R Shiny

Most surveillance methods in the literature focus on temporal aberration detections with data aggregated to certain geographical boundaries. SaTScan has been widely used for spatiotemporal aberration detection due to its user friendly software interface. However, the software is limited to spatial scan statistics and suffers from location imprecision and heterogeneity of population. R Surveillance has a collection of spatiotemporal methods that focus more on research instead of surveillance.

 Objective

To build an open source spatiotemporal system that integrates analysis and visualization for disease surveillance. 

Public health surveillance largely relies on the use of surveillance systems to facilitate the identification and investigation of epidemiologic concerns reflected in data. In order to support public health response, these systems must present relevant information, and be user-friendly, dynamic, and easily-implementable. The abundance of R tools freely-available online for data analysis and visualization presents not only opportunities but also challenges for adoption in that these tools must be integrated so as to allow a structured workflow. Many public health surveillance practitioners do not have the time available to 1) scavenge for tools, 2) align their functions so as to create a relevant set of visuals, and 3) integrate these visuals into a dashboard that allows a streamlined surveillance workflow. An openly-available, structured framework that allows simple integration of analytic capabilities packaged into readily- implementable modules would simplify the creation of relevant dashboard visuals by surveillance practitioners. 

Objective

A framework and toolbox for creating point-and-click dashboard applications (at no cost) for monitoring several facets of syndromic surveillance data were created. These tools (and associated documentation) are being made available freely online for other surveillance practitioners to adopt. 

To describe the results of the new organization of influenza surveillance in France, based on a regional approach. This regional multi-source approach has been made possible by the sharing of data visualizations and statistical results through a web application. This application helped detecting early the epidemic start and allowed a reactive communication with the regional health authorities in charge of the organization of health care, the management and the setting up of the appropriate preventive measures.