ArticleSpatial and spatio-temporal epidemiology2020
Daily surveillance of COVID-19 using the prospective space-time scan statistic in the United States.
Article in Spatial and spatio-temporal epidemiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers, 2 of them syntheses that pooled it.
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Who cites it
72 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Methods Used in the Spatial and Spatiotemporal Analysis of COVID-19 Epidemiology: A Systematic Review.International journal of environmental research and public health · 2022Pooled it
- Analysis of distribution characteristics of COVID-19 in America based on space-time scan statistic.Frontiers in public health · 2022Pooled it
- Detection of Acute Hepatitis C Outbreaks in California Using SaTScan: Statewide Spatiotemporal Analysis.JMIR public health and surveillance · 2026Article
- Spatial-temporal patterns, seasonality, and age-specific trends of varicella in Hangzhou, China, 2019-2024.Frontiers in public health · 2026Article
- State-level nutritional disparities and policy priorities in India.Frontiers in nutrition · 2026Article
- Four million COVID-19 cases in four European cross-border regions reveal minimal cross-border transmission effect on domestic burden: space-time cluster analysis.BMC infectious diseases · 2025Article
- Epidemiological Investigation of Infectious Diseases at the Domestic-Synanthropic-Wild Animal Interface Reveals Threats to Endangered Species Reintroduction in AlUla, Saudi Arabia.Veterinary sciences · 2025Article
- Global infectious disease early warning models: An updated review and lessons from the COVID-19 pandemic.Infectious Disease Modelling · 2025Review
- Geospatial analysis of cholera outbreak in Lusaka, Zambia, between 2023 and 2024.Tropical medicine and health · 2025Article
- The use of SatScan software to map spatiotemporal trends and detect disease clusters: a systematic review.Communications medicine · 2025Article
- A Novel Bayesian Spatio-Temporal Surveillance Metric to Predict Emerging Infectious Disease Areas of High Disease Risk.Statistics in medicine · 2024Article
- Spatiotemporal Cluster Detection for COVID-19 Outbreak Surveillance: Descriptive Analysis Study.JMIR public health and surveillance · 2024Article
- Environmental and geographical factors influencing the spread of SARS-CoV-2 over 2 years: a fine-scale spatiotemporal analysis.Frontiers in public health · 2024Article
- Dimensions of Uncertainty: A spatiotemporal review of five COVID-19 datasets.Cartography and geographic information science · 2024Article
- The Next Generation of Dashboards: a Spatial Online Analytical Processing (SOLAP) Platform for COVID-19.Journal of maps · 2024Article
- Understanding spatiotemporal patterns of COVID-19 incidence in Portugal: A functional data analysis from August 2020 to March 2022.PloS one · 2024Article
- Spatiotemporal Patterns of the Omicron Wave of COVID-19 in the United States.Tropical medicine and infectious disease · 2023Article
- Spatio-temporal evolution of COVID-19 in the Republic of Ireland and the Greater Dublin Area (March to November 2020): A space-time cluster frequency approach.Spatial and spatio-temporal epidemiology · 2023Article
- One health system supporting surveillance during COVID-19 epidemic in Abruzzo region, southern Italy.One health (Amsterdam, Netherlands) · 2023Article
- The spatial distribution of infectious agents in wild Pacific salmon along the British Columbia coast.Scientific reports · 2023Article
12 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first discovered in late 2019 in Wuhan City, China. The virus may cause novel coronavirus disease 2019 (COVID-19) in symptomatic individuals. Since December of 2019, there have been over 7,000,000 confirmed cases and over 400,000 confirmed deaths worldwide. In the United States (U.S.), there have been over 2,000,000 confirmed cases and over 110,000 confirmed deaths. COVID-19 case data in the United States has been updated daily at the county level since the first case was reported in January of 2020. There currently lacks a study that showcases the novelty of daily COVID-19 surveillance using space-time cluster detection techniques. In this paper, we utilize a prospective Poisson space-time scan statistic to detect daily clusters of COVID-19 at the county level in the contiguous 48 U.S. and Washington D.C. As the pandemic progresses, we generally find an increase of smaller clusters of remarkably steady relative risk. Daily tracking of significant space-time clusters can facilitate decision-making and public health resource allocation by evaluating and visualizing the size, relative risk, and locations that are identified as COVID-19 hotspots.
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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.