UPDATED: Syndromic Surveillance 101 - Introduction to R for Health Surveillance

In this 26 minute video, Eric Bakota offers an overview of a free statistical package, R, and an overview of commonly used tips and tricks shared in the surveillance community for analysis work in R.

Objectives:

April 30, 2019

Use of ESSENCE APIs to Support Flexible Analysis and Reporting

The ESSENCE application supports users' interactive analysis of data by clicking through menus in a user interface (UI), and provides multiple types of user defined data visualization options, including various charts and graphs, tables of statistical alerts, table builder functionality, spatial mapping, and report generation. However, no UI supports all potential analysis and visualization requirements.

June 18, 2019

Data capture and visualization for a canine influenza outbreak - New York City, 2018

Data-driven decision-making is a cornerstone of public health emergency response; therefore, a highly-configurable and rapidly deployable data capture system with built-in quality assurance (QA; e.g., completeness, standardization) is critical. Additionally, to keep key stakeholders informed of developments during an emergency, data need to be shared in a timely and effective manner.

June 18, 2019

Dashboards as strategy to integrate multiple data streams for real time surveillance

The mission of the Infectious-Disease-Epidemiology Department at the Robert Koch Institute is the prevention, detection and control of infections in the German population. For this purpose it has a set of surveillance and outbreak-detection systems in place. Some of these cover a wide range of diseases, e.g. the traditional surveillance of about 80 notifiable diseases, while others are specialised for the timely assessment of only one or a few diseases, e.g. participatory syndromic surveillance of acute respiratory infections.

June 18, 2019

On estimation the relative risk of small area and visualization spatio-temporal map

Disease mapping is a method used to descript the geographical variation in risk (heterogeneity of risk) and to provide the potential reason (factors or confounders) to explain the distribution. Possibly the most famous uses of disease mapping in epidemiology were the studies by John Snow of the cholera epidemics in London. Accurate estimation relative risk of small areas such as mortality and morbidity, by different age, ethnic group, interval and regions, is important for government agencies to identify hazards and mitigate disease burden.

June 18, 2019

Developing Mindful and Targeted Data Visualizations for Diverse Audiences

Tennessee has experienced an increase of fatal and non-fatal drug overdoses which has been almost entirely driven by the opioid epidemic. Increased awareness by medical professionals, new legislation surrounding prescribing practices, and mandatory use of the state's prescription drug monitoring program has resulted in a decrease of opioid prescriptions and dosages. Paradoxically, emergency department discharges and inpatient hospitalizations due to opioid overdoses have continued to increase.

June 18, 2019

Dashboard Prototype for Improved HIV Monitoring and Reporting for Indiana

In 2015, ISDH responded to an HIV outbreak among persons using injection drugs in Scott County [1]. Information to manage the public health response to this event and aftermath included data from multiple sources (e.g., HIV testing, surveillance, contact tracing, medical care, and HIV prevention activities). During the outbreak, access to timely and accurate data for program monitoring and reporting was difficult for health department staff. Each dataset was managed separately and tailored to the relevant HIV program area’s needs.

June 18, 2019

Using R Markdown, SQL, and RODBC to Generate Reports

Presented May 31, 2017.

Eric Bakota will go over the results from the survey and then I’ll show a report that we generate at HHD using RMarkdown, SQL, and RODBC. This report uses RODBC to connect to our Electronic Disease Surveillance System (MAVEN) to query data needed for the report. The data are imported to R, where they are processed into the various tables, graphs, charts that are used to generate the report. Automating this report has saved 8-10 hours each month.

September 20, 2017

Metadata Visualization App (MVA) Workgroup

The Metadata Visualization App (MVA) workgroup has been developing a metadata visualization application as part of a proof of concept tool containing jurisdiction specific information on Electronic Health Record (EHR) vendors, EHR  vendor products, aggregate data quality metrics(timeliness, validity and completeness), and facility types participating in syndromic surveillance.

October 31, 2018

Facile Dashboard Creation Using Library of Syndromic Surveillance Visualization Tools

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.

June 19, 2017

Pages

Contact Us

National Syndromic
Surveillance Program

Email:nssp@cdc.gov

The National Syndromic Surveillance Program (NSSP) is a collaboration among states and public health jurisdictions that contribute data to the BioSense Platform, public health practitioners who use local syndromic surveillance systems, Center for Disease Control and Prevention programs, other federal agencies, partner organizations, hospitals, healthcare professionals, and academic institutions.

Site created by Fusani Applications