Keep Social Distancing on Social Networks (Networks Distancing): Infodemic During COVID-19 Pandemic (Preprint)

2020 ◽  
Author(s):  
Amrollah Shamsi
Keyword(s):  
Social Networks ◽  
Social Distancing

scholarly journals The effect of social distancing on the reach of an epidemic in social networks

2021 ◽  
Author(s):  
Gregory Gutin ◽  
Tomohiro Hirano ◽  
Sung-Ha Hwang ◽  
Philip R. Neary ◽  
Alexis Akira Toda
Keyword(s):  
Public Health ◽  
Infectious Disease ◽  
Social Networks ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Disease Transmission ◽  
Global Level ◽  
Social Distancing ◽  
The Public ◽  
Simulation Results

AbstractHow does social distancing affect the reach of an epidemic in social networks? We present Monte Carlo simulation results of a susceptible–infected–removed with social distancing model. The key feature of the model is that individuals are limited in the number of acquaintances that they can interact with, thereby constraining disease transmission to an infectious subnetwork of the original social network. While increased social distancing typically reduces the spread of an infectious disease, the magnitude varies greatly depending on the topology of the network, indicating the need for policies that are network dependent. Our results also reveal the importance of coordinating policies at the ‘global’ level. In particular, the public health benefits from social distancing to a group (e.g. a country) may be completely undone if that group maintains connections with outside groups that are not following suit.

scholarly journals Ladies Selling Breakfast

2021 ◽  
Vol 28 (1) ◽  
pp. 34-38
Author(s):  
Ngoc-Bich Pham ◽  
Hong-Xoan Nguyen ◽  
Catherine Earl
Keyword(s):  
Social Capital ◽  
Social Networks ◽  
Interpersonal Relations ◽  
Economic Security ◽  
Food Culture ◽  
Ho Chi Minh City ◽  
Street Food ◽  
Social Distancing ◽  
Street Trading ◽  
Trading Activities

Ho Chi Minh City, Vietnam’s largest city, supports a vibrant street food culture. Most of the city’s street-engaged food traders are poor and unskilled women, and there is scant research about how they build social networks and social capital that sustain their microbusinesses. This article focusses on the intimate socialities that street-engaged food traders develop with customers, shop owners and sister-traders in order to stabilise their incomes while their informal street-trading activities are policed and potentially shut down. Recent COVID-19 lockdown and social-distancing measures disrupted the crucial interpersonal relations of street trading and left the traders with no income. This article explores traders’ strategies for achieving economic security, and outlines transformations of intimate socialities into mediated and digital relations after the lockdown.

ENDOGENOUS SOCIAL DISTANCING AND CONTAINMENT POLICIES IN SOCIAL NETWORKS

2021 ◽  
Vol 257 ◽  
pp. 101-117
Author(s):  
Fabrizio Adriani ◽  
Dan Ladley
Keyword(s):  
Social Networks ◽  
Network Formation ◽  
Crowding Out ◽  
Policy Intervention ◽  
Negative Externalities ◽  
Formation Theory ◽  
Social Distancing ◽  
Face To Face ◽  
Underlying Network

Can smart containment policies crowd out private efforts at social distancing? We analyse this question from the perspective of network formation theory. We focus in particular on the role of externalities in social distancing choices. We also look at how these choices are affected by factors such as the agents’ risk perception, the speed of the policy intervention, the structure of the underlying network and the presence of strategic complementarities. We argue that crowding out is a problem when the probability that an outbreak may spread undetected is relatively high (either because testing is too infrequent or because tests are highly inaccurate). This is also the case where the choice of relaxing social distancing generates the largest negative externalities. Simulations on a real-world network suggest that crowding out is more likely to occur when, in the absence of interventions, face-to-face contacts are perceived to carry relatively high risk.

scholarly journals Association Between Public Knowledge About COVID-19, Trust in Information Sources, and Adherence to Social Distancing: Cross-Sectional Survey (Preprint)

2020 ◽  
Author(s):  
Ilona Fridman ◽  
Nicole Lucas ◽  
Debra Henke ◽  
Christina K Zigler
Keyword(s):  
Social Networks ◽  
Information Sources ◽  
Public Knowledge ◽  
Trust In Government ◽  
Government Information ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Negatively Associated ◽  
Social Distancing ◽  
The Impact

