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Prior to the mandate young adults wore masks 42.7% (n = 565) of the time and elderly adults wore masks 81.4% (n = 129) of the time. Also, 56.7% (n = 979) of females and 48.2% (n = 678) of males wore masks. Whereas almost all the observed participants (95.9%, n = 73) who appeared of Asian descent wore masks, individuals perceived as White were far less likely to wear masks with only 47.2% (n = 1,089) wearing masks, and 62.6% (n = 401) of perceived Black individuals wearing masks. After the mask mandate was issued 91.7% (n = 109) of those observed were wearing masks. Mask wearing declined shortly after the CDC guidelines changed to indicate that fully vaccinated people did not need to wear masks indoors.

Understanding demographic differences in mask wearing and responses to policy changes are important for public policy and public health.

This chapter is one of a few that include observational data of actual mask wearing during the COVID-19 pandemic of 2020–2021.

The COVID-19 epidemic is still spreading globally and will not be completely over in a short time. Wearing a mask is an effective means to combat the spread of COVID-19. However, whether the public wear a mask for epidemic prevention and control will be affected by stochastic factors such as vaccination, cultural differences and irrational emotions, which bring a high degree of uncertainty to the prevention and control of the epidemic. The purpose of this study is to explore and analyze the epidemic prevention and control strategies of the public in an uncertain environment.

Based on the stochastic evolutionary game model of the Moran process, the study discusses the epidemic prevention and control strategies of the public under the conditions of the dominance of stochastic factors, expected benefits and super-expected benefits.

The research shows that the strategic evolution of the public mainly depends on stochastic factors, cost-benefit and the number of the public. When the stochastic factors are dominant, the greater the perceived benefit, the lower the cost and the greater the penalty for not wearing masks, the public will choose to wear a mask. Under the dominance of expected benefits and super-expected benefits, when the number of the public is greater than a certain threshold, the mask-wearing strategy will become an evolutionary stable strategy. From the evolutionary process, the government’s punishment measures will slow down the speed of the public choosing the strategy of not wearing masks. The speed of the public evolving to the stable strategy under the dominance of super-expected benefits is faster than that under the dominance of expected benefits.

The study considers the impact of stochastic factors on public prevention and control strategies and provides decision-making support and theoretical guidance for the scientific prevention of the normalized public.

To the best of the authors’ knowledge, no research has considered the impact of different stochastic interference intensities on public prevention and control strategies. Therefore, this paper can be seen as a valuable resource in this field.

The purpose of this paper is to intelligibly demonstrate the effectiveness of face mask wearing as a means to prevent COVID-19 transmission. Through understanding the benefits of wearing masks, it is hoped to facilitate the change of societal behavior and more people are willing to wear face mask.

The paper investigates the 50 states in the United States of America (U.S.) and Washington, D.C. that implemented the mask mandates before September 30, 2020, which are divided into four groups: (1) those implemented the statewide mask mandates before June 5, 2020 when World Health Organization (WHO) recommended mask wearing; (2) those implemented statewide mask mandates after June 5, 2020; (3) those implemented partial mandates affecting 30 percent or more of the state’s population; and (4) those implemented partial mandates affecting less than 30 percent. Simple descriptive statistics are analyzed.

For the 50 U.S. states and Washington, D.C., the higher the mask wearing rate, the lower the number of COVID-19 cases (correlation coefficient: −0.69 (p<0.001)). For the 23 states with mobility reduction of less than 15 percent, the higher the proportion of population required to wear masks, the lower the number of cases. This can be seen from the difference in the number of cases among the four groups by ANOVA (p = 0.013).

The positive effect of wearing masks is shown based on simple descriptive statistics for intuitive and intelligible understanding, which may lead people to comprehend the importance of wearing masks, and break through their custom, culture, and norms, and wear masks.

Face masks have been integrated into daily life and come to signify different meanings due to the fight against the COVID-19 pandemic. Drawing on social perception and attribution theories, this paper investigates the possible additional benefits of face mask use in the service marketplace by understanding how consumers react to the new social norm.

