Optimal exponentially weighted moving average (EWMA) plans for detecting seasonal epidemics when faced with non-homogeneous negative binomial counts

Exponentially weighted moving average (EWMA) plans for non-homogeneous negative binomial counts are developed for detecting the onset of seasonal disease outbreaks in public health surveillance. These plans are robust to changes in the in-control mean and over-dispersion parameter of the negative binomial distribution, and therefore are referred to as adaptive plans. They differ from the traditional approach of using standardized forecast errors based on the normality assumption. Plans are investigated in terms of early signal properties for seasonal epidemics. The paper demonstrates that the proposed EWMA plan has efficient early detection properties that can be useful to epidemiologists for communicable and other disease control and is compared with the CUSUM plan.     

What's an Oscar worth?

This article examines the impact of an Academy Award nomination and award for best picture, best actor/actress, and best supporting actor/actress on a film's (i) market share of theaters, (ii) average revenue per screen, and (iii) its probability of survival. The model is estimated using weekly box-office data for a matched sample of nominated and non-nominated films. The results indicate substantial financial benefits for a nomination and award for best picture and best actor/actress. The structure of rewards is consistent with that found in two-stage, single-elimination tournaments.     

Gender role identity in a sample of Italian male homosexuals

Gender role is a multifactorial concept, as gender-related attitudes, behaviors, and personality are partially autonomous. The aim of the study was to evaluate the prevalent gender role identity in a sample of male homosexuals. One hundred male homosexuals and 50 male heterosexuals matched for age and sex, have been assessed with the Italian version of the Bem Sex-Role Inventory (BSRI; Bem, 1974). Statistically significant differences have been found between the two groups at the dimensions "Masculine" (z = 1.963; p = 0.001) and "Androgyny" (z = 2.367; p < 0.0001). The results obtained from the present study tend to confirm that homosexuals view themselves as adrogynous individuals, sharing both features of masculine and feminine gender roles.     

Is bounded-vision an adequate explanation of strategic decision-making failures

One important area in which Management Science should be involved must surely be in the prevention of corporate failure. In this paper we therefore use a scientific methodology to try to identify the major causes of such failure. Two widely differing systems are examined and a large number of hypotheses considered as explanations of failure. In each case the only hypothesis which we are unable to reject, is that prior to the failure the dominant decision-makers in the system were not prepared to accept facts which were plainly available and which, if acted upon, could have prevented disaster. This allows us to suggest some ways of helping to prevent failure. Nevertheless, we feel that research into the mechanisms generating this phenomenon, which we have called bounded-vision, is required before adequate technologies can be designed.     

Early warning CUSUM plans for surveillance of negative binomial daily disease counts

Automated public health surveillance of disease counts for rapid outbreak, epidemic or bioterrorism detection using conventional control chart methods can be hampered by over-dispersion and background (‘in-control’) mean counts that vary over time. An adaptive cumulative sum (CUSUM) plan is developed for signalling unusually high incidence in prospectively monitored time series of over-dispersed daily disease counts with a non-homogeneous mean. Negative binomial transitional regression is used to prospectively model background counts and provide ‘one-step-ahead’ forecasts of the next day's count. A CUSUM plan then accumulates departures of observed counts from an offset (reference value) that is dynamically updated using the modelled forecasts. The CUSUM signals whenever the accumulated departures exceed a threshold. The amount of memory of past observations retained by the CUSUM plan is determined by the offset value; a smaller offset retains more memory and is efficient at detecting smaller shifts. Our approach optimises early outbreak detection by dynamically adjusting the offset value. We demonstrate the practical application of the ‘optimal’ CUSUM plans to daily counts of laboratory-notified influenza and Ross River virus diagnoses, with particular emphasis on the steady-state situation (i.e. changes that occur after the CUSUM statistic has run through several in-control counts).