App/Software

Shahnoza Eshonkhojaeva of Sinostream AB in Sweden will use machine-learning algorithms to predict the amount of medicines and supplies needed at individual health clinics in low-resource settings, and to inform medical stores for delivery. Their approach involves obtaining daily consumption patterns that are recorded on smart paper stock cards at rural health clinics, which requires no training, internet access, or electricity.

T.J. Corcoran of Hemalytics LLC in the U.S. will create a platform incorporating a web portal and smartphone application to track patients and their samples during diagnostic testing in low-resource settings to ensure they receive the results, and in a timely manner. They will develop a suite of mobile health tools for storing encrypted patient and sample data, capturing test results in the laboratory, and notifying patients and health workers of the results. They will test their platform using patients, laboratories, and administrators located in different cities in the U.S.

Sanjay Jain of Johns Hopkins University School of Medicine in the U.S. and colleagues in the U.S. and India will develop a cloud-based platform to record the location, caregiver relationships, and immunization records of infants in developing countries, and provide personalized reminders and incentives via mobile phone to improve the coverage of childhood immunizations. Low immunization coverage has been linked to inaccurate or incomplete records, and the difficulties of encouraging follow-up immunizations and identifying those who miss them.

Sara Grobbelaar of Stellenbosch University in South Africa will develop a platform that can analyze existing real-time data on the stocks of health products at clinics across South Africa and present it to all players in the supply chain to ensure products are available when needed. In partnership with a Northern academic institution they will collect and sort relevant data, analyze trends, and develop decision-making tools.

Oldimeji Oladepo of the University of Ibadan in Nigeria will use mobile phone messaging reminders to encourage parents in Nigeria to complete the full series of routine vaccinations for their children at the recommended times. They will conduct a 10-month study of 1800 mothers with infants aged up to two months at selected health clinics and collect mobile phone numbers also from their families and friends. They will develop a database to store this information and an SMS platform to deliver vaccination reminders, and let them know where they can be obtained and why they are important.

We aim to develop and validate simple, low-cost, low-technology tools to improve community-based identification, referral, and care of premature and jaundiced newborns by frontline health workers.

We will develop a mobile phone application to be used by community health workers in rural, low-resource settings that a) provides local, rapid and accurate risk assessment, referral, and treatment advice for pre-eclampsia, and b) transmits information to referral centers for coordination of triage, transportation and treatment.

Tanvir Huda of ICDDRB in Bangladesh will improve care and nutrition for pregnant women and young children by setting up a system whereby mobile phones are used to receive nutritional information and financial incentives for positive health-related behavior, such as attending clinics. They will perform a pilot study in Bangladesh by recruiting 350 pregnant women, providing them with mobile handsets, and establishing trained health workers who will send weekly nutritional advice and supply nutritional supplements.

Peter Gichangi of the International Centre for Reproductive Health Kenya in Kenya will develop a website for 10 - 24 year olds with HIV to help guide them safely through adolescence and improve adherence to treatment. This age group experiences unique physical and emotional stresses, and for those with HIV, adherence to treatment is relatively low.

Eamonn Keogh from University of California, Riverside in the U.S. will design and test a human computational game for individuals in developing countries to encourage positive behavior such as taking medication or attending school. The game is played on mobile phones, and begins with an automatic prompt to perform a specific healthy behavior, which then requires the individual to respond by sending photographic evidence of the behavior to a randomly selected individual for evaluation, with rewards offered for compliance.