Online Map Design for Public-Health Decision Makers

Bibliographic Data

ID14701740
AuthorsJonathan Cinnamon (0000-0001-7383-6886, Simon Fraser University, corresponding author), Claus Rinner (0000-0002-3847-5664, Toronto Metropolitan University), Michael D Cusimano (0000-0002-9989-0650), Sean Marshall (0000-0003-1794-6065), Tsegaye Bekele (0000-0002-8735-5941, Injury Prevention Research Office / Keenan Research Centre / Li Ka Shing Knowledge Institute / St. Michael's Hospital / University of Toronto / Toronto / ON / Canada), Tony Hernandez (0000-0003-1276-7316, Toronto Metropolitan University), Richard H Glazier (0000-0002-7952-8320, University of Toronto), Mary L Chipman (University of Toronto)
Year2009
Volume44
Issue4
Pages289-300
Publication date2009-12-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueCartographica The International Journal for Geographic Information and Geovisualization (JOURNAL)
Journal identifiersISSN: 0317-7173 • E-ISSN: 1911-9925
PublisherUniversity of Toronto Press Inc. (UTPress) (PUBLISHER)
DOI10.3138/carto.44.4.289
OpenAlexW2061244579
LanguageEN
Citations received2
References cited24

Injury places a heavy burden on public-health resources that is not distributed evenly in space, making the mapping of injury and its socio-demographic risk factors an effective tool for prevention planning. In a survey of health-related interactive Web mapping applications we found great variation with respect to content, cartography, and technical aspects. Based on the survey results, input from a group of potential end users, cartographic design principles, and data-set requirements, we created a Web site with static, animated, and interactive injury maps. We mapped injury rates and possible socio-demographic risk factors for the City of Toronto. Through the three functionally different types of maps, a variety of ways to explore the same public-health data sets could be demonstrated. The results highlight the practical options available to public-health analysts and decision makers who wish to expand their data-exploration and decision-support tools with a spatial component

Data science · Geography · Public health · Set (abstract data type · Variety (cybernetics · Computer Science · Data-Driven Disease Surveillance · Injury Epidemiology and Prevention · Medicine · Nursing · Traffic and Road Safety · Artificial Intelligence

Tools

Open DOISci-HubOpen Access