scholarly journals Interplay of global multi-scale human mobility, social distancing, government interventions, and COVID-19 dynamics

2020 ◽  
Author(s):  
Aniruddha Adiga ◽  
Lijing Wang ◽  
Adam Sadilek ◽  
Ashish Tendulkar ◽  
Srinivasan Venkatramanan ◽  
...  
Keyword(s):  
Human Mobility ◽  
The United States ◽  
Global Scale ◽  
International Travel ◽  
Population Mixing ◽  
Government Interventions ◽  
Social Distancing ◽  
Epidemic Dynamics ◽  
The Us ◽  
The Impact

AbstractThis work quantifies the impact of interventions to curtail mobility and social interactions in order to control the COVID-19 pandemic. We analyze the change in world-wide mobility at multiple spatio-temporal resolutions – county, state, country – using an anonymized aggregate mobility map that captures population flows between geographic cells of size 5 km2. We show that human mobility underwent an abrupt and significant change, partly in response to the interventions, resulting in 87% reduction of international travel and up to 75% reduction of domestic travel. Taking two very different countries sampled from the global spectrum, we observe a maximum reduction of 42% in mobility across different states of the United States (US), and a 68% reduction across the states of India between late March and late April. Since then, there has been an uptick in flows, with the US seeing 53% increase and India up to 38% increase with respect to flows seen during the lockdown. As we overlay this global map with epidemic incidence curves and dates of government interventions, we observe that as case counts rose, mobility fell – often before stay-at-home orders were issued. Further, in order to understand mixing within a region, we propose a new metric to quantify the effect of social distancing on the basis of mobility. We find that population mixing has decreased considerably as the pandemic has progressed and are able to measure this effect across the world. Finally, we carry out a counterfactual analysis of delaying the lockdown and show that a one week delay would have doubled the reported number of cases in the US and India. To our knowledge, this work is the first to model in near real-time, the interplay of human mobility, epidemic dynamics and public policies across multiple spatial resolutions and at a global scale.

scholarly journals Mining Google and Apple mobility data: temporal anatomy for COVID-19 social distancing

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Corentin Cot ◽  
Giacomo Cacciapaglia ◽  
Francesco Sannino
Keyword(s):  
Infection Rate ◽  
The United States ◽  
Strong Decrease ◽  
Social Distancing ◽  
Mobility Data ◽  
Actual Measure ◽  
The Us ◽  
The Impact ◽  
Political Decisions ◽  
Mobility Reduction

AbstractWe employ the Google and Apple mobility data to identify, quantify and classify different degrees of social distancing and characterise their imprint on the first wave of the COVID-19 pandemic in Europe and in the United States. We identify the period of enacted social distancing via Google and Apple data, independently from the political decisions. Our analysis allows us to classify different shades of social distancing measures for the first wave of the pandemic. We observe a strong decrease in the infection rate occurring two to five weeks after the onset of mobility reduction. A universal time scale emerges, after which social distancing shows its impact. We further provide an actual measure of the impact of social distancing for each region, showing that the effect amounts to a reduction by 20–40% in the infection rate in Europe and 30–70% in the US.

scholarly journals Impact of US vaccination strategy on COVID-19 wave dynamics

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Corentin Cot ◽  
Giacomo Cacciapaglia ◽  
Anna Sigridur Islind ◽  
María Óskarsdóttir ◽  
Francesco Sannino
Keyword(s):  
Renormalization Group ◽  
Human Mobility ◽  
Vaccination Campaign ◽  
Vaccination Strategy ◽  
Flight Data ◽  
Social Distancing ◽  
Wave Dynamics ◽  
The Us ◽  
The Impact ◽  
Pandemic Wave

AbstractWe employ the epidemic Renormalization Group (eRG) framework to understand, reproduce and predict the COVID-19 pandemic diffusion across the US. The human mobility across different geographical US divisions is modelled via open source flight data alongside the impact of social distancing for each such division. We analyse the impact of the vaccination strategy on the current pandemic wave dynamics in the US. We observe that the ongoing vaccination campaign will not impact the current pandemic wave and therefore strict social distancing measures must still be enacted. To curb the current and the next waves our results indisputably show that vaccinations alone are not enough and strict social distancing measures are required until sufficient immunity is achieved. Our results are essential for a successful vaccination strategy in the US.

