• Pre-Collegiate Global Health Review

Efficacy of Mask Use in Reducing SARS-CoV-2 Infection Rates

Sabrina Guo, Syosset High School, Syosset, New York, USA


ABSTRACT


SARS-CoV-2, a novel coronavirus which causes the disease known as COVID-19, has produced a global pandemic, claiming the lives of over 6.1 million people, and counting. Governments and local polities have implemented public health mandates to reduce the spread of the disease, including mandatory mask-wearing, a policy that remains controversial. This study aimed to examine how effective stricter enforcement of mask wearing policies is in reducing COVID-19 infection rates, to better guide public health directives in the effort to mitigate the present pandemic, future variants, and other viruses which may behave similarly. A total of 45 countries and subnational political jurisdictions were randomly selected, then sorted into three categories of mask-enforcement: strict, moderate, and lax, each characterized by punishments, non-enforcement, or lack of precautions, respectively. The percent changes in COVID-19 cases were recorded over a 3-month period prior to and after declaration of mask mandates for each locality, then analyzed using Kruskal-Wallis test to rank the three categories. The mean rankings from greatest to least were: lax (36.33), moderate (19.33), and strict (12.73). The Kruskal-Wallis test result was H(2)= 25.442, P=.000. Data showed locations with stricter mask policies were found to have lower infection rates. The results suggest that strictly enforced mask policies are more effective in limiting COVID-19 transmission. Confounding variables include political agendas, sway of public opinion, and a relative lack of data on COVID-19. Future research could analyze the effectiveness of mask enforcement for different COVID-19 variants.


INTRODUCTION

In December 2019, a novel coronavirus, SARS-CoV-2, later termed coronavirus disease 2019 (COVID-19), was identified in Wuhan, China as the cause of an acute epidemic that has rapidly become a global pandemic. Per the WHO Coronavirus Dashboard, the coronavirus has claimed nearly 6.2 million people’s lives globally to date and has impacted countless more (World Health Organization, 2022). Analysis of the efficacy of public health policies and the governmental responses of various nations is imperative to better understand how to limit the spread of COVID-19 and to restore some semblance of normalcy to the general populations of the world. 

Masking policies have been one of the key governmental responses to limit the transmission of COVID-19. Since the start of the pandemic, a rising body of evidence has increasingly pointed to labeling mask enforcement as a necessary policy to reduce mortality rates. For example, a study published by the New England Journal of Medicine created a high-speed video demonstrating that hundreds of droplets from 20-500 micrometers are produced when saying a short phrase; but when the mouth was covered with a damp washcloth, nearly all the particles were blocked (Anfinrud et al., 2020). It was also found that mask mandates in 15 states and the District of Columbia slowed down the COVID-19 death rate; COVID-19 growth rates declined by 0.9% five days after the mandate compared to five days prior; and after three weeks, the growth rate had declined by 2% (Lyu & Wehby, 2020). Another published study analyzed COVID-19 deaths in 198 countries and concluded that countries with cultural norms that encouraged compliance with mask-wearing mandates and enforced policies favoring mask-wearing had the lowest death rates (Leffler et al., 2020). Overall, scientific consensus is positively favoring the claim that masks have been effective in preventing COVID-19 transmission. Despite the evidence in favor of masking, qualms about the protective nature of masks exist in many countries and vary depending on the differing cultures and political climates. The highly partisan climate of American politics is a particularly salient example. Political gridlock and vastly polarizing ideologies have made it difficult for the U.S. to mobilize its vast resources to mitigate the pandemic (Vaida, 2020). The lack of central leadership, from the federal government deferring to state governments regarding COVID-19 protocols, to former President Trump contradicting his own public health advisors and retweeting conspiracy theories, has been particularly detrimental to U.S. virus containment. Unfortunately, many leadership and partisanship issues persist in the U.S. today, meaning that even with increasing availability of vaccines and pending therapeutic treatments, the road to recovery for the U.S. will be challenging. 

As an increasing number of studies concluded that masks are effective in preventing transmission of COVID-19, several studies were conducted by the CDC to determine which specific characteristics of masks (fit, fabric, thickness, etc.) make mask-wearing most effective (Brooks & Butler, 2021). Testing 10 different mask combinations, the CDC found that modifying the fit of masks substantially increased the wearer’s protection against COVID-19; in fact, when a cloth mask was worn over a surgical mask as snugly as possible (using fitters, knotting, or tucking), the wearer was found to be 90% protected from exposure or more (Brooks & Butler, 2021).

