TY - JOUR
T1 - Modeling mobility, risk, and pandemic severity during the first year of COVID
AU - Gilgur, Alexander
AU - Ramirez-Marquez, Jose Emmanuel
N1 - Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2022/12
Y1 - 2022/12
N2 - During the COVID-19 pandemic, most US states have taken measures of varying strength, enforcing social and physical distancing in the interest of public safety. These measures have enabled counties and states, with varying success, to slow down the propagation and mortality of the disease by matching the propagation rate to the capacity of medical facilities. However, each state's government was making its decisions based on limited information and without the benefit of being able to look retrospectively at the problem at large and to analyze the commonalities and the differences among the states and the counties across the country. We developed models connecting people's mobility, socioeconomic, and demographic factors with severity of the COVID pandemic in the US at the County level. These models can be used to inform policymakers and other stakeholders on measures to be taken during a pandemic. They also enable in-depth analysis of factors affecting the relationship between mobility and the severity of the disease. With the exception of one model, that of COVID recovery time, the resulting models accurately predict the vulnerability and severity metrics and rank the explanatory variables in the order of statistical importance. We also analyze and explain why recovery time did not allow for a good model.
AB - During the COVID-19 pandemic, most US states have taken measures of varying strength, enforcing social and physical distancing in the interest of public safety. These measures have enabled counties and states, with varying success, to slow down the propagation and mortality of the disease by matching the propagation rate to the capacity of medical facilities. However, each state's government was making its decisions based on limited information and without the benefit of being able to look retrospectively at the problem at large and to analyze the commonalities and the differences among the states and the counties across the country. We developed models connecting people's mobility, socioeconomic, and demographic factors with severity of the COVID pandemic in the US at the County level. These models can be used to inform policymakers and other stakeholders on measures to be taken during a pandemic. They also enable in-depth analysis of factors affecting the relationship between mobility and the severity of the disease. With the exception of one model, that of COVID recovery time, the resulting models accurately predict the vulnerability and severity metrics and rank the explanatory variables in the order of statistical importance. We also analyze and explain why recovery time did not allow for a good model.
KW - COVID-19
KW - Coronavirus
KW - Data For Good
KW - Mobility
KW - OxCGRT
KW - Pandemic
KW - Severity metrics
KW - Socioeconomic data
KW - Vulnerability
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UR - http://www.scopus.com/inward/citedby.url?scp=85135955265&partnerID=8YFLogxK
U2 - 10.1016/j.seps.2022.101397
DO - 10.1016/j.seps.2022.101397
M3 - Article
AN - SCOPUS:85135955265
SN - 0038-0121
VL - 84
JO - Socio-Economic Planning Sciences
JF - Socio-Economic Planning Sciences
M1 - 101397
ER -