scholarly journals More Active Internet-Search on Google and Twitter Posting for COVID-19 Corresponds with Lower Infection Rate in the 50 U.S. States

2020 ◽  
Author(s):  
Jiachen Sun ◽  
Peter Gloor
Keyword(s):  
Infection Rate ◽  
Predictive Accuracy ◽  
State Level ◽  
The United States ◽  
The Novel ◽  
Internet Search ◽  
Online Social Media ◽  
Lower Infection ◽  
Novel Coronavirus ◽  
Lower Infection Rate

Abstract As the novel coronavirus disease 2019 (COVID-19) continues to rage worldwide, the United States has become the most affected country with more than 2.5 million total confirmed cases up to now (June 2, 2020). In this work, we investigate the predictive power of online social media and Internet search for the COVID-19 pandemic among 50 U.S. states. By collecting the state-level daily trends through both Twitter and Google Trends, we observe a high but state-different lag correlation with the number of daily confirmed cases. We further find that the predictive accuracy measured by the correlation coefficient is positively correlated to a state’s demographic, air traffic volume and GDP development. Most importantly, we show that a state’s early infection rate is negatively correlated with the lag to the previous peak in Internet search and tweeting about COVID-19, indicating that the earlier the collective awareness on Twitter/Google in a state, the lower is the infection rate.

scholarly journals Assessing the Predictive Power of Online Social Media to Analyze COVID-19 Outbreaks in the 50 U.S. States

2021 ◽  
Vol 13 (7) ◽  
pp. 184
Author(s):  
Jiachen Sun ◽  
Peter A. Gloor
Keyword(s):  
Social Media ◽  
Infection Rate ◽  
State Level ◽  
The United States ◽  
The Public ◽  
Online Social Media ◽  
Lower Infection ◽  
Internet Searches ◽  
Affected Country ◽  
Lower Infection Rate

As the coronavirus disease 2019 (COVID-19) continues to rage worldwide, the United States has become the most affected country, with more than 34.1 million total confirmed cases up to 1 June 2021. In this work, we investigate correlations between online social media and Internet search for the COVID-19 pandemic among 50 U.S. states. By collecting the state-level daily trends through both Twitter and Google Trends, we observe a high but state-different lag correlation with the number of daily confirmed cases. We further find that the accuracy measured by the correlation coefficient is positively correlated to a state’s demographic, air traffic volume and GDP development. Most importantly, we show that a state’s early infection rate is negatively correlated with the lag to the previous peak in Internet searches and tweeting about COVID-19, indicating that earlier collective awareness on Twitter/Google correlates with a lower infection rate. Lastly, we demonstrate that correlations between online social media and search trends are sensitive to time, mainly due to the attention shifting of the public.

scholarly journals Political Ideology and the Outbreak of COVID-19 in the United States

2020 ◽  
Author(s):  
Daniel L. Rosenfeld
Keyword(s):  
United States ◽  
Political Ideology ◽  
State Level ◽  
The United States ◽  
The State ◽  
The Novel ◽  
Unique Role ◽  
Rapid Spread ◽  
Novel Coronavirus

At the state level within the United States, did political ideology predict the outbreak of the novel coronavirus (COVID-19)? Throughout March 2020, the United States became the epicenter of the COVID-19 pandemic, recording the most cases of any country worldwide. The current research found that, at the state level within the United States, more conservative political ideology predicted delayed implementation of stay-at-home orders and more rapid spread of COVID-19. Effects were significant across two distinct operationalizations of political ideology and held over and above relevant covariates, suggesting a potentially unique role of political ideology in the United States’ COVID-19 outbreak. Considering political ideological factors may offer valuable insights into epidemiological processes surrounding COVID-19.

scholarly journals Pandemic Politics: Timing State-Level Social Distancing Responses to COVID-19

2020 ◽  
Author(s):  
Christopher Adolph ◽  
Kenya Amano ◽  
Bree Bang-Jensen ◽  
Nancy Fullman ◽  
John Wilkerson
Keyword(s):  
Event History Analysis ◽  
State Level ◽  
The United States ◽  
The Novel ◽  
Social Distancing ◽  
Policy Responses ◽  
Original Dataset ◽  
Political Partisanship ◽  
History Analysis ◽  
Novel Coronavirus

AbstractSocial distancing policies are critical but economically painful measures to flatten the curve against emergent infectious diseases. As the novel coronavirus that causes COVID-19 spread throughout the United States in early 2020, the federal government issued social distancing recommendations but left to the states the most difficult and consequential decisions restricting behavior, such as canceling events, closing schools and businesses, and issuing stay-at-home orders. We present an original dataset of state-level social distancing policy responses to the epidemic and explore how political partisanship, COVID-19 caseload, and policy diffusion explain the timing of governors’ decisions to mandate social distancing. An event history analysis of five social distancing policies across all fifty states reveals the most important predictors are political: all else equal, Republican governors and governors from states with more Trump supporters were slower to adopt social distancing policies. These delays are likely to produce significant, on-going harm to public health.

