Project Summary/Abstract Increased access to cesarean sections (c-sections) has contributed to the decline of maternal mortality in sub- Saharan Africa (SSA); however, as the rate of c-sections has increased, so has the rate of c-section related complications. While women who deliver vaginally in rural SSA often receive postpartum follow-up care in their homes from community health workers (CHWs), most programs require that women who deliver via c-section return to health centers or hospitals for follow-up because of the increased complexity of their care. Facility- based follow-up can be financially catastrophic and physically burdensome for mothers, leading to delays in care and increased risk for morbidity. The overall goal of this proposal is to develop a safe mobile health (mHealth) tool to support CHW-led home- based follow-up for women delivering via c-section in rural Rwanda at postoperative days (PODs) 5 and 10. In the first R21 phase, we will develop a software library for an existing photo-based surgical site infection (SSI) diagnostic algorithm to run locally on a smartphone (without internet or cell network connection) (Aim 1a). We will work with Insightiv Technologies to develop the comprehensive mHealth-CHW tool, including incorporating the SSI diagnostic algorithm software library and integrating three CHW usability assessments into the design phase (Aim 1b). Finally, we will test the usability and acceptability of the new tool in a group of 30 CHWs (Aim 2). When we achieve 80% usability and acceptability, we will continue to the second phase. The R33 phase of the grant will study the validity of the mHealth-CHW tool for c-section follow-up (Aim 3) by prospectively following 450 women delivering via c-section and implementing the mHealth-CHW tool and follow- up in their homes at PODs 5 and 10. The women will then return to the hospital at POD 16 for a physical examination and we will compare diagnoses and complications identified via the mHealth-CHW tool to those from the physical exam. We will then evaluate the time-to-diagnosis for c-section complications by randomizing 1350 women to follow-up by the mHealth-CHW tool versus standard of care (Aim 4). Finally, we will assess the acceptability of mHealth-CHW follow-up in 40 women who have delivered via c-section through focus group discussions (Aim 5). We will also conduct two research training series, one in quantitative methods and one in qualitative methods, to strengthen our team's ability to lead mHealth research in the future.