BACKGROUND The success of behavioral interventions and policies designed to reduce the impact of the COVID-19 pandemic depends on how well individuals are informed about both the consequences of infection and the steps that should be taken to reduce the impact of the disease. OBJECTIVE The aim of this study was to investigate associations between public knowledge about COVID-19, adherence to social distancing, and public trust in government information sources (eg, the US Centers for Disease Control and Prevention), private sources (eg, FOX and CNN), and social networks (eg, Facebook and Twitter) to inform future policies related to critical information distribution. METHODS We conducted a cross-sectional survey (N=1243) between April 10 and 14, 2020. Data collection was stratified by US region and other demographics to ensure representativeness of the sample. RESULTS Government information sources were the most trusted among the public. However, we observed trends in the data that suggested variations in trust by age and gender. White and older populations generally expressed higher trust in government sources, while non-White and younger populations expressed higher trust in private sources (eg, CNN) and social networks (eg, Twitter). Trust in government sources was positively associated with accurate knowledge about COVID-19 and adherence to social distancing. However, trust in private sources (eg, FOX and CNN) was negatively associated with knowledge about COVID-19. Similarly, trust in social networks (eg, Facebook and Twitter) was negatively associated with both knowledge and adherence to social distancing. CONCLUSIONS During pandemics such as the COVID-19 outbreak, policy makers should carefully consider the quality of information disseminated through private sources and social networks. Furthermore, when disseminating urgent health information, a variety of information sources should be used to ensure that diverse populations have timely access to critical knowledge.

scholarly journals The Role of Social Networks During the COVID-19 Lockdown: Real-Life Social Distancing Vs Virtual Interactions

2021 ◽  
Vol 16 (5) ◽  
pp. 133
Author(s):  
Donata Tania Vergura ◽  
Beatrice Luceri ◽  
Cristina Zerbini
Keyword(s):  
Social Support ◽  
Social Networks ◽  
Online Survey ◽  
Real Life ◽  
Strong Impact ◽  
Emotional Instability ◽  
Social Distancing ◽  
The Social ◽  
The World

Online social networks have become one of the most widely used sources of information in the world and also an important part of our daily life. A huge boost to their spreading came with the outbreak of the COVID-19 pandemic. As social distancing and lockdown orders due to COVID-19 health emergency grew more pervasive, individuals began to spend more time online and to use social networks (SNs) to keep up to date regarding the spread of pandemic and also to maintain communication with friends and family and reduce isolation. Given these evidences, the present study aims to investigate the social supporting role of SNs during the pandemic emergency. Specifically, it intends to analyze (a) the use of SNs as a means of interaction in the face of the social containment imposed by the COVID-19 spreading, and (b) the factors (homophily, trust, loneliness, and emotional instability) that affect such use. An online survey with a sample of 194 Italian people was conducted. Structural equation modelling was used to estimate the model proposed. Results revealed that sense of belonging to SNs had a strong impact on search for social support and is, in turn, positively influenced by trust in SNs and homophily. Emotional instability also increased the search for social support. The study contributes both theoretically and empirically to the understanding of the role of SNs in influencing individual behavior. As the use of SNs continues to spread around the world, understanding why consumers rely in SNs and what gratifications they receive from them is undoubtedly of interest for both academics and practitioners.

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 Modeling the Consequences of Social Distancing Over Epidemics Spreading in Complex Social Networks: From Link Removal Analysis to SARS-CoV-2 Prevention

2021 ◽  
Vol 9 ◽  
Author(s):  
M. Bellingeri ◽  
M. Turchetto ◽  
D. Bevacqua ◽  
F. Scotognella ◽  
R. Alfieri ◽  
...  
Keyword(s):  
Social Networks ◽  
Temporal Dynamics ◽  
Epidemiological Models ◽  
Connected Component ◽  
Epidemic Spreading ◽  
Social Distancing ◽  
Promising Tool ◽  
The Social ◽  
Network Topologies ◽  
Pharmaceutical Interventions

In this perspective, we describe how the link removal (LR) analysis in social complex networks may be a promising tool to model non-pharmaceutical interventions (NPIs) and social distancing to prevent epidemics spreading. First, we show how the extent of the epidemic spreading and NPIs effectiveness over complex social networks may be evaluated with a static indicator, that is, the classic largest connected component (LCC). Then we explain how coupling the LR analysis and type SIR epidemiological models (EM) provide further information by including the temporal dynamics of the epidemic spreading. This is a promising approach to investigate important aspects of the recent NPIs applied by government to contain SARS-CoV-2, such as modeling the effect of the social distancing severity and timing over different network topologies. Further, implementing different link removal strategies to halt epidemics spreading provides information to individuate more effective NPIs, representing an important tool to offer a rationale sustaining policies to prevent SARS-CoV-2 and similar epidemics.

