scholarly journals The Spread of COVID-19 Increases With Individual Mobility and Depends on Political Leaning

Author(s):  
Chris Parker ◽  
Jorge Mejia ◽  
Franco Pestilli

Abstract The implementation of social distancing policies is key to reducing the impact of the current COVID-19 pandemic. However, their effectiveness ultimately depends on human behavior. In the United States, compliance with social distancing policies has widely varied thus far during the pandemic. But what drives such variability? Through six open datasets, including actual human mobility, we estimated the association between mobility and the growth rate of COVID-19 cases across 3,107 U.S. counties, generalizing previous reports. In addition, data from the 2016 U.S. presidential election was used to measure how the association between mobility and COVID-19 growth rate differed based on voting patterns. A significant association between political leaning and the COVID-19 growth rate was measured. Our results demonstrate that political orientation may inform models predicting the impact of policies in reducing the spread of COVID-19.

2021 ◽  
pp. 003335492110112
Author(s):  
Hongjie Liu ◽  
Chang Chen ◽  
Raul Cruz-Cano ◽  
Jennifer L. Guida ◽  
Minha Lee

Objective We quantified the association between public compliance with social distancing measures and the spread of SARS-CoV-2 during the first wave of the epidemic (March–May 2020) in 5 states that accounted for half of the total number of COVID-19 cases in the United States. Methods We used data on mobility and number of COVID-19 cases to longitudinally estimate associations between public compliance, as measured by human mobility, and the daily reproduction number and daily growth rate during the first wave of the COVID-19 epidemic in California, Illinois, Massachusetts, New Jersey, and New York. Results The 5 states mandated social distancing directives during March 19-24, 2020, and public compliance with mandates started to decrease in mid-April 2020. As of May 31, 2020, the daily reproduction number decreased from 2.41-5.21 to 0.72-1.19, and the daily growth rate decreased from 0.22-0.77 to –0.04 to 0.05 in the 5 states. The level of public compliance, as measured by the social distancing index (SDI) and daily encounter-density change, was high at the early stage of implementation but decreased in the 5 states. The SDI was negatively associated with the daily reproduction number (regression coefficients range, –0.04 to –0.01) and the daily growth rate (from –0.009 to –0.01). The daily encounter-density change was positively associated with the daily reproduction number (regression coefficients range, 0.24 to 1.02) and the daily growth rate (from 0.05 to 0.26). Conclusions Social distancing is an effective strategy to reduce the incidence of COVID-19 and illustrates the role of public compliance with social distancing measures to achieve public health benefits.


Author(s):  
Niayesh Afshordi ◽  
Benjamin Holder ◽  
Mohammad Bahrami ◽  
Daniel Lichtblau

The SARS-CoV-2 pandemic has caused significant mortality and morbidity worldwide, sparing almost no community. As the disease will likely remain a threat for years to come, an understanding of the precise influences of human demographics and settlement, as well as the dynamic factors of climate, susceptible depletion, and intervention, on the spread of localized epidemics will be vital for mounting an effective response. We consider the entire set of local epidemics in the United States; a broad selection of demographic, population density, and climate factors; and local mobility data, tracking social distancing interventions, to determine the key factors driving the spread and containment of the virus. Assuming first a linear model for the rate of exponential growth (or decay) in cases/mortality, we find that population-weighted density, humidity, and median age dominate the dynamics of growth and decline, once interventions are accounted for. A focus on distinct metropolitan areas suggests that some locales benefited from the timing of a nearly simultaneous nationwide shutdown, and/or the regional climate conditions in mid-March; while others suffered significant outbreaks prior to intervention. Using a first-principles model of the infection spread, we then develop predictions for the impact of the relaxation of social distancing and local climate conditions. A few regions, where a significant fraction of the population was infected, show evidence that the epidemic has partially resolved via depletion of the susceptible population (i.e., “herd immunity”), while most regions in the United States remain overwhelmingly susceptible. These results will be important for optimal management of intervention strategies, which can be facilitated using our online dashboard.


2020 ◽  
Vol 39 (7) ◽  
pp. 1237-1246 ◽  
Author(s):  
Charles Courtemanche ◽  
Joseph Garuccio ◽  
Anh Le ◽  
Joshua Pinkston ◽  
Aaron Yelowitz

2020 ◽  
Author(s):  
Romain Garnier ◽  
Jan R Benetka ◽  
John Kraemer ◽  
Shweta Bansal

BACKGROUND Eliminating disparities in the burden of COVID-19 requires equitable access to control measures across socio-economic groups. Limited research on socio-economic differences in mobility hampers our ability to understand whether inequalities in social distancing are occurring during the SARS-CoV-2 pandemic. OBJECTIVE We aimed to assess how mobility patterns have varied across the United States during the COVID-19 pandemic and to identify associations with socioeconomic factors of populations. METHODS We used anonymized mobility data from tens of millions of devices to measure the speed and depth of social distancing at the county level in the United States between February and May 2020, the period during which social distancing was widespread in this country. Using linear mixed models, we assessed the associations between social distancing and socioeconomic variables, including the proportion of people in the population below the poverty level, the proportion of Black people, the proportion of essential workers, and the population density. RESULTS We found that the speed, depth, and duration of social distancing in the United States are heterogeneous. We particularly show that social distancing is slower and less intense in counties with higher proportions of people below the poverty level and essential workers; in contrast, we show that social distancing is intensely adopted in counties with higher population densities and larger Black populations. CONCLUSIONS Socioeconomic inequalities appear to be associated with the levels of adoption of social distancing, potentially resulting in wide-ranging differences in the impact of the COVID-19 pandemic in communities across the United States. These inequalities are likely to amplify existing health disparities and must be addressed to ensure the success of ongoing pandemic mitigation efforts.


