The Mobile WACh RCT demonstrates that SMS improved practice of exclusive breastfeeding and early postpartum contraception.

In low-income regions, mobile phone-based tools can improve the scope and efficiency of field health workers. They can also address challenges in monitoring and supervising a large number of geographically distributed health workers. Several tools have been built and deployed in the field, but little comparison has been done to help understand their effectiveness. This is largely because no framework exists in which to analyze the different ways in which the tools help strengthen existing health systems. In this article we highlight 6 key functions that health systems currently perform where mobile tools can provide the most benefit. Using these 6 health system functions, we compare existing applications for community health workers, an important class of field health workers who use these technologies, and discuss common challenges and lessons learned about deploying mobile tools.

A growing body of HCI4D research studies the use of SMS communication to deliver health and information services to underserved populations. This paper contributes a novel dimension to this field of study by examining if a hybrid computer-human SMS system can engage pregnant women in Kenya in health-related communication. Our approach leverages the different strengths of both the computer and the human. The computer automates the bulk-sending of personalized messages to patients, allowing the human to read patients' replies and respond to those in need of attention. Findings from a 12-month deployment with 100 women show that our approach is capable of engaging the majority of participants in health-related conversations. We show that receiving messages from the system triggers participant communication and the amount of communication increases as participants approach their expected due date. In addition, analysis of participants' messages shows that they often contain sensitive health information conveyed through a complex mixture of languages and 'txting' abbreviations, all of which highlight the benefits of including a human in the workflow. Our findings are relevant for HCI researchers and practitioners interested in understanding or engaging underserved populations.

Background Lifelong antiretroviral therapy (ART) (Option B+) is recommended for all HIV-infected pregnant/postpartum women, but high adherence is required to maximize HIV prevention potential and maintain maternal health. Mobile health (mHealth) interventions may provide treatment adherence support for women during, and beyond, the pregnancy and postpartum periods. Methods and Design We are conducting an unblinded, triple-arm randomized clinical trial (Mobile WACh X) of one-way short message service (SMS) versus two-way SMS versus control (no SMS) to improve maternal ART adherence and retention in care by 2 years postpartum. We will enroll 825 women from Nairobi and Western Kenya. Women in the intervention arms receive weekly, semi-automated motivational and educational SMS and visit reminders via an interactive, human-computer hybrid communication system. Participants in the two-way SMS arm are also asked to respond to a question related to the message. SMS are based in behavioral theory, are tailored to participant characteristics through SMS tracks, and are timed along the pregnancy/postpartum continuum. After enrollment, follow-up visits are scheduled at 6 weeks; 6, 12, 18, and 24 months postpartum. The primary outcomes, virological failure (HIV viral load ≥1000 copies/mL), maternal retention in care, and infant HIV-free survival, will be compared in an intent to treat analysis. We will also measure ART adherence and drug resistance. Discussion Personalized and tailored SMS to support HIV-infected women during and after pregnancy may be an effective strategy to motivate women to adhere to ART and remain in care and improve maternal and infant outcomes.

No abstract

No abstract

Design space exploration during high-level synthesis is often conducted through ad hoc probing of the solution space using some scheduling algorithm. This is not only time consuming but also very dependent on designer's experience. We propose a novel design exploration method that exploits the duality of time-and resource-constrained scheduling problems. Our exploration automatically constructs a time/area tradeoff curve in a fast, effective manner. It is a general approach and can be combined with any high-quality scheduling algorithm. In our work, we use the max-min ant colony optimization technique to solve both time-and resource-constrained scheduling problems. Our algorithm provides significant solution-quality savings (average 17.3% reduction of resource counts) with similar runtime compared to using force-directed scheduling exhaustively at every time step. It also scales well across a comprehensive benchmark suite constructed with classic and real-life samples.

Systematic interviewer error is a potential issue in any health survey, and it can be especially pernicious in low-and middleincome countries, where survey teams may face problems of limited supervision, chaotic environments, language barriers, and low literacy. Survey teams in such environments could benefit from software that leverages mobile data collection tools to provide solutions for automated data quality control. As a first step in the creation of such software, we investigate and test several algorithms that find anomalous patterns in data. We validate the algorithms using one labeled data set and two unlabeled data sets from two community outreach programs in East Africa. In the labeled set, some of the data is known to be fabricated and some is believed to be relatively accurate. The unlabeled sets are from actual field operations. We demonstrate the feasibility of tools for automated data quality control by showing that the algorithms detect the fake data in the labeled set with a high sensitivity and specificity, and that they detect compelling anomalies in the unlabeled sets.