Mobile technologies for disease surveillance in humans and animals

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.

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

“…African health ministries are fast adopting mHealth solutions to improve disease surveillance timeliness and capture real-time field data for surveillance and case management at the community level [32][33][34]. Tanzania piloted an IDSR reporting system using SMS function and regular phones for report in 2011 [35] and further expanded it to be the national strategy for diseases surveillance using Unstructured Supplementary Service Data (USSD) technology linked with DHIS2 for the immediate reporting for IDSR [33,36,37]. Zambia tried to use DHIS2 mobile to enhance its malaria surveillance in Lusaka district and to improve case management and reporting [38].…”

Integrated Disease Surveillance and Response (IDSR) in Malawi: Implementation Gaps and Challenges for Timely Alert

“…African health ministries are quickly adopting mHealth solutions to improve disease surveillance and health programmes. Tanzania piloted an IDSR reporting system using SMS function and regular phones for report in 2011 [28] and further expanded it to be the national strategy for diseases surveillance using Unstructured Supplementary Service Data (USSD) technology linked with DHIS2 for the immediate reporting for IDSR [29][30][31]. Zambia tried to use DHIS2 mobile to enhance its malaria surveillance in Lusaka district and to improve case management and reporting [32].…”

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

“…There is thus an urgent need for resource-poor settings to implement alternate surveillance systems and although lack of technological resources and infrastructure may preclude the use of novel internet-based surveillance approaches, mobile devices such as the now out-of-date personal digital assistants (PDAs) Shirima et al, 2007;Yu et al, 2009;Seebregts et al, 2009;Dale and Hagen, 2007 and more recently mobile phones (Robertson et al, 2010;Jean-Richard et al, 2014;Thinyane et al, 2010), smartphones (Forsell et al, 2011) and tablet computers, are playing an increasingly fundamental role in the collection and processing of animal and human health surveillance data in resource-poor locations (Betjeman et al, 2013;Chretien et al, 2008;Mwabukusi et al, 2014;Istepanian et al, 2004). This is, in part, a result of the extensive penetration of mobile phone use in developing countries over the last decade; estimated to be 63% in sub-Saharan Africa in 2013 and projected to pass 70% by 2015 (Betjeman et al, 2013).…”

“…Real-time reporting and processing of disease data, followed by rapid transmission of information to decision makers, allows swift action to be taken against possible outbreaks. For example, use of real-time reporting and summarising of surveillance data via mobile devices allowed a potential FMD outbreak in the Ngara district of Tanzania to be rapidly contained (Mwabukusi et al, 2014).…”

“…Unfortunately, mHealth surveillance approaches are not an automatic panacea to the problems associated with data collection in resource-poor settings. The Southern African Centre for Infectious Disease Surveillance (SACIDS; Rweyemamu et al, 2013) used EpiCollect (Aanensen et al, 2009) and ODK (Anokwa et al, 2009) to design an mHealth surveillance strategy incorporating the human, livestock, and wildlife sectors (Karimuribo et al, 2012;Mwabukusi et al, 2014) but reported that for a mobile technology-based disease surveillance system to be effective and sustainable it required three key elements: (i) participatory epidemiological approaches; (ii) form-based reporting; and (iii) resident ICT expertise at the discovery end together with local support for database handling, customized programming, trouble-shooting, and training at the user end (Karimuribo et al, 2012;Mwabukusi et al, 2014).…”