Disease Visualization

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Client

Developed with InSTEDD and the Task Force for Global Health in a project with the link_to 'Public Health Informations Institute', 'http://www.phii.org/', 'aria-label': 'Public Health Informations Institute' for the US Centers for Disease Control and Prevention, the Surveillance Platform’s goal is to simplify access to national notifiable diseases information for the programs in charge of monitoring them.

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Approach

In conjunction with other software development companies, which developed the parsers and processing pipelines for the different formats in which data is currently sent by the States to the CDC, we used our expertise in providing comprehensive visualizations and ease-of-access to different users by building a visualization platform that allowed the consumers of this data to filter, group and compare large amounts of information on the diseases they monitor.

Feedback workshop

One of the highlights of the development was the workshop we organised in PHII with about 25 users from different CDC programs, that allowed us and all parties involved in the project to get a clear picture on the previously unheard needs of these users. We conducted multiple sessions in which we went from the user’s high-level goals to their daily issues with the current system, distilling the multiple features that were to be built into the platform, which had to provide access to information to both tech-savvy and non-technical users.

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Results

We developed an initial open-source pilot which provides customisable visualizations based on geographic and demographic indicators, combined with information from the US Census Bureau to obtain incidence rates.

The pilot also provides the platform administrators permission to grant or restrict access to the different users at CDC, based on the diseases they monitor, and to comply with US policies, relies on both email/password authentication and HSPD-12 compliant Personal Identification Verification via government-issued Smartcards.

Report

Demographic filters and charts help analyze the evolution of disease.

MMWR Tables

Visualization for disease statistics by district and week.

Contributors

Nicolás di Tada Founder

Santiago Palladino Alumni

Valeria Tiffenberg Alumni

Juan Blandini Alumni

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