Simple Estimation of Incident HIV Infection Rates in Notification Cohorts Based on Window Periods of Algorithms for Evaluation of Line-Immunoassay Result Patterns

Background Tests for recent infections (TRIs) are important for HIV surveillance. We have shown that a patient's antibody pattern in a confirmatory line immunoassay (Inno-Lia) also yields information on time since infection. We have published algorithms which, with a certain sensitivity and specificity, distinguish between incident (< = 12 months) and older infection. In order to use these algorithms like other TRIs, i.e., based on their windows, we now determined their window periods. Methods We classified Inno-Lia results of 527 treatment-naïve patients with HIV-1 infection < = 12 months according to incidence by 25 algorithms. The time after which all infections were ruled older, i.e. the algorithm's window, was determined by linear regression of the proportion ruled incident in dependence of time since infection. Window-based incident infection rates (IIR) were determined utilizing the relationship ‘Prevalence = Incidence x Duration’ in four annual cohorts of HIV-1 notifications. Results were compared to performance-based IIR also derived from Inno-Lia results, but utilizing the relationship ‘incident = true incident + false incident’ and also to the IIR derived from the BED incidence assay. Results Window periods varied between 45.8 and 130.1 days and correlated well with the algorithms' diagnostic sensitivity (R2 = 0.962; P<0.0001). Among the 25 algorithms, the mean window-based IIR among the 748 notifications of 2005/06 was 0.457 compared to 0.453 obtained for performance-based IIR with a model not correcting for selection bias. Evaluation of BED results using a window of 153 days yielded an IIR of 0.669. Window-based IIR and performance-based IIR increased by 22.4% and respectively 30.6% in 2008, while 2009 and 2010 showed a return to baseline for both methods. Conclusions IIR estimations by window- and performance-based evaluations of Inno-Lia algorithm results were similar and can be used together to assess IIR changes between annual HIV notification cohorts.

Push and Pull Motivations for Quitting: A three-wave investigation of predictors and consequences of turnover

We report a new analysis of data from a multi-year study, some of which were previously published in the current journal. A longitudinal sample of 380 computer specialists was followed over two years, yielding three measures each of job satisfaction, organizational commitment, and turnover intentions, as well as actual turnover, and reasons for leaving, at Times 2 and 3. Career paths were more diverse than the classical distinction between stayers and leavers implies. Furthermore, although the largest single group of leavers cited “push” reasons, conforming to the classical withdrawal model, a sizable number were attracted to another job (“pull motivation”). In a three-wave structural equation model, job (dis)satisfaction predicted turnover, while organizational commitment exerted its influence only via its association with job satisfaction. As expected, however, attitudes predicted turnover only for participants with push motivation. Quitting, in turn, predicted an improvement in both satisfaction and commitment, indicating that it paid off for the individual. The necessity to study consequences of turnover and to distinguish between different subgroups of stayers and leavers is emphasized.

Enabling knowledge creation through outsiders: towards a push model of open innovation

Open innovation is increasingly being adopted in business and describes a situation in which firms exchange ideas and knowledge with external participants, such as customers, suppliers, partner firms, and universities. This article extends the concept of open innovation with a push model of open innovation: knowledge is voluntarily created outside a firm by individuals and organisations who proceed to push knowledge into a firm’s open innovation project. For empirical analysis, we examine source code and newsgroup data on the Eclipse Development Platform. We find that outsiders invest as much in the firm’s project as the founding firm itself. Based on the insights from Eclipse, we develop four propositions: ‘preemptive generosity’ of a firm, ‘continuous commitment’, ‘adaptive governance structure’, and ‘low entry barrier’ are contexts that enable the push model of open innovation.

Gender differences in tuberculosis notification in Pakistan

Worldwide the male:female ratio of new smear-positive TB cases is estimated to be roughly 2:1. However in Pakistan this is not the case. Rates of notified TB cases are 20–30% higher in young females compared with males and female rates remain high regardless of increasing age. This is in stark contrast to neighboring India which is characterized by a huge excess of male TB cases. It is currently unknown why rates of notified TB are so high in females in Pakistan, but it is clear this epidemiology is a public health issue of great importance that impacts transmission dynamics and disease control initiatives.^