基于前瞻性时空重排扫描统计量的传染病早期预警系统

目的探索前瞻性时空重排扫描统计量在传染病早期预警中的应用。方法模拟实时监测系统,采用前瞻性时空重排扫描统计量对成都市2005年麻疹病例数据进行逐日前瞻性分析。结果前瞻性时空重排扫描统计量能早期探测到传染病的爆发。结论利用前瞻性时空重排扫描统计量结合地理信息软件建立的早期预警系统,能有效地对传染病爆发做出早期预警。     

The use of outbreak information in the interpretation of clustering of reported cases of Escherichia coli O157 in space and time in Alberta, Canada, 2000-2002

We obtained a list of all reported cases of Escherichia coli O157 in Alberta during the 2000-2002 period, and using scan statistics we identified yearly temporal and spatial clusters of reported cases of E. coli O157 during the summer and in southern Alberta. However, the location of the spatial cluster in the south was variable among years. The impact of using both outbreak and sporadic data or only sporadic data on the identification of spatial and temporal clusters was small when analysing individual years, but the difference between spatial clusters was pronounced when scanning the entire study period. We also identified space-time clusters that incorporated known outbreaks, and clusters that were suggestive of undetected outbreaks that we attempted to validate with molecular data. Our results suggest that scan statistics, based on a space-time permutation model, may have a role in outbreak investigation and surveillance programmes by identifying previously undetected outbreaks.     

Development of spatial density maps based on geoprocessing web services: application to tuberculosis incidence in Barcelona, Spain

Background

The Prospective Space-Time scan statistic (PST) is widely used for the evaluation of space-time clusters of point event data. Usually a window of cylindrical shape is employed, with a circular or elliptical base in the space domain. Recently, the concept of Minimum Spanning Tree (MST) was applied to specify the set of potential clusters, through the Density-Equalizing Euclidean MST (DEEMST) method, for the detection of arbitrarily shaped clusters. The original map is cartogram transformed, such that the control points are spread uniformly. That method is quite effective, but the cartogram construction is computationally expensive and complicated.

Results

A fast method for the detection and inference of point data set space-time disease clusters is presented, the Voronoi Based Scan (VBScan). A Voronoi diagram is built for points representing population individuals (cases and controls). The number of Voronoi cells boundaries intercepted by the line segment joining two cases points defines the Voronoi distance between those points. That distance is used to approximate the density of the heterogeneous population and build the Voronoi distance MST linking the cases. The successive removal of edges from the Voronoi distance MST generates sub-trees which are the potential space-time clusters. Finally, those clusters are evaluated through the scan statistic. Monte Carlo replications of the original data are used to evaluate the significance of the clusters. An application for dengue fever in a small Brazilian city is presented.

Conclusions

The ability to promptly detect space-time clusters of disease outbreaks, when the number of individuals is large, was shown to be feasible, due to the reduced computational load of VBScan. Instead of changing the map, VBScan modifies the metric used to define the distance between cases, without requiring the cartogram construction. Numerical simulations showed that VBScan has higher power of detection, sensitivity and positive predicted value than the Elliptic PST. Furthermore, as VBScan also incorporates topological information from the point neighborhood structure, in addition to the usual geometric information, it is more robust than purely geometric methods such as the elliptic scan. Those advantages were illustrated in a real setting for dengue fever space-time clusters.     

A flexibly shaped space-time scan statistic for disease outbreak detection and monitoring

Background  

Early detection of disease outbreaks enables public health officials to implement disease control and prevention measures at the earliest possible time. A time periodic geographical disease surveillance system based on a cylindrical space-time scan statistic has been used extensively for disease surveillance along with the SaTScan software. In the purely spatial setting, many different methods have been proposed to detect spatial disease clusters. In particular, some spatial scan statistics are aimed at detecting irregularly shaped clusters which may not be detected by the circular spatial scan statistic.     

2005年成都市麻疹模拟实时监测与预警研究

目的探索前瞻性时空重排扫描统计量在麻疹早期预警中的应用。方法模拟实时监测,采用前瞻性时空重排扫描统计量,对成都市2005年麻疹数据进行逐日前瞻性分析。结果以6月份预警结果为例,6月10日发出预警信号,该预警信号包括的天数为2 d,所包括的乡镇街道为武侯区的簇桥街道和金花桥街道。结论前瞻性时空重排扫描统计量能充分利用数据信息,及时探测到传染病的聚集性发病。     

An empirical comparison of spatial scan statistics for outbreak detection

Background  

The spatial scan statistic is a widely used statistical method for the automatic detection of disease clusters from syndromic data. Recent work in the disease surveillance community has proposed many variants of Kulldorff's original spatial scan statistic, including expectation-based Poisson and Gaussian statistics, and incorporates a variety of time series analysis methods to obtain expected counts. We evaluate the detection performance of twelve variants of spatial scan, using synthetic outbreaks injected into four real-world public health datasets.     

