Face Masks as a Factor in Eventuality of Changes in Driving Safety

During the COVID-19, pandemics or worsening virus situation, taxi and regular-route bus drivers are recommended to work in medical masks. However, the quantitative and qualitative influence of wearing protective face masks on safety of driving vehicles has not been previously studied. Therefore, this became the objective of preliminary studies to determine the specifics of the influence of a face protective mask on the change in psychophysiological qualities of a car driver as a factor in safety eventuality under urban traffic conditions.The method of an open-ended survey of 108 healthy adult drivers was used to obtain a quantitative subjective assessment of the effect of face masks on changing driving safety conditions and a comfortable emotional state while driving. A qualitative analysis of assessment of the level of psychophysiological qualities of drivers wearing and not wearing a face mask was carried out using Meleti hardware-software complex.A sharp decrease in neuropsychic functions with a simultaneous increase in quality of thinking and visual analysis of the traffic situation was revealed regarding the drivers wearing a face protective mask compared to those driving without a mask while the level of psychomotor reaction remains unchanged regardless of the gender of the driver.The subjective assessment of survey participants of the effect of a face mask on professionally important, psychophysiological characteristics of drivers revealed a significant (41,7 %) or insignificant (20,4 %) decrease in reaction, while 38 % of drivers did not notice significant changes in driving because of the effect of the mask.Based on these results, it is assumed that the face mask may serve as a predictor of a road pre-accident situation.To assess the effect of the face mask on the driver, a coefficient of eventuality of reducing road safety is proposed. It is recommended to use it as an additional factor in a situational pandemic environment when developing recommendations for the use of face masks for car and bus drivers, and when analysing the causes of road accidents.

Knowledge and Awareness of Masks and N95 Respirators Used for COVID-19 Prevention Among Chemical Engineering Students at Al-Balqa Applied University, Jordan

Background and Objectives: On March 11, the World Health Organization stated coronavirus disease 2019 (COVID-19) was a global pandemic; the rapid and extended spread of the COVID-19 pandemic has become a significant cause of concern for face-to-face university study. This study investigated the knowledge and awareness of chemical engineering students in Al-Balqa Applied University (BAU) in Jordan about respiratory protective measures against COVID-19.Materials and Methods: A cross-sectional study was developed using a multi-stage random sampling technique conducted from April 21–28, 2020. The data were collected through an online questionnaire distributed to BAU's chemical engineering students, with 179 responders completed the survey correctly. The data were analyzed statistically using the SPSS program. The questionnaire consisted of two parts: the first measured the student's general knowledge about the COVID-19 pandemic, while the second focused on the respiratory protection methods against COVID-19; it was structured to assess the student's knowledge about the suitable types of masks and respirators used in COVID-19 prevention, their detailed mechanism of action and filtration process type, their production materials, and finally how the student's knowledge affects choosing a proper preventive method.Results: The study found moderate awareness among engineering students about COVID-19 causative agent, effective preventive masks/respirators used, and the mask's viral blockage mechanisms. A total of 89 respondents (49.7%) pointed to the correct best protective mask, i.e., N95 mask. On the other hand, 119 respondents (66.5%) believed that a surgical mask is the best protective mask. The study also showed differences in knowledge between different academic years; the knowledge about respirators, masks, and their action mechanism among senior students in the last three academic years was better than the younger students with a P-value of 0.047 for knowledge about respirator used for protection against coronavirus disease and the P-value of 0.028 for knowledge of the comparisons between the N95 and surgical mask. On the other hand, the study showed a lack of awareness of the most suitable mask types used in pandemics and the appropriate use method.Conclusions: The study found that chemical engineering students in Al-Balqa university were moderately knowledgeable regarding COVID-19 respiratory preventive methods; these results provided an overview of each student's community's knowledge level. Therefore, efforts are needed to improve public awareness through comprehensive educational campaigns to increase students' knowledge, attitude, and practice.

Concerns about Wearing Masks to Avoid COVID-19 Infection in China: Assessment of an Internet-based Cross-sectional Study (Preprint)

