scholarly journals Forecasting the Spread of COVID-19 under Different Reopening Strategies

2020 ◽  
Author(s):  
Meng Liu ◽  
Raphael Thomadsen ◽  
Song Yao
Keyword(s):  
United States ◽  
Growth Rate ◽  
Population Density ◽  
The United States ◽  
Sir Model ◽  
Social Distancing ◽  
Mobility Data ◽  
The Social ◽  
The Us ◽  
Case Data

ABSTRACTWe combine COVID-19 case data with demographic and mobility data to estimate a modified susceptible-infected-recovered (SIR) model for the spread of this disease in the United States. We find that the incidence of infectious COVID-19 individuals has a concave effect on contagion, as would be expected if people have inter-related social networks. We also demonstrate that social distancing and population density have large effects on the rate of contagion. The social distancing in late March and April substantially reduced the number of COVID-19 cases. However, the concave contagion pattern means that when social distancing measures are lifted, the growth rate is considerable but will not be exponential as predicted by standard SIR models. Furthermore, counties with the lowest population density could likely avoid high levels of contagion even with no social distancing. We forecast rates of new cases for COVID-19 under different social distancing norms and find that if social distancing is eliminated there will be a massive increase in the cases of COVID-19, about double what would occur if the US only restored to 50% of the way to normalcy.

scholarly journals Forecasting the spread of COVID-19 under different reopening strategies

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Meng Liu ◽  
Raphael Thomadsen ◽  
Song Yao
Keyword(s):  
United States ◽  
Social Networks ◽  
Exponential Growth ◽  
The United States ◽  
Sir Model ◽  
Disease Spread ◽  
Social Distancing ◽  
Mobility Data ◽  
The Us ◽  
Case Data

AbstractWe combine COVID-19 case data with mobility data to estimate a modified susceptible-infected-recovered (SIR) model in the United States. In contrast to a standard SIR model, we find that the incidence of COVID-19 spread is concave in the number of infectious individuals, as would be expected if people have inter-related social networks. This concave shape has a significant impact on forecasted COVID-19 cases. In particular, our model forecasts that the number of COVID-19 cases would only have an exponential growth for a brief period at the beginning of the contagion event or right after a reopening, but would quickly settle into a prolonged period of time with stable, slightly declining levels of disease spread. This pattern is consistent with observed levels of COVID-19 cases in the US, but inconsistent with standard SIR modeling. We forecast rates of new cases for COVID-19 under different social distancing norms and find that if social distancing is eliminated there will be a massive increase in the cases of COVID-19.

scholarly journals Impacts of social distancing policies on mobility and COVID-19 case growth in the US

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Gregory A. Wellenius ◽  
Swapnil Vispute ◽  
Valeria Espinosa ◽  
Alex Fabrikant ◽  
Thomas C. Tsai ◽  
...  
Keyword(s):  
Public Health ◽  
United States ◽  
Infection Control ◽  
State Level ◽  
The United States ◽  
Social Consequences ◽  
Social Distancing ◽  
Mobility Data ◽  
The Us ◽  
Public Health Officials

AbstractSocial distancing remains an important strategy to combat the COVID-19 pandemic in the United States. However, the impacts of specific state-level policies on mobility and subsequent COVID-19 case trajectories have not been completely quantified. Using anonymized and aggregated mobility data from opted-in Google users, we found that state-level emergency declarations resulted in a 9.9% reduction in time spent away from places of residence. Implementation of one or more social distancing policies resulted in an additional 24.5% reduction in mobility the following week, and subsequent shelter-in-place mandates yielded an additional 29.0% reduction. Decreases in mobility were associated with substantial reductions in case growth two to four weeks later. For example, a 10% reduction in mobility was associated with a 17.5% reduction in case growth two weeks later. Given the continued reliance on social distancing policies to limit the spread of COVID-19, these results may be helpful to public health officials trying to balance infection control with the economic and social consequences of these policies.

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.

A Critical Transnational Perspective to Asian America

2017 ◽  
Author(s):  
Yen Le Espiritu
Keyword(s):  
United States ◽  
Civil Rights ◽  
Asian American ◽  
The United States ◽  
Human Welfare ◽  
Vietnamese Refugees ◽  
The Social ◽  
The Us ◽  
The Status ◽  
Rights Discourse

Much of the early scholarship in Asian American studies sought to establish that Asian Americans have been crucial to the making of the US nation and thus deserve full inclusion into its polity. This emphasis on inclusion affirms the status of the United States as the ultimate protector and provider of human welfare, and narrates the Asian American subject by modern civil rights discourse. However, the comparative cases of Filipino immigrants and Vietnamese refugees show how Asian American racial formation has been determined not only by the social, economic, and political forces in the United States but also by US colonialism, imperialism, and wars in Asia.

scholarly journals Diverse local epidemics reveal the distinct effects of population density, demographics, climate, depletion of susceptibles, and intervention in the first wave of COVID-19 in the United States

2020 ◽  
Author(s):  
Niayesh Afshordi ◽  
Benjamin Holder ◽  
Mohammad Bahrami ◽  
Daniel Lichtblau
Keyword(s):  
United States ◽  
Population Density ◽  
The United States ◽  
Effective Response ◽  
Susceptible Population ◽  
Local Climate ◽  
Climate Conditions ◽  
Mortality And Morbidity ◽  
Social Distancing ◽  
The Impact

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.

scholarly journals Mexico: «the population explosion» and mass migration

2017 ◽  
pp. 56-62
Author(s):  
Nadejda Kudeyarova
Keyword(s):  
United States ◽  
The United States ◽  
Mexican Migration ◽  
Mexican Migrants ◽  
Migratory Activity ◽  
Mass Migration ◽  
The Social ◽  
The Us ◽  
Demographic Processes ◽  
Migration Analysis

