16 January 2018Published4 January 2018AcceptedSubjects: Agriculture > Animal culture
Science > Mathematics > Electronic computers. Computer scienceDepartment: Faculty of Science > Computer and Information Sciences Depositing user: Pure Administrator Date deposited: 04 Jun 2018 10:58 Last modified: 12 Dec 2024 06:45 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/64222