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10.1371/journal.pone.0241957 http://scihub22266oqcxt.onion/10.1371/journal.pone.0241957 33170889!7654838!33170889     free     free     free 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       PLoS+One 2020 ; 15 (11): e0241957 Nephropedia Template TP {{tp|p=33170889|t=2020. Twitter reveals human mobility dynamics during the COVID-19 pandemic |pdf=|usr=}}{{33170889}} gab.com Text Twitter reveals human mobility dynamics during the COVID-19 pandemic JO: PLoS One http://www.kidney.de/pget.php?&tw=1&pmid=33170889 #FOAvip The current COVID-19 pandemic raises concerns worldwide, leading to serious health, economic, and social challenges. The rapid spread of the virus at a global scale highlights the need for a more harmonized, less privacy-concerning, easily accessible approach to monitoring the human mobility that has proven to be associated with viral transmission. In this study, we analyzed over 580 million tweets worldwide to see how global collaborative efforts in reducing human mobility are reflected from the user-generated information at the global, country, and U.S. state scale. Considering the multifaceted nature of mobility, we propose two types of distance: the single-day distance and the cross-day distance. To quantify the responsiveness in certain geographic regions, we further propose a mobility-based responsive index (MRI) that captures the overall degree of mobility changes within a time window. The results suggest that mobility patterns obtained from Twitter data are amenable to quantitatively reflect the mobility dynamics. Globally, the proposed two distances had greatly deviated from their baselines after March 11, 2020, when WHO declared COVID-19 as a pandemic. The considerably less periodicity after the declaration suggests that the protection measures have obviously affected people's travel routines. The country scale comparisons reveal the discrepancies in responsiveness, evidenced by the contrasting mobility patterns in different epidemic phases. We find that the triggers of mobility changes correspond well with the national announcements of mitigation measures, proving that Twitter-based mobility implies the effectiveness of those measures. In the U.S., the influence of the COVID-19 pandemic on mobility is distinct. However, the impacts vary substantially among states. Twit Text FOAVip Twitter reveals human mobility dynamics during the COVID-19 pandemic ????PLoS One http://www.kidney.de/pget.php?&tw=1&pmid=33170889 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33170889 #FOAvip English Wikipedia <ref>{{Cite pmid|33170889}}</ref> Twitter reveals human mobility dynamics during the COVID-19 pandemic #MMPMID33170889 Huang X; Li Z; Jiang Y; Li X; Porter D PLoS One 2020[]; 15 (11): e0241957 PMID33170889show ga The current COVID-19 pandemic raises concerns worldwide, leading to serious health, economic, and social challenges. The rapid spread of the virus at a global scale highlights the need for a more harmonized, less privacy-concerning, easily accessible approach to monitoring the human mobility that has proven to be associated with viral transmission. In this study, we analyzed over 580 million tweets worldwide to see how global collaborative efforts in reducing human mobility are reflected from the user-generated information at the global, country, and U.S. state scale. Considering the multifaceted nature of mobility, we propose two types of distance: the single-day distance and the cross-day distance. To quantify the responsiveness in certain geographic regions, we further propose a mobility-based responsive index (MRI) that captures the overall degree of mobility changes within a time window. The results suggest that mobility patterns obtained from Twitter data are amenable to quantitatively reflect the mobility dynamics. Globally, the proposed two distances had greatly deviated from their baselines after March 11, 2020, when WHO declared COVID-19 as a pandemic. The considerably less periodicity after the declaration suggests that the protection measures have obviously affected people's travel routines. The country scale comparisons reveal the discrepancies in responsiveness, evidenced by the contrasting mobility patterns in different epidemic phases. We find that the triggers of mobility changes correspond well with the national announcements of mitigation measures, proving that Twitter-based mobility implies the effectiveness of those measures. In the U.S., the influence of the COVID-19 pandemic on mobility is distinct. However, the impacts vary substantially among states. |*Movement[MESH] |Betacoronavirus/isolation & purification[MESH] |COVID-19[MESH] |Coronavirus Infections/epidemiology/*pathology/virology[MESH] |Humans[MESH] |Pandemics[MESH] |Pneumonia, Viral/epidemiology/*pathology/virology[MESH] |SARS-CoV-2[MESH]Twitter reveals human mobility dynamics during the COVID-19 pandemic (epmc).pdf DeepDyve Pubget Overpricing