SaTScan-User-Guide.pdf

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Introduction

The SaTScan Software

Purpose

Data Types and Methods

Developers and Funders

Download and Installation

Test Run

Sample Data Sets

Discrete Poisson Model, Space-Time and Spatial Variation in Temporal Trends: Brain Cancer Incidence in New Mexico

Bernoulli Model, Purely Spatial : Childhood Leukemia and Lymphoma Incidence in North Humberside

Space-Time Permutation Model: Hospital Emergency Room Admissions Due to Fever at New York City Hospitals

Multinomial and Ordinal Model, Purely Spatial: Education Attainment Levels in Maryland

Exponential Model, Space-Time : Artificially Created Survival Data

Normal Model, Purely Spatial : Artificially Created Continuous Data

Statistical Methodology

Spatial, Temporal and Space-Time Scan Statistics

Spatial Scan Statistic

Space-Time Scan Statistic

Temporal Scan Statistic

Bernoulli Model

Discrete Poisson Model

Space-Time Permutation Model

Multinomial Model

Ordinal Model

Exponential Model

Normal Model

Continuous Poisson Model

Probability Model Comparison

Few Cases Compared to Controls

Bernoulli versus Ordinal Model

Normal versus Exponential Model

Normal versus Ordinal Model

Discrete versus Homogeneous Poisson Model

Temporal Data

Likelihood Ratio Test

Non-Compactness Penalty Function

Secondary Clusters

Adjusting for More Likely Clusters

Covariate Adjustments

Covariate Adjustment Using the Input Files

E[c] = p*C/P

Covariate Adjustment Using Statistical Regression Software

Covariate Adjustment Using Multiple Data Sets

Spatial and Temporal Adjustments

Adjusting for Temporal Trends

Adjusting for Purely Spatial Clusters

Adjusting for Known Relative Risks

Missing Data

Bernoulli Model

Multinomial and Ordinal Models

Discrete Poisson Model

Continuous Poisson Model

Space-Time Permutation Model

Multivariate Scan with Multiple Data Sets

Comparison with Other Methods

Scan Statistics

Spatial and Space-Time Clustering

Descriptive Cluster Detection Methods

Cluster Detection Tests

Focused Cluster Tests

Global Clustering Tests

Global Space-Time Interaction Tests

Input Data

Data Requirements

Case File

Control File

Population File

Coordinates File

Cartesian Coordinates

Latitude and Longitude

Grid File

Non-Euclidian Neighbors File

Meta Location File

Max Circle Size File

Adjustments File

SaTScan Import Wizard

Step 1 – Selecting the Source File

Step 2: Specifying the File Format

Step 3: Matching Source File Variables with SaTScan Variables

Step 4: Saving the Imported File

SaTScan ASCII File Format

Time Formats

Basic SaTScan Features

Input Tab

Case File Name

Control File Name

Time Precision

Study Period

Population File Name

Coordinates File Name

Grid File Name

Coordinates

Analysis Tab

Type of Analysis

Probability Model

Discrete Poisson Model: The discrete Poisson model should be used when the background population reflects a certain risk mass such as total person years lived in an area. The cases are then included as part of the population count.

Continuous Poisson Model: The continuous Poisson model should be used when the null hypothesis is that observations are distributed randomly with constant intensity according to a homogeneous Poisson process over a user defined study area.

