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
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
REFERENCES
  • Ashar, D., Kanojia, A., Parihar, R., Kudoo, S., 2021. Livestock Disease Prediction System. IVA-Tech International Journal for Research and Innovation, 97 1, 1–3.
  • AU-IBAR, 2019. AU-IBAR Rolls Out 3rd Version of Animal Resources Information System to African Union Member States. African Union, Inter African Bureau for Animal Resources.
  • Bharaneedharan, M., 2020. Animal Detection and its Disease Prediction by Neural Network Classifier. International Journal for Research in Applied Science and Engineering Technology 8, 1730–1734. https://doi.org/10.22214/ijraset.2020.5280
  • Bonnet, P., Bedane, B., Bheenick, K.J., Juanes, X., Girardot, B., Coste, C., Gourment, C., Wanda, G., Madzima, W., Oosterwijk, G., Erwin, T., 2010. The LIMS Community and its collaborative Livestock Information Management System for managing livestock statistics and sharing information in the SADC region (Southern African Development Community), in: IAALD ; Agropolis In (Ed.), . Presented at the IAALD World Congress, s.n., public, p. 9 p.
  • Bradhurst, R.A., Roche, S.E., East, I.J., Kwan, P., Garner, M.G., 2015. A hybrid modeling approach to simulating foot-and-mouth disease outbreaks in Australian livestock. Frontiers in Environmental Science 3.
  • Brinkel, J., Krämer, A., Krumkamp, R., May, J., Fobil, J., 2014. Mobile phone-based mHealth approaches for public health surveillance in sub-Saharan Africa: a systematic review. Int J Environ Res Public Health 11, 11559–11582. https://doi.org/10.3390/ijerph111111559
  • China.cn, 2021. 4/8/16/32/64 ports modem pool [WWW Document]. Shenzhen Antecheng Technology Co., Ltd. URL https://atcb2b.en.china.cn/851114-3g-modem. (accessed 11.2.21).
  • Colangeli, P., Iannetti, S., Cerella, A., Ippoliti, C., Di Lorenzo, A., Santucci, U., Simonetti, P., Paolo Calistri, Lelli, R., 2011. The National information system for the notification of animal diseases. Veterinaria italiana 47, 303–12, 291.
  • Diafaan, 2021. SMS software for Windows [WWW Document]. Diafaan. URL https://www.diafaan.com (accessed 11.2.21).
  • Dion, E., VanSchalkwyk, L., Lambin, E.F., 2011. The landscape epidemiology of foot-and-mouth disease in South Africa: A spatially explicit multi-agent simulation. Ecological Modelling 222, 2059–2072. https://doi.org/10.1016/j.ecolmodel.2011.03.026
  • Erraguntla, M., Zapletal, J., Lawley, M., 2019. Framework for Infectious Disease Analysis: A comprehensive and integrative multi-modeling approach to disease prediction and management. Health Informatics J 25, 1170–1187. https://doi.org/10.1177/1460458217747112
  • European Commission, 2020. Animal Disease Notification System (ADNS) [WWW Document]. European Commission. URL https://ec.europa.eu/food/animals/animal-diseases/not-system_en (accessed 9.8.21).
  • FAO, 2021. EMPRES Global Animal Disease Information System (EMPRES-i) [WWW Document]. URL http://aims.fao.org/news/empres-global-animal-disease-information-system (accessed 9.3.21).
  • FAO, 2018. February 2018, in: Food and Agriculture Organization (FAO) FMD Report (Issue February).
  • FAO, 2015. EMA-i: a mobile app for timely animal disease field reporting to enhance surveillance [WWW Document]. Food and Agriculture Organization (FAO) of the United Nations. URL http://www.fao.org/3/a-i4853e.pdf (accessed 12.18.21).
  • Gloster, J., Jones, A., Redington, A., Burgin, L., Sørensen, J.H., Turner, R., Dillon, M., Hullinger, P., Simpson, M., Astrup, P., Garner, G., Stewart, P., D’Amours, R., Sellers, R., Paton, D., 2010. Airborne spread of foot-and-mouth disease – Model intercomparison. The Veterinary Journal 183, 278–286. https://doi.org/10.1016/j.tvjl.2008.11.011
  • Hashimu, H.C., 2018. Assessment of Farmers’ Use of Mobile Phones in Communicating Agricultural Information in Magharibi A District, Zanzibar, A (PhD Thesis). Sokoine University of Agriculture, Morogoro, Tanzania.
