A global analysis of national cardiovascular disease control plans using a multi-agent artificial intelligence model
Abstract
Cardiovascular diseases cause nearly one-third of global deaths, yet standalone National Cardiovascular Disease Control Plans remain uncommon and inconsistently structured. We assessed the comprehensiveness of recent national plans using a validated health-systems framework and a multi-agent artificial intelligence model.
Introduction
Cardiovascular diseases (CVDs) are the leading cause of death globally, accounting for an estimated 19.8 million deaths annually and 32% of all global mortality in 2023 [1–3]. Although this burden is widespread, differences in demographics, economic conditions, and health-system capacity create substantial disparities in how CVDs are prevented, diagnosed, treated, cared for, and rehabilitated worldwide
Methods
National cardiovascular disease control plan collection
We identified the most recent official NCVDCP for each country by searching the WHO NCD Document Repository [15], WHF resources [6], and government websites. Inclusion was limited to CVD specific national plans in any language. We excluded broader NCD plans with CVD components, sub-national plans, draft documents, and superseded versions.
Results
Plan characteristics
We identified 45 NCVDCPs outlined in Table 2. The majority originated from high-income countries (n = 27), followed by upper-middle-income (n = 10), lower-middle-income (n = 6), and low-income countries (n = 2). Geographically, the plans were predominantly from the European region (n = 22, 48.9%), with limited representation from the Americas (n = 8), Africa (n = 4), the Western Pacific (n = 4), the Eastern Mediterranean (n = 5), and South-East Asia (n = 2).
Discussion
The validated 11-element, 69-sub-element framework constitutes a reusable policy instrument applicable to national CVD planning assessment independent of the computational pipeline described here. It was developed through systematic literature review and two-stage Delphi consensus with 42 specialists. Our analysis of 45 NCVDCPs indicates that while high-level strategic vision is often present, the financing, governance and operational architecture required to execute that vision is frequently under-specified. A median overall comprehensiveness score of 1.20/5 reveals a substantial gap between the scale of the global CVD burden and the granularity of national planning documentation.
Conclusion
Acknowledgments
Members of CVD Control Collaborative
Note: Stage One: 42 completed questionnaires (participants not listed elected to remain anonymous), Stage Two: 16 participants (participants not listed elected to remain anonymous).
Human Review of LLM
Completed by Dr Aminu Osman Alem, Maia Cullen, and Brooke Forde from the Harvard University Health Systems Innovation Lab
Citation: Pearson H, Kumar CJ, Reddy CL, LeBlanc ER, Atun R, With the CVD Control Collaborative (2026) A global analysis of national cardiovascular disease control plans using a multi-agent artificial intelligence model. PLOS Digit Health 5(6): e0001447. https://doi.org/10.1371/journal.pdig.0001447
Editor: Cleva Villanueva, Instituto Politécnico Nacional Escuela Superior de Medicina: Instituto Politécnico Nacional Escuela Superior de Medicina, México
Received: January 13, 2026; Accepted: May 5, 2026; Published: June 1, 2026
Copyright: © 2026 Pearson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The national cardiovascular disease control plans analysed in this study are publicly available through the World Health Organisation Noncommunicable Disease Document Repository (https://extranet.who.int/ncdccs/documents/) and government websites. The scoring dataset and human validation data have been deposited in the Harvard Dataverse and are available at https://dataverse.harvard.edu/dataverse/NCVDCP_Analysis.
Funding: This work was supported by Harvard University (to HP, CLR, ERL, RA). CK was supported by funding from the Virchow Foundation to the Global Health Policy Lab Initiative. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: RA reports institutional grants from Novo Nordisk, the Virchow Foundation, and the Bill & Melinda Gates Foundation, and honoraria from Merck & Co, all unrelated to the submitted work. HP, CLR, CK, and ERL declare no competing interests.
