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Special Sessions

Special sessions are very small and specialized events to be held during the conference as a set of oral and poster presentations that are highly specialized in some particular theme or consisting of the works of some particular international project. The goal of special sessions (minimum 4 papers; maximum 9) is to provide a focused discussion on innovative topics. All accepted papers will be published in a special section of the conference proceedings book, under an ISBN reference, and on digital support. All papers presented at the conference venue will be available at the SCITEPRESS Digital Library. SCITEPRESS is a member of CrossRef and every paper is given a DOI (Digital Object Identifier). The proceedings are submitted for indexation by SCOPUS, Google Scholar, DBLP, Semantic Scholar, EI and Web of Science / Conference Proceedings Citation Index.


VisConVOD 2024Special Session on Visualizing Contagion / Visualizing Outbreak Data
Chair(s): Andres Colubri

Special Session on Visualizing Contagion / Visualizing Outbreak Data - VisConVOD 2024

Paper Submission: December 21, 2023
Authors Notification: January 9, 2024
Camera Ready and Registration: January 17, 2024


Andres Colubri
University of Massachusetts Chan Medical School
United States

This session is dedicated to applications of data visualization and information design in understanding infectious disease outbreaks. Papers in this session will explore how novel visual representations and algorithms can help to gain insight from complex outbreak datasets. This session welcomes epidemiologists, data scientists, public health experts, and visualization enthusiasts to share breakthroughs, techniques, and innovations in the field. The COVID-19 pandemic brought visualization of outbreak data to the forefront, specially thanks to “situation dashboards” that were shown on the news around the world, but also had several limitations, including data presentation biases, overwhelming complexity, and lack of context. The primary goal of this session is to explore new visualization approaches that could overcome these limitations during future outbreaks.