Daily surveillance of COVID-19 using the prospective space-time scan statistic in the United States

Spatial and Spatio-temporal Epidemiology - Tập 34 - Trang 100354 - 2020
Alexander Hohl1, Eric M. Delmelle2, Michael R. Desjardins3, Yu Lan2
1Department of Geography, The University of Utah, 260 S Campus Dr., Rm 4625, Salt Lake City, UT 84112, USA
2Department of Geography and Earth Sciences, Center for Applied Geographic Information Science, University of North Carolina at Charlotte, Charlotte, NC 28223,, USA
3Department of Epidemiology & Spatial Science for Public Health Center, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA

Tài liệu tham khảo

Amin, 2020, Geographical surveillance of covid-19: diagnosed cases and death in the united states, medRxiv Bai, 2020, Presumed asymptomatic carrier transmission of covid-19, JAMA, 323, 1406, 10.1001/jama.2020.2565 Boulos, M. N. K., Geraghty, E. M., 2020. Geographical tracking and mapping of coronavirus disease COVID-19/severe acute respiratory syndrome coronavirus 2 (sars-cov-2) epidemic and associated events around the world: how 21st century gis technologies are supporting the global fight against outbreaks and epidemics. Chang, 2018, Shiny: web application framework for r, 2015, R Pckage Version, 1, 14 Cheng, 2018, Leaflet: create interactive web maps with the javascriptleafletlibrary, R Package Version, 2 Correa, 2015, A critical look at prospective surveillance using a scan statistic, Stat. Med., 34, 1081, 10.1002/sim.6400 De Oliveira, 2011, Detection of patterns in water distribution pipe breakage using spatial scan statistics for point events in a physical network, J. Comput. Civil Eng., 25, 21, 10.1061/(ASCE)CP.1943-5487.0000079 Desjardins, 2020, Rapid surveillance of COVID-19 in the united states using a prospective space-time scan statistic: detecting and evaluating emerging clusters, Appl. Geogr., 102202, 10.1016/j.apgeog.2020.102202 Desjardins, 2018, Space-time clusters and co-occurrence of chikungunya and dengue fever in colombia from 2015 to 2016, Acta Trop., 185, 77, 10.1016/j.actatropica.2018.04.023 Dong, 2020, An interactive web-based dashboard to track covid-19 in real time, Lancet Infect. Dis., 20, 533, 10.1016/S1473-3099(20)30120-1 Duczmal, 2007, A genetic algorithm for irregularly shaped spatial scan statistics, Computat. Stat. Data Anal., 52, 43, 10.1016/j.csda.2007.01.016 Gao, 2013, Early detection of terrorism outbreaks using prospective space–time scan statistics, Prof. Geogr., 65, 676, 10.1080/00330124.2012.724348 Goodchild, 2007, Citizens as sensors: the world of volunteered geography, GeoJournal, 69, 211, 10.1007/s10708-007-9111-y Greene, 2016, Daily reportable disease spatiotemporal cluster detection, new york city, new york, usa, 2014–2015, Emerging Infect. Dis., 22, 1808, 10.3201/eid2210.160097 Han, 2019, The kernel spatial scan statistic, 349 Hay, 2013, Big data opportunities for global infectious disease surveillance, PLoS Med., 10, 10.1371/journal.pmed.1001413 Hohl, 2020, Rapid detection of covid-19 clusters in the united states using a prospective space-time scan statistic: an update, SIGSPATIAL Special, 12, 2733, 10.1145/3404820.3404825 Huang, 2020, Clinical features of patients infected with 2019 novel coronavirus in wuhan, china, Lancet, 395, 497, 10.1016/S0140-6736(20)30183-5 Kulldorff, 1997, A spatial scan statistic, Commun. Stat.-Theory Methods, 26, 1481, 10.1080/03610929708831995 Kulldorff, 2001, Prospective time periodic geographical disease surveillance using a scan statistic, J. R. Stat. Soc.), 164, 61, 10.1111/1467-985X.00186 Kulldorff, M., 2018. SatscanTM user guide for version 9.6, 2018. Kulldorff, 1998, Evaluating cluster alarms: a space-time scan statistic and brain cancer in los alamos, new mexico., Am. J. Public Health, 88, 1377, 10.2105/AJPH.88.9.1377 Kulldorff, 2006, An elliptic spatial scan statistic, Stat. Med., 25, 3929, 10.1002/sim.2490 Kulldorff, 2015, Comments on a critical look at prospective surveillance using a scan statisticby t. correa, m. costa, and r. assunção, Stat. Med., 34, 1094, 10.1002/sim.6430 Li, 2020, Early transmission dynamics in wuhan, china, of novel coronavirus–infected pneumonia, N top N. Engl. J. Med., 10.1056/NEJMoa2001316 Lurie, 2020, Developing covid-19 vaccines at pandemic speed, N top N. Engl. J. Med., 382, 1969, 10.1056/NEJMp2005630 Mulatti, 2015, Retrospective space–time analysis methods to support west nile virus surveillance activities, Epidemiol. Infect., 143, 202, 10.1017/S0950268814000442 Nakaya, 2010, Visualising crime clusters in a space-time cube: an exploratory data-analysis approach using space-time kernel density estimation and scan statistics, Trans. GIS, 14, 223, 10.1111/j.1467-9671.2010.01194.x Noble, 2009, How does multiple testing correction work?, Nat. Biotechnol., 27, 1135, 10.1038/nbt1209-1135 Shaffer, 1995, Multiple hypothesis testing, Annu Rev Psychol, 46, 561, 10.1146/annurev.ps.46.020195.003021 Takahashi, 2008, A flexibly shaped space-time scan statistic for disease outbreak detection and monitoring, Int J Health Geogr, 7, 14, 10.1186/1476-072X-7-14 Tango, 2005, A flexibly shaped spatial scan statistic for detecting clusters, Int J Health Geogr, 4, 11, 10.1186/1476-072X-4-11 Team, 2015, Rstudio: integrated development for r, RStudio, Inc., Boston, MA URL http://www. rstudio. com, 42, 14 Team, 2019, R: a language and environment for statistical computing, dim (ca533), 1, 34 Whiteman, 2018, Detecting space-time clusters of dengue fever in panama after adjusting for vector surveillance data, PLoS Negl Trop Dis, 13, e0007266, 10.1371/journal.pntd.0007266 WHO, 2020, Critical Preparedness, Readiness and Response Actions for COVID-19: Interim Guidance, 22 March 2020 Yang, 2017