Four experimental studies were run across different service contexts. Study 1 examines consumers’ evaluation of a service promotion when an employee wears a face mask; Study 2 focuses on the impact of face mask usage on salesperson credibility and service satisfaction; Studies 3 and 4 investigate the consequences of not using face masks on consumers’ intention to spread positive word-of-mouth for the service provider.

The results revealed that the presence of a face mask in a service promotion determined a higher level of service liking, while in a service encounter, it led to a higher level of salesperson credibility, which then positively affected consumer satisfaction. Finally, the non-utilization of a face mask negatively affected consumer intention to spread positive word-of-mouth about the service provider, even when the social norm is to not wear one.

The manuscript adds to research on salespeople appearance and tries to understand consumers’ reactions toward face mask use in the services sector, as, to the best of the authors’ knowledge, few empirical studies in the service marketing literature have investigated the topic so far. Findings also provide useful insights that can further promote companies’ adoption of face masks beyond the COVID-19 emergency.

The purpose of this article was to investigate the relationship between symptoms related to air pollution, mask-wearing, mask choices and related factors.

A cross-sectional study among outpatient department (OPD) pollution clinic patients at Nopparat Rajathanee Hospital (PCNRH) during 2019 in Bangkok, Thailand.

The most common symptom after exposure to air pollution that affects treatment in the OPD is respiratory symptoms. A total of 45.7% (107/234) of the population wears a mask, 55.1% (59/107) of the population that wears a mask wears a surgical mask, and only 10.3% (11/107) of them wear an N95 mask. Mask-wearing and air quality index (AQI) onset were associated with the respiratory symptoms group, whereas wearing an N95 mask or surgical mask was found to be a protective factor for the occurrence of respiratory symptoms (adjusted OR = 0.065, 95% CI: 0.014–0.306, p = 0.001 and adjusted OR = 0.154, 95% CI: 0.058–0.404, p < 0.001, respectively). Therefore, the best practice in the face of air pollution, while the resolution needs a long period, is to wear a mask. In this study, the results showed that the best type of mask to prevent respiratory symptoms from air pollution is the N95, followed by the surgical mask; cloth masks are not recommended to use to protect against respiratory symptoms from air pollution.

Wearing an N95 and a surgical mask can help reduce respiratory symptoms. Hence, in addition to establishing hospital measures, cooperation from local and government agencies is necessary to effectively and jointly build a national health public policy framework.

1. This study provides evidence of a correlation between symptoms associated with air pollution and related factors, in-hospital visits in Bangkok, Thailand. 2. In this study, wearing an N95 mask and a surgical mask were found to be a protective factor for the occurrence of respiratory symptoms.

The novel coronavirus (COVID-19) has completely changed the landscape of the hospitality industry. The World Health Organization does not officially recommend wearing face masks in the workplace. Wearing face masks is controversial worldwide, however it has been widely adopted in Hong Kong society. Hospitality practitioners have worn face masks to work and serve customers for almost a year long, matching the duration of the COVID-19 pandemic. This paper proposes a conceptual model of face mask effects and also discusses and evaluates the effects of wearing face masks during the pandemic.

A convenience sampling method is employed to investigate hospitality operators using in-depth and focus group interviews with managers, front-line staff and customers.

The perspectives of both hospitality practitioners and customers are included in this study. The concepts of (1) invisible care, (2) sense of safety and (3) service trust have been introduced in this study. These provide valuable insights for the service industry when facing a large-scale health crisis, now and in the future.

This paper analyzes interview data collected from 35 respondents – 14 managers, 6 practitioners and 15 customers – in order to understand the critical effects of wearing face masks during the pandemic and the perspectives of both hospitality practitioners and customers.

For the hospitality industry, wearing face mask in service has already become a “new normal”, face mask effects might create an impact on service design, service delivery and service quality.

The findings show that wearing face masks turns hygiene and safety into a form of invisible care in the Asian hospitality industry. Practitioners' perspective regarding the necessity of a smile is less important to Asian customers, showing a discrepancy between the two parties. Customers do not believe that service quality has dropped due to the wearing of masks, but that the level of hygiene has risen. Unlike customers, practitioners are more concerned about not providing good quality service. However, the interview data show that respondents generally agree that mask wearing is a gesture and symbol for the hospitality industry to make tangible a new form of caring, professionalism, safety concern and communication.

