Journal ArticleDOI
A spatial scan statistic
TLDR
In this article, a spatial scan statistic for the detection of clusters in a multi-dimensional point process is proposed, where the area of the scanning window is allowed to vary, and the baseline process may be any inhomogeneous Poisson process or Bernoulli process with intensity pro-portional to some known function.Abstract:
The scan statistic is commonly used to test if a one dimensional point process is purely random, or if any clusters can be detected. Here it is simultaneously extended in three directions:(i) a spatial scan statistic for the detection of clusters in a multi-dimensional point process is proposed, (ii) the area of the scanning window is allowed to vary, and (iii) the baseline process may be any inhomogeneous Poisson process or Bernoulli process with intensity pro-portional to some known function. The main interest is in detecting clusters not explained by the baseline process. These methods are illustrated on an epidemiological data set, but there are other potential areas of application as well.read more
Citations
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Journal ArticleDOI
Rapid phylogenetic analysis of large samples of recombinant bacterial whole genome sequences using Gubbins.
Nicholas J. Croucher,Andrew J. Page,Thomas R. Connor,Aidan Delaney,Jacqueline A. Keane,Stephen D. Bentley,Julian Parkhill,Simon R. Harris +7 more
TL;DR: Gubbins is an iterative algorithm that uses spatial scanning statistics to identify loci containing elevated densities of base substitutions suggestive of horizontal sequence transfer while concurrently constructing a maximum likelihood phylogeny based on the putative point mutations outside these regions of high sequence diversity.
Journal ArticleDOI
Geographical Detectors-Based Health Risk Assessment and its Application in the Neural Tube Defects Study of the Heshun Region, China
TL;DR: In a real‐world study, the primary physical environment was found to strongly control the neural tube defects (NTD) occurrences in the Heshun region (China) and basic nutrition was finding to be more important than man‐made pollution in the control of the spatial NTD pattern.
Book
Spatial Data Analysis: Theory and Practice
TL;DR: This work focuses on the development of models for statistical modeling of spatial variation in the context of scientific and policy context, as well as the nature of spatial data.
Journal ArticleDOI
A space-time permutation scan statistic for disease outbreak detection.
Martin Kulldorff,Richard Heffernan,Jessica Hartman,Jessica Hartman,Renato M. Assunção,Farzad Mostashari +5 more
TL;DR: If results hold up over longer study times and in other locations, the space–time permutation scan statistic will be an important tool for local and national health departments that are setting up early disease detection surveillance systems.
Journal ArticleDOI
Graph based anomaly detection and description: a survey
TL;DR: This survey aims to provide a general, comprehensive, and structured overview of the state-of-the-art methods for anomaly detection in data represented as graphs, and gives a general framework for the algorithms categorized under various settings.
References
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Journal ArticleDOI
Hypothesis testing when a nuisance parameter is present only under the alternative
TL;DR: In this article, the authors used a test derived from the corresponding family of test statistics appropriate for the case when 0 is given and applied to the two-phase regression problem in the normal case.
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Modified Randomization Tests for Nonparametric Hypotheses
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The Detection of Space-Time Interactions
TL;DR: Any useful concept of epidemicity at this level is a corpuscular one and the methodological problems in many respects analogous with those of the physicist studying low-intensity radiation.
Journal ArticleDOI
Spatial clustering for inhomogeneous populations
Jack Cuzick,Robert Edwards +1 more
TL;DR: A new method for detecting spatial clustering of events in populations with non-uniform density is proposed, based on selecting controls from the population at risk and computing interpoint distances for the combined sample.