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

2021 ◽  
Author(s):  
Chris Parker ◽  
Jorge Mejia ◽  
Franco Pestilli
Keyword(s):  
United States ◽  
Growth Rate ◽  
Presidential Election ◽  
Human Mobility ◽  
The United States ◽  
Political Orientation ◽  
Social Distancing ◽  
Individual Mobility ◽  
Open Datasets ◽  
The Impact

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.

scholarly journals Modeling COVID19 mortality in the US: Community context and mobility matter

2020 ◽  
Author(s):  
Sarah F. McGough ◽  
Ryan W. Gan ◽  
Robert Tibshirani ◽  
Anne-Marie Meyer
Keyword(s):  
The United States ◽  
Mortality Rates ◽  
Community Context ◽  
Community Factors ◽  
Social Distancing ◽  
Delayed Effects ◽  
The Us ◽  
Causal Impact ◽  
The Impact ◽  
Insight Into

AbstractThe United States has become an epicenter for the coronavirus disease 2019 (COVID-19) pandemic. However, communities have been unequally affected and evidence is growing that social determinants of health may be exacerbating the pandemic. Furthermore, the impact and timing of social distancing at the community level have yet to be fully explored. We investigated the relative associations between COVID-19 mortality and social distancing, sociodemographic makeup, economic vulnerabilities, and comorbidities in 24 counties surrounding 7 major metropolitan areas in the US using a flexible and robust time series modeling approach. We found that counties with poorer health and less wealth were associated with higher daily mortality rates compared to counties with fewer economic vulnerabilities and fewer pre-existing health conditions. Declines in mobility were associated with up to 15% lower mortality rates relative to pre-social distancing levels of mobility, but effects were lagged between 25-30 days. While we cannot estimate causal impact, this study provides insight into the association of social distancing on community mortality while accounting for key community factors. For full transparency and reproducibility, we provide all data and code used in this study.One-sentence summaryCounty-level disparities in COVID19 mortality highlight inequalities in socioeconomic and community factors and delayed effects of social distancing.

The Impact of Monetary and Fiscal Policies on the Stock Market in the United States (U.S); Evidence from Linear ARDL Framework

2020 ◽  
Vol 11 (1) ◽  
pp. 132-132
Author(s):  
Aref Emamian
Keyword(s):  
United States ◽  
Stock Market ◽  
The United States ◽  
Real Effective Exchange Rate ◽  
Annual Data ◽  
Fiscal Policies ◽  
Long Run ◽  
The Us ◽  
Short Run ◽  
The Impact

This study examines the impact of monetary and fiscal policies on the stock market in the United States (US), were used. By employing the method of Autoregressive Distributed Lags (ARDL) developed by Pesaran et al. (2001). Annual data from the Federal Reserve, World Bank, and International Monetary Fund, from 1986 to 2017 pertaining to the American economy, the results show that both policies play a significant role in the stock market. We find a significant positive effect of real Gross Domestic Product and the interest rate on the US stock market in the long run and significant negative relationship effect of Consumer Price Index (CPI) and broad money on the US stock market both in the short run and long run. On the other hand, this study only could support the significant positive impact of tax revenue and significant negative impact of real effective exchange rate on the US stock market in the short run while in the long run are insignificant. Keywords: ARDL, monetary policy, fiscal policy, stock market, United States

scholarly journals Spring Freeze Damage of Pecan Bloom: A Review

Horticulturae ◽  
2020 ◽  
Vol 6 (4) ◽  
pp. 82
Author(s):  
Amandeep Kaur ◽  
Louise Ferguson ◽  
Niels Maness ◽  
Becky Carroll ◽  
William Reid ◽  
...  
Keyword(s):  
Tree Height ◽  
The United States ◽  
Reproductive Organs ◽  
Tree Age ◽  
The Us ◽  
Nut Production ◽  
Freeze Damage ◽  
Terminal Buds ◽  
And Function ◽  
The Impact

Pecan is native to the United States. The US is the world’s largest pecan producer with an average yearly production of 250 to 300 million pounds; 80 percent of the world’s supply. Georgia, New Mexico, Texas, Arizona, Oklahoma, California, Louisiana, and Florida are the major US pecan producing states. Pecan trees frequently suffer from spring freeze at bud break and bloom as the buds are quite sensitive to freeze damage. This leads to poor flower and nut production. This review focuses on the impact of spring freeze during bud differentiation and flower development. Spring freeze kills the primary terminal buds, the pecan tree has a second chance for growth and flowering through secondary buds. Unfortunately, secondary buds have less bloom potential than primary buds and nut yield is reduced. Spring freeze damage depends on severity of the freeze, bud growth stage, cultivar type and tree age, tree height and tree vigor. This review discusses the impact of temperature on structure and function of male and female reproductive organs. It also summarizes carbohydrate relations as another factor that may play an important role in spring growth and transition of primary and secondary buds to flowers.

State Intervention During Public Health Emergencies: Is the United States Prepared for an Ebola Outbreak?