Polygons for the Continuous Poisson Model

Scan for High or Low Rates

Time Aggregation

Output Tab

Results File Name

Additional Output Files

Advanced Features

Multiple Data Sets Tab

Data Checking Tab

Temporal Data Check

Geographical Data Check

Neighbors Tab

Non-Euclidian Neighbors File

Meta Location File

Multiple Coordinates per Location

Spatial Window Tab

Maximum Spatial Cluster Size

Include Purely Temporal Clusters

Elliptic Scanning Window

Isotonic Spatial Scan Statistic

Temporal Window Tab

Maximum Temporal Cluster Size

Include Purely Spatial Clusters

Flexible Temporal Window Definition

Spatial and Temporal Adjustments Tab

Temporal Trend Adjustment

Spatial Adjustment

Adjustment with Known Relative Risks

Inference Tab

P-Value

Adjust for Earlier Analyses in Prospective Surveillance

Iterative Scan Statistic

Clusters Reported Tab

Criteria for Reporting Secondary Clusters

Maximum Reported Spatial Cluster Size

Additional Output Tab

Critical Values

Monte Carlo Rank

Column Headers

Running SaTScan

Specifying Analysis and Data Options

Launching the Analysis

Status Messages

Warnings and Errors

Warning Messages

Error Messages

Saving Analysis Parameters

To save analysis parameters

To open a saved parameter file

Parallel Processors

Batch Mode

Computing Time

Single Data Set

Multiple Data Sets

Memory Requirements

Standard Memory Allocation

Special Memory Allocation

Insufficient Memory

Results of Analysis

Standard Results File (*.out.*)

Cluster Information File (*.col.*)

Stratified Cluster Information File (*.sci.*)

Location Information File (*.gis.*)

Risk Estimates for Each Location File (*.rr.*)

Simulated Log Likelihood Ratios File (*.llr.*)

Miscellaneous

New Versions

Analysis History File

Random Number Generator

Acknowledgements

Financial Support

Comments and Suggestions

Frequently Asked Questions

Input Data

Analysis

Results

Interpretation

Operating Systems

SaTScan Bibliography

Suggested Citations

SaTScan Methodology Papers

Statistical Methodology

Normal Model

Adjustments

Adjusting for Covariates

Iterative Scan Statistics, Adjusting for More Likely Clusters

Computational Aspects

Algorithms

Random Number Generator

Macros

Visualization and Mapping

Methods Evaluations and Comparisons

Selected SaTScan Applications by Field of Study

Infectious Diseases

Parasitology

Syndromic Surveillance

Cancer

Cardiology

Rheumatology / Auto-Immune Diseases

Liver Diseases

Diabetes

Allergy and Asthma

Birth Defects and Other Congenital Outcomes

Pediatrics

Geriatrics

Neurological Diseases

Psychology

Brain Imaging

Alcohol and Drugs

Accidents and Suicide

Demography

Veterinary Medicine, Domestic Animals

Veterinary Medicine, Wildlife

Entomology

Ichthyology

Botany

Forestry

Ecology and the Environment

Natural and Human Disasters

Criminology

Transportation

History

Astronomy

Other References Mentioned in the User Guide

SaTScan TM User Guide for version 9.0 By Martin Kulldorff July, 2010 http://www.satscan.org/