scholarly journals Creating COVID-19 Stigma by Referencing the Novel Coronavirus as the “Chinese virus” on Twitter: Quantitative Analysis of Social Media Data (Preprint)

2020 ◽  
Author(s):  
Henna Budhwani ◽  
Ruoyan Sun
Keyword(s):  
New York ◽  
Quantitative Analysis ◽  
National Level ◽  
State Level ◽  
Fold Increase ◽  
The United States ◽  
The Novel ◽  
Structural Force ◽  
Novel Coronavirus ◽  
Derivatives Of

BACKGROUND Stigma is the deleterious, structural force that devalues members of groups that hold undesirable characteristics. Since stigma is created and reinforced by society—through in-person and online social interactions—referencing the novel coronavirus as the “Chinese virus” or “China virus” has the potential to create and perpetuate stigma. OBJECTIVE The aim of this study was to assess if there was an increase in the prevalence and frequency of the phrases “Chinese virus” and “China virus” on Twitter after the March 16, 2020, US presidential reference of this term. METHODS Using the Sysomos software (Sysomos, Inc), we extracted tweets from the United States using a list of keywords that were derivatives of “Chinese virus.” We compared tweets at the national and state levels posted between March 9 and March 15 (preperiod) with those posted between March 19 and March 25 (postperiod). We used Stata 16 (StataCorp) for quantitative analysis, and Python (Python Software Foundation) to plot a state-level heat map. RESULTS A total of 16,535 “Chinese virus” or “China virus” tweets were identified in the preperiod, and 177,327 tweets were identified in the postperiod, illustrating a nearly ten-fold increase at the national level. All 50 states witnessed an increase in the number of tweets exclusively mentioning “Chinese virus” or “China virus” instead of coronavirus disease (COVID-19) or coronavirus. On average, 0.38 tweets referencing “Chinese virus” or “China virus” were posted per 10,000 people at the state level in the preperiod, and 4.08 of these stigmatizing tweets were posted in the postperiod, also indicating a ten-fold increase. The 5 states with the highest number of postperiod “Chinese virus” tweets were Pennsylvania (n=5249), New York (n=11,754), Florida (n=13,070), Texas (n=14,861), and California (n=19,442). Adjusting for population size, the 5 states with the highest prevalence of postperiod “Chinese virus” tweets were Arizona (5.85), New York (6.04), Florida (6.09), Nevada (7.72), and Wyoming (8.76). The 5 states with the largest increase in pre- to postperiod “Chinese virus” tweets were Kansas (n=697/58, 1202%), South Dakota (n=185/15, 1233%), Mississippi (n=749/54, 1387%), New Hampshire (n=582/41, 1420%), and Idaho (n=670/46, 1457%). CONCLUSIONS The rise in tweets referencing “Chinese virus” or “China virus,” along with the content of these tweets, indicate that knowledge translation may be occurring online and COVID-19 stigma is likely being perpetuated on Twitter.

scholarly journals Creating COVID-19 Stigma by Referencing the Novel Coronavirus as the “Chinese virus” on Twitter: Quantitative Analysis of Social Media Data

10.2196/19301 ◽  
2020 ◽  
Vol 22 (5) ◽  
pp. e19301 ◽  
Author(s):  
Henna Budhwani ◽  
Ruoyan Sun
Keyword(s):  
New York ◽  
Quantitative Analysis ◽  
National Level ◽  
State Level ◽  
Fold Increase ◽  
The United States ◽  
The Novel ◽  
Structural Force ◽  
Novel Coronavirus ◽  
Derivatives Of

