Surveillance mobile phone
We describe the implementation and evaluation of a large-scale mobile-phone—based system used in the context of rabies surveillance in southern Tanzania. Rabies is a fatal disease that kills thousands of people every year in LMICs, where it is primarily spread by domestic dogs [ 8 ]. Following a bite, human rabies deaths can be prevented through prompt administration of post-exposure prophylaxis PEP , which involves a course of vaccinations administered over several weeks, together with immunoglobulin administration for high-risk exposures [ 9 ].
More proactively, the risk of exposure can be reduced and the disease ultimately eliminated through well-implemented mass vaccination programmes for dogs [ 10 ]. Surveillance typically requires intersectoral collaboration, especially for zoonoses. For example, in the context of rabies, health workers need to report animal bites to veterinary officers to trigger outbreak investigations, and veterinarians need to alert medical authorities to exposure risks from animal rabies cases.
Defining institutional responsibilities for collecting and compiling surveillance information and maintaining effective communication across sectors and hierarchies pose challenges. Solutions that address rabies surveillance needs should therefore have wide applicability across a variety of health applications and other societal needs.
Our mobile-phone—based surveillance system was designed for frontline health workers to report patients seeking PEP or presenting with clinical signs of rabies and for livestock field officers to report mass dog vaccination campaigns and suspected animal cases. Operating routinely since , the system is currently used by over health workers and livestock field officers across health facilities and 26 veterinary offices Fig 1 and supports a WHO-coordinated, government-led rabies control programme across southern Tanzania.
We discuss challenges of the design, development, implementation, and evaluation of this system; how they were overcome; and lessons learned for scaling up mobile-phone—based health mHealth systems in LMICs. In the map, blue dots represent facilities that provide post-exposure prophylaxis PEP and report using the surveillance system large dots represent hospitals, small dots represent health centres.
The map is shaded by population density with wildlife-protected areas in white. The panels illustrate example surveillance data S1 Data from different districts that are annotated on the map by their initials. This project was conceived during an outbreak of rabies in the Kilombero Valley, southern Tanzania, in Subsequent research estimated the burden of rabies in these communities, revealing recurring shortages of PEP, as well as considerable economic costs and barriers to those seeking PEP [ 11 ].
Meetings with district, regional, and national medical and veterinary personnel revealed frustrations at all levels concerning provision of these life-saving vaccinations. We discussed the design and development of a prototype mobile-phone—based system with stakeholders to address the highlighted problems, drawing on experience of previous pilot mHealth projects and developers in East Africa [ 12 , 13 ]. In , the WHO and government of Tanzania secured funding for a large-scale rabies control programme across southern Tanzania, as part of a multi-country initiative [ 14 ].
Existing paper-based surveillance in the health sector was insufficient for timely evaluation of this control programme, whilst surveillance for monitoring rabies control in the veterinary sector was absent. Most health and veterinary facilities in southern Tanzania had no Internet access and unreliable power, but mobile phone network coverage was widespread and local staff already owned phones Fig 2A , S2 Data.
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The system employs a data-entry application openXdata on Java-enabled mobile phones Fig 3 and uses an http protocol to send data to a server running a MySQL database for storage and management. The application only needs to be connected to the remote server for data transfer; user authentication as well as data entry and validation occurs on the mobile phone, where data can be saved until submission. The effects are shown of user B age and C self-reported use of text messaging short message service or SMS , on the standardized time to complete surveillance forms on mobile phones, with boxes shaded in proportion to the sample size in the group S2 Data.
Time to completion in minutes was standardized by computing z-scores by sector, because forms used by health workers for recording bite patients were longer than forms used by livestock field officers to record mass dog vaccination campaigns S3 Table , S1 Text. Additional forms submitted by staff involved in system development and therefore familiar with the mobile phone application were excluded. Mobile phone interface showing form being A completed for an example bite patient and B submitted.
Forms for phone-based data entry largely adopted formats of existing paper registers used in health facilities for reporting bites, PEP use and rabies deaths.
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New forms were designed with livestock officers to report suspect animal cases, diagnostic samples submitted to laboratories, and operational details of vaccination campaigns. Forms were designed to minimize free typing, for example, by using radio buttons for multi-choice selection or drop-down menus Fig 3. The application interface was adapted for local use, with information in the Kiswahili language, and prompts running across the phone screen to assist users [ 15 ].
