ArticleJMIR public health and surveillance2024
Prospective Spatiotemporal Cluster Detection Using SaTScan: Tutorial for Designing and Fine-Tuning a System to Detect Reportable Communicable Disease Outbreaks.
Article in JMIR public health and surveillance, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed.
- Detection of Acute Hepatitis C Outbreaks in California Using SaTScan: Statewide Spatiotemporal Analysis.JMIR public health and surveillance · 2026Article
- Geospatial clustering of type 1 diabetes in Sweden: a cohort study based on all residential locations from birth to diagnosis.Diabetologia · 2026Article
- Asyndromic surveillance of New York City emergency department diagnoses with the tree-temporal scan statistic.Journal of public health research · 2026Article
- Epidemiological characteristics and spatiotemporal trend analysis of human brucellosis in Shanxi Province, China, 2014-2024.BMC public health · 2026Article
- Socioeconomic drivers of human Brucellosis in Ningxia, China: A one health and spatiotemporal analysis for targeted intervention.PLoS neglected tropical diseases · 2026Article
- An Open-Source Data Driven Hybrid Modeling System for Infectious Disease Surveillance and Early Warning.China CDC weekly · 2026Article
- CalCORVID: a dynamic RShiny dashboard approach to visualize spatiotemporal clusters for public health surveillance.BMC public health · 2026Article
- Spatiotemporal clusters and dengue hotspots in the Philippines: a nationwide analysis spanning 2017-2024.Frontiers in public health · 2026Article
- From Clustered to Sporadic: Structural Shifts in the Spatiotemporal Dynamics of HPAI Following the 2017 Policy Reinforcement in South Korea (2003-2025).Transboundary and emerging diseases · 2026Article
- Geographical variations of health facilities management teams' functionality in Ethiopia: Spatial analysis of Ethiopian Service Provision Assessment (SPA) 2021-2022.SAGE open medicine · 2026Article
- Spatiotemporal Analysis of Mortality from Cardiomyopathies in Brazil between 2001 and 2021.Arquivos brasileiros de cardiologia · 2026Article
- Spatiotemporal analysis and risk prediction of foodborne diseases based on meteorological risk factors: a case study of Wuxi city, China.BMC infectious diseases · 2025Article
- Spatial and temporal behavior of rocky mountain spotted fever in Sinaloa, Mexico: study period 2015-2023.Revista peruana de medicina experimental y salud publica · 2025Article
- Spatiotemporal dynamics and policy impact on farmer suicides in Maharashtra, India.Scientific reports · 2025Article
- Global patterns and trends in deaths of influenza-associated lower respiratory infections from 1990 to 2019.Epidemiology and infection · 2025Article
- Applying prospective tree-temporal scan statistics to genomic surveillance data to detect emerging SARS-CoV-2 variants and salmonellosis clusters in New York City.International journal of epidemiology · 2025Article
- Investigating Transboundary Spread Patterns and Cluster Characteristics of Lumpy Skin Disease (LSD) Outbreaks in Asia: Levering the Outbreak Data (2019-2023) to Support the LSD Prevention and Control Strategies.Transboundary and emerging diseases · 2025Article
- Spatiotemporal Cluster Detection for COVID-19 Outbreak Surveillance: Descriptive Analysis Study.JMIR public health and surveillance · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Staff at public health departments have few training materials to learn how to design and fine-tune systems to quickly detect acute, localized, community-acquired outbreaks of infectious diseases. Since 2014, the Bureau of Communicable Disease at the New York City Department of Health and Mental Hygiene has analyzed reportable communicable diseases daily using SaTScan. SaTScan is a free software that analyzes data using scan statistics, which can detect increasing disease activity without a priori specification of temporal period, geographic location, or size. The Bureau of Communicable Disease's systems have quickly detected outbreaks of salmonellosis, legionellosis, shigellosis, and COVID-19. This tutorial details system design considerations, including geographic and temporal data aggregation, study period length, inclusion criteria, whether to account for population size, network location file setup to account for natural boundaries, probability model (eg, space-time permutation), day-of-week effects, minimum and maximum spatial and temporal cluster sizes, secondary cluster reporting criteria, signaling criteria, and distinguishing new clusters versus ongoing clusters with additional events. We illustrate how to support health equity by minimizing analytic exclusions of patients with reportable diseases (eg, persons experiencing homelessness who are unsheltered) and accounting for purely spatial patterns, such as adjusting nonparametrically for areas with lower access to care and testing for reportable diseases. We describe how to fine-tune the system when the detected clusters are too large to be of interest or when signals of clusters are delayed, missed, too numerous, or false. We demonstrate low-code techniques for automating analyses and interpreting results through built-in features on the user interface (eg, patient line lists, temporal graphs, and dynamic maps), which became newly available with the July 2022 release of SaTScan version 10.1. This tutorial is the first comprehensive resource for health department staff to design and maintain a reportable communicable disease outbreak detection system using SaTScan to catalyze field investigations as well as develop intuition for interpreting results and fine-tuning the system. While our practical experience is limited to monitoring certain reportable diseases in a dense, urban area, we believe that most recommendations are generalizable to other jurisdictions in the United States and internationally. Additional analytic technical support for detecting outbreaks would benefit state, tribal, local, and territorial public health departments and the populations they serve.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.