key: cord-0886957-x8qsvufz authors: Managi, Shunsuke; Chen, Zhuo title: Social-economic impacts of epidemic diseases date: 2021-10-29 journal: Technol Forecast Soc Change DOI: 10.1016/j.techfore.2021.121316 sha: 7b12550d6b67575ed5db8a02fdfd80c635593997 doc_id: 886957 cord_uid: x8qsvufz nan Social-economic impacts of epidemic diseases COVID-19 has impacted our world in all aspects of economic, social, technological, environmental, and international relations. On the economic side, according to the World Bank's Global Economic Prospects, the growth rate of global GDP in 2020 was − 3.5% (World Bank, 2021) . On the policy side, new policies such as social distancing policy and (legally binding/non-legally binding) emergency declarations are being implemented simultaneously worldwide. Katafuchi et al. (2021) empirically show that the declaration of a state of emergency in Japan has a self-restraint effect after controlling for infection risk and weather conditions using mobility data. This special issue collects studies on the socioeconomic impact of the spread of infectious diseases such as new coronaviruses. Table 1 shows the summary of the articles included in this special issue. We have published excellent studies presented as follows: The COVID-19 pandemic has increased the focus on automation and robotization. Caselli et al. (2021) investigated the inter-industry relationship between the adoption of robots and the risk of contracting COVID-19 in the workplace in Italy. The analysis results provided empirical support for the hypothesis that robots can reduce the risk of transmission among workers by reducing the need for physical interaction. While this research acknowledged the importance of robots in the fight against COVID-19 and their potential role in increasing the resilience of the economic system against future pandemics, it also highlighted a series of potential trade-offs between workplace safety and employment conditions that could arise (especially in the short term) from a significant increase in robot adoption. A series of potential trade-offs were also thoroughly discussed. Shareef et al. (2021) identified the reasons why the lock-down failed to fulfill its original goals and formulate a comprehensive behavioral model that reflects comprehensive human behavior and social psychology. They conducted extensive interviews with individuals who were subjected to the lock-down system to answer the research questions. The results showed that four parameters (Derogation and Argument; SDA, Tangible Need and Deficiency; TND, Intangible Desire and Expectancy; IDE, Evaluation of Benefit and Loss; UBL) are key to understanding the behavior and social psychology of people who violate the lock-down. It has been argued that it is essential to flat the infection curve. Debecker and Modis (2021) analyzed the spread of the virus by fitting an S-shaped logistic curve to the 25 most-affected countries at the time of analysis (mid-May 2020). Interpreting the results of this analysis in terms of the speed with which governments intervened, the efficiency of the actions taken, and the number of days the curve lagged, suggests that early and decisive action, such as a country-wide lock-down, is the optimal strategy among the countries studied. COVID-19 also had a significant impact on natural resources such as oil. Güngör et al. (2021) investigated the impact of the COVID-19 outbreak on gasoline consumption in Turkey. In particular, they evaluated the predictive performance of the ARIMA model both before and after the outbreak. The results showed that even the best-fitting model forecasts failed after the COVID-19 outbreak. However, the addition of volatility improves the forecasts. Outbreaks increase consumption volatility. Their work suggested that policies that target volatility can reduce the negative impact of similar shocks on market participants, tax revenues, and vulnerable groups. The pandemic of COVID-19 continues to disrupt the global economy and capital markets. Governments worldwide are relentlessly taking health policy measures to contain the coronavirus and implementing economic relief programs to mitigate the impact on their economies. Hunjra et al. (2021) investigated the impact of COVID-19 government health measures on the volatility of capital markets in East Asia. This study used Monte Carlo simulations to assess the volatility of stock prices during the period in which the health policy measures were implemented. The results showed that distinct health policy measures impacted investor behavior and induced volatility in the stock market. The results of this study induce significant insights that will be useful when considering COVID-19 health policy measures to mitigate the influence on the stock market. COVID-19 also had a significant impact on financial markets. Umar et al. (2021) seek to explore the impact of COVID-19-related media coverage