Christy Leung
COVID-19, caused by SARS-CoV-2 virus, emerged in late 2019 into a global pandemic. Although governments worldwide imposed lockdown restrictions, the number of COVID-19 cases was not well-controlled as evidenced by the recurrence of waves. Realising that it is not feasible to suspend all activities indefinitely, infectious disease experts have been investigating policies to minimise disease transmission.
In general, COVID-19 transmission is less likely to occur outdoors than indoors due to better ventilation and the presence of ultraviolet and natural light. Natural light contains blue light, which deactivates viral particles. Similarly, UV light damages protein and nucleotide structures in single-stranded RNA viruses like SARS-CoV-2. However, classrooms are enclosed, high-occupancy indoor spaces, rendering them high-risk zones of infectious aerosol build-up and thus COVID-19 infection. The situation is far from ideal if in-class teaching persists in the long term. This month, Zhu and colleagues from Johns Hopkins University published an article in the Journal of Young Investigators on how schools can reduce COVID-19 transmission. This is an urgent and necessary issue to address, since there have been clusters of cases concerning transmission among masked individuals despite social distancing.
Investigators observed the association between variables and the likelihood of COVID-19 transmission. This was achieved by two parts: computational fluid dynamics (CFD) models and a literature review. In this research, CFD models were used to assess the particle dispersion and viral transmission pattern in different spaces. Variables tested in CFD models include seating arrangements, window and door opening, and air purifier placement. On the other hand, the literature review was based on analysing the use of heating, ventilation and air conditioning (HVAC) filters, portable air purifiers, disinfection (visible light, ultraviolet and chemical fogging) and mask-wearing.
Figure 1. CFD model tracer lines depicting flow of air in the classroom (image provided by the authors of the main article)
Figure 1 shows an example where the CFD model was applied. In CFD models, dark grey tracer lines were reflective of the flow pattern of the filtered air, while tracer lines of different colours represented the particle flow of exhaled air from computerised human figures. The extent of overlap between tracer lines implied the degree of cross-contamination. Turbulence was then calculated for analysis of indoor air particle flow modelling. It was then deduced that students should be seated in staggered formation in concentric circles. For both classrooms and lecture halls, students should avoid sitting at the edges of rooms, which have the highest particle density and a higher risk of infectious aerosol build-up. Windows, doors and blinds should be open whenever possible to allow air to escape into outdoor space for better ventilation. Placement of air purifiers (AP) encourages air circulation for lower particle density to reduce infectivity.
Researchers also carried out a literature review to list recommendations on variables. The results are summarised in Table 1.
Table 1. Findings from literature review analysis
Variable | Recommendation | ||
HVAC filters | HEPA filters to be used at best; otherwise use HVAC filters with the highest possible MERV rating | ||
APs | Directed flow APs are better than radial flow APs | ||
Ultraviolet germicidal irradiation (UVGI) | Upper-room type preferable if floor-to-ceiling air mixing technology is available; otherwise use overhead/standing UVGI but only between periods of room occupancy | ||
Chemical fogging | Accompanied with health risks such as skin irritation; only use between periods of room occupancy | ||
Use of masks | Disposable masks preferable over home-made ones (particles are less likely to diffuse through disposable masks); increase in thread count increases effectiveness | ||
The above findings serve to facilitate classroom planning now that schools reopen.
One of the study’s merits lies in its transferability of findings — the designs of classroom and lecture hall are comparable throughout different institutions. The results are therefore likely similar for other schools. However, assumptions that air expelled from APs is clean and human figures were all of standard body measurements may not be reflective of reality. Investigation on temperature and humidity was also inconclusive. Despite these limitations, researchers can now estimate the likelihood of transmission in other classroom scenarios and indoor spaces using similar study designs.
References:
Mueller, B. (2022) ‘Another Covid Surge May Be Coming. Are We Ready for It?’ The New York Times, 19 Mar, available: https://www.nytimes.com/2022/03/19/health/covid-ba2-surge-variant.html [accessed 3 May 2022]
Ratnesar-Shumat et al. (2020). Simulated sunlight rapidly inactivates SARS-CoV-2 on Surfaces. The Journal of Infectious Diseases, 222(2), available: https://doi.org/10.1093/infdis/jiaa274
Hadi et al. (2020). Control measures for SARS-CoV-2: A review of light-based inactivation of single-stranded RNA viruses. Pathogens, 9(9), 737, available: https://doi.org/10.3390/pathogens9090737
Zhu et al. (2022). Minimizing COVID-19 Aerosol Transmission in Enclosed Classroom Spaces. Journal of Young Investigators, 25(5), 57-74, available: 10.22186/jyi.25.5.1.1
Mohamadi et al. (2022). A Review on Applications of CFD Modeling in COVID-19 Pandemic. Archives of Computational Methods in Engineering, available: https://doi.org/10.1007/s11831-021-09706-3