A model-adjusted space-time scan statistic with an application to syndromic surveillance

The space-time scan statistic is often used to identify incident disease clusters. We introduce a method to adjust for naturally occurring temporal trends or geographical patterns in illness. The space-time scan statistic was applied to reports of lower respiratory complaints in a large group practice. We compared its performance with unadjusted populations from: (1) the census, (2) group-practice membership counts, and on adjustments incorporating (3) day of week, month, and holidays; and (4) additionally, local history of illness. Using a nominal false detection rate of 5%, incident clusters during 1 year were identified on 26, 22, 4 and 2% of days for the four populations respectively. We show that it is important to account for naturally occurring temporal and geographic trends when using the space-time scan statistic for surveillance. The large number of days with clusters renders the census and membership approaches impractical for public health surveillance. The proposed adjustment allows practical surveillance.     

Characteristics of Tuberculosis Cases that Started Outbreaks in the United States, 2002–2011

A review of 26 tuberculosis outbreaks in the United States (2002–2011) showed that initial source case-patients had long infectious periods (median 10 months) and were characterized by substance abuse, incarceration, and homelessness. Improved timeliness of diagnosis and thorough contact investigations for such cases may reduce the risk for outbreaks.     

Geographic clustering of nonmedical exemptions to school immunization requirements and associations with geographic clustering of pertussis

School immunization requirements are important in controlling vaccine-preventable diseases in the United States. Forty-eight states offer nonmedical exemptions to school immunization requirements. Children with exemptions are at increased risk of contracting and transmitting vaccine-preventable diseases. The clustering of nonmedical exemptions can affect community risk of vaccine-preventable diseases. The authors evaluated spatial clustering of nonmedical exemptions in Michigan and geographic overlap between exemptions clusters and clusters of reported pertussis cases. Kulldorf's scan statistic identified 23 statistically significant census tract clusters for exemption rates and 6 significant census tract clusters for reported pertussis cases between 1993 and 2004. The time frames for significant space-time pertussis clusters were August 1993-September 1993, August 1994-February 1995, May 1998-June 1998, April 2002, May 2003-July 2003, and June 2004-November 2004. Census tracts in exemptions clusters were more likely to be in pertussis clusters (odds ratio = 3.0, 95% confidence interval: 2.5, 3.6). The overlap of exemptions clusters and pertussis clusters remained significant after adjustment for population density, proportion of racial/ethnic minorities, proportion of children aged 5 years or younger, percentage of persons below the poverty level, and average family size (odds ratio = 2.7, 95% confidence interval: 2.2, 3.3). Geographic pockets of vaccine exemptors pose a risk to the whole community. In addition to monitoring state-level exemption rates, health authorities should be mindful of within-state heterogeneity.     

Evaluating cluster alarms: a space-time scan statistic and brain cancer in Los Alamos, New Mexico.

OBJECTIVES: This article presents a space-time scan statistic, useful for evaluating space-time cluster alarms, and illustrates the method on a recent brain cancer cluster alarms in Los Alamos, NM. METHODS: The space-time scan statistic accounts for the preselection bias and multiple testing inherent in a cluster alarm. Confounders and time trends can be adjusted for. RESULTS: The observed excess of brain cancer in Los Alamos was not statistically significant. CONCLUSIONS: The space-time scan statistic is useful as a screening tool for evaluating which cluster alarms merit further investigation and which clusters are probably chance occurrences.     

Detecting COVID-19 Clusters at High Spatiotemporal Resolution,New York City,New York,USA, June–July 2020

A surveillance system that uses census tract resolution and the SaTScan prospective space-time scan statistic detected clusters of increasing severe acute respiratory syndrome coronavirus 2 test percent positivity in New York City, NY, USA. Clusters included one in which patients attended the same social gathering and another that led to targeted testing and outreach.     

2011-2012年武威市凉州区胃癌时空特征分析

目的 探究2011-2012年武威市凉州区胃癌发病的时空分布特征。方法 利用空间经验贝叶斯平滑、时空扫描统计量分析方法,对胃癌发病数据进行分析。结果 平滑后的胃癌发病率高低值地区分布集中,有明显的聚集趋势。纯空间扫描与时空扫描均探测到该地区胃癌发病存在聚集性,纯空间扫描结果包括永昌镇、五和乡、洪祥镇等三个聚集区,扫描时间为2011-2012年;时空扫描同样得到三个聚集区,但在聚集区类别和大小上与空间扫描存在差异,其聚集时间为2011年1月1日～2011年12月31日。男女性时空扫描结果表明男女性胃癌发病也具有聚集性,且女性聚集区范围大于男性。结论 武威市胃癌发病持续走高,防控工作严峻。结合空间经验贝叶斯平滑、时空扫描统计量方法,能够克服区域人口间的差异,准确的找出胃癌空间分布特征及时空聚集性。     

前瞻性时空扫描统计量在传染病预警中的基线选择研究

目的探索将前瞻性时空扫描统计量运用于传染病预警中适宜基线的选择方法。方法根据当年流行情况选择发病高峰时段结合固定长度基线以及可变长度基线运用前瞻性时空扫描统计量进行模拟实时预警分析,通过不同长度基线的结果比较,探索不同基线在不同流行状况的适用差异并寻找选择适当基线的方法。结果固定长度基线产生了18个信号,而采用可变长度基线只纳入高峰期数据的预警则产生了28个信号,且这28个信号中完全包括了固定长度基线产生的18个信号。其中2009年4月17日及18日固定长度基线的1号信号均被以可变长度基线的时空扫描统计量分为3个较小但发病率更高的信号。结论在发病高峰期选择可变长度基线能够更加精确地区分聚集性区域,并且在经过排除重叠信号后,可以得到更高的探测效能。     

