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Background Immunization supply chains (iSCs) move vaccines from manufacturer to point of use with the added complexities of requiring cold chain and an increasing need for agility and efficiency to ensure vaccine quality and availability. Underperforming iSCs have been widely acknowledged as a key constraint to achieving high immunization coverage rates in low- and middle-income countries. This paper details the system design approach used to analyze the iSC network in Sierra Leone, Madagascar, Niger and Guinea and documents six lessons. Methodology Between 2018 and 2020, these countries implemented the system design approach, involving four key steps: (1) advocate and introduce to engage stakeholders and prioritize identification of modeling scenarios; (2) collect data and plan analysis through document review and key informant interviews; (3) analyze system design scenarios using computer software modeling tools (LLamasoft’s Supply Chain Guru and AnyLogic's AnyLogistix) for optimization and simulation modeling as well as further analysis with Excel, Google maps, and OpenStreetMap; and (4) build consensus on optimized model and implementation roadmap using the Traffic Light Analysis tool and building on stakeholder input. Findings Key lessons include the following: (1) define system design objectives based on country priorities; (2) establish consensus with stakeholders on scenarios to model; (3) modeling provides the evidence but not the answer; (4) costs should not be weighted above other decision criteria; (5) data collection—work smarter, not harder; (6) not all questions can be answered with a computer model. Discussion A system design approach can identify changes to the design of the supply chain that can introduce efficiencies and improve reliability. This approach can be more effective when these lessons and principles are applied at the country level. The lessons from these four countries contribute to global thinking and best practices related to system design. The modeling and system design approach provides illustrative results to guide decision-makers. It does not give a "final answer", but compares and contrasts.

We describe our experiences integrating ODK Scan into the community health worker (CHW) supply chain in Mozambique. ODK Scan is a mobile application that uses computer vision techniques to digitize data from paper forms. The application automatically classifies machine-readable data types, like bubbles and checkboxes, and assists users with the manual entry of handwritten text and numbers. We designed an intervention that uses paper forms in conjunction with ODK Scan to monitor CHW usage of essential health commodities, finding that the application is capable of providing supervisors and stakeholders with important information regarding health commodity availability in the field. Specifically, we (1) detail our experiences integrating ODK Scan into the health worker supply chain in Mozambique, with particular emphasis on the critical (and often under-reported) role of practitioners; (2) evaluate the impact of the technology at multiple levels of the information hierarchy, providing quantitative and qualitative data that exposes the benefits, challenges and limitations of the technology; and (3) share lessons learned and provide actionable guidance to researchers and practitioners interested in ODK Scan or other systems that bridge the gap between paper-based and digital data collection.