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Mapping county-level mobility pattern changes in the United States in response to COVID-19 by Gao, Song ;Rao, Jinmeng ;Kang, Yuhao ;Liang, Yunlei ;Kruse, Jake is a Social Sciences article available to read on EtoBox.

What is Mapping county-level mobility pattern changes in the United States in response to COVID-19 about?

To contain the COVID-19 epidemic, one of the non-pharmacological epidemic control measures is reducing the transmission rate of SARS-COV-2 in the population through social distancing. An interactive web-based mapping platform that provides timely quantitative information on how people in different counties and states reacted to the social distancing guidelines was developed by the GeoDS Lab @UW-Madison with the support of the National Science Foundation RAPID program. The web portal integrates geographic information systems (GIS) and daily updated human mobility statistical patterns (median travel distance and stay-at-home dwell time) derived from large-scale anonymized and aggregated smartphone location big data at the county-level in the United States, and aims to increase risk awareness of the public, support data-driven public health and governmental decision-making, and help enhance community responses to the COVID-19 pandemic.

Who reads Mapping county-level mobility pattern changes in the United States in response to COVID-19?

Author

Gao, Song ;Rao, Jinmeng ;Kang, Yuhao ;Liang, Yunlei ;Kruse, Jake

Publisher

Association for Computing Machinery (ACM)

Published

2020

Language

EN

Field

Social Sciences (Physical Sciences)