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Visual Communication of Public Health Data: A Scoping Review

Michael Arthur Ofori1*, Stella Lartey1, Polina Durneva2, Niharika Jha1, Nidhi Mittal1, Nichole Saulsberry-Scarboro1, Michelle Taylor3, Ashish Joshi1

*Corresponding author: Michael Arthur Ofori (E-mail: mofori@memphis.edu)

Affiliation

  1. University of Memphis School of Public Health, Memphis, TN
  2. University of Memphis, Fogelman College of Business & Economics, Memphis, TN
  3. Shelby County Health Department, Memphis, TN

ABSTRACT

Introduction: By 2024, the U.S. government investment in health data and data accessibility will reach $19.9 billion. Despite the effort, health data are not entirely accessible and understood due to data sharing and visualization challenges. Visual communication challenges have created public health information gaps which are compounded in emergencies such as the COVID-19 pandemic, and potentially impacting poor health outcomes and increasing health inequities. Using the right data visualization techniques and tools for public health data communication has therefore become essential.
 
Objective: To examine visualization techniques and tools effective for public health visual data communication.

Methods: A scoping review was conducted to summarize the available evidence related to visualization, techniques, and tools for public health visual data communication as well as related principles and best practices. Original research articles from PubMed databases from 2020 -2024 were included.

Results: Twenty-eight published studies were included. Categorical data were mostly visualized using pie- and various variants of bar charts; continuous variables, mostly with line graphs, dot plots, box and whisker plots, and histograms; and the spread of disease as well as identifying spatial clustered patterns of incidence were visualized using geographic maps, e.g., choropleth and hotspot maps.

Conclusion: Most health data were presented visually with charts and figures, interactive dashboards, and geographic maps using ArcGIS, Tableau, D3.js, ggplot2, and plotly dash framework. The usage of the appropriate visualization techniques and tools for the right data improves comprehension, reduces public health information gaps, and potentially reduces poor health outcomes.

Keywords: Visual communication, Interactive dashboards, Data visualization, Health Data