Cody Dunne, Michael J. Muller, N. Perra, Mauro Martino
{"title":"VoroGraph: Visualization Tools for Epidemic Analysis","authors":"Cody Dunne, Michael J. Muller, N. Perra, Mauro Martino","doi":"10.1145/2702613.2725459","DOIUrl":null,"url":null,"abstract":"Epidemiologists struggle to integrate complex information about the incidence and spread of disease, in relation to population density and other demographic conditions, at geographical scales ranging from global air travel down to local commuting. A partial solution overlays air travel as arcs above color-coded maps. However, commuting is not shown and it is often challenging to understand changing relationships due to the visual complexity arcs introduce. Moreover, when region sizes and shapes vary their color-codings become difficult to perceive. We introduce three visualizations which combine representations of population, movement, and disease spread at a local scale that is consistent with a zoomable global scale: (1) a map with commuting border encodings, (2) a centroidal Voronoi tessellation morphing technique, and (3) a meta-layout showing commuting alongside air travel. Our work provides mid-level abstractions that expert epidemiologists can use for insights into contagion.","PeriodicalId":142786,"journal":{"name":"Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2702613.2725459","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
Abstract
Epidemiologists struggle to integrate complex information about the incidence and spread of disease, in relation to population density and other demographic conditions, at geographical scales ranging from global air travel down to local commuting. A partial solution overlays air travel as arcs above color-coded maps. However, commuting is not shown and it is often challenging to understand changing relationships due to the visual complexity arcs introduce. Moreover, when region sizes and shapes vary their color-codings become difficult to perceive. We introduce three visualizations which combine representations of population, movement, and disease spread at a local scale that is consistent with a zoomable global scale: (1) a map with commuting border encodings, (2) a centroidal Voronoi tessellation morphing technique, and (3) a meta-layout showing commuting alongside air travel. Our work provides mid-level abstractions that expert epidemiologists can use for insights into contagion.