Forms included an option for users to send feedback. Users from the two sectors were trained together to improve familiarity amongst veterinary and medical officers of their respective roles and responsibilities, then registered and provided with configured phones Fig 3. Prior to deployment, pilot data were collected to check system functioning and were reviewed for quality assurance. Since establishing the system in , we have registered over users from the human and animal health sectors stationed at the four health facilities per district that provide PEP through the control programme and all the district livestock offices.
However, accounting for staff turnover and relocation, we maintain a user base of around active users. In the five years since , 29, reports were submitted. By generating disaggregated and spatially localized data, the surveillance system allows detailed monitoring and evaluation of this large-scale control programme across sectors Fig 1 , S1 Data. Overall, the data show progressive increases in coverage and extent of mass dog vaccinations and also identify gaps in coverage. These shared successes reported through stakeholder meetings have helped to reinforce the benefits of working across sectors and also highlight where action is needed.
For example, the data reveal substantial improvements in health service provision overall, whilst allowing quantification of previously overlooked PEP supply shortages in some locations Fig 1. Feedback sent by users from their phones provided a powerful mechanism for identifying and communicating previously overlooked problems.
Such feedback submitted directly from frontline workers prompted changes to training and the distribution and supply of PEP and phones to underserved areas without PEP access.
More generally, users reported being more aware of rabies and the need to administer PEP to bite victims, suggesting improved service provision. They were also able and frequently did redirect patients to other centres providing PEP when shortages occurred. Comments mostly indicated that livestock officers were satisfied with vaccination campaigns e. With four visits to health facilities over a one-month period required for the full PEP course, compliance of patients is often low, which can have deadly consequences because prevention of rabies is not ensured.
In summary, the system allowed many inadequacies of surveillance systems in LMICs to be addressed [ 17 , 18 ] by providing accurate and timely information to improve health service provision and disease control activities. Furthermore, the system can be adapted far more generally. For example, it has already been modified to monitor maternal health interventions, as well as malaria vector populations elsewhere in Tanzania.
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We used observations of 40 health workers and 27 livestock officers to examine factors affecting system usability and support required. After only ten minutes of training, most users could log on without problems. We considered the observed time to fill in and submit a form as an indicator of usability that captures data entry abilities and need of assistance.
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On first use, users took approximately ten minutes to complete their respective form. Age was a useful alternative predictor of potential difficulties for first-time users Fig 2B. The important role of interface familiarity therefore suggests that employment of more advanced technologies may currently have disadvantages in terms of usability. In case of problems with phones, replacements were issued. A user helpline staffed by surveillance personnel helped users overcome challenges, and helpline logs recorded difficulties encountered.
Occasionally, users were identified as reporting infrequently and were reminded of submission steps, or new users required training due to staff turnover or relocation, but over-the-phone support was usually sufficient. We evaluated case detection capacity of human rabies cases and exposures, timeliness of reporting, and completeness of surveillance according to standard methods [ 19 ]. These differences likely reflect increased recording of bites and PEP administration—which if not available may have led to health workers neglecting to record bites—and increased reporting from local to central levels, as opposed to increased rabies incidence.
Paper records were entirely lacking from some regions despite health workers recalling people dying of rabies and bite victims attending clinics. Physical collation of paper records was often delayed for many months or never occurred, and was stated as a major obstacle for restocking of PEP. Paper records are aggregated to district level on coarse annual timescales, whereas the mobile phone system provides near real-time data at much finer, village-scale spatial resolution, with potential to dramatically improve outbreak detection and response.
Moreover, the implementation of the system generated interest in rabies and strengthened relationships between local health and veterinary workers who had trained together, catalysing contact and even resulting in the carrying out of joint investigations facilitated by phone support from surveillance staff. These investigations identified suspect rabies victims who did not attend medical facilities and would ordinarily not have been recorded as rabies deaths.
However, some users complained about lack of resources for outbreak investigations, sample collection, and shipment, which is an ongoing limitation for rabies surveillance.
