Effective public health responses require timely access to diverse information and a holistic understanding of the situation. This paper describes a community-centered framework for developing a multi-modal visualization and analytical tool that integrates disparate data sources such as epidemiological data, wastewater surveillance data, and social media sentiment analysis into a unified platform. Our focus is on creating a user-friendly experience that empowers both the public and experts to monitor, analyze, and respond to public health events. We also present the results of our initial evaluation, including an effectiveness and usability assessment based on a survey of over 1,600 participants, demonstrating the platform’s potential to enhance public health communication, decision-making, and overall situational awareness.

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A Multi-modal Data-Driven Dashboard for Enhanced Public Health Surveillance and Awareness

  • Kiana Lesan Pezeshki,
  • Sepinood Haghighi,
  • Farzaneh Jouyandeh,
  • Sarvnaz Sadeghi,
  • Pooya Moradian Zadeh,
  • Jackie Fong,
  • Kendall Soucie,
  • R. Michael McKay,
  • Kenneth K. S. Ng,
  • Lisa A. Porter,
  • Yufeng Tong,
  • Lawrence Goodridge

摘要

Effective public health responses require timely access to diverse information and a holistic understanding of the situation. This paper describes a community-centered framework for developing a multi-modal visualization and analytical tool that integrates disparate data sources such as epidemiological data, wastewater surveillance data, and social media sentiment analysis into a unified platform. Our focus is on creating a user-friendly experience that empowers both the public and experts to monitor, analyze, and respond to public health events. We also present the results of our initial evaluation, including an effectiveness and usability assessment based on a survey of over 1,600 participants, demonstrating the platform’s potential to enhance public health communication, decision-making, and overall situational awareness.