Panic buying is an emerging phenomenon observed during, but not restricted to, pandemic.We aimed to evaluate the nature, extent, and impact of panic buying as reported in the media.This study was conducted by collecting the information from the English media reports published till 22nd May 2020. A structured format was developed to collect data. Searching was done by using the keyword "panic buying". We have excluded the social media posts discussing the panic buying.The majority of media reporting was from the USA (40.7 %), and about 46 % of reports highlighted the scarce item. Approximately 82 % of the reports presented the causes of panic buying whereas almost 80 % report covered the impact of it. About 25.7 % of reports highlighted the rumor about panic buying and only 9.3 % of reports blamed the government. Only 27.1 % reports described the remedial measures, 30.8 % reports conferred the news on the psychology behind panic buying and 67.3 % news displayed the images of empty shelves.A high proportion of reports on panic buying have been found from the developed countries discussing the causes & impact of panic buying on the basis of expert opinion.© 2020 Elsevier GmbH. All rights reserved.

There has been significant recent interest in Agent Based Modeling in many social sciences including economics, sociology, anthropology, political science, and game theory. This article describes three problems that need to be addressed in order for such models to become effective tools for formulating new social theory and informing policy debates and suggests approaches to meeting them. These issues are computational epistemology, research methodology, and software technology. These innovations augment Agent Based Modeling to create an effective new tool base to help better understand complex social systems.

Government communication is an important management tool during a public health crisis, but understanding its impact is difficult. Strategies may be adjusted in reaction to developments on the ground and it is challenging to evaluate the impact of communication separately from other crisis management activities. Agent-based modeling is a well-established research tool in social science to respond to similar challenges. However, there have been few such models in public health. We use the example of the TELL ME agent-based model to consider ways in which a non-predictive policy model can assist policy makers. This model concerns individuals' protective behaviors in response to an epidemic, and the communication that influences such behavior. Drawing on findings from stakeholder workshops and the results of the model itself, we suggest such a model can be useful: (i) as a teaching tool, (ii) to test theory, and (iii) to inform data collection. We also plot a path for development of similar models that could assist with communication planning for epidemics.

The present research examined the relationship between political ideology and perceptions of the threat of COVID-19. Due to Republican leadership’s initial downplaying of COVID-19 and the resulting partisan media coverage, we predicted that conservatives would perceive it as less threatening. Two preregistered online studies supported this prediction. Conservatism was associated with perceiving less personal vulnerability to the virus and the virus’s severity as lower, and stronger endorsement of the beliefs that the media had exaggerated the virus’s impact and that the spread of the virus was a conspiracy. Conservatism also predicted less accurate discernment between real and fake COVID-19 headlines and fewer accurate responses to COVID-19 knowledge questions. Path analyses suggested that presidential approval, knowledge about COVID-19, and news discernment mediated the relationship between ideology and perceived vulnerability. These results suggest that the relationship between political ideology and threat perceptions may depend on issue framing by political leadership and media.

The authors of this paper advocate for the expanded use of mathematical models in epidemiology and provide an overview of the principles of mathematical modeling. Mathematical models can be used throughout the epidemiological research process. Initially they may help to refine study questions by visually expressing complex systems, directing literature searches, and identifying sensitive variables. In the study design phase, models can be used to test sampling strategies, to estimate sample size and power, and to predict outcomes for studies impractical due to time or ethical considerations. Once data are collected, models can assist in the interpretation of results, the exploration of causal pathways, and the combined analysis of data from multiple sources. Finally, models are commonly used in the process of applying research findings to public health practice by estimating population risk, predicting the effects of interventions, and contributing to the evaluation of ongoing programs. Mathematical modeling has the potential to make significant contributions to the field of epidemiology by enhancing the research process, serving as a tool for communicating findings to policymakers, and fostering interdisciplinary collaboration.

