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Updated: Apr 2, 2026

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Channel Allocation and Equity in Preventive Campaigns for Older Adults: Agent-Based Modeling Study.

Jihye Lee1,2, Juyoung Park2, Yuna Kim2

  • 1Seoul National University, Seoul, Republic of Korea.

Journal of Medical Internet Research
|April 1, 2026
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Summary

Personalized preventive campaigns for older adults improve health equity and adoption rates. Agent-based modeling shows tailored strategies outperform broad approaches, optimizing resource allocation for better public health outcomes.

Keywords:
agent-based modelingbudget constraintschannel allocationdistributional equityinfluenza vaccinationloss framingolder adultspreventive campaignsresource allocationstrategic planning

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Area of Science:

  • Public Health
  • Health Communication
  • Computational Social Science

Background:

  • Preventive campaigns for older adults face challenges in resource allocation across media channels.
  • Current strategies often lack explicit criteria for distributional equity or structured planning, potentially widening health disparities.

Purpose of the Study:

  • To develop and apply a data-driven agent-based model (ABM) for strategic planning of preventive campaigns targeting older adults.
  • To compare channel allocation, personalization, and loss framing strategies under budget and equity constraints.

Main Methods:

  • An agent-based model was calibrated using South Korean national survey data on influenza vaccination and health screening.
  • Fifteen campaign scenarios were simulated, varying media channel allocation, budget, personalization strategies, and loss framing.
  • Outcomes included adoption rates, time to adoption, and equity metrics (minimum class-level adoption, 90-10 gap).

Main Results:

  • Personalization strategies significantly improved both adoption rates and equity compared to baseline.
  • In vaccination models, adoption increased, minimum class adoption rose, and the equity gap narrowed.
  • Screening models showed similar improvements in adoption and equity with personalization.

Conclusions:

  • Agent-based modeling can enhance preventive campaign design by integrating explicit equity and budget criteria.
  • Equity-focused personalization and tailored media portfolios improve outcomes and distributional equity for older adults.
  • Prioritizing targeted personalization over undifferentiated channel diversification is recommended for efficiency and equity.