Quantifying human mobility behaviour changes during the COVID-19 outbreak in the United States

[1]  Mark Dredze,et al.  The Twitter Social Mobility Index: Measuring Social Distancing Practices With Geolocated Tweets , 2020, Journal of medical Internet research.

[2]  Yuan Wang,et al.  Identifying airborne transmission as the dominant route for the spread of COVID-19 , 2020, Proceedings of the National Academy of Sciences.

[3]  A. Kabiri,et al.  Interactive COVID-19 Mobility Impact and Social Distancing Analysis Platform , 2020, medRxiv.

[4]  Jianmin Jia,et al.  Population flow drives spatio-temporal distribution of COVID-19 in China , 2020, Nature.

[5]  Y. Liu,et al.  What are the underlying transmission patterns of COVID-19 outbreak? An age-specific social contact characterization , 2020, EClinicalMedicine.

[6]  Peng Wu,et al.  Impact assessment of non-pharmaceutical interventions against coronavirus disease 2019 and influenza in Hong Kong: an observational study , 2020, The Lancet Public Health.

[7]  Filippo Privitera,et al.  Mobility Patterns and Income Distribution in Times of Crisis: U.S. Urban Centers During the COVID-19 Pandemic , 2020 .

[8]  Pietro Cinaglia,et al.  Epidemiology of Coronavirus Disease Outbreak: The Italian Trends. , 2020, Reviews on recent clinical trials.

[9]  Dylan S. Small,et al.  Protocol for an Observational Study on the Effects of Social Distancing on Influenza-Like Illness and COVID-19 , 2020, 2004.02944.

[10]  Mark Dredze,et al.  The Twitter Social Mobility Index: Measuring Social Distancing Practices from Geolocated Tweets , 2020, ArXiv.

[11]  Song Gao,et al.  Mapping county-level mobility pattern changes in the United States in response to COVID-19 , 2020, ACM SIGSPATIAL Special.

[12]  Brent Skorup,et al.  Aggregated Smartphone Location Data to Assist in Response to Pandemic , 2020 .

[13]  Michael S. Warren,et al.  Mobility Changes in Response to COVID-19 , 2020, ArXiv.

[14]  M. Ienca,et al.  On the responsible use of digital data to tackle the COVID-19 pandemic , 2020, Nature Medicine.

[15]  Carl A. B. Pearson,et al.  The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study , 2020, The Lancet Public Health.

[16]  Haoyang Sun,et al.  Interventions to mitigate early spread of SARS-CoV-2 in Singapore: a modelling study , 2020, The Lancet Infectious Diseases.

[17]  An Pan,et al.  Evolving Epidemiology and Impact of Non-pharmaceutical Interventions on the Outbreak of Coronavirus Disease 2019 in Wuhan, China , 2020, medRxiv.

[18]  Nuno R. Faria,et al.  Utilizing general human movement models to predict the spread of emerging infectious diseases in resource poor settings , 2019, Scientific Reports.

[19]  I. Bechmann,et al.  Corpora amylacea in human hippocampal brain tissue are intracellular bodies that exhibit a homogeneous distribution of neo-epitopes , 2019, Scientific Reports.

[20]  P. Tortora,et al.  The polyglutamine protein ataxin-3 enables normal growth under heat shock conditions in the methylotrophic yeast Pichia pastoris , 2017, Scientific Reports.

[21]  Mark Jit,et al.  Projecting social contact matrices in 152 countries using contact surveys and demographic data , 2017, PLoS Comput. Biol..

[22]  M. Biggerstaff,et al.  Community Mitigation Guidelines to Prevent Pandemic Influenza — United States, 2017 , 2017, MMWR. Recommendations and reports : Morbidity and mortality weekly report. Recommendations and reports.

[23]  M. Gatto,et al.  Big-data-driven modeling unveils country-wide drivers of endemic schistosomiasis , 2017, Scientific Reports.

[24]  David L. Smith,et al.  Quantifying the Impact of Human Mobility on Malaria , 2012, Science.

[25]  Dino Pedreschi,et al.  Human mobility, social ties, and link prediction , 2011, KDD.

[26]  Albert-László Barabási,et al.  Understanding the Spreading Patterns of Mobile Phone Viruses , 2009, Science.

[27]  Albert-László Barabási,et al.  Understanding individual human mobility patterns , 2008, Nature.

[28]  A. Comarow How we ranked the plans. This year, 271 managed-care plans were analyzed 28 ways. , 1998, U.S. news & world report.

[29]  D. Bryant,et al.  Environmental indicators : a systematic approach to measuring and reporting on environmental policy performance in the context of sustainable development , 1995 .

[30]  H. O. Wood,et al.  Modified Mercalli intensity scale of 1931 , 1931 .