Contents Introduction .................................................................................................................................................. 4 The SaTScan Software ..................................................................................................................... 4 Download and Installation ................................................................................................................ 5 Test Run ........................................................................................................................................... 5 Sample Data Sets .............................................................................................................................. 6 Statistical Methodology ................................................................................................................................ 9 Spatial, Temporal and Space-Time Scan Statistics ........................................................................ 10 Bernoulli Model ............................................................................................................................. 11 Discrete Poisson Model .................................................................................................................. 12 Space-Time Permutation Model ..................................................................................................... 12 Multinomial Model ........................................................................................................................ 13 Ordinal Model ................................................................................................................................ 14 Exponential Model ......................................................................................................................... 14 Normal Model ................................................................................................................................ 15 Continuous Poisson Model ............................................................................................................. 16 Probability Model Comparison ...................................................................................................... 17 Likelihood Ratio Test ..................................................................................................................... 18 Secondary Clusters ......................................................................................................................... 20 Adjusting for More Likely Clusters ................................................................................................ 20 Covariate Adjustments ................................................................................................................... 21 Spatial and Temporal Adjustments................................................................................................. 24 Missing Data .................................................................................................................................. 25 Multivariate Scan with Multiple Data Sets ..................................................................................... 27 Comparison with Other Methods.............................................................................................................. 28 Scan Statistics ................................................................................................................................. 28 Spatial and Space-Time Clustering ................................................................................................ 28 Input Data ................................................................................................................................................... 30 Data Requirements ......................................................................................................................... 30 Case File ......................................................................................................................................... 31 Control File .................................................................................................................................... 32 Population File ............................................................................................................................... 33 Coordinates File ............................................................................................................................. 33 Grid File ......................................................................................................................................... 35 Non-Euclidian Neighbors File ........................................................................................................ 35 Meta Location File ......................................................................................................................... 36 Max Circle Size File ....................................................................................................................... 36 Adjustments File............................................................................................................................. 37 SaTScan Import Wizard ................................................................................................................. 37 SaTScan ASCII File Format ........................................................................................................... 39 Basic SaTScan Features ............................................................................................................................. 41 Input Tab ........................................................................................................................................ 41 Analysis Tab ................................................................................................................................... 44 Output Tab ..................................................................................................................................... 48 Advanced Features ..................................................................................................................................... 50 Multiple Data Sets Tab ................................................................................................................... 50 Data Checking Tab ......................................................................................................................... 52 Neighbors Tab ................................................................................................................................ 53 Spatial Window Tab ....................................................................................................................... 54 Temporal Window Tab .................................................................................................................. 57 Spatial and Temporal Adjustments Tab ......................................................................................... 59 Inference Tab ................................................................................................................................. 61 SaTScan User Guide v9.0

Clusters Reported Tab .................................................................................................................... 64 Additional Output Tab ................................................................................................................... 66 Running SaTScan ....................................................................................................................................... 68 Specifying Analysis and Data Options ........................................................................................... 68 Launching the Analysis .................................................................................................................. 68 Status Messages .............................................................................................................................. 69 Warnings and Errors....................................................................................................................... 69 Saving Analysis Parameters ........................................................................................................... 70 Parallel Processors ......................................................................................................................... 71 Batch Mode .................................................................................................................................... 71 Computing Time............................................................................................................................. 72 Memory Requirements ................................................................................................................... 73 Results of Analysis ...................................................................................................................................... 76 Standard Results File (*.out.*) ....................................................................................................... 76 Cluster Information File (*.col.*) ................................................................................................... 78 Stratified Cluster Information File (*.sci.*) .................................................................................... 80 Location Information File (*.gis.*) ................................................................................................ 80 Risk Estimates for Each Location File (*.rr.*) ............................................................................... 81 Simulated Log Likelihood Ratios File (*.llr.*) ............................................................................... 81 Miscellaneous .............................................................................................................................................. 82 New Versions ................................................................................................................................. 82 Analysis History File ...................................................................................................................... 82 Random Number Generator ........................................................................................................... 82 Contact Us ...................................................................................................................................... 82 Acknowledgements ........................................................................................................................ 83 Frequently Asked Questions ...................................................................................................................... 85 Input Data ....................................................................................................................................... 85 Analysis .......................................................................................................................................... 86 Results ............................................................................................................................................ 86 Interpretation .................................................................................................................................. 87 Operating Systems .......................................................................................................................... 89 SaTScan Bibliography ................................................................................................................................ 90 Suggested Citations ........................................................................................................................ 90 SaTScan Methodology Papers........................................................................................................ 91 Selected SaTScan Applications by Field of Study ......................................................................... 95 Other References Mentioned in the User Guide ........................................................................... 107 SaTScan User Guide v9.0

