Ethnic differences in unemployment and ill health.

Objective The aim of the study is to evaluate whether health inequalities associated with unemployment are comparable across different ethnic groups. Method A random sample of inhabitants of the city of Rotterdam filled out a questionnaire on health and its determinants, with a response of 55.4% (n = 2,057). In a cross-sectional design the associations of unemployment, ethnicity, and individual characteristics with a perceived poor health were investigated with logistic regression analysis. The associations of these determinants with physical and mental health, measured by the Short Form 36 Health Survey, were evaluated with linear regression analyses. Interactions between ethnicity and unemployment were investigated to determine whether associations of unemployment and health differed across ethnic groups. Results Ill health was more common among unemployed persons [odd

The longitudinal relationship between job mobility, perceived organizational justice, and health

<p>Abstract</p> <p>Background</p> <p>The main purpose of the present study was to examine the 2-year longitudinal and reciprocal relationship between job mobility and health and burnout. A second aim was to elucidate the effects of perceived organizational justice and turnover intentions on the relationship between job mobility (non-, internally and externally mobile), and health (SF-36) and burnout (CBI).</p> <p>Methods</p> <p>The study used questionnaire data from 662 Swedish civil servants and the data were analysed with Structural Equation Modeling statistical methods.</p> <p>Results</p> <p>The results showed that job mobility was a better predictor of health and burnout, than health and burnout were as predictors of job mobility. The predictive effects were most obvious for psychosocial health and burnout, but negligible as far as physical health was concerned. Organizational justice was found to have a direct impact on health, but not on job mobility; whereas turnover intentions had a direct effect on job mobility.</p> <p>Conclusion</p> <p>The predictive relationship between job mobility and health has practical implications for health promotive actions in different organizations.</p

Business unusual: collective action against bribery in international business

Collective action initiatives in which governments and companies make anti-corruption commitments have proliferated in recent years. This apparently prosocial behavior defies the logic of collective action and, given that bribery often goes undetected and unpunished, is not easily explained by principal-agent theory. Club theory suggests that the answer lies in the institutional design of anti-corruption clubs: collective action can work as long as membership has high entry costs, members receive selective benefits, and compliance is adequately policed. This article contributes to the debate by examining how these conditions manifest in the case of anti-corruption clubs in the realm of international business, with particular focus on the international dimension of many initiatives. This vertical aspect of institutional design creates a richer, more complex set of reputational and material benefits for members, as well as allowing for more credible and consistent monitoring and enforcement

Spatio-Temporal Tracking and Phylodynamics of an Urban Dengue 3 Outbreak in São Paulo, Brazil

The dengue virus has a single-stranded positive-sense RNA genome of ∼10.700 nucleotides with a single open reading frame that encodes three structural (C, prM, and E) and seven nonstructural (NS1, NS2A, NS2B, NS3, NS4A, NS4B, and NS5) proteins. It possesses four antigenically distinct serotypes (DENV 1–4). Many phylogenetic studies address particularities of the different serotypes using convenience samples that are not conducive to a spatio-temporal analysis in a single urban setting. We describe the pattern of spread of distinct lineages of DENV-3 circulating in São José do Rio Preto, Brazil, during 2006. Blood samples from patients presenting dengue-like symptoms were collected for DENV testing. We performed M-N-PCR using primers based on NS5 for virus detection and identification. The fragments were purified from PCR mixtures and sequenced. The positive dengue cases were geo-coded. To type the sequenced samples, 52 reference sequences were aligned. The dataset generated was used for iterative phylogenetic reconstruction with the maximum likelihood criterion. The best demographic model, the rate of growth, rate of evolutionary change, and Time to Most Recent Common Ancestor (TMRCA) were estimated. The basic reproductive rate during the epidemics was estimated. We obtained sequences from 82 patients among 174 blood samples. We were able to geo-code 46 sequences. The alignment generated a 399-nucleotide-long dataset with 134 taxa. The phylogenetic analysis indicated that all samples were of DENV-3 and related to strains circulating on the isle of Martinique in 2000–2001. Sixty DENV-3 from São José do Rio Preto formed a monophyletic group (lineage 1), closely related to the remaining 22 isolates (lineage 2). We assumed that these lineages appeared before 2006 in different occasions. By transforming the inferred exponential growth rates into the basic reproductive rate, we obtained values for lineage 1 of R0 = 1.53 and values for lineage 2 of R0 = 1.13. Under the exponential model, TMRCA of lineage 1 dated 1 year and lineage 2 dated 3.4 years before the last sampling. The possibility of inferring the spatio-temporal dynamics from genetic data has been generally little explored, and it may shed light on DENV circulation. The use of both geographic and temporally structured phylogenetic data provided a detailed view on the spread of at least two dengue viral strains in a populated urban area

Time series analysis of dengue incidence in Guadeloupe, French West Indies: Forecasting models using climate variables as predictors

BACKGROUND: During the last decades, dengue viruses have spread throughout the Americas region, with an increase in the number of severe forms of dengue. The surveillance system in Guadeloupe (French West Indies) is currently operational for the detection of early outbreaks of dengue. The goal of the study was to improve this surveillance system by assessing a modelling tool to predict the occurrence of dengue epidemics few months ahead and thus to help an efficient dengue control. METHODS: The Box-Jenkins approach allowed us to fit a Seasonal Autoregressive Integrated Moving Average (SARIMA) model of dengue incidence from 2000 to 2006 using clinical suspected cases. Then, this model was used for calculating dengue incidence for the year 2007 compared with observed data, using three different approaches: 1 year-ahead, 3 months-ahead and 1 month-ahead. Finally, we assessed the impact of meteorological variables (rainfall, temperature and relative humidity) on the prediction of dengue incidence and outbreaks, incorporating them in the model fitting the best. RESULTS: The 3 months-ahead approach was the most appropriate for an effective and operational public health response, and the most accurate (Root Mean Square Error, RMSE = 0.85). Relative humidity at lag-7 weeks, minimum temperature at lag-5 weeks and average temperature at lag-11 weeks were variables the most positively correlated to dengue incidence in Guadeloupe, meanwhile rainfall was not. The predictive power of SARIMA models was enhanced by the inclusion of climatic variables as external regressors to forecast the year 2007. Temperature significantly affected the model for better dengue incidence forecasting (p-value = 0.03 for minimum temperature lag-5, p-value = 0.02 for average temperature lag-11) but not humidity. Minimum temperature at lag-5 weeks was the best climatic variable for predicting dengue outbreaks (RMSE = 0.72). CONCLUSION: Temperature improves dengue outbreaks forecasts better than humidity and rainfall. SARIMA models using climatic data as independent variables could be easily incorporated into an early (3 months-ahead) and reliably monitoring system of dengue outbreaks. This approach which is practicable for a surveillance system has public health implications in helping the prediction of dengue epidemic and therefore the timely appropriate and efficient implementation of prevention activities