Conspiracies about vaccination are prevalent. We assessed how the health information sources people rely upon and their political ideologies are associated with acceptance of vaccine conspiracies.Online survey (N = 599) on Amazon's Mechanical Turk crowdsource platform. Hypotheses were tested via structural equation modeling.Acceptance of vaccine conspiracy beliefs was associated positively with greater reliance on social media for health information (coef. = 0.42, p < .001), inversely related to use of medical websites (coef. = -0.21, p < .001), and not significantly related to use of providers for health information (coef. = -0.13, p = .061). In addition, liberal political orientation was negatively associated with acceptance of vaccine conspiracies (coef. = -0.29, p < .001).An understanding of vaccine conspiracy acceptance requires a consideration of people's health information sources. The greater susceptibility of political conservatives to conspiracy beliefs extends to the topic of vaccination.Copyright © 2019 Elsevier Ltd. All rights reserved.

Population distributions of health emerge from the complex interplay of health-related factors at multiple levels, from the biological to the societal level. Individuals are aggregated within social networks, affected by their locations, and influenced differently across time. From aggregations of individuals, group properties can emerge, including some exposures that are ubiquitous within populations but variant across populations. By combining a focus on social determinants of health with a conceptual framework for understanding how genetics, biology, behavior, psychology, society, and environment interact, a systems science approach can inform our understanding of the underlying causes of the unequal distribution of health across generations and populations, and can help us identify promising approaches to reduce such inequalities. In this paper, we discuss how systems science approaches have already made several substantive and methodological contributions to the study of population health from a social epidemiology perspective.

The 2019 novel coronavirus (COVID-2019) has led to a serious outbreak of often severe respiratory disease, which originated in China and has quickly become a global pandemic, with far-reaching consequences that are unprecedented in the modern era. As public health officials seek to contain the virus and mitigate the deleterious effects on worldwide population health, a related threat has emerged: global media exposure to the crisis. We review research suggesting that repeated media exposure to community crisis can lead to increased anxiety, heightened stress responses that can lead to downstream effects on health, and misplaced health-protective and help-seeking behaviors that can overburden health care facilities and tax available resources. We draw from work on previous public health crises (i.e., Ebola and H1N1 outbreaks) and other collective trauma (e.g., terrorist attacks) where media coverage of events had unintended consequences for those at relatively low risk for direct exposure, leading to potentially severe public health repercussions. We conclude with recommendations for individuals, researchers, and public health officials with respect to receiving and providing effective communications during a public health crisis. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Parents' reluctance to vaccinate their children undermines the effectiveness of vaccination programmes in Western Europe. There is anecdotal evidence suggesting a connection between the rise of political populism and vaccine hesitancy.This paper analyses national-level data to examine the link between political populism and vaccine hesitancy in Western Europe. Political populism is operationalised as the percentage of people in a country who voted for populist parties in the 2014 European Parliament elections. Vaccine hesitancy is operationalised as the percentage of people in a country who believe that vaccines are not important, safe and effective according to data from the Vaccine Confidence Project (2015).There is a highly significant positive association between the percentage of people in a country who voted for populist parties and who believe that vaccines are not important (R = 0.7923, P = 0.007) and effective (R = 0.7222, P = 0.0035). The percentage of people who think vaccines are unsafe just misses being significant at the 5% level (R = 0.5027, P = 0.0669).Vaccine hesitancy and political populism are driven by similar dynamics: a profound distrust in elites and experts. It is necessary for public health scholars and actors to work to build trust with parents that are reluctant to vaccinate their children, but there are limits to this strategy. The more general popular distrust of elites and experts which informs vaccine hesitancy will be difficult to resolve unless its underlying causes-the political disenfranchisement and economic marginalisation of large parts of the Western European population-are also addressed.© The Author(s) 2019. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

Vaccine hesitancy is currently recognized by the WHO as a major threat to global health. Recently, especially during the COVID-19 pandemic, there has been a growing interest in the role of social media in the propagation of false information and fringe narratives regarding vaccination. Using a sample of approximately 60 billion tweets, we conduct a large-scale analysis of the vaccine discourse on Twitter. We use methods from deep learning and transfer learning to estimate the vaccine sentiments expressed in tweets, then categorize individual-level user attitude towards vaccines. Drawing on an interaction graph representing mutual interactions between users, we analyze the interplay between vaccine stances, interaction network, and the information sources shared by users in vaccine-related contexts. We find that strongly anti-vaccine users frequently share content from sources of a commercial nature; typically sources which sell alternative health products for profit. An interesting aspect of this finding is that concerns regarding commercial conflicts of interests are often cited as one of the major factors in vaccine hesitancy. Further, we show that the debate is highly polarized, in the sense that users with similar stances on vaccination interact preferentially with one another. Extending this insight, we provide evidence of an epistemic echo chamber effect, where users are exposed to highly dissimilar sources of vaccine information, depending the vaccination stance of their contacts. Our findings highlight the importance of understanding and addressing vaccine mis- and dis-information in the context in which they are disseminated in social networks.