With the alarming emergence and spread of several COVID-19 variants (Simone, 2021), it is crucial to establish the level of effectiveness of protective measures, namely mask-wearing, by elucidating whether countries that strictly enforce mask-wearing policies have had a lower number of COVID-19 cases than countries that have had less strict policies. Although data suggests that mask-wearing reduces COVID-19 transmission, there is less data on the efficacy of masking policies across different countries, a problem that this study aims to address (Howard et al., 2021). In addition, there is a substantial lack of data on how the degree of mask enforcement affects compliance and therefore COVID-19 transmission rates, an issue that this study aims to also elucidate. It is hypothesized that countries and subnational jurisdictions that strictly enforce mask-wearing in public and shared spaces will have lower infection rates. Thus, this study seeks to answer: Do countries that strictly enforce mask-wearing in public and shared spaces have the lowest coronavirus infection rates?



MATERIALS AND METHODS


A total of 45 locations globally were arbitrarily selected using a random choice generator from Text Finder, then organized into three categories of mask enforcement: strict, moderate, and lax. The number 45 was chosen to allow for adequate samples for each strict, moderate, and lax enforcement policies, and Text Finder was used because of its ability to randomly choose countries. The final sample of countries or subnational political jurisdictions working to reduce COVID-19 transmission was grouped into strict, moderate, and lax (Tables 1-4, Figure 1).






Respective mask-wearing policies were collected from the CDC, WHO, and The New York Times, among other credible sources. Strict enforcement was characterized by a location’s enacting of measurable punishments, such as fines for mask guideline violations (Figure 2). Moderate enforcement was defined as locations only encouraging mask-wearing or that have wavered or loosened mask mandates over the specific time range. Lax enforcement was distinguished as locations that have allowed individuals to make personal decisions about wearing masks, trusting the individual to be responsible about mask-wearing; lax enforcement also included locations with no restrictions at all.


Figure 2: Criteria for Strict, Moderate, and Lax Categorization using identifiable measures of enforcement


Data for the 45 locations were collected in a table showing the percentage of COVID-19 cases on the day mask enforcement was implemented and 3 months after that implementation, in each respective location; for locations that had no mask enforcement, the date of the first governmental public statement regarding COVID-19 and three months following this date was used. This was done to demonstrate how effective the policy was in each locality. The source of this information came from the New York Times’ collection of data from various state and local health agencies. The start date of mask enforcement, and the start and end dates for travel restrictions, stay-at-home orders, the closing of educational facilities, gathering restrictions, and business closures, were also considered. This provided necessary context, as other possible factors could have affected the COVID-19 infection percentage at the 3-month mark; these data were collected from the National Institute of Allergy and Infectious Diseases, as well as the start dates of mask enforcement in the studied countries or subnational political jurisdictions. The percent increase or decrease calculated from the percentage of COVID-19 cases, from the day of mask enforcement to the percentage at the 3-month mark, was recorded for each location and then aggregated with data from the same category of enforcement (Table 4). These percent changes would specifically address the effectiveness of each of the three groups of degrees of mask enforcement. A Kruskal-Wallis test with a = 0.05 was then conducted to rank the percent changes of COVID-19 cases in different locations, with careful attention paid to what patterns emerged among the three groups of mask enforcement (strict, moderate, and lax). A Kruskal-Wallis test determines whether the differences between two or more groups are significant and is used when no distributive assumptions can be made (unlike ANOVA). A non-parametric test was warranted because there were outliers present (e.g., Sudan's percent increase of 19300.00%) and the data would be more accurately presented. As a simplified example calculation of a Kruskal-Wallis test, assume three groups of test takers- A, B, and C. Group A had the 1st highest scoring test, as well as 3rd, 4th, 6th, and 8th. B had ranks of 2, 5, 7, 10, and C had the remaining ranks. The mean rank for A would be (1 + 3 + 4 + 6 + 8)/5 = 4.4. The H statistic is calculated using the formula= (12/(N(N+1)) * (∑T^2/n) - 3(N+1) where N is the total sample, T is the rank sum for each group, and n is the size of each group. The statistic is compared to the critical chi-square value, with g - 1 degrees of freedom. Assuming a significance of 0.05, our critical value is 5.99 which is less than H = 0.05 * 1124.8 – 48 = 8.24 and the result is significant.


