EPHT 101

EPHT 101 is a free online course that was created by the CDC in 2007. It consists of 12 modules with information on biomonitoring, EPHT data, indicators, epidemiology, and more. This course is available to anyone and will provide four continuing education credits upon completion. Participants of this course can log in and out while saving their progress allowing them to take the course at their convenience. To register for this course:

1. Go to www.utah.train.org
2. Log onto UTRAIN or create a free account
3. Search for EPHT 101 or course #1009900
4. Proceed with registration instructions (you will be re-directed to another site).

Newsletters

The Utah Environmental Public Health Tracking Program creates and distributes quarterly newsletters to program stakeholders and any other interested parties. The most recent Tracking Program newsletter is Fall 2010. Click here to see previous newsletters. If you would like to join our newsletter mailing list, email Emily Stembridge.

Fact Sheets, Brochures, Pamphlets, Booklets, and Glossary

• Climate Change and Public Health in Utah (NEW!)
• UEPHT Glossary
• Utah Children And The Environment
• Utah EPHT Fact Sheet
• Utah's Health and Environment Booklet
• Utah EPHT Frequently Asked Questions
• Utah EPHT Pamphlet
• National EPHT Fact Sheet
• National EPHT Data Sources
• National EPHT at a Glance 2007
• Pew Environmental Health Commission Report Summary
• Keeping Track, Promoting Health
• Data Partners Benefits Package
  

Free Analytical Tools

TerraServer and TerraServer Download for ArcGIS
TerraServer-USA is a free online repository of public domain aerial imagery and satellite imagery, formerly known as Microsoft TerraServer. The ArcView tool "TerraServer Download for ArcGIS" provides the user with the ability to download imagery hosted by the Terraserver Server directly into ArcMap.

Space-Time Analysis of Regional Systems (STARS)
Space-Time Analysis of Regional Systems (STARS) is an open source package designed for the analysis of aerial data measured over time. STARS brings together a number of recently developed methods of space-time analysis into a user-friendly graphical environment offering an array of dynamically linked graphical views. It is intended to be used as an exploratory data analysis tool. Written entirely in Python, STARS is cross platform and easy to install and expand.

GeoDa
GeoDa is the latest incarnation of a collection of software tools designed to implement techniques for exploratory spatial data analysis (ESDA) on lattice data. It is intended to provide a user-friendly graphical interface to methods of descriptive spatial data analysis, such as autocorrelation statistics and indicators of spatial outliers. The design of GeoDa consists of an interactive environment that combines maps with statistical graphics, using the technology of dynamically linked windows. The current software is freestanding. Runs on Windows OS.

GeoR
GeoR is a package to perform geostatistical data analysis and spatial prediction, expanding the set of currently available methods and tools for analysis of spatial data in R. It has been developed at the Department of Mathematics and Statistics, Lancaster University, UK.

SaTScan
SaTScan is a free software that analyzes spatial, temporal, and space-time data using the spatial, temporal, or space-time scan statistics. It is designed for any of the following interrelated purposes: to perform geographical surveillance of disease; to detect spatial or space-time disease clusters; and to see if they are statistically significant; to test whether a disease is randomly distributed over space, over time, or over space and time; to evaluate the statistical significance of disease cluster alarms; and to perform repeated time-periodic disease surveillance for early detection of disease outbreaks.

WinBUGS
WinBUGS is part of the BUGS project, which aims to make practical MCMC methods available to applied statisticians. The BUGS (Bayesian inference Using Gibbs Sampling) project is concerned with flexible software for the Bayesian analysis of complex statistical models using Markov chain Monte Carlo (MCMC) methods.

DMAP 4
DMAP 4 is a computer program that enables a user to apply spatial filtering methods to any study region. The program was written and is maintained by Qiang Cai, Ph.D. (2007) Department of Geography, the University of Iowa. The program takes geocoded disease and population data as input and computes disease rate measures at grid points on a predefined spatial grid.

R+Packages
In computing, R is a programming language and software environment for statistical computing and graphics. It is an implementation of the S programming language with lexical scoping semantics inspired by Scheme. R was created by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand, and is now developed by the R Development Core Team. The R language has become a de facto standard among statisticians for the development of statistical software.