The COVID-19 pandemic, with its attendant supply chain disruptions and restrictions on internal movement, has been associated with frequent episodes of panic buying both in its initial phase and in subsequent waves. Empirical evidence suggests that news media content and consumption are important determinants of attitudes and behavior during the pandemic, and existing research both before and during the pandemic suggests that panic buying can be influenced by both exposure to media reports and their specific content. This pilot study was conducted to assess the quality of media reports of panic buying during the second year of the COVID-19 pandemic, using two independent measures of news article quality. Seventy news reports of panic buying across 12 countries, covering the “second wave” of the pandemic from January 1 to December 31, 2021, were collected through an online search of media outlets using the Google News aggregator. These reports were analyzed in terms of the content of their reporting, based on existing research of the factors driving panic buying during the COVID-19 pandemic. Each report was scored for quality using two different systems: one based on an existing WHO guideline, and one based on the work of a research group which has published extensive work related to panic buying during this pandemic. It was observed that a significant number of reports contained elements that were likely to amplify, rather than attenuate, panic buying behavior, and that the quality of news reports was generally poor regardless of pandemic severity, cultural values, or freedom of the press. On the basis of this evidence, suggestions are offered to improve the media reporting of panic buying and minimize the risk of fear contagion and imitation.

The novel coronavirus pandemic continues to ravage communities across the United States. Opinion surveys identified the importance of political ideology in shaping perceptions of the pandemic and compliance with preventive measures.

Agent-based modeling is a computational approach in which agents with a specified set of characteristics interact with each other and with their environment according to predefined rules. We review key areas in public health where agent-based modeling has been adopted, including both communicable and noncommunicable disease, health behaviors, and social epidemiology. We also describe the main strengths and limitations of this approach for questions with public health relevance. Finally, we describe both methodologic and substantive future directions that we believe will enhance the value of agent-based modeling for public health. In particular, advances in model validation, comparisons with other causal modeling procedures, and the expansion of the models to consider comorbidity and joint influences more systematically will improve the utility of this approach to inform public health research, practice, and policy.

This study aims to document the impact of the COVID-19 pandemic on mental health.We compared a nationally representative online sample of 2,032 U.S. adults in late April 2020 to 19,330 U.S. adult internet users who participated in the 2018 National Health Interview Survey (NHIS) using the Kessler-6 scale of mental distress in the last 30 days.Compared to the 2018 NHIS sample, U.S. adults in April 2020 were eight times more likely to fit criteria for serious mental distress (27.7% vs. 3.4%) and three times more likely to fit criteria for moderate or serious mental distress (70.4% vs. 22.0%). Differences between the 2018 and 2020 samples appeared across all demographic groups, with larger differences among younger adults and those with children in the household.These considerable levels of mental distress may portend substantial increases in diagnosed mental disorders and in their associated morbidity and mortality.© 2020 Wiley Periodicals LLC.

Attributed to the recent COVID-19 pandemic, panic buying is now a frequent occurrence in many countries, leading to stockouts and supply chain disruptions. Consequently, it has received much attention from academics and the retail industry. The aim of this study is to review, identify, and synthesise the psychological causes of panic buying, which is a relatively new and unexplored area in consumer behaviour research. A systematic review of the related literature is conducted. The review suggests that panic buying is influenced by (1) individuals’ perception of the threat of the health crisis and scarcity of products; (2) fear of the unknown, which is caused by negative emotions and uncertainty; (3) coping behaviour, which views panic buying as a venue to relieve anxiety and regain control over the crisis; and (4) social psychological factors, which account for the influence of the social network of an individual. This study contributes to the literature by consolidating the scarce and scattered research on the causes of panic buying, drawing greater theoretical insights into each cause and also offers some implications for health professionals, policy makers, and retailers on implementing appropriate policies and strategies to manage panic buying. Recommendations for future research are also provided.