The CART Initiative is a transformative program designed to strengthen Civil Registration and Vital Statistics (CRVS) systems across Africa, Asia and the Pacific by building local research capacity. Through a structured blend of training, mentorship, networking and applied research, CART empowers participants, especially government officials and other CRVS practitioners, to investigate and address real-world challenges in CRVS systems. This hands-on approach not only enhances technical skills but also fosters a deeper understanding of the social, legal, and operational dimensions of CRVS as a cornerstone for sustainable development and inclusive governance.

CART emphasises locally driven research. Participants are encouraged to explore issues that they experience in their day-to-day jobs and are contextually relevant to their countries, ensuring that the research is practical and impactful. The initiative provides access to expert mentors, online learning modules, and peer collaboration, creating a vibrant learning environment that supports innovation and evidence-based policymaking. By focusing on applied research, CART bridges the gap between theory and practice, enabling participants to produce findings that can directly inform CRVS improvements and policy reforms.

CART contributes to the broader goals of the Asia-Pacific CRVS Decade and APAI-CRVS by promoting regional cooperation and knowledge sharing. The initiative not only builds individual capacity but also strengthens institutional frameworks by embedding research into national CRVS strategies. It is inclusive in its design, welcoming participants from diverse backgrounds and countries in Africa, Asia and the Pacific. 

This initiative aims to strengthen the capacity of CRVS practitioners to conduct high quality relevant research. It builds on a successful model implemented previously by the International Union Against Tuberculosis and Lung Disease and Medecins Sans Frontieres to build operational research capacity among health professionals, known as the “SORT-IT” model. While the project will be adapted for the CRVS context, the approach will be similar and incorporate the essential element as identified by Kumar et al. 2020, Zachariah et al. 2020 and Zachariah et al. 2016. Additionally, lessons reflecting the significant advances in elearning in recent years be considered to find the best blend and types of learning to achieve the objectives.

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