Literature DB >> 25005126

Mobile technologies for disease surveillance in humans and animals.

Mpoki Mwabukusi1, Esron D Karimuribo, Mark M Rweyemamu, Eric Beda.   

Abstract

A paper-based disease reporting system has been associated with a number of challenges. These include difficulties to submit hard copies of the disease surveillance forms because of poor road infrastructure, weather conditions or challenging terrain, particularly in the developing countries. The system demands re-entry of the data at data processing and analysis points, thus making it prone to introduction of errors during this process. All these challenges contribute to delayed acquisition, processing and response to disease events occurring in remote hard to reach areas. Our study piloted the use of mobile phones in order to transmit near to real-time data from remote districts in Tanzania (Ngorongoro and Ngara), Burundi (Muyinga) and Zambia (Kazungula and Sesheke). Two technologies namely, digital and short messaging services were used to capture and transmit disease event data in the animal and human health sectors in the study areas based on a server-client model. Smart phones running the Android operating system (minimum required version: Android 1.6), and which supported open source application, Epicollect, as well as the Open Data Kit application, were used in the study. These phones allowed collection of geo-tagged data, with the opportunity of including static and moving images related to disease events. The project supported routine disease surveillance systems in the ministries responsible for animal and human health in Burundi, Tanzania and Zambia, as well as data collection for researchers at the Sokoine University of Agriculture, Tanzania. During the project implementation period between 2011 and 2013, a total number of 1651 diseases event-related forms were submitted, which allowed reporters to include GPS coordinates and photographs related to the events captured. It was concluded that the new technology-based surveillance system is useful in providing near to real-time data, with potential for enhancing timely response in rural remote areas of Africa. We recommended adoption of the proven technologies to improve disease surveillance, particularly in the developing countries.

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Year:  2014        PMID: 25005126     DOI: 10.4102/ojvr.v81i2.737

Source DB:  PubMed          Journal:  Onderstepoort J Vet Res        ISSN: 0030-2465            Impact factor:   1.792


  12 in total

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Authors:  Andrew D Gibson; Ian G Handel; Kate Shervell; Tarryn Roux; Dagmar Mayer; Stanford Muyila; Golden B Maruwo; Edwin M S Nkhulungo; Rachel A Foster; Patrick Chikungwa; Bernard Chimera; Barend M deC Bronsvoort; Richard J Mellanby; Luke Gamble
Journal:  PLoS Negl Trop Dis       Date:  2016-07-14

2.  Experiences in running a complex electronic data capture system using mobile phones in a large-scale population trial in southern Nepal.

Authors:  Sarah Style; B James Beard; Helen Harris-Fry; Aman Sengupta; Sonali Jha; Bhim P Shrestha; Anjana Rai; Vikas Paudel; Meelan Thondoo; Anni-Maria Pulkki-Brannstrom; Jolene Skordis-Worrall; Dharma S Manandhar; Anthony Costello; Naomi M Saville
Journal:  Glob Health Action       Date:  2017       Impact factor: 2.640

3.  Potential use of mobile phones in improving animal health service delivery in underserved rural areas: experience from Kilosa and Gairo districts in Tanzania.

Authors:  Esron D Karimuribo; Emmanuel K Batamuzi; Lucas B Massawe; Richard S Silayo; Frederick O K Mgongo; Elikira Kimbita; Raphael M Wambura
Journal:  BMC Vet Res       Date:  2016-10-07       Impact factor: 2.741

4.  Integrating evidence, models and maps to enhance Chagas disease vector surveillance.

Authors:  Alexander Gutfraind; Jennifer K Peterson; Erica Billig Rose; Claudia Arevalo-Nieto; Justin Sheen; Gian Franco Condori-Luna; Narender Tankasala; Ricardo Castillo-Neyra; Carlos Condori-Pino; Priyanka Anand; Cesar Naquira-Velarde; Michael Z Levy
Journal:  PLoS Negl Trop Dis       Date:  2018-11-29

5.  Integrated Disease Surveillance and Response (IDSR) in Malawi: Implementation gaps and challenges for timely alert.

Authors:  Tsung-Shu Joseph Wu; Matthew Kagoli; Jens Johan Kaasbøll; Gunnar Aksel Bjune
Journal:  PLoS One       Date:  2018-11-29       Impact factor: 3.240

Review 6.  Sources of spatial animal and human health data: Casting the net wide to deal more effectively with increasingly complex disease problems.

Authors:  Kim B Stevens; Dirk U Pfeiffer
Journal:  Spat Spatiotemporal Epidemiol       Date:  2015-05-08

7.  Design Choices for Automated Disease Surveillance in the Social Web.

Authors:  Mark Abraham Magumba; Peter Nabende; Ernest Mwebaze
Journal:  Online J Public Health Inform       Date:  2018-09-21

8.  One million dog vaccinations recorded on mHealth innovation used to direct teams in numerous rabies control campaigns.

Authors:  Andrew D Gibson; Stella Mazeri; Frederic Lohr; Dagmar Mayer; Jordana L Burdon Bailey; Ryan M Wallace; Ian G Handel; Kate Shervell; Barend M deC Bronsvoort; Richard J Mellanby; Luke Gamble
Journal:  PLoS One       Date:  2018-07-26       Impact factor: 3.240

9.  Knowledge, attitude, and use of mHealth technology among students in Ghana: A university-based survey.

Authors:  Prince Peprah; Emmanuel Mawuli Abalo; Williams Agyemang-Duah; Razak M Gyasi; Okwei Reforce; Julius Nyonyo; Godfred Amankwaa; Jones Amoako; Paulinus Kaaratoore
Journal:  BMC Med Inform Decis Mak       Date:  2019-11-12       Impact factor: 2.796

10.  Lessening barriers to healthcare in rural Ghana: providers and users' perspectives on the role of mHealth technology. A qualitative exploration.

Authors:  Prince Peprah; Emmanuel Mawuli Abalo; Williams Agyemang-Duah; Hayford Isaac Budu; Emmanuel Appiah-Brempong; Anthony Kwame Morgan; Adjei Gyimah Akwasi
Journal:  BMC Med Inform Decis Mak       Date:  2020-02-10       Impact factor: 2.796

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