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.

Squared Extrapolation Methods (SQUAREM): A New Class of Simple and Efficient Numerical Schemes for Accelerating the Convergence of the EM Algorithm

We derive a new class of iterative schemes for accelerating the convergence of the EM algorithm, by exploiting the connection between fixed point iterations and extrapolation methods. First, we present a general formulation of one-step iterative schemes, which are obtained by cycling with the extrapolation methods. We, then square the one-step schemes to obtain the new class of methods, which we call SQUAREM. Squaring a one-step iterative scheme is simply applying it twice within each cycle of the extrapolation method. Here we focus on the first order or rank-one extrapolation methods for two reasons, (1) simplicity, and (2) computational efficiency. In particular, we study two first order extrapolation methods, the reduced rank extrapolation (RRE1) and minimal polynomial extrapolation (MPE1). The convergence of the new schemes, both one-step and squared, is non-monotonic with respect to the residual norm. The first order one-step and SQUAREM schemes are linearly convergent, like the EM algorithm but they have a faster rate of convergence. We demonstrate, through five different examples, the effectiveness of the first order SQUAREM schemes, SqRRE1 and SqMPE1, in accelerating the EM algorithm. The SQUAREM schemes are also shown to be vastly superior to their one-step counterparts, RRE1 and MPE1, in terms of computational efficiency. The proposed extrapolation schemes can fail due to the numerical problems of stagnation and near breakdown. We have developed a new hybrid iterative scheme that combines the RRE1 and MPE1 schemes in such a manner that it overcomes both stagnation and near breakdown. The squared first order hybrid scheme, SqHyb1, emerges as the iterative scheme of choice based on our numerical experiments. It combines the fast convergence of the SqMPE1, while avoiding near breakdowns, with the stability of SqRRE1, while avoiding stagnations. The SQUAREM methods can be incorporated very easily into an existing EM algorithm. They only require the basic EM step for their implementation and do not require any other auxiliary quantities such as the complete data log likelihood, and its gradient or hessian. They are an attractive option in problems with a very large number of parameters, and in problems where the statistical model is complex, the EM algorithm is slow and each EM step is computationally demanding.

ASSOCIATON TESTS THAT ACCOMMODATE GENOTYPING ERRORS

High-throughput SNP arrays provide estimates of genotypes for up to one million loci, often used in genome-wide association studies. While these estimates are typically very accurate, genotyping errors do occur, which can influence in particular the most extreme test statistics and p-values. Estimates for the genotype uncertainties are also available, although typically ignored. In this manuscript, we develop a framework to incorporate these genotype uncertainties in case-control studies for any genetic model. We verify that using the assumption of a “local alternative” in the score test is very reasonable for effect sizes typically seen in SNP association studies, and show that the power of the score test is simply a function of the correlation of the genotype probabilities with the true genotypes. We demonstrate that the power to detect a true association can be substantially increased for difficult to call genotypes, resulting in improved inference in association studies.

LEARNING FROM NEAR MISSES IN MEDICATION ERRORS: A BAYESIAN APPROACH

Medical errors originating in health care facilities are a significant source of preventable morbidity, mortality, and healthcare costs. Voluntary error report systems that collect information on the causes and contributing factors of medi- cal errors regardless of the resulting harm may be useful for developing effective harm prevention strategies. Some patient safety experts question the utility of data from errors that did not lead to harm to the patient, also called near misses. A near miss (a.k.a. close call) is an unplanned event that did not result in injury to the patient. Only a fortunate break in the chain of events prevented injury. We use data from a large voluntary reporting system of 836,174 medication errors from 1999 to 2005 to provide evidence that the causes and contributing factors of errors that result in harm are similar to the causes and contributing factors of near misses. We develop Bayesian hierarchical models for estimating the log odds of selecting a given cause (or contributing factor) of error given harm has occurred and the log odds of selecting the same cause given that harm did not occur. The posterior distribution of the correlation between these two vectors of log-odds is used as a measure of the evidence supporting the use of data from near misses and their causes and contributing factors to prevent medical errors. In addition, we identify the causes and contributing factors that have the highest or lowest log-odds ratio of harm versus no harm. These causes and contributing factors should also be a focus in the design of prevention strategies. This paper provides important evidence on the utility of data from near misses, which constitute the vast majority of errors in our data.

Reduced Bayesian Hierarchical Models: Estimating Health Effects of Simultaneous Exposure to Multiple Pollutants

Quantifying the health effects associated with simultaneous exposure to many air pollutants is now a research priority of the US EPA. Bayesian hierarchical models (BHM) have been extensively used in multisite time series studies of air pollution and health to estimate health effects of a single pollutant adjusted for potential confounding of other pollutants and other time-varying factors. However, when the scientific goal is to estimate the impacts of many pollutants jointly, a straightforward application of BHM is challenged by the need to specify a random-effect distribution on a high-dimensional vector of nuisance parameters, which often do not have an easy interpretation. In this paper we introduce a new BHM formulation, which we call "reduced BHM", aimed at analyzing clustered data sets in the presence of a large number of random effects that are not of primary scientific interest. At the first stage of the reduced BHM, we calculate the integrated likelihood of the parameter of interest (e.g. excess number of deaths attributed to simultaneous exposure to high levels of many pollutants). At the second stage, we specify a flexible random-effect distribution directly on the parameter of interest. The reduced BHM overcomes many of the challenges in the specification and implementation of full BHM in the context of a large number of nuisance parameters. In simulation studies we show that the reduced BHM performs comparably to the full BHM in many scenarios, and even performs better in some cases. Methods are applied to estimate location-specific and overall relative risks of cardiovascular hospital admissions associated with simultaneous exposure to elevated levels of particulate matter and ozone in 51 US counties during the period 1999-2005.