on the dynamic return and volatility linkages of the three dominant cryptocurrencies (Bitcoin; BTC, Ethereum; ETH, and Ripple; XRP) and the Fiat currencies of Euro, British Pound, and Chinese Yuan. They estimated dynamic return and volatility connectivity measures using the time-varying parameter-VAR method. The connectivity analysis of returns shows that the media coverage index (only before the first wave) and cryptocurrencies are net senders of shocks, whereas fiat money is a net receiver of shocks. Similar results were obtained for volatility, except for the euro, which showed a clear net receiver profile in January and February. This fiat currency (the euro) was a net sender in March and during the first wave of the COVID-19 crisis, which probably indicates the toxicity of a pandemic on the European continent. COVID-19 has had a technological impact on the way we live and work. For example, the development of remote work has led to the spread of software for online meetings worldwide. Baudier et al. (2021) analyze the impact of COVID-19 on certain technologies and how they can improve our lives. Technologies directly related to the treatment of the virus and those that will help us adapt to life in this critical situation are presented. They also discuss the technological challenges, the logic of related innovations, and their social implications to consider how these technologies can be helpful in the future, given that such a pandemic could strike humanity again. Brem et al. (2021) analyze the impact of this global phenomenon on specific technologies and how they can improve our lives. Technologies that are directly related to the treatment of the virus and those that will help us adapt to life in this critical situation are presented. It also shows how these technologies can be useful in the future, given that such a pandemic could strike humanity again. To this end, we discuss the technological challenges, the logic of related innovations, and their social implications. The food supply chain (FSC) is one of the essential services during a pandemic. In particular, the perishable food supply chain (PFSC) is operating under a higher risk during the COVID-19 pandemic, facing increased waste and product life cycle issues in addition to logistical, operational, financial, and health risks. Kumar et al. (2021) identified and analyzed PFSC's risk mitigation strategies in the COVID-19 pandemic. First, they discussed the uncertainties and risks associated with a pandemic situation and then identified risk mitigation strategies for managing a PFSC in such a situation. They then used the Fuzzy Best Worst Method (FWM) to prioritize the strategies they identified. Top risk mitigation strategies include ``collaborative management,'' ``proactive business continuity planning,'' and ``financial sustainability.'' This study was a novel attempt to identify and analyze risk mitigation strategies to improve the socioeconomic and ecological performance of PFSCs to achieve the Sustainable Development Goal of healthy and safe food for all. Social media is playing an essential role in the pandemic of COVID-19. Based on the affordance lens and cognitive load theory, Islam et al. (2020) investigate how motivational factors and personal attributes affect social media fatigue and the sharing of unverified information during the COVID-19 pandemic. They developed the model using data collected from young adults in Bangladesh (N = 433) and analyzed it using structural equation modeling and neural network techniques. The results indicate that people with a strong desire for self-expression and entertainment and those who lack self-regulation skills are more likely to share information that has not been verified. They also found that exploration and religiosity were negatively correlated with the sharing of unverified information, and that the higher the level of exploration, the greater the fatigue caused by social media. These results suggest that differences in the purpose of social media use can cause problems, especially in increasing the sharing of misinformation. Jun et al. (2021) used big social data provided by Google RSV (Relative Search Volume) to investigate how the WHO's pandemic declaration affected public awareness and behavior. They analyzed 37 OECD countries, clustered them according to the degree of reaction to the declaration, and selected the United States, France, and Germany for comparison. The results of this study statistically confirmed the effect of the pandemic declaration on public awareness and increased the search for information on COVID-19 by more than $20 \%$. This rapid increase in RSV also reflected the interest in COVID-19 testing and induced individuals to get tested, which helped in identifying new cases. The contribution of this study is that it has provided a theoretical basis for using RSV and its implications to understand and strategize