前瞻性时空扫描统计量与时空重排扫描统计量在传染病聚集性探测中的适用性探讨

目的探讨前瞻性时空扫描统计量与时空重排扫描统计量在传染病聚集性探测中的适用性。方法以成都市2009年5、6月细菌性痢疾病例数据为例,分别采用前瞻性时空扫描统计量与时空重排扫描统计量,运用SaTScan9.0软件进行聚集性探测,并对结果进行比较分析。结果前瞻性时空扫描统计量扫描结果与成都各区县实际发病轨迹较接近,前瞻性时空重排扫描统计量在发病率较低的区域扫描结果有相对较多的误报。结论由于前瞻性时空扫描统计量考虑了人口数据信息,在低发病区域,实际应用中应尽量采用时空扫描统计量进行聚集性探测。     

Use of the local Knox statistic for the prospective monitoring of disease occurrences in space and time

The detection of clusters of events occurring close together both temporally and spatially is important in finding outbreaks of disease within a geographic region. The Knox statistic is often used in epidemiology to test for space-time clustering retrospectively. For quicker detection of epidemics, prospective methods should be used in which observed events in space and time are assessed as they are recorded. The cumulative sum (CUSUM) surveillance method for monitoring the local Knox statistic tests for space-time clustering each time there is an incoming observation. We consider the design of this control chart by determining the in-control average run length (ARL) performance of the CUSUM chart for different space and time closeness thresholds as well as for different control limit values. We also explain the effect of population density and region shape on the in-control ARL and discuss other distributional issues that should be considered when implementing this method.     

Daily Reportable Disease Spatiotemporal Cluster Detection,New York City,New York,USA, 2014–2015

Each day, the New York City Department of Health and Mental Hygiene uses the free SaTScan software to apply prospective space–time permutation scan statistics to strengthen early outbreak detection for 35 reportable diseases. This method prompted early detection of outbreaks of community-acquired legionellosis and shigellosis.     

Timeliness of national reporting of communicable diseases: the experience of the National Electronic Telecommunications System for Surveillance.

The timeliness of reporting four nationally notifiable diseases was examined using data reported via the National Electronic Telecommunications System for Surveillance. Timeliness of reporting varied by disease (bacterial meningitis: median 20 days; salmonellosis: median 22 days; shigellosis: median 23 days; and hepatitis A: median 33 days) and by state. These findings indicate a need to standardize surveillance definitions and to account for reporting differences between states in interpreting regional disease trends or detecting multistate disease outbreaks.     

2012年北京市手足口病时空扫描分析研究

目的探讨北京市手足口病发病时空分布特征,为手足口病预防控制提供理论依据。方法利用SaTScan 9.1.1软件进行时空扫描分析,通过ArcGIS 9.3软件呈现不同扫描半径下手足口病空间聚集区域。结果 2012年北京市累计报告手足口病病例38 528例,年均发病率为190.86/10万。通过时空扫描分析发现,2012年大兴区为手足口病发病最可能聚集区域,聚集时间可能为5月23～29日和6月1～7日。结论 2012年北京市手足口病高发地区存在明显空间区域性,时空扫描分析方法较好地分析北京市手足口病高发重点区域,为防控工作提供技术支持。     

Space-time pattern of hepatitis A in Spain, 1997-2007

In Spain hepatitis A is a compulsory notifiable disease and individual cases are reported to the national epidemiological surveillance network. Incidence rates show variations in different regions. The aim of this study was to analyse the space-time pattern of hepatitis A risk at municipal level in Spain and at global and local levels during the period 1997-2007. At global level we used two estimates of risk: the standardized incidence ratio (SIR) and the posterior probability that the smoothed relative risk is >1 (PP). At local level we used the scan statistic method to analyse the space-time clusters. The SIR and significant PP (>0·8) showed the highest risk concentrated in areas of the Mediterranean coast. The most likely cluster gave a relative risk of 53·530. These spatial statistics methodologies can be complementary tools in the epidemiological surveillance of infectious diseases.     

Dead bird clusters as an early warning system for West Nile virus activity

An early warning system for West Nile virus (WNV) outbreaks could provide a basis for targeted public education and surveillance activities as well as more timely larval and adult mosquito control. We adapted the spatial scan statistic for prospective detection of infectious disease outbreaks, applied the results to data on dead birds reported from New York City in 2000, and reviewed its utility in providing an early warning of WNV activity in 2001. Prospective geographic cluster analysis of dead bird reports may provide early warning of increasing viral activity in birds and mosquitoes, allowing jurisdictions to triage limited mosquito-collection and laboratory resources and more effectively prevent human disease caused by the virus. This adaptation of the scan statistic could also be useful in other infectious disease surveillance systems, including those for bioterrorism.