عنوان انگلیسی مقاله:
Asynchrony Between Individual and Government Actions Accounts for Disproportionate Impact of COVID-19 on Vulnerable Communities
ترجمه فارسی عنوان مقاله:
ناهمزمانی بین اقدامات فردی و دولتی تاثیر نامتناسب COVID-19 بر جوامع آسیب پذیر
ScienceDirect- Elsevier- American Journal of Preventive Medicine, 60 (2021) 318-326: doi:10:1016/j:amepre:2020:10:012
Moustafa Abdalla PhD
Introduction: Previously estimated effects of social distancing do not account for changes in individual behavior before the implementation of stay-at-home policies or model this behavior in relation to the burden of disease. This study aims to assess the asynchrony between individual behavior
and government stay-at-home orders, quantify the true impact of social distancing using mobility
data, and explore the sociodemographic variables linked to variation in social distancing practices.
Methods: This study was a retrospective investigation that leveraged mobility data to quantify the
time to behavioral change in relation to the initial presence of COVID-19 and the implementation of
government stay-at-home orders. The impact of social distancing that accounts for both individual
behavior and testing data was calculated using generalized mixed models. The role of sociodemographics in accounting for variation in social distancing behavior was modeled using a 10-fold crossvalidated elastic net (linear machine learning model). Analysis was conducted in April‒July 2020.
Results: Across all the 1,124 counties included in this analysis, individuals began to socially distance at a median of 5 days (IQR=38) after 10 cumulative cases of COVID-19 were confirmed in
their state, with state governments taking a median of 15 days (IQR=1219) to enact stay-at-home
orders. Overall, people began social distancing at a median of 12 days (IQR=817) before their
state enacted stay-at-home orders. Of the 16 studies included in the review, 13 exclusively used government dates as a proxy for social distancing behavior, and none accounted for both testing and
mobility. Using government stay-at-home dates as a proxy for social distancing (10.2% decrease in
the number of daily cases) accounted for only 55% of the true impact of the intervention when compared with estimates using mobility (18.6% reduction). Using 10-fold cross-validation, 23 of 43 sociodemographic variables were significantly and independently predictive of variation in individual
social distancing, with delays corresponding to an increase in a county’s proportion of people without a high school diploma and proportion of racial and ethnic minorities.
Conclusions: This retrospective analysis of mobility patterns found that social distancing behavior
occurred well before the onset of government stay-at-home dates. This asynchrony leads to the
underestimation of the impact of social distancing. Sociodemographic characteristics associated
with delays in social distancing can help explain the disproportionate case burden and mortality
among vulnerable communities.