BACKGROUND The novel coronavirus disease of 2019 (COVID-19) has the potential to spread from person to person in close contact settings. The Chinese Center for Disease Control and Prevention has released a handbook on COVID-19 in the context of disseminating health information among the public, specifically related to wearing masks correctly and adopting preventive measures to avoid the COVID-19 infection. OBJECTIVE The current study aimed to assess the level of mask knowledge, behavior related to mask usage, and major information channels in China. METHODS An Internet-based survey was conducted primarily using the DingXiang Doctor WeChat public accounts, and there were 10,304 respondents to the survey. The data about mask knowledge and behavior were recollected and analyzed. RESULTS The findings revealed that 64.49% of the participants practiced protective mask behavior, 97.93% believed that wearing masks is effective against COVID-19, 96.85% chose the mask that has two of more layers of washable, breathable fabric, 70.57% wore masks correctly, and 51.62% changed masks within four hours. Gender, age, occupation, and education level had significant effects on behavior, while marital and infection status of family members were not significant. There were ten major information channels, such as WeChat public account (89.55%), news applications (55.78%), WeChat (50.12%), television/radio (45.05%), microblogs (44.24%), friends/relatives/colleagues (27.84%), websites (25.99%), SMS (17.29%), community outreach (16.58%), and newspapers (7.53%). CONCLUSIONS This study elucidated that the Chinese netizens’ protective mask behavior was far lower than mask knowledge. Improved information channels and adequate information on wearing masks are necessary to improve the public’s protective mask behavior, particularly among the males, elderly, and people with less education.

Face Mask Detection System

COVID-19 pandemic has affected the world severely, according to the World Health Organization (WHO), coronavirus disease (COVID-19) has globally infected over 176 million people causing over 3.8 million deaths. Wearing a protective mask has become a norm. However, it is seen in most public places that people do not wear masks or don’t wear them properly. In this paper, we propose a high accuracy and efficient face mask detector based on MobileNet architecture. The proposed method detects the face in real-time with OpenCV and then identifies if it has a mask on it or not. As a surveillance task, it supports motion, and is trained using transfer learning and compared in terms of both precision and efficiency, with special attention to the real-time requirements of this context.

Computational Investigation of The Exhalation Process with and Without Wearing a Protective Mask

This paper shows different simulations of airflow patterns for the human face during exhalation with and without wearing a protective mask. The nasal airways were defined based on biological anthropology and medicine instructions. A three-dimensional body-manikin of African athlete of 1.8 meters tall was employed to the expiration (exhalation) flow study using ANSYS-Fluent software. There were two different mask models included in the flow simulations and were manufactured by means of 3D-printing technology. The two manufactured masks were designed using SolidWorks software. The study was carried out four times during the exhalation process of a human wearing the two masks and without wearing them. The velocity magnitudes were significantly different while wearing the mask in comparison to the cases of not wearing it. The results demonstrate the capability of using 3D-printed masks as a replacement of the traditional medical masks (i.e., N95 and surgical masks) with retaining the same functions of the protective mask. Thus, based on the present study and due to the great shortage of surgical and medical masks availability locally and globally, the 3D-printed masks might be a temporary solution to limit the vast spread of contagious diseases like the dangerous COVID-19 outbreak.

A NOVEL METHOD FOR PROTECTIVE FACE MASK DETECTION USING CONVOLUTIONAL NEURAL NETWORKS AND IMAGE HISTOGRAMS

This paper proposes a new hybrid method for automatic detection and recognition of the presence/absence of a protective mask on human's face. It combines visual features extracted using Convolutional Neural Network (CNN) with image histograms that convey information about pixel intensity. Several pre-trained models for building feature extraction systems using a CNN and several types of image histograms are considered in this paper. We test our approach on the Medical Mask Dataset and perform cross-corpus analysis on two other databases named Masked Faces (MAFA) and Real-World Masked Face Dataset (RMFD). We demonstrate that the proposed hybrid method increases the Unweighted Average Recalls (UARs) of recognition of the presence/absence of a protective mask on human's face in comparison with traditional CNNs on the MAFA and RMFD databases by 0.96% and 1.32%, respectively. The proposed method can be generalized and used for other tasks of biometry, computer vision, machine learning and automatic face recognition.

Exploring the use of web searches for risk communication during COVID-19 in Germany

Risk communication during pandemics is an element of utmost importance. Understanding the level of public attention—a prerequisite for effective communication—implicates expensive and time-consuming surveys. We hypothesise that the relative search volume from Google Trends could be used as an indicator of public attention of a disease and its prevention measures. The search terms ‘RKI’ (Robert Koch Institute, national public health authority in Germany), ‘corona’ and ‘protective mask’ in German language were shortlisted. Cross-correlations between these terms and the reported cases from 15 February to 27 April were conducted for each German federal state. The findings were contrasted against a timeline of official communications concerning COVID-19. The highest correlations of the term ‘RKI’ with reported COVID-19 cases were found between lags of − 2 and − 12 days, meaning web searches were already performed from 2 to 12 days before case numbers increased. A similar pattern was seen for the term ‘corona’. Cross-correlations indicated that most searches on ‘protective mask’ were performed from 6 to 12 days after the peak of cases. The results for the term ‘protective mask’ indicate a degree of confusion in the population. This is supported by conflicting recommendations to wear face masks during the first wave. The relative search volumes could be a useful tool to provide timely and location-specific information on public attention for risk communication.