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10.1016/S1473-3099(20)30581-8 http://scihub22266oqcxt.onion/10.1016/S1473-3099(20)30581-8 32738203!7836788!32738203     free     free     free Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 263.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 263.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 263.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 263.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Lancet+Infect+Dis 2020 ; 20 (11): 1255-1262 Nephropedia Template TP {{tp|p=32738203|t=2020. Observations of the global epidemiology of COVID-19 from the prepandemic period using web-based surveillance: a cross-sectional analysis |pdf=|usr=}}{{32738203}} gab.com Text Observations of the global epidemiology of COVID-19 from the prepandemic period using web-based surveillance: a cross-sectional analysis JO: Lancet Infect Dis http://www.kidney.de/pget.php?&tw=1&pmid=32738203 #FOAvip Background Scant data are available about global patterns of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spread and global epidemiology of early confirmed cases of COVID-19 outside mainland China. We describe the global spread of SARS-CoV-2 and characteristics of COVID-19 cases and clusters before the characterisation of COVID-19 as a pandemic. METHODS: Cases of COVID-19 reported between Dec 31, 2019, and March 10, 2020 (ie, the prepandemic period), were identified daily from official websites, press releases, press conference transcripts, and social media feeds of national ministries of health or other government agencies. Case characteristics, travel history, and exposures to other cases were abstracted. Countries with at least one case were classified as affected. Early cases were defined as those among the first 100 cases reported from each country. Later cases were defined as those after the first 100 cases. We analysed reported travel to affected countries among the first case reported from each country outside mainland China, demographic and exposure characteristics among cases with age or sex information, and cluster frequencies and sizes by transmission settings. FINDINGS: Among the first case reported from each of 99 affected countries outside of mainland China, 75 (76%) had recent travel to affected countries; 60 (61%) had travelled to China, Italy, or Iran. Among 1200 cases with age or sex information, 874 (73%) were early cases. Among 762 early cases with age information, the median age was 51 years (IQR 35-63); 25 (3%) of 762 early cases occurred in children younger than 18 years. Overall, 21 (2%) of 1200 cases were in health-care workers and none were in pregnant women. 101 clusters were identified, of which the most commonly identified transmission setting was households (76 [75%]; mean 2.6 cases per cluster [range 2-7]), followed by non-health-care occupational settings (14 [14%]; mean 4.3 cases per cluster [2-14]), and community gatherings (11 [11%]; mean 14.2 cases per cluster [4-36]). INTERPRETATION: Cases with travel links to China, Italy, or Iran accounted for almost two-thirds of the first reported COVID-19 cases from affected countries. Among cases with age information available, most were among adults aged 18 years and older. Although there were many clusters of household transmission among early cases, clusters in occupational or community settings tended to be larger, supporting a possible role for physical distancing to slow the progression of SARS-CoV-2 spread. FUNDING: None. Twit Text FOAVip Observations of the global epidemiology of COVID-19 from the prepandemic period using web-based surveillance: a cross-sectional analysis ????Lancet Infect Dis http://www.kidney.de/pget.php?&tw=1&pmid=32738203 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32738203 #FOAvip English Wikipedia <ref>{{Cite pmid|32738203}}</ref> Observations of the global epidemiology of COVID-19 from the prepandemic period using web-based surveillance: a cross-sectional analysis #MMPMID32738203 Dawood FS; Ricks P; Njie GJ; Daugherty M; Davis W; Fuller JA; Winstead A; McCarron M; Scott LC; Chen D; Blain AE; Moolenaar R; Li C; Popoola A; Jones C; Anantharam P; Olson N; Marston BJ; Bennett SD Lancet Infect Dis 2020[Nov]; 20 (11): 1255-1262 PMID32738203show ga Background Scant data are available about global patterns of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spread and global epidemiology of early confirmed cases of COVID-19 outside mainland China. We describe the global spread of SARS-CoV-2 and characteristics of COVID-19 cases and clusters before the characterisation of COVID-19 as a pandemic. METHODS: Cases of COVID-19 reported between Dec 31, 2019, and March 10, 2020 (ie, the prepandemic period), were identified daily from official websites, press releases, press conference transcripts, and social media feeds of national ministries of health or other government agencies. Case characteristics, travel history, and exposures to other cases were abstracted. Countries with at least one case were classified as affected. Early cases were defined as those among the first 100 cases reported from each country. Later cases were defined as those after the first 100 cases. We analysed reported travel to affected countries among the first case reported from each country outside mainland China, demographic and exposure characteristics among cases with age or sex information, and cluster frequencies and sizes by transmission settings. FINDINGS: Among the first case reported from each of 99 affected countries outside of mainland China, 75 (76%) had recent travel to affected countries; 60 (61%) had travelled to China, Italy, or Iran. Among 1200 cases with age or sex information, 874 (73%) were early cases. Among 762 early cases with age information, the median age was 51 years (IQR 35-63); 25 (3%) of 762 early cases occurred in children younger than 18 years. Overall, 21 (2%) of 1200 cases were in health-care workers and none were in pregnant women. 101 clusters were identified, of which the most commonly identified transmission setting was households (76 [75%]; mean 2.6 cases per cluster [range 2-7]), followed by non-health-care occupational settings (14 [14%]; mean 4.3 cases per cluster [2-14]), and community gatherings (11 [11%]; mean 14.2 cases per cluster [4-36]). INTERPRETATION: Cases with travel links to China, Italy, or Iran accounted for almost two-thirds of the first reported COVID-19 cases from affected countries. Among cases with age information available, most were among adults aged 18 years and older. Although there were many clusters of household transmission among early cases, clusters in occupational or community settings tended to be larger, supporting a possible role for physical distancing to slow the progression of SARS-CoV-2 spread. FUNDING: None. |*Betacoronavirus[MESH] |*Epidemiological Monitoring[MESH] |*Global Health[MESH] |*Internet[MESH] |Adolescent[MESH] |Adult[MESH] |COVID-19[MESH] |Child[MESH] |Coronavirus Infections/*epidemiology/*transmission/virology[MESH] |Cross-Sectional Studies[MESH] |Family Characteristics[MESH] |Female[MESH] |Health Personnel[MESH] |Humans[MESH] |Male[MESH] |Middle Aged[MESH] |Pandemics[MESH] |Pneumonia, Viral/*epidemiology/*transmission/virology[MESH] |SARS-CoV-2[MESH] |Travel[MESH]Observations of the global epidemiology of COVID-19 from the prepandem(epmc).pdf DeepDyve Pubget Overpricing