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10.1002/jmv.25834 http://scihub22266oqcxt.onion/10.1002/jmv.25834 32249952!ä!32249952 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Med+Virol 2020 ; 92 (9): 1587-1595 Nephropedia Template TP {{tp|p=32249952|t=2020. An analysis of spatiotemporal pattern for COIVD-19 in China based on space-time cube |pdf=|usr=}}{{32249952}} gab.com Text An analysis of spatiotemporal pattern for COIVD-19 in China based on space-time cube JO: J Med Virol http://www.kidney.de/pget.php?&tw=1&pmid=32249952 #FOAvip This study seeks to examine and analyze the spatial and temporal patterns of 2019 novel coronavirus disease (COVID-19) outbreaks and identify the spatiotemporal distribution characteristics and changing trends of cases. Hence, local outlier analysis and emerging spatiotemporal hot spot analysis were performed to analyze the spatiotemporal clustering pattern and cold/hot spot trends of COVID-19 cases based on space-time cube during the period from 23 January 2020 to 24 February 2020. The main findings are as follows: (1) The outbreak had spread rapidly throughout the country within a short time and the current totality incidence rate has decreased. (2) The spatiotemporal distribution of cases was uneven. In terms of the spatiotemporal clustering pattern, Wuhan and Shiyan city were the center as both cities had high-high clustering pattern with a surrounding unstable multiple-type pattern in partial areas of Henan, Anhui, Jiangxi, and Hunan provinces, and Chongqing city. Those regions are continuously in the hot spot on the spatiotemporal tendency. (3) The spatiotemporal analysis technology based on the space-time cube can analyze comprehensively the spatiotemporal pattern of epidemiological data and produce a visual output of the consequences, which can reflect intuitively the distribution and trend of data in space-time. Therefore, the Chinese government should strengthen the prevention and control efforts in a targeted manner to cope with a highly changeable situation. Twit Text FOAVip An analysis of spatiotemporal pattern for COIVD-19 in China based on space-time cube ????J Med Virol http://www.kidney.de/pget.php?&tw=1&pmid=32249952 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32249952 #FOAvip English Wikipedia <ref>{{Cite pmid|32249952}}</ref> An analysis of spatiotemporal pattern for COIVD-19 in China based on space-time cube #MMPMID32249952 Mo C; Tan D; Mai T; Bei C; Qin J; Pang W; Zhang Z J Med Virol 2020[Sep]; 92 (9): 1587-1595 PMID32249952show ga This study seeks to examine and analyze the spatial and temporal patterns of 2019 novel coronavirus disease (COVID-19) outbreaks and identify the spatiotemporal distribution characteristics and changing trends of cases. Hence, local outlier analysis and emerging spatiotemporal hot spot analysis were performed to analyze the spatiotemporal clustering pattern and cold/hot spot trends of COVID-19 cases based on space-time cube during the period from 23 January 2020 to 24 February 2020. The main findings are as follows: (1) The outbreak had spread rapidly throughout the country within a short time and the current totality incidence rate has decreased. (2) The spatiotemporal distribution of cases was uneven. In terms of the spatiotemporal clustering pattern, Wuhan and Shiyan city were the center as both cities had high-high clustering pattern with a surrounding unstable multiple-type pattern in partial areas of Henan, Anhui, Jiangxi, and Hunan provinces, and Chongqing city. Those regions are continuously in the hot spot on the spatiotemporal tendency. (3) The spatiotemporal analysis technology based on the space-time cube can analyze comprehensively the spatiotemporal pattern of epidemiological data and produce a visual output of the consequences, which can reflect intuitively the distribution and trend of data in space-time. Therefore, the Chinese government should strengthen the prevention and control efforts in a targeted manner to cope with a highly changeable situation. |*SARS-CoV-2[MESH] |COVID-19/*epidemiology/*virology[MESH] |China/epidemiology[MESH] |Disease Outbreaks[MESH] |Geography, Medical[MESH] |Humans[MESH] |Prevalence[MESH] |Public Health Surveillance[MESH]An analysis of spatiotemporal pattern for COIVD-19 in China based on s(epmc).pdf DeepDyve Pubget Overpricing