Introduction The SaTScan Software Purpose SaTScan is a free software that analyzes spatial, temporal and space-time data using the spatial, temporal, or space-time scan statistics. It is designed for any of the following interrelated purposes: • Perform geographical surveillance of disease, to detect spatial or space-time disease clusters, and to see if they are statistically significant. • Test whether a disease is randomly distributed over space, over time or over space and time. • Evaluate the statistical significance of disease cluster alarms. • Perform prospective real-time or time-periodic disease surveillance for the early detection of disease outbreaks. The software may also be used for similar problems in other fields such as archaeology, astronomy, botany, criminology, ecology, economics, engineering, forestry, genetics, geography, geology, history, neurology or zoology. Data Types and Methods SaTScan can be used for discrete as well as continuous scan statistics. For discrete scan statistics the geographical locations where data are observed are non-random and fixed by the user. These locations may be the actual locations of the observations, such as houses, schools or ant nests, or it could be a central location representing a larger area, such as the geographical or population weighted centroids of postal areas, counties or provinces. For continuous scan statistics, the locations of the observations are random and can occur anywhere within a predefined study area defined by the user, such as a rectangle. For discrete scan statistics, SaTScan uses either a discrete Poisson-based model, where the number of events in a geographical location is Poisson-distributed, according to a known underlying population at risk; a Bernoulli model, with 0/1 event data such as cases and controls; a space-time permutation model, using only case data; a multinomial model for categorical data; an ordinal model, for ordered categorical data; an exponential model for survival time data with or without censored variables; a normal model for other types of continuous data; or a spatial variation in temporal trends model, looking for geographical areas with unusually high or low temporal trends. A common feature of all these discrete scan statistics is that the geographical locations where data can be observed are non-random and fixed by the user. For the discrete scan statistics, the data may be either aggregated at the census tract, zip code, county or other geographical level, or there may be unique coordinates for each observation. SaTScan adjusts for the underlying spatial inhomogeneity of a background population. It can also adjust for any number of categorical covariates provided by the user, as well as for temporal trends, known space-time clusters and missing data. It is possible to scan multiple data sets simultaneously to look for clusters that occur in one or more of them. For continuous scan statistics, SaTScan uses a continuous Poisson model. SaTScan User Guide v9.0 4

Developers and Funders The SaTScan™ software was developed by Martin Kulldorff together with Information Management Services Inc. Financial support for SaTScan has been received from the following institutions: • National Cancer Institute, Division of Cancer Prevention, Biometry Branch [v1.0, 2.0, 2.1] • National Cancer Institute, Division of Cancer Control and Population Sciences, Statistical Research and Applications Branch [v3.0 (part), v6.1 (part), 8.0 (part), v9.0 (part)] • Alfred P. Sloan Foundation, through a grant to the New York Academy of Medicine (Farzad Mostashari, PI) [v3.0 (part), 3.1, 4.0, 5.0, 5.1] • Centers for Disease Control and Prevention, through Association of American Medical Colleges Cooperative Agreement award number MM-0870 [v6.0, 6.1 (part)]. • National Institute of Child Health and Development, through grant #RO1HD048852 [7.0, 8.0, 9.0 (part)] • National Cancer Institute, Division of Cancer Epidemiology and Genetics [v9.0 (part)] • National Institute of General Medical Sciences, through a Modelling Infectious Disease Agent Studies grant #U01GM076672 [v9.0 (part)] Their financial support is greatly appreciated. The contents of SaTScan are the responsibility of the developer and do not necessarily reflect the official views of the funders. Related Topics: Statistical Methodology, SaTScan Bibliography Download and Installation To install SaTScan, go to the SaTScan Web site at: http://www.satscan.org/ and select the SaTScan download link. After downloading the SaTScan installation executable to your PC, click on its icon and install the software by following the step-wise instructions. Related Topics: New Versions. Test Run Before using your own data, we recommend trying one of the sample data sets provided with the software. Use these to get an idea of how to run SaTScan. To perform a test run: 1. Click on the SaTScan application icon. 2. Click on ‘Open Saved Session’. 3. Select one of the parameter files, for example ‘nm.prm’ (Poisson model), ‘NHumberside.prm’ (Bernoulli model) or ‘NYCfever.prm’ (space-time permutation model). 4. Click on ‘Open’. 5. Click on the Execute button. A new window will open with the program running in the top section and a Warnings/Errors section below. When the program finishes running the results will be displayed. SaTScan User Guide v9.0 5

