Iowa Unemployment Rates by County, August 2015

Iowa Unemployment Rates by County map produced by the Iowa Workforce Development.

Comparing interval breast cancer rates in Norway and North Carolina: results and challenges.

OBJECTIVE: To compare interval breast cancer rates (ICR) between a biennial organized screening programme in Norway and annual opportunistic screening in North Carolina (NC) for different conceptualizations of interval cancer. SETTING: Two regions with different screening practices and performance. METHODS: 620,145 subsequent screens (1996-2002) performed in women aged 50-69 and 1280 interval cancers were analysed. Various definitions and quantification methods for interval cancers were compared. RESULTS: ICR for one year follow-up were lower in Norway compared with NC both when the rate was based on all screens (0.54 versus 1.29 per 1000 screens), negative final assessments (0.54 versus 1.29 per 1000 screens), and negative screening assessments (0.53 versus 1.28 per 1000 screens). The rate of ductal carcinoma in situ was significantly lower in Norway than in NC for cases diagnosed in both the first and second year after screening. The distributions of histopathological tumour size and lymph node involvement in invasive cases did not differ between the two regions for interval cancers diagnosed during the first year after screening. In contrast, in the second year after screening, tumour characteristics remained stable in Norway but became prognostically more favorable in NC. CONCLUSION: Even when applying a common set of definitions of interval cancer, the ICR was lower in Norway than in NC. Different definitions of interval cancer did not influence the ICR within Norway or NC. Organization of screening and screening performance might be major contributors to the differences in ICR between Norway and NC.

Iowa Unemployment Rates by County, September 2015

Iowa Unemployment Rates by County map produced by the Iowa Workforce Development.

Iowa Unemployment Rates by County, October 2015

Iowa Unemployment Rates by County map produced by the Iowa Workforce Development.

Deaths rates in public hospitals of eastern cape province of South Africa.

BACKGROUND: South Africa (SA) is experiencing a rapid epidemiologic transition as a consequence of political, economic and social changes. In this study we described, based on hospital data, the mortality patterns of Non communicable Diseases (NCD), Communicable Diseases (CD), the NCD/CD ratios, and the trends of deaths. METHODS: We conducted a cross-sectional survey of all deaths occurring in several public hospitals in the Eastern Cape Province of SA between 2002 and 2006. Causes of deaths were coded according to the ICD 10 Edition. RESULTS: A total of 107380 admissions responded to the inclusion criteria between 2002 and 2006. The crude death rate was 4.3% (n=4566) with a mean age of 46±21 years and a sex ratio of 3.1 men (n=3453): 1 woman (n=1113). Out of all deaths, there were 62.9% NCD (n=2872) vs. 37.1% CD (n=1694) with NCD/CD ratio of 1.7. The ratio NCD/CD deaths in men was 1.3 (n=1951/1502) vs. NCD/CD deaths in women of 1.9 (n=735/378). The peak of deaths was observed in winter season. The majority of NCD deaths were at age of 30-64 years, whereas the highest rate of CD deaths was at age< 30 years. The trend of deaths including the majority of NCD, increased from 2002 to 2006. There was a tendency of increase in tuberculosis deaths, but a tendency of decrease in HIV/AIDS deaths was from 2002 to 2006. CONCLUSION: Non-communicable diseases are the leading causes of deaths in rural Eastern Cape province of SA facing Post-epidemiologic transition stages. We recommend overarching priority actions for the response to the Non-communicable Diseases: policy change, prevention, treatment, international cooperation, research, monitoring, accountability, and re-orientation of health systems.

The effect of pesticides and alien invesive species on soil biota and litter decomposition rates in a Mediterrean-climate ecosystem of Western Australia

Ecosystems are complex systems and changing one of their components can alter their whole functioning. Decomposition and biodiversity are two factors that play a role in this stability, and it is vital to study how these two factors are interrelated and how other factors, whether of human origin or not, can affect them. This study has tested different hypotheses regarding the effects of pesticides and invasive species on the biodiversity of the soil fauna and litter decomposition rate. Decomposition was measured using the litterbags technique. Our results indicate that pesticides had a negative effect on decomposition whereas invasive species increased decomposition rate. At the same time, the diversity of the soil biota was unaffected by either factor. These results allow us to better understand the response of important ecosystem functions to human‐induced alterations, in order to mitigate harmful effects or restore them wherever necessary.

