Verbal Autopsy Manager (VMan3): A comprehensive software tool for managing and improving quality, availability and use of cause of death data from community deaths.

Accurate mortality and cause-of-death (COD) data are critical for informing health policy, guiding resource allocation, and supporting epidemiological surveillance. However, many low- and middle-income countries (LMICs) face persistent challenges in reporting deaths and determining causes of death for deaths occurring outside health facilities, largely due to the absence of robust community-level reporting systems. Verbal Autopsy (VA), which involves interviewing the deceaseds relatives or caregivers to infer COD, provides a feasible alternative in such contexts. Ensuring high-quality data collection and management is essential to derive valid COD outcomes from VAs. This study presents the development of Verbal Autopsy Manager Version 3 (VMan3) - a comprehensive software platform designed to improve the management, analysis, and quality of VA data. VMan3 supports digital COD assignment, integrated data quality assessment, and interoperability with national health information systems. The platform features a modular architecture that supports future scalability. Its backend is developed using Pythons FastAPI framework for high-performance API integration, while the frontend is built with AngularJS to deliver a responsive and interactive user experience. Data storage and retrieval are handled through the ArangoDB open-source database. The initial release of VMan3 includes features such as a dashboard for visualizing VA submissions by month, sex, and age group (neonates, children, adults), a geospatial module for mapping interview locations, a computer-coded verbal autopsy (CCVA) module for automated COD assignment, a physician-coded verbal autopsy (PCVA) module supporting online physician review, a data quality module to assess and improve reliability, and a system settings module for customization and configuration. VMan3 represents a significant step toward strengthening mortality surveillance and data-driven decision-making in LMICs Author SummaryVA instrument consists of structured and semi-structured questions designed to collect information on the deceaseds signs and symptoms, medical history, demographic characteristics, and care-seeking behavior prior to death. Depending on the specific circumstances surrounding each death, the length and complexity of the VA interview can vary, resulting in records with diverse depth and structure. This variability presents challenges for data management, consistency, and quality. Verbal Autopsy Manager Version 3 (VMan3) addresses these challenges by utilizing a document-oriented data model, which allows flexible, schema-less handling of VA records. This approach accommodates the complex and variable nature of VA data, improving the user experience and enabling efficient processing and analysis. VMan3 supports both automated (computer-coded verbal autopsy, CCVA) and physician-led (physician-coded verbal autopsy, PCVA) cause-of-death assignment, while its configurable system settings allow easy adaptation to country-specific needs and workflows. We recommend the adoption of VMan3 by countries and programs implementing VA to strengthen data collection processes and enhance the completeness, accuracy, and availability of mortality statistics essential for informed public health planning and policy.