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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Jun 7, 2025
Date Accepted: Jan 13, 2026

The final, peer-reviewed published version of this preprint can be found here:

Framing the Convergence of One Health and Digital Health in the Global South With a Gender-Sensitive Foresight Perspective: Delphi Study Using Latent Semantic Analysis

Kong J, Bragazzi NL

Framing the Convergence of One Health and Digital Health in the Global South With a Gender-Sensitive Foresight Perspective: Delphi Study Using Latent Semantic Analysis

J Med Internet Res 2026;28:e78702

DOI: 10.2196/78702

PMID: 41707187

PMCID: 12961381

Framing the Convergence of One Health and Digital Health in the Global South: A Gender-Sensitive Foresight Perspective Using Latent Semantic Analysis

  • Jude Kong; 
  • Nicola Luigi Bragazzi

ABSTRACT

Background:

The convergence of Digital Health and One Health represents an emergent paradigm in global health governance. While widely discussed in high-income settings, there is limited understanding of how this convergence is conceptualized in the Global South, particularly when viewed through a gender- and equity-sensitive foresight lens.

Objective:

To map and classify expert discourse on Digital Health, One Health, and their convergence in the Global South using Latent Semantic Analysis (LSA), with particular attention to structural drivers, emerging issues, weak signals, and gendered patterns of anticipation.

Methods:

A three-round online Delphi survey was conducted with 45 experts from 19 countries across the Global South. Open-ended responses were analyzed using LSA and stratified by gender. A foresight framework was applied to categorize topics as structural drivers, emerging issues, or weak signals, based on their temporal persistence, salience, and consensus.

Results:

In Digital Health, structural drivers included the systemic integration of digital technologies into public health systems, strategic alignment, and infrastructure development. Emerging issues comprised the adoption of artificial intelligence, chronic disease management via mobile health (mHealth), and concerns about digital inclusion and interoperability. Weak signals included feminist digital ethics, trust in digital systems, and relational accountability—more frequently emphasized by female experts. In One Health, structural drivers were centered on intersectoral coordination, ecological integration, and the institutionalization of health-environment frameworks. Emerging issues encompassed anticipatory risk governance, food system sustainability, and the integration of environmental and population-level data. Weak signals included indigenous knowledge systems, sub-national antimicrobial resistance (AMR) governance, and structural underinvestment in ecological public health, with gendered divergence in framing. In the convergence discourse (Digital Health and One Health), structural drivers focused on the integration of digital surveillance systems, data infrastructures, and health information platforms to operationalize One Health. Emerging issues included climate-triggered system redesign, AI and ecological monitoring, and the governance of cross-sectoral data. Weak signals pointed to algorithmic bias in zoonotic prediction, digital sovereignty in environmental health, and feminist critiques of convergence—all thematically rich but peripheral in consensus.

Conclusions:

This study revealed a multi-layered and gender-influenced foresight architecture shaping the future of Digital Health and One Health in the Global South. Structural drivers denote maturing domains of implementation, while emerging issues and weak signals highlight latent, often overlooked opportunities and tensions. Incorporating equity-sensitive and gender-aware foresight methods is essential for crafting inclusive and anticipatory health governance strategies.


 Citation

Please cite as:

Kong J, Bragazzi NL

Framing the Convergence of One Health and Digital Health in the Global South With a Gender-Sensitive Foresight Perspective: Delphi Study Using Latent Semantic Analysis

J Med Internet Res 2026;28:e78702

DOI: 10.2196/78702

PMID: 41707187

PMCID: 12961381

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