Background Stigma is the deleterious, structural force that devalues members of groups that hold undesirable characteristics. Since stigma is created and reinforced by society—through in-person and online social interactions—referencing the novel coronavirus as the “Chinese virus” or “China virus” has the potential to create and perpetuate stigma. Objective The aim of this study was to assess if there was an increase in the prevalence and frequency of the phrases “Chinese virus” and “China virus” on Twitter after the March 16, 2020, US presidential reference of this term. Methods Using the Sysomos software (Sysomos, Inc), we extracted tweets from the United States using a list of keywords that were derivatives of “Chinese virus.” We compared tweets at the national and state levels posted between March 9 and March 15 (preperiod) with those posted between March 19 and March 25 (postperiod). We used Stata 16 (StataCorp) for quantitative analysis, and Python (Python Software Foundation) to plot a state-level heat map. Results A total of 16,535 “Chinese virus” or “China virus” tweets were identified in the preperiod, and 177,327 tweets were identified in the postperiod, illustrating a nearly ten-fold increase at the national level. All 50 states witnessed an increase in the number of tweets exclusively mentioning “Chinese virus” or “China virus” instead of coronavirus disease (COVID-19) or coronavirus. On average, 0.38 tweets referencing “Chinese virus” or “China virus” were posted per 10,000 people at the state level in the preperiod, and 4.08 of these stigmatizing tweets were posted in the postperiod, also indicating a ten-fold increase. The 5 states with the highest number of postperiod “Chinese virus” tweets were Pennsylvania (n=5249), New York (n=11,754), Florida (n=13,070), Texas (n=14,861), and California (n=19,442). Adjusting for population size, the 5 states with the highest prevalence of postperiod “Chinese virus” tweets were Arizona (5.85), New York (6.04), Florida (6.09), Nevada (7.72), and Wyoming (8.76). The 5 states with the largest increase in pre- to postperiod “Chinese virus” tweets were Kansas (n=697/58, 1202%), South Dakota (n=185/15, 1233%), Mississippi (n=749/54, 1387%), New Hampshire (n=582/41, 1420%), and Idaho (n=670/46, 1457%). Conclusions The rise in tweets referencing “Chinese virus” or “China virus,” along with the content of these tweets, indicate that knowledge translation may be occurring online and COVID-19 stigma is likely being perpetuated on Twitter.

scholarly journals Pandemic Politics: Timing State-Level Social Distancing Responses to COVID-19

2020 ◽  
Author(s):  
Christopher Adolph ◽  
Kenya Amano ◽  
Bree Bang-Jensen ◽  
Nancy Fullman ◽  
John Wilkerson
Keyword(s):  
Event History Analysis ◽  
State Level ◽  
The United States ◽  
Event History ◽  
The Novel ◽  
Critical Window ◽  
Social Distancing ◽  
Policy Responses ◽  
History Analysis ◽  
Novel Coronavirus

Abstract Context: Social distancing is an essential but economically painful measure to flatten the curve of emergent infectious diseases. As the novel coronavirus that causes COVID-19 spread throughout the United States in early 2020, the federal government left to the states the difficult and consequential decisions about when to cancel events, close schools and businesses, and issue stay-at-home orders. Methods: We present an original, detailed dataset of state-level social distancing policy responses to the epidemic, then apply event history analysis to study the timing of implementation of five social distancing policies across all fifty states. Results: The most important predictor of when states adopted social distancing policies is political: All else equal, states led by Republican governors were slower to implement such policies during a critical window of early COVID-19 response. Conclusions: Continuing actions driven by partisanship, rather than public health expertise and scientific recommendations, may exact greater tolls on health and broader society.

scholarly journals The impact of quarantine on Covid-19 infections

2021 ◽  
Vol 10 (s1) ◽  
Author(s):  
Pablo Marshall
Keyword(s):  
Health System ◽  
Infection Rate ◽  
District Level ◽  
Infection Model ◽  
Social Distancing ◽  
Proposed Model ◽  
Lower Infection ◽  
The Impact ◽  
Lower Infection Rate ◽  
Over Time

Abstract Objectives: Coronavirushas had profound effects on people’s lives and the economy of many countries, generating controversy between the need to establish quarantines and other social distancing measures to protect people’s health and the need to reactivate the economy. This study proposes and applies a modification of the SIR infection model to describe the evolution of coronavirus infections and to measure the effect of quarantine on the number of people infected. Methods: Two hypotheses, not necessarily mutually exclusive, are proposed for the impact of quarantines. According to the first hypothesis, quarantine reduces the infection rate, delaying new infections over time without modifying the total number of people infected at the end of the wave. The second hypothesis establishes that quarantine reduces the population infected in the wave. The two hypotheses are tested with data for a sample of 10 districts in Santiago, Chile. Results: The results of applying the methodology show that the proposed model describes well the evolution of infections at the district level. The data shows evidence in favor of the first hypothesis, quarantine reduces the infection rate; and not in favor of the second hypothesis, that quarantine reduces the population infected. Districts of higher socio-economic levels have a lower infection rate, and quarantine is more effective. Conclusions: Quarantine, in most districts, does not reduce the total number of people infected in the wave; it only reduces the rate at which they are infected. The reduction in the infection rate avoids peaks that may collapse the health system.

scholarly journals Belonging in the Coronaverse: Will There Be Time?

