A Space–Time Permutation Scan Statistic for Disease Outbreak Detection

Abstract

BackgroundThe ability to detect disease outbreaks early is important in order to minimize morbidity and mortality through timely implementation of disease prevention and control measures. Many national, state, and local health departments are launching disease surveillance systems with daily analyses of hospital emergency department visits, ambulance dispatch calls, or pharmacy sales for which population-at-risk information is unavailable or irrelevant.Methods and FindingsWe propose a prospective space–time permutation scan statistic for the early detection of disease outbreaks that uses only case numbers, with no need for population-at-risk data. It makes minimal assumptions about the time, geographical location, or size of the outbreak, and it adjusts for natural purely spatial and purely temporal variation. The new method was evaluated using daily analyses of hospital emergency department visits in New York City. Four of the five strongest signals were likely local precursors to citywide outbreaks due to rotavirus, norovirus, and influenza. The number of false signals was at most modest.ConclusionIf such 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.

Geostatistical visualisation and spatial statistics for evaluation of the dispersion of epidemic highly pathogenic avian influenza subtype H5N1

“…Spatial weights were defined by the inverse of Euclidean distance squared, and were globally standardized. Reported outbreaks were also examined (SaTScan version 6.1.2, www.satscan.org) for clusters in time and space using the scan statistic space-time permutation model [14]. Outbreak data -location [x, y] and reported date of outbreaks [z] -were analysed.…”

A susceptible-infected model of early detection of respiratory infection outbreaks on a background of influenza

“…This number is then representative of a subpopulation of infected children who have lived in the vicinity of CH and have made visits to its ED when ill. Such spatial specificity, however, is imperative for detecting abnormal events rapidly and decisively because unusual events often occur in a spatially localized manner, and are seldom distributed uniformly throughout space (Kleinman et al, 2004;Kulldorff et al, 2005).…”

Multivariate scan statistics for disease surveillance

“…Other probability models have also been used for scan statistics. A Bernoulli model is used for 0/1 case-control type data [2], an ordinal model for ordinal data [20], an exponential model for survival data [21] and a space-time permutation model for looking at space-time interaction clusters when only case data is available [9]. The latter also uses the Poisson distribution but it is an approximate rather than an exact log likelihood ratio.…”

“…For this example, the prospective space-time permutation scan statistic [9] was used for the early detection of disease outbreaks. This scan statistic uses only case data and the expected values for each location and time period is calculated by conditioning on the marginals.…”

“…One very interesting application of the space-time scan statistic is in syndromic surveillance for the early detection of disease outbreaks [8,9]. In syndromic surveillance, symptoms such as fever or vomiting are used for the early detection of disease outbreaks.…”