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Journal of Information Systems Engineering and Management

Towards an Integrated Mobile Technology on Animal Disease Surveillance Framework in Tanzania: A Systematic Review
Ahmed Kijazi 1 2 * , Michael Kisangiri 1, Shubi Kaijage 1, Gabriel Shirima 3
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1 School of Computational and Communication Science and Engineering (CoCSE), Nelson Mandela African Institution of Science and Technology (NM-AIST), Arusha, Tanzania
2 Mathematics and ICT Department College of Business Education (CBE), Dar es salaam, Tanzania
3 School of Life Sciences and Bioengineering (LiSBE), Nelson Mandela African Institution of Science and Technology (NM-AIST), Arusha, Tanzania
* Corresponding Author
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Literature Review

Journal of Information Systems Engineering and Management, 2022 - Volume 7 Issue 2, Article No: 14383
https://doi.org/10.55267/iadt.07.12044

Published Online: 23 Apr 2022

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APA 6th edition
In-text citation: (Kijazi et al., 2022)
Reference: Kijazi, A., Kisangiri, M., Kaijage, S., & Shirima, G. (2022). Towards an Integrated Mobile Technology on Animal Disease Surveillance Framework in Tanzania: A Systematic Review. Journal of Information Systems Engineering and Management, 7(2), 14383. https://doi.org/10.55267/iadt.07.12044
Vancouver
In-text citation: (1), (2), (3), etc.
Reference: Kijazi A, Kisangiri M, Kaijage S, Shirima G. Towards an Integrated Mobile Technology on Animal Disease Surveillance Framework in Tanzania: A Systematic Review. J INFORM SYSTEMS ENG. 2022;7(2):14383. https://doi.org/10.55267/iadt.07.12044
AMA 10th edition
In-text citation: (1), (2), (3), etc.
Reference: Kijazi A, Kisangiri M, Kaijage S, Shirima G. Towards an Integrated Mobile Technology on Animal Disease Surveillance Framework in Tanzania: A Systematic Review. J INFORM SYSTEMS ENG. 2022;7(2), 14383. https://doi.org/10.55267/iadt.07.12044
Chicago
In-text citation: (Kijazi et al., 2022)
Reference: Kijazi, Ahmed, Michael Kisangiri, Shubi Kaijage, and Gabriel Shirima. "Towards an Integrated Mobile Technology on Animal Disease Surveillance Framework in Tanzania: A Systematic Review". Journal of Information Systems Engineering and Management 2022 7 no. 2 (2022): 14383. https://doi.org/10.55267/iadt.07.12044
Harvard
In-text citation: (Kijazi et al., 2022)
Reference: Kijazi, A., Kisangiri, M., Kaijage, S., and Shirima, G. (2022). Towards an Integrated Mobile Technology on Animal Disease Surveillance Framework in Tanzania: A Systematic Review. Journal of Information Systems Engineering and Management, 7(2), 14383. https://doi.org/10.55267/iadt.07.12044
MLA
In-text citation: (Kijazi et al., 2022)
Reference: Kijazi, Ahmed et al. "Towards an Integrated Mobile Technology on Animal Disease Surveillance Framework in Tanzania: A Systematic Review". Journal of Information Systems Engineering and Management, vol. 7, no. 2, 2022, 14383. https://doi.org/10.55267/iadt.07.12044
ABSTRACT
Tanzanian Government, through its national audit office in March 2020, reported the prevalence decline of two animal diseases, namely; Foot and Mouth Disease (FMD) and Contagious Bovine Pleuropneumonia (CBPP). Similarly, an increase in three animal diseases, which are African Swine Fever (ASV), Contagious Caprine Pleuropneumonia (CCPP), and Lumpy Skin Disease (LSD). The national audit office mentioned inadequate animal disease surveillance system in the country was among the challenges that hinder diseases control. Therefore, this study reviews the existing animal diseases surveillance systems global and suggests measures to enhance animal diseases surveillance systems in Tanzania. This review focuses on the possibility of sharing surveillance data among livestock stakeholders (including livestock keepers) in Tanzania, considering available resources such as animal diseases existing prediction models and mobile-based surveillance systems. Also, the availability of mobile technologies such as Short Message Service (SMS), Unstructured Supplementary Service Data (USSD) and automatic voice calls (Robocalls). Reviews synthesize the previous studies to explore strengths, opportunities, weaknesses and challenges for better future interventions through proper and timely information sharing. This study selected 46 records from the 147 identified for review. The selected records include 24 from bibliographic databases, 14 from full-text journals and other non-bibliographic databases, and 8 from the open search on websites
KEYWORDS
Animal Disease Surveillance Framework Tanzanian livestock keepers’ demographics data feature mobile phone Tanzania Animal diseases surveillance system animal diseases prediction models Robocalls System interoperability
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