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Infrastructure and personnel costs for paper-based surveillance were lower than for the mobile phone-based system, but paper-based surveillance required costly processing and transportation S5 Table. However, care should be taken in extrapolating to other contexts because scale and terrain affect training and distribution costs. Another caveat is that, in practice, paper-based surveillance costs may appear lower simply because many records were never submitted and collated.
http://objectifcoaching.com/components/chesapeake/nouveau-companion-moulinex.php We sought more general feedback through, for example, regular attendance at government meetings to understand stakeholder requirements, and we adapted the system wherever possible, e. User feedback sent via phones revealed potential areas for improvement of rabies prevention and control activities as well as service delivery system shortcomings, whilst stakeholder discussions during a workshop in October led to suggestions for future system development Box 1.
Through the development, implementation, and evaluation of this mobile-phone—based surveillance system in southern Tanzania, we have demonstrated the considerable value and feasibility for mobile technologies to improve health systems, services, and outcomes in LMICs. Frontline health and veterinary workers needed only minimum education and experience to operate the system, with usability mostly affected by their previous level of experience with mobile phones. The system has facilitated ongoing data collection across large programmatic scales, greatly improving data quality, timeliness, completeness, and cost-effectiveness.
The resulting surveillance is being used to evaluate the impacts of ongoing rabies control activities and improve their management, directly informed by the experiences of frontline users. As a result, the system has become an integrated, popular, and valuable tool within the health and veterinary sectors in southern Tanzania. MHealth has been criticised for the proliferation of pilot studies with little coordination and programmatic evidence of effectiveness to inform scale-up [ 3 , 21 , 22 ].
Although the pace of ongoing technical advances is exciting, with mHealth piggybacking on this momentum, the goal for mHealth now is to move beyond pilots to sustainable integration within health systems and culture [ 20 , 23 , 24 ]. Box 1 lists technical and acceptability challenges of large-scale mHealth programmes, possible solutions, and further opportunities for development as drawn from experiences of our system.
For neglected zoonotic diseases, such as anthrax, cystic echinococcus, leishmaniasis, human African trypanosomiasis, Rift Valley fever, and plague, that cause considerable mortality and morbidity in low-income countries, there is a real unmet need for integrated intersectoral surveillance systems, which could be facilitated through shared architecture [ 21 ].
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In Tanzania, there is demand to expand the system to other zoonoses and to further harmonize it within existing health and veterinary systems. Using phones as the building blocks for establishing and maintaining relationships with users can make systems participatory, empowering otherwise isolated frontline workers and, critically, can lead to the improved control and management of disease [ 22 ].
The period of monitoring prior to the SMS intervention was from 1 May to 18 Nov , whilst the period of monitoring during the implementation of SMS reminders was from 19 Nov to 1 July One phone was allocated to each facility clinic or livestock office , but four health workers per clinic and five livestock officers per office were trained. Similarly we did not consider depreciation of capital costs such as vehicles for distributing phones and registers, as we assumed the same assets would be required for both types of surveillance.
Our colleague Dr. Eberhard Mbunda sadly passed away before this work was published. Mbunda was a great champion of rabies control in Tanzania. We wish to honour his memory. Summary Points Surveillance is critical to manage preventative health services and control infectious diseases. Integrated surveillance involving public health, veterinary, and environmental sectors is urgently needed to effectively manage zoonoses and vector-borne diseases.
However, most surveillance in low-income countries is paper-based, provides negligible timely feedback, is poorly incentivised, and results in delays, limited reporting, inaccurate data, and costly processing. The potential of mobile technologies for improving health system surveillance has been demonstrated through small-scale pilots, but large-scale evaluations under programmatic implementation remain rare.
An intersectoral mobile-phone—based system was developed and implemented for rabies surveillance across southern Tanzania. The surveillance system infrastructure is a platform that can be further developed to improve services and deliver health interventions; for example, generating automated personalized text messages SMS to alert patients to their vaccination schedules improved their compliance with regimens. Other interventions targeting patients and health workers can now be implemented easily.
The system has become an integrated, popular, and valuable tool across sectors, used routinely throughout southern Tanzania to evaluate the impacts of rabies control and prevention activities and to improve their management, directly informed by the experiences of frontline users. We discuss challenges encountered during development and deployment, how we overcame these, and our recommendations for scaling up mobile-phone—based health mHealth interventions in low-income countries.
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