  • Hugo, A., Makinde, O.D., Kumar, S., Chibwana, F.F., 2017. Optimal control and cost effectiveness analysis for Newcastle disease eco-epidemiological model in Tanzania. null 11, 190–209. https://doi.org/10.1080/17513758.2016.1258093
  • Hunter, E., MacNamee, B., Kelleher, J., 2018. A comparison of agent-based models and equation based models for infectious disease epidemiology. CEUR Workshop Proceedings, 2259, 33–44. CEUR Workshop Proceedings 2259. https://doi.org/10.21427/rtq2-hs52
  • Juma, M., 2019. Evaluating the Usage of Mobile Phones in Accessing Farm Input Information among Smallholder Farmers in Mpwapwa District, Tanzania. College of Business Education, Dar es salaam, Tanzania.
  • Karimuribo, E., Batamuzi, E., Massawe, L., Silayo, R., Mgongo, F., Kimbita, E., Wambura, R., 2016. Potential use of mobile phones in improving animal health service delivery in underserved rural areas: Experience from Kilosa and Gairo districts in Tanzania. BMC Veterinary Research 12. https://doi.org/10.1186/s12917-016-0860-z
  • Karimuribo, E.D., Batamuzi, E.K., Massawe, L.B., Silayo, R.S., Mgongo, F.O.K., Kimbita, E., Wambura, R.M., 2016. Potential use of mobile phones in improving animal health service delivery in underserved rural areas: Experience from Kilosa and Gairo districts in Tanzania. BMC Veterinary Research 12, 1–7. https://doi.org/10.1186/s12917-016-0860-z
  • Kasanga, C.J., Yamazaki, W., Mioulet, V., Mulumba, M., Ranga, E., Deve, J., Mundia, C., Chikungwa, P., João, L., Wambura, P.N., Rweyemanu, M.M., 2014. Rapid, sensitive and effective diagnostic tools for foot-and-mouth disease virus in Africa. Onderstepoort J Vet Res 12, 1–5. https://doi.org/10.1089/fpd.2015.1950
  • Kijazi, A., Kisangiri, M., Kaijage, S., Shirima, G., 2021. A Monitoring System for Transboundary Foot and Mouth Disease (FMD) considering the Demographic Characteristics in Gairo, Tanzania. Engineering, Technology & Applied Science Research 11, 7302–7310. https://doi.org/10.48084/etasr.4140
  • Kijazi, Ahmed, Kisangiri, M., Kaijage, S., Shirima, G., 2021. A Proposed Information System for Communicating Foot-and-Mouth Disease Events among Livestock Stakeholders in Gairo District, Morogoro Region, Tanzania. Advances in Human-Computer Interaction 2021, 8857338. https://doi.org/10.1155/2021/8857338
  • Kim, H., Xiao, N., Moritz, M., Garabed, R., Pomeroy, L.W., 2016. Simulating the Transmission of Foot-And-Mouth Disease Among Mobile Herds in the Far North Region, Cameroon. Journal of Artificial Societies and Social Simulation 19, 6. https://doi.org/10.18564/jasss.3064
  • Lungo, J., Kaasbøll, J., Koleleni, I., 2012. Collecting Integrated Disease Surveillance and Response Data through Mobile Phones.
