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10.2196/19589 http://scihub22266oqcxt.onion/10.2196/19589 32931439!7572119!32931439     free     free     free Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 253.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 253.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 253.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       JMIR+Mhealth+Uhealth 2020 ; 8 (10): e19589 Nephropedia Template TP {{tp|p=32931439|t=2020. Using WeChat, a Chinese Social Media App, for Early Detection of the COVID-19 Outbreak in December 2019: Retrospective Study |pdf=|usr=}}{{32931439}} gab.com Text Using WeChat, a Chinese Social Media App, for Early Detection of the COVID-19 Outbreak in December 2019: Retrospective Study JO: JMIR Mhealth Uhealth http://www.kidney.de/pget.php?&tw=1&pmid=32931439 #FOAvip BACKGROUND: A novel coronavirus, SARS-CoV-2, was identified in December 2019, when the first cases were reported in Wuhan, China. The once-localized outbreak has since been declared a pandemic. As of April 24, 2020, there have been 2.7 million confirmed cases and nearly 200,000 deaths. Early warning systems using new technologies should be established to prevent or mitigate such events in the future. OBJECTIVE: This study aimed to explore the possibility of detecting the SARS-CoV-2 outbreak in 2019 using social media. METHODS: WeChat Index is a data service that shows how frequently a specific keyword appears in posts, subscriptions, and search over the last 90 days on WeChat, the most popular Chinese social media app. We plotted daily WeChat Index results for keywords related to SARS-CoV-2 from November 17, 2019, to February 14, 2020. RESULTS: WeChat Index hits for "Feidian" (which means severe acute respiratory syndrome in Chinese) stayed at low levels until 16 days ahead of the local authority's outbreak announcement on December 31, 2019, when the index increased significantly. The WeChat Index values persisted at relatively high levels from December 15 to 29, 2019, and rose rapidly on December 30, 2019, the day before the announcement. The WeChat Index hits also spiked for the keywords "SARS," "coronavirus," "novel coronavirus," "shortness of breath," "dyspnea," and "diarrhea," but these terms were not as meaningful for the early detection of the outbreak as the term "Feidian". CONCLUSIONS: By using retrospective infoveillance data from the WeChat Index, the SARS-CoV-2 outbreak in December 2019 could have been detected about two weeks before the outbreak announcement. WeChat may offer a new approach for the early detection of disease outbreaks. Twit Text FOAVip Using WeChat, a Chinese Social Media App, for Early Detection of the COVID-19 Outbreak in December 2019: Retrospective Study ????JMIR Mhealth Uhealth http://www.kidney.de/pget.php?&tw=1&pmid=32931439 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32931439 #FOAvip English Wikipedia <ref>{{Cite pmid|32931439}}</ref> Using WeChat, a Chinese Social Media App, for Early Detection of the COVID-19 Outbreak in December 2019: Retrospective Study #MMPMID32931439 Wang W; Wang Y; Zhang X; Jia X; Li Y; Dang S JMIR Mhealth Uhealth 2020[Oct]; 8 (10): e19589 PMID32931439show ga BACKGROUND: A novel coronavirus, SARS-CoV-2, was identified in December 2019, when the first cases were reported in Wuhan, China. The once-localized outbreak has since been declared a pandemic. As of April 24, 2020, there have been 2.7 million confirmed cases and nearly 200,000 deaths. Early warning systems using new technologies should be established to prevent or mitigate such events in the future. OBJECTIVE: This study aimed to explore the possibility of detecting the SARS-CoV-2 outbreak in 2019 using social media. METHODS: WeChat Index is a data service that shows how frequently a specific keyword appears in posts, subscriptions, and search over the last 90 days on WeChat, the most popular Chinese social media app. We plotted daily WeChat Index results for keywords related to SARS-CoV-2 from November 17, 2019, to February 14, 2020. RESULTS: WeChat Index hits for "Feidian" (which means severe acute respiratory syndrome in Chinese) stayed at low levels until 16 days ahead of the local authority's outbreak announcement on December 31, 2019, when the index increased significantly. The WeChat Index values persisted at relatively high levels from December 15 to 29, 2019, and rose rapidly on December 30, 2019, the day before the announcement. The WeChat Index hits also spiked for the keywords "SARS," "coronavirus," "novel coronavirus," "shortness of breath," "dyspnea," and "diarrhea," but these terms were not as meaningful for the early detection of the outbreak as the term "Feidian". CONCLUSIONS: By using retrospective infoveillance data from the WeChat Index, the SARS-CoV-2 outbreak in December 2019 could have been detected about two weeks before the outbreak announcement. WeChat may offer a new approach for the early detection of disease outbreaks. |*Disease Outbreaks[MESH] |*Mobile Applications[MESH] |*Social Media[MESH] |COVID-19[MESH] |China/epidemiology[MESH] |Coronavirus Infections/*epidemiology[MESH] |Humans[MESH] |Pandemics[MESH] |Pneumonia, Viral/*epidemiology[MESH] |Public Health Surveillance/*methods[MESH]Using WeChat, a Chinese Social Media App, for Early Detection of the C(epmc).pdf DeepDyve Pubget Overpricing