CIRAS News, Fall 2013, Vol. 49, no. 1

CIRAS is to enhance the performance of Iowa industry, and associated entities, through education and technology-based services. This newsletter holds information regarding these services.

CIRAS News, Spring 2013, Vol. 48, no. 3

CIRAS is to enhance the performance of Iowa industry, and associated entities, through education and technology-based services. This newsletter holds information regarding these services.

CIRAS News, Summer 2013, Vol. 48, no. 4

CIRAS is to enhance the performance of Iowa industry, and associated entities, through education and technology-based services. This newsletter holds information regarding these services.

CIRAS News, Winter 2013, Vol. 49, no. 2

CIRAS is to enhance the performance of Iowa industry, and associated entities, through education and technology-based services. This newsletter holds information regarding these services.

CIRAS News, Fall 2014, Vol. 50, no. 1

CIRAS is to enhance the performance of Iowa industry, and associated entities, through education and technology-based services. This newsletter holds information regarding these services.

CIRAS News, Spring 2014, Vol. 49, no. 3

CIRAS is to enhance the performance of Iowa industry, and associated entities, through education and technology-based services. This newsletter holds information regarding these services.

CIRAS News, Summer 2014, Vol. 49, no. 4

CIRAS is to enhance the performance of Iowa industry, and associated entities, through education and technology-based services. This newsletter holds information regarding these services.

CIRAS News, Winter 2015, Vol. 50, no. 2

CIRAS is to enhance the performance of Iowa industry, and associated entities, through education and technology-based services. This newsletter holds information regarding these services.

Iowa State Profile Tool: An Assessment of Iowa's Long-Term Support System, March 31, 2009

The Iowa State Profile Tool is a comprehensive, high-level assessment of Iowa’s progress toward a balanced long-term care system – a system that relies less on institutional services and provides greater opportunities for the in-home and community-based services that most people prefer. This report includes long-term support for people of all ages and disability types and is based on a variety of state and federal data sources and interviews with public and private leaders in Iowa’s long-term care system.

CIRAS News, Winter 2007, Vol. 42, no. 2

CIRAS is to enhance the performance of Iowa industry, and associated entities, through education and technology-based services. This newsletter holds information regarding these services.

CIRAS News, Fall 2015, Vol. 51, no. 1

CIRAS is to enhance the performance of Iowa industry, and associated entities, through education and technology-based services. This newsletter holds information regarding these services.

CIRAS News, Spring 2015, Vol. 50, no. 3

CIRAS is to enhance the performance of Iowa industry, and associated entities, through education and technology-based services. This newsletter holds information regarding these services.

CIRAS News, Summer 2015, Vol. 50, no. 4

CIRAS is to enhance the performance of Iowa industry, and associated entities, through education and technology-based services. This newsletter holds information regarding these services.

Iowa Department of Corrections, Strategic Plan 2015-2019, January 2015

Iowa’s adult correctional system carries out its legal mandate of protecting the public and promoting offender rehabilitation through a continuum of institution and community evidence based services and interventions. This continuum is designed with recognition that for most offenders, reentry planning starts upon admission to the corrections system. The effective and efficient management of offenders in accordance with their risk and carcinogenic needs (those needs that contribute to criminality) is accomplished through targeted programming, release preparation, and transition services. Success in these endeavors assists offenders to become productive members of the community and makes it less likely that they will re-offend, resulting in lowered recidivism rates. In 1990 the Department’s prison recidivism rate was 44.7% and today it is 30.3%. Our overall desired outcome is to reduce the prison recidivism rate to 25% during the next five years by focusing resources toward our highest risk offenders.

Spatial Scale of Clustering of Motor Vehicle Crash Types and Appropriate Countermeasures, 2009

This project analyzes the characteristics and spatial distributions of motor vehicle crash types in order to evaluate the degree and scale of their spatial clustering. Crashes occur as the result of a variety of vehicle, roadway, and human factors and thus vary in their clustering behavior. Clustering can occur at a variety of scales, from the intersection level, to the corridor level, to the area level. Conversely, other crash types are less linked to geographic factors and are more spatially “random.” The degree and scale of clustering have implications for the use of strategies to promote transportation safety. In this project, Iowa's crash database, geographic information systems, and recent advances in spatial statistics methodologies and software tools were used to analyze the degree and spatial scale of clustering for several crash types within the counties of the Iowa Northland Regional Council of Governments. A statistical measure called the K function was used to analyze the clustering behavior of crashes. Several methodological issues, related to the application of this spatial statistical technique in the context of motor vehicle crashes on a road network, were identified and addressed. These methods facilitated the identification of crash clusters at appropriate scales of analysis for each crash type. This clustering information is useful for improving transportation safety through focused countermeasures directly linked to crash causes and the spatial extent of identified problem locations, as well as through the identification of less location-based crash types better suited to non-spatial countermeasures. The results of the K function analysis point to the usefulness of the procedure in identifying the degree and scale at which crashes cluster, or do not cluster, relative to each other. Moreover, for many individual crash types, different patterns and processes and potentially different countermeasures appeared at different scales of analysis. This finding highlights the importance of scale considerations in problem identification and countermeasure formulation.