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

By Song Gao, Jinmeng Rao, Yuhao Kang, Yunlei Liang, Jake Kruse. ACM SIGSPATIAL Special, 2020

323 citations recorded by the source corpus.

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.

Subfields: Epidemiology, Modeling and Simulation, Transportation

View Paper: https://www.semanticscholar.org/paper/9000e9e6f3685e49be3628a006c080d16e7617bb

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Citations in the corpus

The use of mobile phone data to inform analysis of COVID-19 pandemic epidemiology (2020, background): “…already identi ﬁ ed associations between reductions in population-level mobility within and between different locations and COVID-19 incidence 6,10,29 , though further exploration of which population-level metrics are most closely related to changes in disease risk and whether these associations…”
COVID-19 lockdown induces disease-mitigating structural changes in mobility networks (2020, unknown): “We found a considerable reduction of mobility during the pandemic, similar to what was previously reported for other countries that passed and implemented comparable policies (8–11).”
Spatial analysis and GIS in the study of COVID-19. A review (2020, background): “According to the authors, this information is very relevant for the treatment of COVID-19 because there are a number of antimalarial drugs that, reportedly, are useful in its treatment (Gao et al. 2020, cited in Kuupiel et al., 2020).”