Background: COVID-19, caused by SARS-CoV-2, is highly contagious and causes substantial morbidity and mortality. Mask usage has been advocated by health professionals to minimize its spread. Thus, it is important to develop a simulation that models SARS-CoV-2 spread in indoor environments to evaluate mask usage effectiveness. Methods: A visual computer simulation was developed with Pygame in Python 3. A virtual indoor supermarket is simulated by a given flow of customers with an initial infection percentage and mask usage percentage who enter, move around, and exit a supermarket with shelves, tables, and cashiers to demonstrate a system’s dynamic complexity, i.e., nonlinear interactions of system elements over time. A supermarket was simulated with initial infection rates of 5%, 10%, and 20% and mask use percentages of 0%, 25%, 50% 75%, and 100%. The environmental settings (e.g., shelf number and location) and total customers (N=200) were kept constant. Results: The number of infected customers increased as the percentage of mask usage decreased (p<0.01). At 5% initial infection, almost no infections were observed at 50% mask usage and greater, with a logarithmic best-fit model (R2=0.947). At 10% initial infection, the association between mask usage and decrease in number of infections was best fit with a linear model (R2=0.924). For 20% initial infection, a quadratic model was the best fit (R2=0.934). While a linear model suggests proportional decreases in infection, the quadratic model suggests more significant reductions in infections at higher rates of mask use (i.e., increasing mask usage from 5% to 10% is less impactful than from 65% to 70%). Conclusion: The results suggest that mask usage has a significant impact on decreasing COVID-19 transmission. Ideally, mask usage should be as high as possible to achieve more significant reductions in COVID-19 infections. Various parameters can be adjusted during simulation as we learn more about SARS-CoV-2 to guide policies for minimizing COVID-19 transmission.
| Published in | American Journal of Science, Engineering and Technology (Volume 7, Issue 1) |
| DOI | 10.11648/j.ajset.20220701.11 |
| Page(s) | 1-7 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2022. Published by Science Publishing Group |
COVID-19, Transmission, Computer Simulation, Mask Usage, Modelling
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APA Style
Roger Lacson, Peter Veldkamp, Conrad Zapanta. (2022). Assessing the Impact of Mask Usage on COVID-19 Transmission Using a Computer Simulation. American Journal of Science, Engineering and Technology, 7(1), 1-7. https://doi.org/10.11648/j.ajset.20220701.11
ACS Style
Roger Lacson; Peter Veldkamp; Conrad Zapanta. Assessing the Impact of Mask Usage on COVID-19 Transmission Using a Computer Simulation. Am. J. Sci. Eng. Technol. 2022, 7(1), 1-7. doi: 10.11648/j.ajset.20220701.11
AMA Style
Roger Lacson, Peter Veldkamp, Conrad Zapanta. Assessing the Impact of Mask Usage on COVID-19 Transmission Using a Computer Simulation. Am J Sci Eng Technol. 2022;7(1):1-7. doi: 10.11648/j.ajset.20220701.11
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Download@article{10.11648/j.ajset.20220701.11,
author = {Roger Lacson and Peter Veldkamp and Conrad Zapanta},
title = {Assessing the Impact of Mask Usage on COVID-19 Transmission Using a Computer Simulation},
journal = {American Journal of Science, Engineering and Technology},
volume = {7},
number = {1},
pages = {1-7},
doi = {10.11648/j.ajset.20220701.11},
url = {https://doi.org/10.11648/j.ajset.20220701.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajset.20220701.11},
abstract = {Background: COVID-19, caused by SARS-CoV-2, is highly contagious and causes substantial morbidity and mortality. Mask usage has been advocated by health professionals to minimize its spread. Thus, it is important to develop a simulation that models SARS-CoV-2 spread in indoor environments to evaluate mask usage effectiveness. Methods: A visual computer simulation was developed with Pygame in Python 3. A virtual indoor supermarket is simulated by a given flow of customers with an initial infection percentage and mask usage percentage who enter, move around, and exit a supermarket with shelves, tables, and cashiers to demonstrate a system’s dynamic complexity, i.e., nonlinear interactions of system elements over time. A supermarket was simulated with initial infection rates of 5%, 10%, and 20% and mask use percentages of 0%, 25%, 50% 75%, and 100%. The environmental settings (e.g., shelf number and location) and total customers (N=200) were kept constant. Results: The number of infected customers increased as the percentage of mask usage decreased (p2=0.947). At 10% initial infection, the association between mask usage and decrease in number of infections was best fit with a linear model (R2=0.924). For 20% initial infection, a quadratic model was the best fit (R2=0.934). While a linear model suggests proportional decreases in infection, the quadratic model suggests more significant reductions in infections at higher rates of mask use (i.e., increasing mask usage from 5% to 10% is less impactful than from 65% to 70%). Conclusion: The results suggest that mask usage has a significant impact on decreasing COVID-19 transmission. Ideally, mask usage should be as high as possible to achieve more significant reductions in COVID-19 infections. Various parameters can be adjusted during simulation as we learn more about SARS-CoV-2 to guide policies for minimizing COVID-19 transmission.},
year = {2022}
}
TY - JOUR T1 - Assessing the Impact of Mask Usage on COVID-19 Transmission Using a Computer Simulation AU - Roger Lacson AU - Peter Veldkamp AU - Conrad Zapanta Y1 - 2022/01/24 PY - 2022 N1 - https://doi.org/10.11648/j.ajset.20220701.11 DO - 10.11648/j.ajset.20220701.11 T2 - American Journal of Science, Engineering and Technology JF - American Journal of Science, Engineering and Technology JO - American Journal of Science, Engineering and Technology SP - 1 EP - 7 PB - Science Publishing Group SN - 2578-8353 UR - https://doi.org/10.11648/j.ajset.20220701.11 AB - Background: COVID-19, caused by SARS-CoV-2, is highly contagious and causes substantial morbidity and mortality. Mask usage has been advocated by health professionals to minimize its spread. Thus, it is important to develop a simulation that models SARS-CoV-2 spread in indoor environments to evaluate mask usage effectiveness. Methods: A visual computer simulation was developed with Pygame in Python 3. A virtual indoor supermarket is simulated by a given flow of customers with an initial infection percentage and mask usage percentage who enter, move around, and exit a supermarket with shelves, tables, and cashiers to demonstrate a system’s dynamic complexity, i.e., nonlinear interactions of system elements over time. A supermarket was simulated with initial infection rates of 5%, 10%, and 20% and mask use percentages of 0%, 25%, 50% 75%, and 100%. The environmental settings (e.g., shelf number and location) and total customers (N=200) were kept constant. Results: The number of infected customers increased as the percentage of mask usage decreased (p2=0.947). At 10% initial infection, the association between mask usage and decrease in number of infections was best fit with a linear model (R2=0.924). For 20% initial infection, a quadratic model was the best fit (R2=0.934). While a linear model suggests proportional decreases in infection, the quadratic model suggests more significant reductions in infections at higher rates of mask use (i.e., increasing mask usage from 5% to 10% is less impactful than from 65% to 70%). Conclusion: The results suggest that mask usage has a significant impact on decreasing COVID-19 transmission. Ideally, mask usage should be as high as possible to achieve more significant reductions in COVID-19 infections. Various parameters can be adjusted during simulation as we learn more about SARS-CoV-2 to guide policies for minimizing COVID-19 transmission. VL - 7 IS - 1 ER -
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