Reimagining vaccine advocacy: a digital health and policy perspective to overcome HPV hesitancy

Abstract

Vaccines have eliminated once-deadly diseases, yet rising vaccine hesitancy threatens these gains. Human papillomavirus (HPV) illustrates this crisis: Although it is one of the few vaccines that directly prevents cancer, uptake remains low in the United States and globally, particularly in regions with high cervical cancer incidence. This persistent gap undermines both individual and public health. This paper examines how digital health technologies, aligned with policy frameworks and community engagement, can address HPV vaccine hesitancy. We propose the Digital Vaccine Advocacy Toolkit, a structured, HPV-focused framework that integrates electronic health record (EHR)-based clinical decision support, personalized reminders, population dashboards, AI-driven misinformation surveillance, and culturally tailored education. As a conceptual model, it draws on secondary evidence and policy recommendations rather than original empirical data, emphasizing interoperability, privacy safeguards, equity-driven design, and stakeholder engagement to support feasibility across diverse health systems. The Toolkit is organized into illustrative workflows that demonstrate how technical features could be combined with policy mechanisms and financing models to strengthen HPV vaccination. By situating HPV within the World Health Organization’s 90-70-90 elimination targets and the recent adoption of single-dose schedules, the framework highlights both translational relevance and global applicability, though its recommendations require pilot testing and empirical validation. Overall, the Digital Vaccine Advocacy Toolkit offers a practical roadmap for improving HPV vaccine uptake through the integration of technology, policy, and ethics, and provides a transferable model for advancing digital health strategies to increase vaccine confidence and equity in immunization programs worldwide.

Keywords

digital health / vaccine hesitancy / human papillomavirus / electronic health records / clinical decision support / artificial intelligence / public health policy

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