Note: The sample files should not produce warnings or errors. Related Topics: Sample Data Sets. Sample Data Sets Six different sample data sets are provided with the software. They are automatically downloaded to your computer sets are available at the http://www.satscan.org/datasets/. together with sample data software itself. Other Discrete Poisson Model, Space-Time and Spatial Variation in Temporal Trends: Brain Cancer Incidence in New Mexico Case file: nm.cas Format: Population file: nm.pop Format: Coordinates file: nm.geo Format:

Study period: 1973-1991 Aggregation: 32 counties Precision of case times: Years Coordinates: Cartesian Covariate #1, age groups: 1 = 0-4 years, 2 = 5-9 years, ... 18 = 85+ years Covariate #2, gender: 1 = male, 2 = female Population years: 1973, 1982, 1991 Data source: New Mexico SEER Tumor Registry This is a condensed version of a more complete data set with the population given for each year from 1973 to 1991, and with ethnicity as a third covariate. The complete data set can be found at: http://www.satscan.org/datasets/ Bernoulli Model, Purely Spatial : Childhood Leukemia and Lymphoma Incidence in North Humberside Case file: NHumberside.cas Format: <# cases> Control file: Nhumberside.ctl Format: <# controls> Coordinates file: Nhumberside.geo Format:

SaTScan User Guide v9.0 6

Study period: 1974-1986 Controls: Randomly selected from the birth registry Aggregation: 191 Postal Codes (most with only a single individual) Precision of case and control times: None Coordinates: Cartesian Covariates: None Data source: Drs. Ray Cartwright and Freda Alexander. Published by J. Cuzick and R. Edwards, Journal of the Royal Statistical society, B:52 73-104, 1990 Space-Time Permutation Model: Hospital Emergency Room Admissions Due to Fever at New York City Hospitals Case file: NYCfever.cas Format: <#cases=1> Coordinates file: NYCfever.geo Format: Study period: Nov 1, 2001 – Nov 24, 2001 Aggregation: Zip code areas Precision of case times: Days Coordinates: Latitude/Longitude Covariates: None Data source: New York City Department of Health Multinomial and Ordinal Model, Purely Spatial: Education Attainment Levels in Maryland Case file: MarylandEducation.cas Format: <# individuals> Coordinates file: MarylandEducation.geo Format: Study period: 2000 Aggregation: 24 Counties and County Equivalents Precision of case times: None Coordinates: Latitude / Longitude Covariates: None Categories: 1 = Less than 9th grade 2 = 9th to 12th grade, but no high school diploma 3 = High school diploma, but no bachelor degree 4 = Bachelor or higher degree SaTScan User Guide v9.0 7

Data source: United States Census Bureau: Information about education comes from the long Census 2000 form, filled in by about 1/6 households. Note: Only people age 25 and above are included in the data. For each county, the census provides information about the percent of people with different levels of formal education. The number of individuals reporting different education levels in each county was estimated as this percentage times the total population age 25+ divided by six to reflect the 1/6 sampling fraction for the long census form. Exponential Model, Space-Time : Artificially Created Survival Data Case file: SurvivalFake.cas Format: <# individuals> Coordinates file: SurvivalFake.geo Format:

Study period: 2000-2005 Aggregation: 5 Locations Precision of times of diagnosis: Year Precision of survival/censoring times: Day Coordinates: Cartesian Covariates: None Data source: Artificially created data. Normal Model, Purely Spatial : Artificially Created Continuous Data Case file: NormalFake.cas Format: <# individuals> Coordinates file: NormalFake.geo Format:

Study period: 2006 Aggregation: 26 Locations Coordinates: Cartesian Covariates: None Data source: Artificially created data. Related Topics: Test Run, Input Data. SaTScan User Guide v9.0 8

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