Iowa Insurance Division Four Year Strategic Plan FY13, October 2012

Strategic Plan for the Iowa Insurance Division

Iowa Unemployment Rates by County, November 2015

Iowa Unemployment Rates by County map produced by the Iowa Workforce Development.

Unemployment Rates For Iowa Counties, November 2015

Iowa Unemployment Rates by County map produced by the Iowa Workforce Development.

Iowa Department of Insurance Division Performance Plan FY2015, July 2014

Performance report on the Insurance Division for Iowa Department.

Structural macro factors and the affine term structure of interest rates

This work consists of three essays investigating the ability of structural macroeconomic models to price zero coupon U.S. government bonds. 1. A small scale 3 factor DSGE model implying constant term premium is able to provide reasonable a fit for the term structure only at the expense of the persistence parameters of the structural shocks. The test of the structural model against one that has constant but unrestricted prices of risk parameters shows that the exogenous prices of risk-model is only weakly preferred. We provide an MLE based variance-covariance matrix of the Metropolis Proposal Density that improves convergence speeds in MCMC chains. 2. Affine in observable macro-variables, prices of risk specification is excessively flexible and provides term-structure fit without significantly altering the structural parameters. The exogenous component of the SDF is separating the macro part of the model from the term structure and the good term structure fit has as a driving force an extremely volatile SDF and an implied average short rate that is inexplicable. We conclude that the no arbitrage restrictions do not suffice to temper the SDF, thus there is need for more restrictions. We introduce a penalty-function methodology that proves useful in showing that affine prices of risk specifications are able to reconcile stable macro-dynamics with good term structure fit and a plausible SDF. 3. The level factor is reproduced most importantly by the preference shock to which it is strongly and positively related but technology and monetary shocks, with negative loadings, are also contributing to its replication. The slope factor is only related to the monetary policy shocks and it is poorly explained. We find that there are gains in in- and out-of-sample forecast of consumption and inflation if term structure information is used in a time varying hybrid prices of risk setting. In-sample yield forecast are better in models with non-stationary shocks for the period 1982-1988. After this period, time varying market price of risk models provide better in-sample forecasts. For the period 2005-2008, out of sample forecast of consumption and inflation are better if term structure information is incorporated in the DSGE model but yields are better forecasted by a pure macro DSGE model.

Ruin and related quantities in some advanced insurance risk models

Risk theory has been a very active research area over the last decades. The main objectives of the theory are to find adequate stochastic processes which can model the surplus of a (non-life) insurance company and to analyze the risk related quantities such as ruin time, ruin probability, expected discounted penalty function and expected discounted dividend/tax payments. The study of these ruin related quantities provides crucial information for actuaries and decision makers. This thesis consists of the study of four different insurance risk models which are essentially related. The ruin and related quantities are investigated by using different techniques, resulting in explicit or asymptotic expressions for the ruin time, the ruin probability, the expected discounted penalty function and the expected discounted tax payments. - La recherche en théorie du risque a été très dynamique au cours des dernières décennies. D'un point de vue théorique, les principaux objectifs sont de trouver des processus stochastiques adéquats permettant de modéliser le surplus d'une compagnie d'assurance non vie et d'analyser les mesures de risque, notamment le temps de ruine, la probabilité de ruine, l'espérance de la valeur actuelle de la fonction de pénalité et l'espérance de la valeur actuelle des dividendes et taxes. L'étude de ces mesures associées à la ruine fournit des informations cruciales pour les actuaires et les décideurs. Cette thèse consiste en l'étude des quatre différents modèles de risque d'assurance qui sont essentiellement liés. La ruine et les mesures qui y sont associées sont examinées à l'aide de différentes techniques, ce qui permet d'induire des expressions explicites ou asymptotiques du temps de ruine, de la probabilité de ruine, de l'espérance de la valeur actuelle de la fonction de pénalité et l'espérance de la valeur actuelle des dividendes et taxes.

Iowa Unemployment Rates by County, December 2015

Iowa Unemployment Rates by County map produced by the Iowa Workforce Development.

Report on a review of certain Unemployment Insurance payments made by Iowa Workforce Development during the period January 1, 2012 through January 13, 2015

Report on a review of certain Unemployment Insurance payments made by Iowa Workforce Development during the period January 1, 2012 through January 13, 2015