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. 2016 Apr;22 Suppl 1(Suppl 1):i27-33.
doi: 10.1136/injuryprev-2015-041812. Epub 2016 Jan 4.

Data visualisation in surveillance for injury prevention and control: conceptual bases and case studies

Ramon Martinez  1 , Pedro Ordunez  1 , Patricia N Soliz  2 , Michael F Ballesteros  3
Affiliations

Data visualisation in surveillance for injury prevention and control: conceptual bases and case studies

Ramon Martinez et al. Inj Prev. 2016 Apr.

Abstract

Background: The complexity of current injury-related health issues demands the usage of diverse and massive data sets for comprehensive analyses, and application of novel methods to communicate data effectively to the public health community, decision-makers and the public. Recent advances in information visualisation, availability of new visual analytic methods and tools, and progress on information technology provide an opportunity for shaping the next generation of injury surveillance.

Objective: To introduce data visualisation conceptual bases, and propose a visual analytic and visualisation platform in public health surveillance for injury prevention and control.

Methods: The paper introduces data visualisation conceptual bases, describes a visual analytic and visualisation platform, and presents two real-world case studies illustrating their application in public health surveillance for injury prevention and control.

Results: Application of visual analytic and visualisation platform is presented as solution for improved access to heterogeneous data sources, enhance data exploration and analysis, communicate data effectively, and support decision-making.

Conclusions: Applications of data visualisation concepts and visual analytic platform could play a key role to shape the next generation of injury surveillance. Visual analytic and visualisation platform could improve data use, the analytic capacity, and ability to effectively communicate findings and key messages. The public health surveillance community is encouraged to identify opportunities to develop and expand its use in injury prevention and control.

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Figures

Figure 1
Figure 1
The cycle of visual analytics. When people are exploring and analysing data, they enter into a cycle where at any point they may need to skip steps, back up, seek additional data or even start over. Adapted from the cycle of visual analytic diagram.
Figure 2
Figure 2
Visual analytic and visualisation platform high-level system architecture. Diagram adapted from Kimball technical system architecture.
Figure 3
Figure 3
Data preparation workflow. This workflow illustrates data preparation procedures to extract, transform and integrate demographic data from World Population Prospects, UN Population Division and the International Database (IDB), US Census Bureau into the data storage and management component.
Figure 4
Figure 4
Public health surveillance of injury mortality in the region of the Americas, 1999–2013. Interactive visualisation available online http://bit.ly/1VmCt6e.
Figure 5
Figure 5
Geographical distribution of overall injury death rates at state level, USA, 2009–2011. (A) Age-adjusted injury death rates for men. (B) Age-adjusted injury death rates for women.
See this image and copyright information in PMC

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