Lay-Operator mHealth Network: Real-Time Syndromic Surveillance and Intervention



 DESCRIPTION (provided by applicant): This project explores the development, implementation, and evaluation of a smartphone-/ tablet -based network of village-based, custom-trained, layperson mHealth workers who use simple-to-operate, network-integrated software regularly to report presumptive and medically diagnosed cases of a single illustrative chronic disease: Nodding Syndrome . The long-term goal is to develop a sustainable, inexpensive, monitored, real-time `population-based medical e-geography' and case-based electronic medical record system with which to identify disease hotspots and to mount, as appropriate, rapid diagnosis and treatment , enhanced community education, epidemiological research and long-term health planning. Creation of a cadre of village-based lay mHealth operators who are attracted to a future health-related career (thereby increasing healthcare capacity) is a second long-term goal. Research will be carried out in a rural region of post-conflict northern Uganda where poor nutrition and infectious disease ravage the health of impoverished villagers. Research focus is placed exclusively on Nodding Syndrome (NS), an easily recognizable, chronic, non-communicable childhood disorder of unknown etiology characterized by behavioral changes, including head nodding triggered by eating and other sensory stimuli, retardation of physical and mental development, convulsions and, if untreated, early death.Our pilot study has revealed inordinately long delays (~4 years on average, which we aim to reduce >10-fold) between the time when abnormal behavior (absences, head nodding, and/or convulsions) is first noted by caregivers and medical diagnosis. While treatment is not part of this research proposal, we have shown that appropriate pharmaceutical, nutritional, physical, and educational intervention in a fit-for-purpose facility can dramatically advance the growth and development of affected children, markedly reduce their seizure frequency, and improve cognitive status and learning capacity. We will test whether village-based lay mHealth workers can accurately detect new NS cases, speed their medical diagnosis to activate treatment, and help populate the beginnings of a regional electronic medical record system in Uganda that has been developed, piloted and adopted in neighboring Kenya. Aged 18-25 years, the mHealth workers will reside in the villages they survey and weekly transmit information relating to NS. Electronic tablets will be also be used to collect, enter and download health history into ZidiTM, a DHIS2 integrated central management healthcare information system that has been adopted by the neighboring country of Kenya. Data on NS cases received from mHealth workers and via ZidiTM will be integrated, used to map the disease across the catchment area, and shared with government health authorities. The impact of this program on mHealth workers, medical students, and community health personnel will be evaluated to assess whether a lay-operator mHealth network has utility on a broader scale.