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10.17269/s41997-021-00560-1 http://scihub22266oqcxt.onion/10.17269/s41997-021-00560-1 34374036!8352554!34374036     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Can+J+Public+Health 2021 ; 112 (5): 807-817 Nephropedia Template TP {{tp|p=34374036|t=2021. Detection of COVID-19 case clusters in Quebec, May-October 2020 |pdf=|usr=}}{{34374036}} gab.com Text Detection of COVID-19 case clusters in Quebec, May-October 2020 JO: Can J Public Health http://www.kidney.de/pget.php?&tw=1&pmid=34374036 #FOAvip OBJECTIVES: The Quebec Public Health Institute (INSPQ) was mandated to develop an automated tool for detecting space-time COVID-19 case clusters to assist regional public health authorities in identifying situations that require public health interventions. This article aims to describe the methodology used and to document the main outcomes achieved. METHODS: New COVID-19 cases are supplied by the "Trajectoire de sante publique" information system, geolocated to civic addresses and then aggregated by day and dissemination area. To target community-level clusters, cases identified as residents of congregate living settings are excluded from the cluster detection analysis. Detection is performed using the space-time scan statistic and Poisson statistical model, and implemented in the SaTScan software. Information on detected clusters is disseminated daily via an online interactive mapping interface. RESULTS: The number of clusters detected tracked with the number of new cases. Slightly more than 4900 statistically significant (p </= 0.01) space-time clusters were detected over 14 health regions from May to October 2020. The Montreal region was the most affected. CONCLUSION: Considering the objective of timely cluster detection, the use of near-real-time health surveillance data of varying quality over time and by region constitutes an acceptable compromise between timeliness and data quality. This tool serves to supplement the epidemiologic investigations carried out by regional public health authorities for purposes of COVID-19 management and prevention. Twit Text FOAVip Detection of COVID-19 case clusters in Quebec, May-October 2020 ????Can J Public Health http://www.kidney.de/pget.php?&tw=1&pmid=34374036 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34374036 #FOAvip English Wikipedia <ref>{{Cite pmid|34374036}}</ref> Detection of COVID-19 case clusters in Quebec, May-October 2020 #MMPMID34374036 Lebel G; Fortin E; Lo E; Boivin MC; Tandonnet M; Gravel N Can J Public Health 2021[Oct]; 112 (5): 807-817 PMID34374036show ga OBJECTIVES: The Quebec Public Health Institute (INSPQ) was mandated to develop an automated tool for detecting space-time COVID-19 case clusters to assist regional public health authorities in identifying situations that require public health interventions. This article aims to describe the methodology used and to document the main outcomes achieved. METHODS: New COVID-19 cases are supplied by the "Trajectoire de sante publique" information system, geolocated to civic addresses and then aggregated by day and dissemination area. To target community-level clusters, cases identified as residents of congregate living settings are excluded from the cluster detection analysis. Detection is performed using the space-time scan statistic and Poisson statistical model, and implemented in the SaTScan software. Information on detected clusters is disseminated daily via an online interactive mapping interface. RESULTS: The number of clusters detected tracked with the number of new cases. Slightly more than 4900 statistically significant (p |*COVID-19/epidemiology[MESH] |*Public Health[MESH] |Cluster Analysis[MESH] |Humans[MESH]Detection of COVID-19 case clusters in Quebec, May-October 2020 (epmc).pdf DeepDyve Pubget Overpricing