Reducing Spread of COVID-19 in a University Community Setting: Role of a Low-Cost Reusable Form-Fitting Fabric Mask

The primary aim of the proposed research is to test the role of a newly developed reusable form-fitting fabric mask in reducing the spread of COVID-19 in a community setting comprising undergraduate students living in dormitories at Georgia Tech. The study has been designed such that it also leads to the corollary aim of assessing the role of wearing any type of face covering in reducing spread in the same community setting. Yet another aim is to assess the social, behavioral, aesthetic, and usability aspects of wearing face coverings in public settings. The study design is to assign student users of masks randomly to the Treatment group of focal mask users (n=100) and a Control group of other mask users (n=100).

The Study Population and Data Collection: The subject population will comprise 200 undergraduate students staying in the dormitories at Georgia Tech, preferably freshmen and sophomores with meal plans. There will be no restriction of race, gender, or sexual orientation for this study. The final cohort chosen will attempt to reflect the demographics of the undergraduate student body at Georgia Tech. The participating subjects will have the option to withdraw from the study at any time. The recruitment of subjects will be carried out in collaboration with Georgia Tech Housing through e-mail and web announcements. The research team will be accessible to the subjects at all times during the study.

As part of the informed consent process during recruitment, the Treatment Group will be told about the use, care and laundering of the focal mask during the study. The planned sample size of 200 accounts for dropouts, which are likely to occur so that a statistically significant sample is present to assess the effect of the mask. A randomized study cannot be undertaken for ethical and practical reasons (e.g., the fact that the behaviors of students cannot be controlled leading to heterogeneity); therefore, a DID (Difference-in-Difference) approach that has been used extensively in public health research will be utilized in this study . The DID method assumes that unobserved heterogeneity in participation is present but that such factors are time invariant. With data on observations before and after the treatment intervention, this fixed component can be differenced out. For this reason, the study is spread over six weeks consisting of three phases: Pre-treatment, Treatment, and Post-treatment, with each phase lasting two weeks. The two-week period for each phase is based on the following rationale: The incubation period of COVID-19 virus has been found to be five days. About 97% of the people who get infected and develop symptoms will do so within 11 to 12 days, and about 99% will within 14 days, which is the basis for the 14-day quarantine recommended by Centers of Disease Control. The health and well-being of the subjects will be tracked during the study. Any student falling sick will be given medical help using on-campus health services. Georgia Tech has a system in place with the ability to conduct 1,500 tests per day, going to possibly 3,000 per day. If the COVID-19 test is positive, the subject will be excluded from the remainder of the study. The subject will, however, be compensated at the end of the study.

Data Collection: During the study, demographic, behavioral, and mask use data will be recorded and appropriately de-identified. No specimens will be obtained from the subjects. All the collected data will be access limited, and destroyed when no longer needed to perform the study or analysis or after completion and publication of the study, whichever comes first. COVID-19 diagnoses will be self-reported by the subjects.

At the beginning of the study, each subject will provide the following data:

• Subject Profile: Demographic information, class schedule, dining plans
• Baseline Practice Data: Mask usage practice (type, duration), typical social interactions
• During the study, each subject will provide the following data every day:
• Health Metrics: Temperature, Typical COVID-19 symptoms (if any)
• Mask Usage Data: Type and duration of mask usage including washing
• Activity Data: Classes attended, group meetings, social and dining interactions

At the end of the study, each subject will provide the following data:

• Usability: Comfort, Ease of Donning/Doffing, Impact on Communication
• Shape Conformability: Conforms to face, Shape retention after washing
• Ease of Care: Ease of washing
• Aesthetic and Social Perceptions: Style, Perceptions of others, Impact on personal behavior and degree of social interactions

The Difference-in-Difference (DID) methodology will be used to analyze the data from the Control and Treatment groups. The difference in infection rates between the groups will help determine the role of the focal mask.