scholarly journals Social distancing beliefs and human mobility: Evidence from Twitter

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0246949 ◽  
Author(s):  
Simon Porcher ◽  
Thomas Renault
Keyword(s):  
Social Networks ◽  
Human Mobility ◽  
State Level ◽  
The State ◽  
Policy Makers ◽  
Social Distancing ◽  
Mobility Data ◽  
Twitter Data ◽  
Precipitation And Temperature

We construct a novel database containing hundreds of thousands geotagged messages related to the COVID-19 pandemic sent on Twitter. We create a daily index of social distancing—at the state level—to capture social distancing beliefs by analyzing the number of tweets containing keywords such as “stay home”, “stay safe”, “wear mask”, “wash hands” and “social distancing”. We find that an increase in the Twitter index of social distancing on day t-1 is associated with a decrease in mobility on day t. We also find that state orders, an increase in the number of COVID-19 cases, precipitation and temperature contribute to reducing human mobility. Republican states are also less likely to enforce social distancing. Beliefs shared on social networks could both reveal the behavior of individuals and influence the behavior of others. Our findings suggest that policy makers can use geotagged Twitter data—in conjunction with mobility data—to better understand individual voluntary social distancing actions.

scholarly journals DISTANCIAMENTO SOCIAL E REPERCUSSÕES OCUPACIONAIS DA PANDEMIA PARA CUIDADORAS DE CRIANÇAS E ADOLESCENTES

2021 ◽  
Vol 7 (2) ◽  
pp. 295-313
Author(s):  
Marina Batella Martins ◽  
Bruna Lídia Taño ◽  
Marina Vilaça Cavallari Machado
Keyword(s):  
Social Networks ◽  
Content Analysis ◽  
Children And Adolescents ◽  
Multidisciplinary Team ◽  
Quantitative Data ◽  
Leisure Activities ◽  
Social Distancing ◽  
Occupational Profile ◽  
The Social ◽  
The Impact

This study aimed to identify the impact of social distancing caused by the COVID-19 pandemic on the occupational profile of children and adolescents caregivers accompained by a multidisciplinary team. 34 caregivers participated by fulfilling a questionnaire composed of 31 questions. Quantitative data were analyzed descriptively and the content analysis was performed by open grid questions. The results of this study point to the intensification of the caregiver's role, absence of participation in leisure activities and the importance of involvement in significant activities that support and sustain health. Participants indicated strategies that were effective in coping with the impacts caused by the pandemic, such as leisure and prevetion activities. Further, it was observed that theses strategies were developed by the participants themselves, on the social networks or internet.

scholarly journals COVID-19 Outbreak, Social Response, and Early Economic Effects: A Global VAR Analysis of Cross-Country Interdependencies

2020 ◽  
Author(s):  
Fabio Milani
Keyword(s):  
Social Networks ◽  
Risk Perceptions ◽  
Economic Effects ◽  
Social Connections ◽  
Central Component ◽  
Health Shocks ◽  
Social Distancing ◽  
Global Var ◽  
Cross Country ◽  
The U.S

AbstractThe COVID-19 pandemic underscored the importance of countries’ interconnections in understanding and reacting to the spread of the virus.This paper uses a global model with a sample of 41 countries to study the interdependencies between COVID-19 health shocks, populations’ risk perceptions about the disease, and their social distancing responses; it also provides some early evidence about potential economic effects.Social networks are a central component in understanding the international transmission.We exploit a dataset on existing social connections across country borders, made available by Facebook, and show that social networks help explain not only the spread of the disease, but also cross-country spillovers in risk perceptions and in social behavior. Social distancing responses across countries are measured based on aggregated mobility tracking indicators, obtained from Google Mobility Reports.We estimate a Global VAR (GVAR) model, which allows for endogeneity of each health, social, and economic, domestic variable, and for a dependence of domestic variables on country-specific foreign aggregates, which depend in turn on the matrix of social connections.Our empirical results highlight the importance of cross-country interdependencies and social networks. Risk perceptions and social responses are affected by experiences abroad, with Italy and the U.S. playing large roles in our sample. The social distancing responses to domestic health shocks are heterogeneous across countries, but they share some similarities: they adjust only gradually and with delay, hence displaying adaptive behavior.Early indicators are suggestive of unemployment consequences that vary widely across countries, depending on their labor market characteristics. Unemployment is particularly responsive to health shocks in the U.S. and Spain, while the fluctuations are attenuated almost everywhere else.

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