This paper proposes a solution for recognizing human faces under mask-wearing. The lower part of human face is occluded and could not be used in the learning process of face recognition. So, the proposed solution is developed to recognize human faces on any available facial components which could be varied depending on wearing or not wearing a mask.

The proposed solution is developed based on the FaceNet framework, aiming to modify the existing facial recognition model to improve the performance of both scenarios of mask-wearing and without mask-wearing. Then, simulated masked-face images are computed on top of the original face images, to be used in the learning process of face recognition. In addition, feature heatmaps are also drawn out to visualize majority of parts of facial images that are significant in recognizing faces under mask-wearing.

The proposed method is validated using several scenarios of experiments. The result shows an outstanding accuracy of 99.2% on a scenario of mask-wearing faces. The feature heatmaps also show that non-occluded components including eyes and nose become more significant for recognizing human faces, when compared with the lower part of human faces which could be occluded under masks.

The convolutional neural network based solution is tuned up for recognizing human faces under a scenario of mask-wearing. The simulated masks on original face images are augmented for training the face recognition model. The heatmaps are then computed to prove that features generated from the top half of face images are correctly chosen for the face recognition.

This paper asks how values and beliefs around gender influence social norms regarding masking. Specifically, the paper explores how the gendered meme “Karen” fits into social media discussions on support for and opposition to the wearing of masks to fight the spread of COVID-19.

The authors analyze tweets containing the hashtags #Masks4All and #NoMasks over a three-week period, using adjacent hashtag analysis to determine the terms most associated with Karen in the pro and anti-mask communities associated with these hashtags.

Anti-maskers reference Karen more often than pro-maskers, although she is presented in negative terms with gendered overtones by those on both sides of the masking debate.

The paper highlights how hypermasculinity rhetoric impedes social change that normalizes mask wearing.

The COVID-19 pandemic placed many challenges on policing, from limiting officers' ability to interact with citizens to enforcing regulations to prevent the spread of the virus. One of those regulations, and the focus of the current study, is mask mandates.

Using a sample of over 550 US adults recruited on Amazon MTurk, the current study examines factors that may influence citizen attitudes toward the police's role in mask enforcement, with a specific focus on perceptions of the police, political leanings, and views about COVID-19 and mask-wearing.

The authors find that when respondents believed COVID-19 was serious and a major public health threat, they were more likely to believe the police should enforce masks, regardless of attitudes about the police, political party affiliation or other demographics.

The enforcement of public health mandates, such as mask wearing, often result in arguments related to the infringement of rights and questions about the overall legality of enforcement. This often puts law enforcement in a difficult position regarding how such mandates should be enforced and whether it is the responsibility of the police. Additional policy implications are discussed.

This study aims to compare the effect of barista type (human vs robot) on perceived safety and examine the role of two moderators (mask-wearing and coronavirus vaccination) on the effects of barista type on perceived safety and visit intention.

The research design consists of three studies. Three experiments were sequentially designed and conducted to address research questions.

Study 1 found that perceived safety mediates the effect of barista type on customers’ visit intention. Study 2 revealed that the mask-wearing of human and robot baristas differently influences perceived safety. Study 3 showed that customers, especially where robot baristas are used, perceive the effect of mask-wearing differently depending on their coronavirus vaccination status.

Given that the levels of restrictions vary worldwide, together with the extent of countries’ vaccination rollouts, caution is required when generalising the research findings.

The findings have practical implications for the hospitality industry, where the roles of face masks and coronavirus vaccines in shaping consumer psychology and behaviour have been underexplored.

Coronavirus vaccination is considered one of the most important driving forces for the recovery of hospitality businesses. As a heuristic-systematic model postulated, this study identified that vaccination status (fully vaccinated vs not vaccinated) changes the level of involvement when customers assess the level of risk in service environments. By pinpointing the function of service robots in safeguarding customers from the potential spread of the disease, this study broadens the scope of human–robot interaction research in hospitality.