2021 ◽  
Vol 1 (1) ◽  
pp. 100-115
Author(s):  
Kate Fischer ◽  
Malika Rakhmonova ◽  
Mike Tran
Keyword(s):  
College Experience ◽  
The United States ◽  
Limited Time ◽  
The Novel ◽  
Residential University ◽  
To Come ◽  
Novel Coronavirus ◽  
University Experience ◽  
The U.S ◽  
Older Siblings

Abstract Since the spring of 2020 SARS-CoV-2, the novel coronavirus, has upended lives and caused a rethinking of nearly all social behaviors in the United States. This paper examines the ways in which the pandemic, shutdown, and gradual move towards “normal” have laid bare and obfuscated societal pressures regarding running out of time as it pertains to the residential university experience. Promised by movies, television, and older siblings and friends as a limited-time offer, the “typical” college experience is baked into the U.S. imaginary, reinforcing a host of notions of who “belongs” on campus along lines of race, class, and age. Fed a vision of what their whole lives “should be”, students who enter a residential four-year college are already imbued with a nostalgia for what is yet to come, hailed, in Althusser’s (2006[1977]) sense, as university subjects even before their first class. The upheaval of that subjecthood during the pandemic has raised important questions about the purpose of the college experience as well as how to belong to a place that is no longer there.

scholarly journals Covid-19 and food security: Jeopardy management and posterity deliberations

2021 ◽  
Vol 10 (2) ◽  
pp. 01-05
Author(s):  
Augustine Owusu-Addo ◽  
Atianashie Miracle A ◽  
Chukwuma Chinaza Adaobi ◽  
Larissa Agbemelo-Tsomafo
Keyword(s):  
Food Processing ◽  
Respiratory Illness ◽  
The United States ◽  
The Novel ◽  
Food Handling ◽  
Global Pandemic ◽  
Food Borne ◽  
Novel Coronavirus ◽  
Food Borne Infections ◽  
Safety Guidelines

COVID-19, also known as the ‘novel coronavirus disease 2019’, is a respiratory illness and the causative pathogen is officially named as ‘SARS-CoV-2’. Infections with SARS-CoV-2 have now been amplified to a global pandemic – as of April 3, 2020, nearly 1,018,000 cases have been confirmed in more than 195 countries, including more than 300,000 cases within the United States. Public safety guidelines are followed worldwide to stop the spread of COVID-19 and stay healthy. Despite COVID-19 is a respiratory illness with mode of invasion through the respiratory tract, not the gastrointestinal tract, an average food consumer is anxious and concerned about the food safety. Could an individual catch the deadly contagious COVID-19 from groceries brought home from the supermarket – or from the next restaurant takeout order? This brief review elucidates the epidemiology and pathobiological mechanism(s) of SARS-CoV-2 and its implications in food-borne infections, transmission via food surfaces, food processing and food handling.

Curating the Evidence About COVID-19 for Frontline Public Health and Clinical Care: The Novel Coronavirus Research Compendium

2021 ◽  
pp. 003335492110587
Author(s):  
Andrew D. Redd ◽  
Lauren S. Peetluk ◽  
Brooke A. Jarrett ◽  
Colleen Hanrahan ◽  
Sheree Schwartz ◽  
...  
Keyword(s):  
Public Health ◽  
Clinical Care ◽  
The United States ◽  
The Novel ◽  
Health Crisis ◽  
The Public ◽  
Successful Model ◽  
Medical Response ◽  
Public Consumption ◽  
Novel Coronavirus

The public health crisis created by the COVID-19 pandemic has spurred a deluge of scientific research aimed at informing the public health and medical response to the pandemic. However, early in the pandemic, those working in frontline public health and clinical care had insufficient time to parse the rapidly evolving evidence and use it for decision-making. Academics in public health and medicine were well-placed to translate the evidence for use by frontline clinicians and public health practitioners. The Novel Coronavirus Research Compendium (NCRC), a group of >60 faculty and trainees across the United States, formed in March 2020 with the goal to quickly triage and review the large volume of preprints and peer-reviewed publications on SARS-CoV-2 and COVID-19 and summarize the most important, novel evidence to inform pandemic response. From April 6 through December 31, 2020, NCRC teams screened 54 192 peer-reviewed articles and preprints, of which 527 were selected for review and uploaded to the NCRC website for public consumption. Most articles were peer-reviewed publications (n = 395, 75.0%), published in 102 journals; 25.1% (n = 132) of articles reviewed were preprints. The NCRC is a successful model of how academics translate scientific knowledge for practitioners and help build capacity for this work among students. This approach could be used for health problems beyond COVID-19, but the effort is resource intensive and may not be sustainable in the long term.

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