  • Milinovich, G.J., Williams, G.M., Clements, A.C.A., Hu, W., 2014. Internet-based surveillance systems for monitoring emerging infectious diseases. Lancet Infect Dis 14, 160–168. https://doi.org/10.1016/S1473-3099(13)70244-5
  • Mittal, A., Mantri, A., Tandon, U., Dwivedi, Y.K., 2021. A unified perspective on the adoption of online teaching in higher education during the COVID-19 pandemic. Information Discov. Deliv. https://doi.org/10.1108/IDD-09-2020-0114
  • Mwabukusi, M., Karimuribo, E., Rweyemamu, M., Beda, E., 2014. Mobile technologies for disease surveillance in humans and animals. The Onderstepoort journal of veterinary research 81, E1-5. https://doi.org/10.4102/ojvr.v81i2.737
  • Namayanja, J., Dione, M., Kungu, J.M., 2019a. Stakeholders’ perceptions on performance of the Livestock Disease Surveillance system in Uganda: A case of Pallisa and Kumi Districts. Pastoralism 9, 12. https://doi.org/10.1186/s13570-019-0149-5
  • Namayanja, J., Dione, M., Kungu, J.M., 2019b. Stakeholders’ perceptions on performance of the Livestock Disease Surveillance system in Uganda: A case of Pallisa and Kumi Districts. Pastoralism 9. https://doi.org/10.1186/s13570-019-0149-5
  • OIE, 2021. OIE World Animal Health Information System (OIE-WAHIS) [WWW Document]. World Organization for Animal Health (OIE). URL https://wahis.oie.int/#/home
  • ProMED-mail, 2018. Map of the Latest Alerts on Infectious Disease Around the World, ProMED-mail, Boston, MA, USA. [WWW Document]. URL https://www.promedmail.org/ (accessed 9.9.21).
  • Respickius, C., 2016. Exploiting the Full Potential of Information Systems Interoperability in Public Institutions. Business Education Journal (BEJ) I, 1–2.
  • Robertson, C., Sawford, K., Daniel, S.L.A., Nelson, T.A., Stephen, C., 2010. Mobile phone-based infectious disease surveillance system, Sri Lanka. Emerging Infectious Diseases 16, 1524–1531. https://doi.org/10.3201/eid1610.100249
  • Sankaranarayanan, J., Sallach, R.E., 2014. Rural patients’ access to mobile phones and willingness to receive mobile phone-based pharmacy and other health technology services: a pilot study. Telemed J E Health 20, 182–185. https://doi.org/10.1089/tmj.2013.0150
  • SearchHealthIT., 2021. mHealth (mobile health) [WWW Document]. URL https://searchhealthit.techtarget.com/definition/mHealth (accessed 12.1.21).
  • SMSDeliverer, 2021. MMS & SMS software [WWW Document]. URL https://www.smsdeliverer.com/onlinehelp/index.htm?page=Send_SMS_by_HTTP_API.htm (accessed 11.22.21).
  • The Conversation, 2019. Rob calls are unstoppable-3 questions answered about why your phone won’t quit ringing [WWW Document]. The Conversation. URL https://theconversation.com/robocalls-are-unstoppable-3questions-answered-about-why-your-phone-wont-quit-ri nging-108554. (accessed 9.9.21).
  • The United Republic of Tanzania National Audit Office, 2020. Performance Audit Report on the Prevention and Control of Livestock Diseases [WWW Document]. The United Republic of Tanzania National Audit Office. URL https://www.nao.go.tz/uploads/PREVENTION_AND_CONTROL_OF_LIVESTOCK_DISEASES.pdf (accessed 9.9.21).
  • Thirumurthy, H., Lester, R.T., 2012. M-health for health behaviour change in resource-limited settings: applications to HIV care and beyond. Bull World Health Organ 90, 390–392. https://doi.org/10.2471/BLT.11.099317
  • TTEC, 2021. What is Interactive Voice Response (IVR)? [WWW Document]. URL https://www.ttec.com/glossary/interactive-voice-response (accessed 9.9.21).
  • USSD, 2021. Africa’s Talking [WWW Document]. USSD. URL https://africastalking.com/ussd (accessed 11.2.21).
  • Wamwere-Njoroge, G., Long, B., Kihara, A., Bett, B., 2019. Mobile phone-based syndromic surveillance system for early detection and control of livestock diseases. Presented at the Open Access Week Workshop, Nairobi, Nairobi, Kenya, pp. 23–25.
  • Woolhouse, M., 2011. How to make predictions about future infectious disease risks. Philosophical transactions of the Royal Society of London. Series B, Biological sciences 366, 2045–54. https://doi.org/10.1098/rstb.2010.0387
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