Epidemiology, clinical characteristics of the first cases of COVID‐19

Liu, Jialin; Liu, Siru; Wei, Hailong; Yang, Xi

doi:10.1111/eci.13364

Cited by 10 publications

(8 citation statements)

References 28 publications

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“…In other words, nearly 22% of COVID-19 deaths worldwide were in the USA. As a result, it’s only natural that COVID-19’s spread has had a significant influence on the US economy (Liu et al 2020 ).…”

Section: Introductionmentioning

confidence: 99%

RETRACTED ARTICLE: COVID-19 and stock exchange return variation: empirical evidences from econometric estimation

Latif

Bashir

et al. 2021

Environ Sci Pollut Res

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This research looked at the effects of COVID-19 on a number of the world’s most important stock exchanges, as well as the empirical relation between the COVID-19 wave and stock market volatility. In order to plan proper portfolio diversification in international financial markets, researchers must examine COVID-19 anxiety in relation to stock market volatility. The stock market volatility connected with the COVID-19 pandemic was measured using AR(1)-GARCH(1,1). COVID-19 fear, according to our research, is the ultimate driver of public attention and stock market volatility. The findings show that throughout the pandemic, stock market performance and GDP growth both declined significantly due to average increases. Furthermore, a 1% increase in COVID-19 causes a 0.8% and 0.56% decline in stock return and GDP, respectively. The stock market, on the other hand, showed a slight movement in GDP growth. Furthermore, the COVID-19 pandemic reported cases index, death index, and global panic index all influenced public perceptions of purchasing and selling. As a result, rather than investing in stocks, it is recommended that you invest in gold. The research also makes policy recommendations for important stakeholders. We look to examine how stock returns respond dynamically to unanticipated changes in the COVID-19 scenarios, as well as the uncertainty that comes with a pandemic. Using daily data from Canada and the USA, we conclude that a spike in COVID-19 instances has a negative impact on the stock market in general. Furthermore, in both the increase and decline scenarios in Canada, the stock return reactions are asymmetric. The disparity is due to the unfavorable impact of the pandemic’s unpredictability. We also discovered that uncertainty had a negative impact on the US stock market. The magnitude, however, is insignificant.

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Section: Introductionmentioning

confidence: 99%

RETRACTED ARTICLE: COVID-19 and stock exchange return variation: empirical evidences from econometric estimation

Latif

Bashir

et al. 2021

Environ Sci Pollut Res

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“…The outbreak of COVID-19 has become one of the most urgent issues in public health recently [9] In the past few months, with the successful development of the COVID-19 vaccine, many countries have started vaccination rollout [10] , [11] , [12] . At this point, the focus of research should also shift to the rapid and effective rollout of the vaccine [13] .…”

Section: Introductionmentioning

confidence: 99%

Public attitudes toward COVID-19 vaccines on English-language Twitter: A sentiment analysis

Liu

2021

Vaccine

Self Cite

111

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Objective To identify themes and temporal trends in the sentiment of COVID-19 vaccine-related tweets and to explore variations in sentiment at world national and United States state levels. Methods We collected English-language tweets related to COVID-19 vaccines posted between November 1, 2020, and January 31, 2021. We applied the Valence Aware Dictionary and sEntiment Reasoner tool to calculate the compound score to determine whether the sentiment mentioned in each tweet was positive (compound ≥ 0.05), neutral (-0.05 < compound < 0.05), or negative (compound ≤ -0.05). We applied the latent Dirichlet allocation analysis to extract main topics for tweets with positive and negative sentiment. Then we performed a temporal analysis to identify time trends and a geographic analysis to explore sentiment differences in tweets posted in different locations. Results Out of a total of 2,678,372 COVID-19 vaccine-related tweets, tweets with positive, neutral, and negative sentiments were 42.8%, 26.9%, and 30.3%, respectively. We identified five themes for positive sentiment tweets (trial results, administration, life, information, and efficacy) and five themes for negative sentiment tweets (trial results, conspiracy, trust, effectiveness, and administration). On November 9, 2020, the sentiment score increased significantly (score = 0.234, p = 0.001), then slowly decreased to a neutral sentiment in late December and was maintained until the end of January. At the country level, tweets posted in Brazil had the lowest sentiment score of −0.002, while tweets posted in the United Arab Emirates had the highest sentiment score of 0.162. The overall average sentiment score for the United States was 0.089, with Washington, DC having the highest sentiment score of 0.144 and Wyoming having the lowest sentiment score of 0.036. Conclusions Public sentiment on COVID-19 vaccines varied significantly over time and geography. Sentiment analysis can provide timely insights into public sentiment toward the COVID-19 vaccine and guide public health policymakers in designing locally tailored vaccine education programs.

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“…The global COVID-19 pandemic is affecting 219 countries worldwide [ 1 ]. An important component of managing COVID-19 is preventing the infection [ 2 , 3 ]. Fortunately, development of vaccines against the disease is progressing well.…”

Section: Introductionmentioning

confidence: 99%

Understanding Behavioral Intentions Toward COVID-19 Vaccines: Theory-Based Content Analysis of Tweets

Liu¹,

Liu²

2021

J Med Internet Res

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Background Acceptance rates of COVID-19 vaccines have still not reached the required threshold to achieve herd immunity. Understanding why some people are willing to be vaccinated and others are not is a critical step to develop efficient implementation strategies to promote COVID-19 vaccines. Objective We conducted a theory-based content analysis based on the capability, opportunity, motivation–behavior (COM-B) model to characterize the factors influencing behavioral intentions toward COVID-19 vaccines mentioned on the Twitter platform. Methods We collected tweets posted in English from November 1-22, 2020, using a combination of relevant keywords and hashtags. After excluding retweets, we randomly selected 5000 tweets for manual coding and content analysis. We performed a content analysis informed by the adapted COM-B model. Results Of the 5000 COVID-19 vaccine–related tweets that were coded, 4796 (95.9%) were posted by unique users. A total of 97 tweets carried positive behavioral intent, while 182 tweets contained negative behavioral intent. Of these, 28 tweets were mapped to capability factors, 155 tweets were related to motivation, 23 tweets were related to opportunities, and 74 tweets did not contain any useful information about the reasons for their behavioral intentions (κ=0.73). Some tweets mentioned two or more constructs at the same time. Tweets that were mapped to capability (P<.001), motivation (P<.001), and opportunity (P=.03) factors were more likely to indicate negative behavioral intentions. Conclusions Most behavioral intentions regarding COVID-19 vaccines were related to the motivation construct. The themes identified in this study could be used to inform theory-based and evidence-based interventions to improve acceptance of COVID-19 vaccines.

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Epidemiology, clinical characteristics of the first cases of COVID‐19

Cited by 10 publications

References 28 publications

RETRACTED ARTICLE: COVID-19 and stock exchange return variation: empirical evidences from econometric estimation

RETRACTED ARTICLE: COVID-19 and stock exchange return variation: empirical evidences from econometric estimation

Public attitudes toward COVID-19 vaccines on English-language Twitter: A sentiment analysis

Understanding Behavioral Intentions Toward COVID-19 Vaccines: Theory-Based Content Analysis of Tweets

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