2015 ◽  
Vol 12 (2) ◽  
Author(s):  
Marie-Helen Maras ◽  
Michelle D. Miranda
Keyword(s):  
Public Health ◽  
State Intervention ◽  
The United States ◽  
International Travel ◽  
American Government ◽  
Training And Education ◽  
Public Health Emergencies ◽  
The Us ◽  
Bioterrorism Agent ◽  
Legal Guidelines

AbstractIn the fall of 2014, the US was faced with the reality that a deadly, foreign virus had entered its borders. Ebola, a disease thought to be of little threat to the US yet classified as a major bioterrorism agent, became a reality for the American government and its citizens. The introduction of Ebola unveiled many deficiencies in the country’s health care system, international travel policies, and ability to control or restrict the movement of exposed individuals in order to protect the larger population. The need to review and establish legal guidelines and policies to deal with these deficiencies is paramount: the inherent lack of training and education; weaknesses in monitoring, maintenance, and treatment; and the lack of uniform guidelines to isolate international travelers have all demonstrated that the country may not be able to control a larger-scale threat in the future.

scholarly journals Impact of temperature and relative humidity on the transmission of COVID-19: a modelling study in China and the United States

BMJ Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. e043863
Author(s):  
Jingyuan Wang ◽  
Ke Tang ◽  
Kai Feng ◽  
Xin Lin ◽  
Weifeng Lv ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Relative Humidity ◽  
Human Mobility ◽  
The United States ◽  
Reproductive Number ◽  
Cross Sectional ◽  
The Usa ◽  
Higher Temperature ◽  
Potential Impact ◽  
The Impact

ObjectivesWe aim to assess the impact of temperature and relative humidity on the transmission of COVID-19 across communities after accounting for community-level factors such as demographics, socioeconomic status and human mobility status.DesignA retrospective cross-sectional regression analysis via the Fama-MacBeth procedure is adopted.SettingWe use the data for COVID-19 daily symptom-onset cases for 100 Chinese cities and COVID-19 daily confirmed cases for 1005 US counties.ParticipantsA total of 69 498 cases in China and 740 843 cases in the USA are used for calculating the effective reproductive numbers.Primary outcome measuresRegression analysis of the impact of temperature and relative humidity on the effective reproductive number (R value).ResultsStatistically significant negative correlations are found between temperature/relative humidity and the effective reproductive number (R value) in both China and the USA.ConclusionsHigher temperature and higher relative humidity potentially suppress the transmission of COVID-19. Specifically, an increase in temperature by 1°C is associated with a reduction in the R value of COVID-19 by 0.026 (95% CI (−0.0395 to −0.0125)) in China and by 0.020 (95% CI (−0.0311 to −0.0096)) in the USA; an increase in relative humidity by 1% is associated with a reduction in the R value by 0.0076 (95% CI (−0.0108 to −0.0045)) in China and by 0.0080 (95% CI (−0.0150 to −0.0010)) in the USA. Therefore, the potential impact of temperature/relative humidity on the effective reproductive number alone is not strong enough to stop the pandemic.

scholarly journals Public Compliance With Social Distancing Measures and SARS-CoV-2 Spread

2021 ◽  
pp. 003335492110112
Author(s):  
Hongjie Liu ◽  
Chang Chen ◽  
Raul Cruz-Cano ◽  
Jennifer L. Guida ◽  
Minha Lee
Keyword(s):  
Growth Rate ◽  
Reproduction Number ◽  
Early Stage ◽  
Human Mobility ◽  
The United States ◽  
Density Change ◽  
Regression Coefficients ◽  
Daily Growth Rate ◽  
Daily Growth ◽  
Social Distancing

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.

scholarly journals The Impact of Policy Measures on Human Mobility, COVID-19 Cases, and Mortality in the US: A Spatiotemporal Perspective

2021 ◽  
Vol 18 (3) ◽  
pp. 996
Author(s):  
Yun Li ◽  
Moming Li ◽  
Megan Rice ◽  
Haoyuan Zhang ◽  
Dexuan Sha ◽  
...  
Keyword(s):  
Growth Rate ◽  
Human Mobility ◽  
Public Information ◽  
Key Factors ◽  
Information Campaigns ◽  
Rapid Spread ◽  
The Us ◽  
Policy Measures ◽  
The Impact ◽  
At Home

Social distancing policies have been regarded as effective in containing the rapid spread of COVID-19. However, there is a limited understanding of policy effectiveness from a spatiotemporal perspective. This study integrates geographical, demographical, and other key factors into a regression-based event study framework, to assess the effectiveness of seven major policies on human mobility and COVID-19 case growth rates, with a spatiotemporal emphasis. Our results demonstrate that stay-at-home orders, workplace closures, and public information campaigns were effective in decreasing the confirmed case growth rate. For stay-at-home orders and workplace closures, these changes were associated with significant decreases (p < 0.05) in mobility. Public information campaigns did not see these same mobility trends, but the growth rate still decreased significantly in all analysis periods (p < 0.01). Stay-at-home orders and international/national travel controls had limited mitigation effects on the death case growth rate (p < 0.1). The relationships between policies, mobility, and epidemiological metrics allowed us to evaluate the effectiveness of each policy and gave us insight into the spatiotemporal patterns and mechanisms by which these measures work. Our analysis will provide policymakers with better knowledge regarding the effectiveness of measures in space–time disaggregation.

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