Tuberculosis

Qian Gao of Shanghai Medical College Fudan University in China, working with Clif Barry of The National Institute of Allergy and Infectious Diseases in the U.S., will support a clinical trial to shorten the treatment time for tuberculosis (TB) from six months to four months by helping to identify predictive biomarkers in individuals that only require the shorter treatment. Shortening treatment when possible will substantially reduce costs and the emergence of drug resistance which is a major barrier to eradicating this deadly disease.

Provide a very low-cost, automated reminder/drug-dispensing machine through "missed call" signals that also allows phone calls between patients and clinics, free of charge to patients, in order to enable patients to manage their disease effectively.

Ann Don Bosco of Good Business in the United Kingdom will run a prevention campaign to reduce the transmission of tuberculosis by making coughing without covering your mouth socially unacceptable. Tuberculosis is a major problem in developing countries, particularly in South Africa, and is primarily spread by coughing. Previous cough prevention campaigns have focused on changing the behavior of the infected person. However, healthy individuals should be more willing to promote preventative behavior in order to avoid becoming infected.

Andrew Cross of Microsoft Research India in India will try to improve adherence to tuberculosis medication in India by evaluating an inexpensive approach combining personalized pill packaging with mobile phones to report when medication has been taken and to receive reminders. Less than half of people with chronic diseases take their medication correctly. And for diseases like tuberculosis this can lead to drug-resistance, which is a serious problem. Solutions such as the electronic pillbox have been successful, but are expensive.

Carlton Evans of Asociacion Benefica PRISMA in Peru will use conditional cash incentives to encourage individuals in poor communities that have been newly diagnosed with tuberculosis to help identify neighboring tuberculosis sufferers and encourage them and their families to receive treatment. Effective treatments exist for most forms of tuberculosis, but reaching the poor and most vulnerable individuals has proven challenging.

Janardan Suresh and team are building a mobile-based application to improve TB adherence. The system, called TB Prasakti, involves SMS-based reminder and follow up, automated telephone reminder and follow up, and a total patient information system, which ensures maximum utilization of technology for TB. It provides for easy scalability and affordability and provides a "single window" to capture, store, remind, follow up and generate reports, thus ensuring a comprehensive and all-encompassing solution.

Manjari Deb and team are developing a small, electronic pill dispenser called the CoxBox that enables real-time tracking of patient treatment adherence and inventory. The CoxBox innovation provides a relatively inexpensive and easily implementable solution for action-oriented monitoring and controlling of anti-tubercular drug adherence through the use of a microcontroller-based electromechanical pill box with programmable alarm annunciator and a built-in mobile device.

Krishna Swamy and team are building a comprehensive tuberculosis (TB) mobile application to improve TB detection, treatment, and adherence. The team will build upon its open-source, mobile health (mHealth) platform CommCare and predeployed CommCare mobile applications for TB in India to develop a comprehensive, SMS-enabled mobile application for TB detection, treatment, and adherence.

Anuradha Lele and team from CDAC are building an integrated SMS and voice calling solution, which involves mobile-based applications with forms to register patients, a lab form for sputum examinations, IVRS/missed call reminders, and a patient monitoring application for doctors and DOTS workers. The system also plans to include next of kin and friends to enable seamless monitoring of drug intake of the patient.