public attitudes and behaviors in situations where WHO and governments must formulate policies in response to new infectious disease outbreaks such as COVID-19. Liu et al. (2021) assessed the effect of media coverage on mitigating the spread of COVID-19 in the early stages of the epidemic in China. They constructed a province-level dataset on COVID-19 and linked it to population movement data and other control variables to estimate how media coverage moderates the spread of COVID-19. The results indicated that the effect of media coverage on the spread of COVID-19 in China has an inverse U-shaped curvature and is mediated by population movement within and between provinces. Simulation results showed that media coverage of COVID-19 in China could reduce the number of infected persons by 394,000 and close contacts by 1.4 million between January 19 and February 29, 2020. These results strongly supported the use of contact tracing to reduce the transmission of COVID-19. The measures taken by governments to minimize person-to-person contact to control the spread of COVID-19 had a severe impact on professional soccer clubs (PFCs) during the 2019/20 season. Hammerschmidt et al. (2021) is based on an exploratory multi-case study methodology of PFCs in five European soccer leagues to investigate the response of these clubs to the COVID-19 pandemic. The results revealed the importance of solidarity with specific stakeholders during a pandemic, but also revealed the vulnerability of PFCs due to their underdeveloped financial structure and management and entrepreneurial strategies to cope with the crisis. This study provided a theoretical and empirical contribution to the literature on entrepreneurial behavior and crisis management in elite sport organizations, as well as a holistic picture of high-density and solidarity stakeholder networks. Beiderbeck et al. (2021) conducted a Delphi-based scenario analysis with 110 subject matter experts who assessed 15 future projections both on a quantitative and qualitative. The results showed, for example, that a salary cap for athletes would have the most significant impact on the ecosystem, but is unlikely to be implemented, and that increased awareness of social responsibility is the most desirable impact of the crisis. In order to elaborate the results, we considered the surface and deep level characteristics of the participants, and found significant effects in both cases. They identify three distinct predictive clusters and discuss the potential threats and opportunities that COVID-19 poses to the European soccer ecosystem, contributing to the scientific debate and providing guidance to policymakers and decision-makers. We hope that various studies on the socioeconomic impact of infectious diseases on a global scale will continue to develop in the future. 2021. Patients' perceptions of teleconsultation during COVID-19: a cross-national study The impact of COVID-19 on the European football ecosystem -A Delphi-based scenario analysis Manufacturing and service supply chain resilience to the COVID-19 outbreak: lessons learned from the automobile and airline industries Implications of the coronavirus (COVID-19) outbreak for innovation: which technologies will improve our lives? Robots and risk of COVID-19 workplace contagion: evidence from Italy Poorly known aspects of flattening the curve of COVID-19 Impact of Covid-19 out-break on Turkish gasoline consumption Professional football clubs and empirical evidence from the COVID-19 crisis: time for sport entrepreneurship? Covid-19 health policy intervention and volatility of Asian capital markets Misinformation sharing and social media fatigue during COVID-19: an affordance and cognitive load perspective The impact of the pandemic declaration on public awareness and behavior: focusing on COVID-19 google searches COVID-19 with stigma: theory and evidence from mobility data Using COVID-19 mortality to select among hospital plant capacity models: an exploratory empirical application to Hubei province Mitigate risks in perishable food supply chains: learning from COVID-19 Role of media coverage in mitigating COVID-19 transmission: evidence from China Measuring the global economic impact of the coronavirus outbreak: evidence from the main cluster countries Threat or opportunity? A case study of digital-enabled redesign of entrepreneurship education in the COVID-19 emergency Lockdown and sustainability: an effective model of information and communication technology The impact of COVID-19-related media coverage on the return and volatility connectedness of cryptocurrencies and fiat currencies Global mortality benefits of COVID-19 action Effects of the COVID-19 pandemic on the US stock market and uncertainty: a comparative assessment between the first and second waves Impact of COVID-19 on the travel and tourism industry Table 1 Classification of articles in this special issue.