RESULTS


After aggregating the percent changes, the strict, moderate, and lax groups were ranked (Table 5). The trend observed was that as the degree of mask enforcement became stricter, the mean rank decreased. As seen in Table 5, the rank value for Lax enforcement was 36.33, while the Moderate group had a mean rank of 19.93 and the Strict group had a mean rank score of 12.73. Lower percent changes on an absolute scale in COVID-19 cases over a 3-month period were strongly associated with stricter levels of mask enforcement. The Kruskal-Wallis test, run with two degrees of freedom, 25.442, resulting in a p-value of .000 (Table 6).



This signifies that the chance of the observed differences in groups occurring due to random variation is approximately 0.0001. Because the p-value was found to be less than a = 0.05, there was a statistically significant difference in the 3 levels of mask enforcement and the respective percent changes in COVID-19 cases.


Thus, it can be concluded that locations with stricter levels of mask enforcement tend to have lower COVID-19 infection rates while lax enforcement tends to have the opposite effect. The aggregation and comparison of COVID-19 transmission rates between groups of strict, moderate, and lax enforcement using Kruskal-Wallis test thus addresses the central question of whether stricter enforcement of masks leads to less COVID-19_transmission.


DISCUSSION

Locations with strict mask enforcement have the lowest COVID-19 infection rates, whereas locations with lax mask enforcement have the highest COVID-19 infection rates (Table 5, 6). It can be concluded that mask-wearing policies are the most effective in reducing COVID-19 infection rates when strictly enforced by governments. An explanation for this finding may be that stricter enforcement often results in penalties or fines, which leads to higher adoption rates of mask wearing, which reduces COVID-19 transmission. Meanwhile, lax mask wearing policies may not provide enough incentive for individuals to adopt masks. The analysis suggests that strictly enforced masking policies are more effective at lowering COVID-19 rates than loosely enforced policies, thus supporting the hypothesis of this study (Table 5, 6). The results of this study are supported by a similar study published by Health Affairs, which concluded that mask mandates in 15 states and the District of Columbia declined COVID-19 death rates and growth rates (Lyu & Wehby, 2020). Evaluated together with the results of this study, it is advisable for governments to consider enforcing more stringent mask-wearing policies to reduce COVID-19 transmission as much as possible. Another study published by the Proceedings of the National Academy of Sciences of the United States of America found that mask wearing in public is most effective at reducing the transmission of COVID-19 when compliance is high, and thus recommends that public officials and governments should strongly encourage the use of widespread face masks in public, including the use of appropriate regulation (Howard et al., 2021). However, the aforementioned studies did not take into account the level of strictness with enforcement, which was what this study aimed to investigate. Both studies confirm and support this study’s results, which is the effectiveness of well-enforced mask guidelines in reducing COVID-19 growth, death, and infection rates.

However, there are certain limitations to this study. The COVID-19 pandemic is still ongoing; data are fluid, and some are immeasurable. For example, there is not enough available data in all the strict mask-enforcement locations to evaluate exactly how many people have been punished with fines for violation of mask guidelines. One confounding factor may be implementation of other policies (social distancing, closure of non-essential businesses, etc.) that would vary among the strict, moderate, and lax enforcement group, creating another possible explanation for the discrepancy in COVID-19 transmission among the groups. Other limitations of this study include the grouping of countries into lax, moderate, and strict mask policies instead of specific policies. This limits the ability to determine exactly which policies have the most impact on results. In addition, another limitation of this study is the time period in which the data is taken. This data only looks at the first three months following mask mandates which limits the scope of the study to the initial pandemic response and may not be as applicable to long term approaches.


A logical continuation of this study would include looking at specific mask enforcement policies such as fines and analyzing how these policies correlate with COVID-19 transmission or investigating how social distancing guidelines and business closures impacted COVID-19 transmission in the same countries this study examined. While COVID-19 is a relatively new public health concern, several COVID-19 variants have emerged and became a topic of concern, one that provides potential alternate courses for future research, including mask policies for different variants. Future research could include analyzing the effectiveness of mask policies in reducing the infectivity of different COVID-19 variants including variants of concern such as B.1.1.7, B.1.351, P.1, B.1.427, B.1.525, B.1.617.1, B.1.621, and P.2. If strict mask policies continue to lower COVID-19 infection rates in variants of concern, it will be crucial for governments and citizens around the world to understand the extent to which mask use protects both the wearer and those around the wearer, and the effectiveness of stricter mask policies. In a rapidly evolving COVID-19 pandemic, gathering as much data as possible is critical to the understanding of the science behind this virus and the implementation of effective guidelines and policies.


 

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