2021 ◽  
Author(s):  
Yuxun Zhou ◽  
Mafizur Rahman Mohammad ◽  
Khanam Rasheda ◽  
Robert Taylor Brad

Abstract Purpose – In responding to COVID-19, governments around the world have imposed various restrictions with different levels of success. One important aspect of pandemic control is the willingness of individuals to stay home when possible. The purpose of this paper is to study the impact of government restrictions on human mobility in the United StatesMethodology/approach – Structural equation modelling is used to explore the issue. First, we use path regression analysis and factor analysis to identify the main factors that influence mobility. Second, we use total effect decomposition to investigate the deeper relationship between government restrictions and human mobility.Finding – Two important findings are revealed First, the economic environment is the fundamental and direct factor affecting human mobility. There is a significant negative relationship between economic environment and human mobility, meaning that where economic conditions are bad mobility is greater. Second, government restrictions and the scale of the pandemic do not directly affect human mobility. Government restriction indirectly influences human mobility through economic environment as a mediating variable. Therefore, the economic environment has a significant mediating effect.Originality/value – Existing literature lacks research on the mediating effect between government restrictions and human mobility. This paper provides new empirical evidence for the research topic by studying the mediating effect between government restrictions and human mobility. This provides policymakers with a more detailed picture of the processes through which policies operate.


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Yixuan Pan ◽  
Aref Darzi ◽  
Aliakbar Kabiri ◽  
Guangchen Zhao ◽  
Weiyu Luo ◽  
...  

AbstractSince the first case of the novel coronavirus disease (COVID-19) was confirmed in Wuhan, China, social distancing has been promoted worldwide, including in the United States, as a major community mitigation strategy. However, our understanding remains limited in how people would react to such control measures, as well as how people would resume their normal behaviours when those orders were relaxed. We utilize an integrated dataset of real-time mobile device location data involving 100 million devices in the contiguous United States (plus Alaska and Hawaii) from February 2, 2020 to May 30, 2020. Built upon the common human mobility metrics, we construct a Social Distancing Index (SDI) to evaluate people’s mobility pattern changes along with the spread of COVID-19 at different geographic levels. We find that both government orders and local outbreak severity significantly contribute to the strength of social distancing. As people tend to practice less social distancing immediately after they observe a sign of local mitigation, we identify several states and counties with higher risks of continuous community transmission and a second outbreak. Our proposed index could help policymakers and researchers monitor people’s real-time mobility behaviours, understand the influence of government orders, and evaluate the risk of local outbreaks.


2018 ◽  
Vol 23 (2) ◽  
pp. 179-194
Author(s):  
Heather M. Claypool ◽  
Alejandro Trujillo ◽  
Michael J. Bernstein ◽  
Steven Young

Presidential elections in the United States pit two (or more) candidates against each other. Voters elect one and reject the others. This work tested the hypothesis that supporters of a losing presidential candidate may experience that defeat as a personal rejection. Before and after the 2016 U.S. presidential election between Donald Trump and Hillary Clinton, voters reported their current feelings of rejection and social pain, along with potential predictors of these feelings. Relative to Trump supporters, Clinton (losing candidate) supporters reported greater feelings of rejection, lower mood, and reduced fundamental needs post-election, while controlling for pre-election levels of these variables. Moreover, as self–candidate closeness and liberal political orientation increased, so too did feelings of rejection and social pain among Clinton supporters. We discuss the implications of these results for understanding human sensitivity to belonging threats and for the vicarious rejection literature.


2010 ◽  
Vol 41 (3) ◽  
pp. 147-151 ◽  
Author(s):  
Michael J. Bernstein ◽  
Steven G. Young ◽  
Heather M. Claypool

Many have questioned what Barack Obama’s victory in the 2008 presidential election means for prejudice and intergroup relations in the United States. In this study, we examined both explicit and implicit prejudice toward African Americans prior to and immediately following the election of the first African American to the nation’s highest office. Results indicated that implicit prejudice (as measured by an IAT) decreased following Obama’s victory, though explicit prejudice remained unchanged. The results are discussed in terms of the malleability of implicit attitudes, race relations, and the impact an Obama presidency and other positive exemplars may have on intergroup relations.


Author(s):  
Sen Pei ◽  
Sasikiran Kandula ◽  
Jeffrey Shaman

Assessing the effects of early non-pharmaceutical interventions1-5 on COVID-19 spread in the United States is crucial for understanding and planning future control measures to combat the ongoing pandemic6-10. Here we use county-level observations of reported infections and deaths11, in conjunction with human mobility data12 and a metapopulation transmission model13,14, to quantify changes of disease transmission rates in US counties from March 15, 2020 to May 3, 2020. We find significant reductions of the basic reproductive numbers in major metropolitan areas in association with social distancing and other control measures. Counterfactual simulations indicate that, had these same control measures been implemented just 1-2 weeks earlier, a substantial number of cases and deaths could have been averted. Specifically, nationwide, 61.6% [95% CI: 54.6%-67.7%] of reported infections and 55.0% [95% CI: 46.1%-62.2%] of reported deaths as of May 3, 2020 could have been avoided if the same control measures had been implemented just one week earlier. We also examine the effects of delays in re-implementing social distancing following a relaxation of control measures. A longer response time results in a stronger rebound of infections and death. Our findings underscore the importance of early intervention and aggressive response in controlling the COVID-19 pandemic.


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