The debate over the Mexican migrants issue has been intensi ed by Donald Trump’s election. His harsh statements have provoked a discussion on the US policy for Mexico, as well as on the migration regulation in the United States. However, the mass migration of the last quarter of XX - beginning of XXI centuries may be also readily associated with the social and demographic processes developed in Mexico throughout the 20th century. The dynamics of migratory activity followed the demographic changes. The internal causes of the Mexican migration analysis will allow more clarity in understanding contemporary migration interaction between the two neighboring countries.

scholarly journals Strong Social Distancing Measures In The United States Reduced The COVID-19 Growth Rate

2020 ◽  
Vol 39 (7) ◽  
pp. 1237-1246 ◽  
Author(s):  
Charles Courtemanche ◽  
Joseph Garuccio ◽  
Anh Le ◽  
Joshua Pinkston ◽  
Aaron Yelowitz
Keyword(s):  
United States ◽  
Growth Rate ◽  
The United States ◽  
Social Distancing

scholarly journals Socioeconomic Disparities in Social Distancing During the COVID-19 Pandemic in the United States: Observational Study (Preprint)

2020 ◽  
Author(s):  
Romain Garnier ◽  
Jan R Benetka ◽  
John Kraemer ◽  
Shweta Bansal
Keyword(s):  
United States ◽  
Black People ◽  
The United States ◽  
Control Measures ◽  
Mobility Patterns ◽  
Poverty Level ◽  
Social Distancing ◽  
Mobility Data ◽  
Black Populations ◽  
The Impact

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.

scholarly journals Social Capital Dimensions are Differentially Associated with COVID-19 Vaccinations, Masks, and Physical Distancing

2021 ◽  
Author(s):  
Ibtihal Ferwana ◽  
Lav R. Varshney
Keyword(s):  
Public Health ◽  
United States ◽  
Social Capital ◽  
Community Health ◽  
Collective Efficacy ◽  
Residential Mobility ◽  
The United States ◽  
Social Distancing ◽  
The Social ◽  
Family Unity

Background Social capital has been associated with health outcomes in communities and can explain variations in different geographic localities. Social capital has also been associated with behaviors that promote better health and reduce the impacts of diseases. During the COVID-19 pandemic, social distancing, face masking, and vaccination have all been essential in controlling contagion. These behaviors have not been uniformly adopted by communities in the United States. Using different facets of social capital to explain the differences in public behaviors among communities during pandemics is lacking. Objective This study examines the relationship among public health behavior, vaccination, face masking, and physical distancing during COVID-19 pandemic and social capital indices in counties in the United States. Methods We used publicly available vaccination data as of June 2021, face masking data in July 2020, and mobility data from mobile phones movements from the end of March 2020. Then, correlation analysis was conducted with county-level social capital index and its subindices (family unity, community health, institutional health, and collective efficacy) that were obtained from the Social Capital Project by the United States Senate. Results We found the social capital index and its subindices differentially correlate with different public health behaviors. Vaccination is associated with institutional health: positively with fully vaccinated population and negatively with vaccination hesitancy. Also, wearing masks negatively associates with community health, whereases reduced mobility associates with better community health. Further, residential mobility positively associates with family unity. By comparing correlation coefficients, we find that social capital and its subindices have largest effect sizes on vaccination and residential mobility. Conclusion Our results show that different facets of social capital are significantly associated with adoption of protective behaviors, e.g., social distancing, face masking, and vaccination. As such, our results suggest that differential facets of social capital imply a Swiss cheese model of pandemic control planning where, e.g., institutional health and community health, provide partially overlapping behavioral benefits.

scholarly journals Social capital dimensions are differentially associated with COVID-19 vaccinations, masks, and physical distancing

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0260818
Author(s):  
Ibtihal Ferwana ◽  
Lav R. Varshney
Keyword(s):  
Public Health ◽  
United States ◽  
Social Capital ◽  
Community Health ◽  
Collective Efficacy ◽  
Residential Mobility ◽  
The United States ◽  
Social Distancing ◽  
The Social ◽  
Family Unity

Background Social capital has been associated with health outcomes in communities and can explain variations in different geographic localities. Social capital has also been associated with behaviors that promote better health and reduce the impacts of diseases. During the COVID-19 pandemic, social distancing, face masking, and vaccination have all been essential in controlling contagion. These behaviors have not been uniformly adopted by communities in the United States. Using different facets of social capital to explain the differences in public behaviors among communities during pandemics is lacking. Objective This study examines the relationship among public health behavior—vaccination, face masking, and physical distancing—during COVID-19 pandemic and social capital indices in counties in the United States. Methods We used publicly available vaccination data as of June 2021, face masking data in July 2020, and mobility data from mobile phones movements from the end of March 2020. Then, correlation analysis was conducted with county-level social capital index and its subindices (family unity, community health, institutional health, and collective efficacy) that were obtained from the Social Capital Project by the United States Senate. Results We found the social capital index and its subindices differentially correlate with different public health behaviors. Vaccination is associated with institutional health: positively with fully vaccinated population and negatively with vaccination hesitancy. Also, wearing masks negatively associates with community health, whereases reduced mobility associates with better community health. Further, residential mobility positively associates with family unity. By comparing correlation coefficients, we find that social capital and its subindices have largest effect sizes on vaccination and residential mobility. Conclusion Our results show that different facets of social capital are significantly associated with adoption of protective behaviors, e.g., social distancing, face masking, and vaccination. As such, our results suggest that differential facets of social capital imply a Swiss cheese model of pandemic control planning where, e.g., institutional health and community health, provide partially overlapping behavioral benefits.

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