TY - JOUR
T1 - Pandemic-influenced human mobility on tribal lands in California
T2 - Data sparsity and analytical precision
AU - Showalter, Esther
AU - Vigil-Hayes, Morgan
AU - Zegura, Ellen
AU - Sutton, Richard
AU - Belding, Elizabeth
N1 - Publisher Copyright:
© 2022 Public Library of Science. All rights reserved.
PY - 2022/12
Y1 - 2022/12
N2 - Human mobility datasets collected from personal mobile device locations are integral to understanding how states, counties, and cities have collectively adapted to pervasive social disruption stemming from the COVID-19 pandemic. However, while indigenous tribal communities in the United States have been disproportionately devastated by the pandemic, the relatively sparse populations and data available in these hard-hit tribal areas often exclude them from mobility studies. We explore the effects of sparse mobility data in untangling the often inter-correlated relationship between human mobility, distancing orders, and case growth throughout 2020 in tribal and rural areas of California. Our findings account for data sparsity imprecision to show: 1) Mobility through legal tribal boundaries was unusually low but still correlated highly with case growth; 2) Case growth correlated less strongly with mobility later in the the year in all areas; and 3) State-mandated distancing orders later in the year did not necessarily precede lower mobility medians, especially in tribal areas. It is our hope that with more timely feedback offered by mobile device datasets even in sparse areas, health policy makers can better plan health emergency responses that still keep the economy vibrant across all sectors.
AB - Human mobility datasets collected from personal mobile device locations are integral to understanding how states, counties, and cities have collectively adapted to pervasive social disruption stemming from the COVID-19 pandemic. However, while indigenous tribal communities in the United States have been disproportionately devastated by the pandemic, the relatively sparse populations and data available in these hard-hit tribal areas often exclude them from mobility studies. We explore the effects of sparse mobility data in untangling the often inter-correlated relationship between human mobility, distancing orders, and case growth throughout 2020 in tribal and rural areas of California. Our findings account for data sparsity imprecision to show: 1) Mobility through legal tribal boundaries was unusually low but still correlated highly with case growth; 2) Case growth correlated less strongly with mobility later in the the year in all areas; and 3) State-mandated distancing orders later in the year did not necessarily precede lower mobility medians, especially in tribal areas. It is our hope that with more timely feedback offered by mobile device datasets even in sparse areas, health policy makers can better plan health emergency responses that still keep the economy vibrant across all sectors.
UR - http://www.scopus.com/inward/record.url?scp=85144236617&partnerID=8YFLogxK
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U2 - 10.1371/journal.pone.0276644
DO - 10.1371/journal.pone.0276644
M3 - Article
C2 - 36516118
AN - SCOPUS:85144236617
SN - 1932-6203
VL - 17
JO - PLoS ONE
JF - PLoS ONE
IS - 12 December
M1 - e0276644
ER -