Making Report-Quality Plots in R with Low-to-Moderate Coding Experience

Presented May 26, 2016.

Eric Bakota will go over Hadley Wickham’s ‘ggplot2’ package using the same grammar of graphics framework outlined in Wickham’s 2010 paper on the subject. This webinar will discuss how to create a plot by looking at the components that make up its overall structure. It will also go into how these graphics can be integrated into RMarkdown to create an automated report that is visually appealing.

September 20, 2017

Use of R for Visual Display of Public Health Data

Presented January 19, 2016.

This presentation will briefly introduce concepts related to effective visual display and a “big picture” of why and how R is an excellent tool to produce such displays. Through examples, the overall mechanics for producing visuals in R will be shown, as will some “nuts and bolts” details (e.g. the use of color). Methods for creating reproducible (e.g. with user made functions) and interactive (e.g. with the Shiny package) displays will be shown.

September 20, 2017

Integrating R into ESSENCE to Enable Custom Data Analysis and Visualization

The use of R is increasing in the public health disease surveillance community. The ISDS pre-conference workshops and newly formed R Group for Surveillance have been well attended and continue to grow in popularity. The use of R in the National Syndromic Surveillance Program (NSSP) has also been of value to many users who wish to analyze and visualize public health data using custom R scripts.

October 10, 2017

Alert-Enabled Application Integrating Data Quality Monitoring for Multiple Sources

Data sets from disparate sources widely vary in the number and type of factors which most hamper integrity and timeliness of the data. To maintain high quality data, data sets must be regularly assessed, particularly for those vulnerabilities that each is especially prone to due to the methods involved in collecting the data. For surveillance practitioners charged with monitoring data from multiple data sources, keeping track of the issues that each data set is susceptible to, and quickly identifying any inconsistencies or deviations from normal trends, may be a challenge.

August 07, 2017

An R Script for Assessment of Data Quality in the BioSense Locker Database

Syndromic surveillance requires reliable, accurate, and complete healthcare encounter data to assess patterns of illness and respond to public health events. Illinois implemented syndromic surveillance statewide in response to Meaningful Use reporting objectives. To address the need for continuous, automated assessment following initial on-boarding of facility Emergency Department data, we developed an R script to assess the quality of data in the private BioSense locker database.

August 23, 2017

Enhancing EpiCenter Data Quality Analytics with R

The EpiCenter syndromic surveillance platform currently uses Java libraries for time series analysis. Expanding the data quality capabilities of EpiCenter requires new analysis methods. While the Java ecosystem has a number of resources for general software engineering, it has lagged behind on numerical tools. As a result, including additional analytics requires implementing the methods de novo.

August 29, 2017

Aberration Detection in Public Health Surveillance using the R package surveillance

Presented September 21, 2015.

This session is about the surveillance R package as a tool for performing prospective outbreak detection in routine collected surveillance data. Michael Höhle will discuss the data structure, invocation of implemented outbreak detection methods as well as visualization. Finally, he shall give a small outlook to handling reporting delays (nowcasting & delay-adjusted outbreak detection). Focus of the session will be on problems and R code and, hence, less on the statistical methods.

September 21, 2017

How to Develop a Simple Shiny App

Recording of R-Group Meeting from February 26, 2015 -  Jarad Niemi and Nick Michaud discuss how to develop a simply shiny app using R.

September 20, 2017

Digital Disease Detection Dashboard: Rapid Detection & Outbreak Management Tool

Booz Allen Hamilton is developing a novel bio-surveillance prototype tool, the Digital Disease Detection Dashboard (D4) to address the questions fundamental to daily biosurveillance analysis and decision making: is something unusual happening (e.g., is an outbreak or novel disease emerging)?, What is the probability that what I’m seeing is by chance?, How confident am I that this data is really detecting a signal?, Why is this happening and can I explain it?; and How many cases should I expect? (e.g., magnitude of event over time).

October 05, 2017

Vetsyn: Veterinary Syndromic Surveillance Streamlined into one R Package

To describe an R package that was designed to provide ready implementation of veterinary syndromic surveillance systems, from classified data to the generation of alerts and an html interface.


November 30, 2017


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