A call for uniform reporting standards in studies assessing endovascular treatment for chronic ischaemia of lower limb arteries

Endovascular therapy is a rapidly evolving field for the treatment of patients with peripheral arterial disease, and a magnitude of studies reporting on various modern revascularization concepts have been recently published. Thus, studies assessing the efficacy of endovascular therapy of peripheral arteries do not operate with uniformly defined endpoints, rendering a direct comparison of studies difficult. The purpose of this consensus statement is to highlight differences in the terminology used in the current literature and to propose some standardized criteria that must be considered when reporting results of endovascular revascularization for chronic ischaemia of lower limb arteries.

Comparison between two caller groups of a medical call centre in Switzerland

OBJECTIVES: The incidence distribution of triage advice in the medical call centre Medi24 and the pattern of service utilisation were analysed with respect to two groups of callers with different insurance schemes. Individuals having contracted insurance of the Medi24 model could use the telephone consultation service of the medical call centre Medi24 (mainly part of the mandatory basic health insurance) voluntarily and free of charge whereas individuals holding an insurance policy of the Telmed model (special contract within the mandatory basic health insurance with a premium discount ranging from 8% to 12%) were obliged to have a telephone consultation before arranging an appointment with a medical doctor. METHODS: A cross-sectional study was carried out in the medical call centre Medi24 based on all triage datasets of the Medi24 and Telmed groups collected during the one year period from July 1st 2005 to June 30th 2006. The distribution of the six different urgency levels within the two groups and their respective pattern of service utilisation was determined. In a multivariable logistic regression model the Odds Ratio for every enquiry originating from the Telmed group versus those originating from the Medi24 group was calculated. RESULTS: During a one-year period 48 388 triage requests reached the medical call centre Medi24, 56% derived from the Telmed group and 44% from the Medi24 group. Within the Medi24 group more than 25% of the individuals received self-care advice, within the Telmed group, on the other hand, only about 18% received such advice. In contrast, 27% of the Telmed triage requests but only 18% of the Medi24 triage requests resulted in the advice to make a routine appointment with a medical doctor. The probability that an individual of the Telmed group obtained the advice to go to the accident and emergency department was lower than for an individual of the Medi24 group (OR 0.77, 95% CI 0.60-0.99). Likewise, the probability of self-care advice was decreased in regard to the Medi24 group (OR 0.80, 95% CI 0.75-0.85). However, regarding the advice to make a routine appointment with a medical doctor, the Telmed group was represented more frequently than the Medi24 group (OR 1.36, 95% CI 1.28-1.44). CONCLUSION: In respect of the triage advice, the Telmed group differed significantly from the Medi24 group within all urgency levels. The differences between the two groups in respect of the advice given were still less pronounced than expected against the background of their different contract conditions and the disparate temporal pattern of utilisation. We interprete this finding with the fact that appraising the urgency of health problems appropriately seems to be very difficult for the majority of people seeking advice.

Call for a reference model of chronic hind limb ischemia to investigate therapeutic angiogenesis

A large number of studies utilize animal models to investigate therapeutic angiogenesis. However, the lack of a standardized experimental model leaves the comparison of different studies problematic. To establish a reference model of prolonged moderate tissue ischemia, we created unilateral hind limb ischemia in athymic rnu-rats by surgical excision of the femoral vessels. Blood flow of the limb was monitored for 60 days by laser Doppler imaging. Following a short postoperative period of substantially depressed perfusion, the animals showed a status of moderate hind limb ischemia from day 14 onwards. Thereafter, the perfusion remained at a constant level (55.5% of normal value) until the end of the observation period. Histopathological assessment of the ischemic musculature on postoperative days 28 and 60 showed essentially no inflammatory cell infiltrate or fibrosis. However, the mitochondrial activity and capillary-to-fiber ratio of the muscular tissue was reduced to 52.7% of normal, presenting with a significant weakness of the ischemic limb evidenced by a progressive decline in performance. Intramuscular injection of culture-expanded human endothelial progenitor cells (EPC) resulted in a significant increase in blood flow (82.0+/-3.5% of normal), capillary density (1.60+/-0.08/muscle fiber) and smooth muscle covered arterioles (8.0+/-0.6/high power field) in the ischemic hind limb as compared to controls (55.0+/-3.1%; 0.99+/-0.03; 5.0+/-0.2). In conclusion, chronic, moderate hind limb ischemia with consistently reduced perfusion levels persisting over a prolonged period can be established reliably in rnu athymic nude rats and is responsive to pro-angiogenic treatments such as EPC transplantation. This study provides a detailed protocol of a highly reproducible reference model to test novel therapeutic options for limb ischemia.