Point Process Methodology for On-line Spatio-temporal Disease Surveillance

The AEGISS (Ascertainment and Enhancement of Gastrointestinal Infection Surveillance and Statistics) project aims to use spatio-temporal statistical methods to identify anomalies in the space-time distribution of non-specific, gastrointestinal infections in the UK, using the Southampton area in southern England as a test-case. In this paper, we use the AEGISS project to illustrate how spatio-temporal point process methodology can be used in the development of a rapid-response, spatial surveillance system. Current surveillance of gastroenteric disease in the UK relies on general practitioners reporting cases of suspected food-poisoning through a statutory notification scheme, voluntary laboratory reports of the isolation of gastrointestinal pathogens and standard reports of general outbreaks of infectious intestinal disease by public health and environmental health authorities. However, most statutory notifications are made only after a laboratory reports the isolation of a gastrointestinal pathogen. As a result, detection is delayed and the ability to react to an emerging outbreak is reduced. For more detailed discussion, see Diggle et al. (2003). A new and potentially valuable source of data on the incidence of non-specific gastro-enteric infections in the UK is NHS Direct, a 24-hour phone-in clinical advice service. NHS Direct data are less likely than reports by general practitioners to suffer from spatially and temporally localized inconsistencies in reporting rates. Also, reporting delays by patients are likely to be reduced, as no appointments are needed. Against this, NHS Direct data sacrifice specificity. Each call to NHS Direct is classified only according to the general pattern of reported symptoms (Cooper et al, 2003). The current paper focuses on the use of spatio-temporal statistical analysis for early detection of unexplained variation in the spatio-temporal incidence of non-specific gastroenteric symptoms, as reported to NHS Direct. Section 2 describes our statistical formulation of this problem, the nature of the available data and our approach to predictive inference. Section 3 describes the stochastic model. Section 4 gives the results of fitting the model to NHS Direct data. Section 5 shows how the model is used for spatio-temporal prediction. The paper concludes with a short discussion.

Introduction of a novel dose saving acquisition mode for the PortalVision aS500 EPID to facilitate on-line patient setup verification

In external beam radiotherapy, electronic portal imaging becomes more and more an indispensable tool for the verification of the patient setup. For the safe clinical introduction of high dose conformal radiotherapy like intensity modulated radiation therapy, on-line patient setup verification is a prerequisite to ensure that the planned dosimetric coverage of the tumor volume is actually realized in the patient. Since the direction of setup fields often deviates from the direction of the treatment beams, extra dose is delivered to the patient during the acquisition of these portal images which may reach clinical relevance. The aim of this work was to develop a new acquisition mode for the PortalVision aS500 electronic portal imaging device from Varian Medical Systems that allows one to take portal images with reduced dose while keeping good image quality. The new acquisition mode, called RadMode, selectively enables and disables beam pulses during image acquisition allowing one to stop wasting valuable dose during the initial acquisition of "reset frames." Images of excellent quality can be taken with 1 MU only. This low dose per image facilitates daily setup verification with considerably reduced extra dose.