COVID-19: Masks could cut more than 130000 deaths in the US


Even if state-level governments in the United States reimpose limited social distancing measures to halt the spread of COVID-19, the death toll could more than double by the end of February 2021 to 511,000, according to projections released Friday.

Near-universal mask wearing over the coming months could reduce that grim tally by nearly 130,000, researchers from the COVID-19 forecasting team at the Institute for Health Metrics and Evaluation (IHME) found.

Even if mask compliance was only 85 percent, the number of lives saved compared to that baseline would still top 95,000, they reported in the peer-reviewed journal Nature Medicine.

“There is now growing evidence that face masks can considerably reduce the transmission of respiratory viruses like SARS-CoV-2, thereby limiting the spread of COVID-19,” the authors noted.

The US national average of self-reported mask use was nearly 50 percent as of September—despite mixed messages from some politicians on their efficacy.

Donald Trump has shunned mask use in public, and has mocked his rival for the White House, Joe Biden, for his consistent wearing of them.

Few of Trump’s followers cover their faces at his campaign rallies, which resumed after the president recovered from a bout with the virus earlier this month.

Since the first confirmed case on US soil of COVID-19 in January 2020, the virus has infected some 8.4 million people across the nation and claimed more than 223,000 lives.

In mid-July, IHME modellers accurately predicted 224,000 deaths by November 1.

Today, a second – and in some locations third – wave of infection is rising as winter sets in, with the total number of new cases in the US topping 75,000 on October 22, nearly double the daily increase from a month earlier.

In the absence of a vaccine and with few options for treatment, non-pharmaceutical measures such as mask wearing, social distancing, self-isolation, and contact tracing are by default the most effective tools available to curb the disease’s spread.

Face mask effect on  Covid-19 deaths
Face mask effect on Covid-19 deaths

A ‘reference’ scenario

Most experts agree that, at best, an effective vaccine in not likely to be approved and available until well into next year.

To map what the near-term future might hold, IHME epidemiologists and modellers designed three possible scenarios for the United States, extending out to the end of February.

In the first, states continue to remove whatever restrictions on movement and social interaction are still in place, leading to more extensive contact among people.

In this unlikely scenario, they predict, total COVID-19 deaths could top one million by that date.

At least 152 million people – 45 percent of the entire population—are forecast to be infected with the virus, which provokes mild or no symptoms in most cases.

But it is more realistic to expect that states will reimpose measures adopted during the first wave, including closing schools, restricting the size of public gatherings, and the partial or full closure of non-essential businesses.

The study shows that these and similar measures were often triggered when daily death rates in a given locality or state passed eight deaths per million of population.

That threshold will be crossed in 45 of 50 states by late February, according to the new findings.

Even with a new round of social distancing mandates, the COVID-19 death toll is projected to surpass 511,000 by March 1 in this second “reference” model, with a total of nearly 72 million infections.

The study goes on to estimate the impact if at least 95 percent of the US adult population wore masks.

“Universal mask use could save an additional 129,574 lives from September 22, 2020 through the end of February 2021,” it concluded.

Mask features

Masks can play at least two roles in viral transmission prevention in the general population. First, masks can impact turbulent gas cloud formation and respiratory pathogen emission [51]. Research demonstrates that masks can either block the rapid turbulent jets generated by coughing or redirect the jets in much less harmful ways for airborne infection control [52].

Second, the mask material can filter viral particles such as aerosols or droplets [53].

Additionally, for asymptomatic infected individuals, wearing a mask can potentially reduce the risk of infecting other people when the exact individual wears a mask to protect him or herself.

We classify masks into three categories in our study:

  1. certified masks, which refers to medical masks that meet government certification standards (that is, in the US, the Centers for Disease Control and Prevention (CDC) National Institute for Occupational Safety and Health (NOISH) certifies medical masks such as N-95 respirators);
  2. medical masks that are not certified but subject to Food and Drug Administration (FDA) jurisdiction as a regulated medical device (that is, loose fitting disposable medical masks);
  3. homemade masks whose quality cannot be guaranteed. For medical masks, the European Medicines Agency (EMA) has established guidelines for effective virus reduction combined with reduction factors [54].

Typically, certified and medical masks can effectively reduce influenza virus loads [55]. Leung et al. described the effectiveness of surgical face masks (with ear loops, cat. no. 62356, Kimberly-Clark) could prevent the transmission of human coronaviruses and influenza viruses from symptomatic individuals.

Based on the guidelines and available data on certified and non-certified medical masks, we recognize that the mask material virus reduction potential is not necessarily equivalent to the mask viral reduction rate (Mred) and we assume that the general mask usage in public has a reduced reduction factor without any fit tests, training, or instructions.

Previous studies compared homemade cloth masks and commercial medical masks, which suggested reduced protection from particle penetration by cloth masks [56–58] and bare protection by handkerchiefs [57]. However, cough pressure can be significantly reduced by wearing any type of mask [59].

As such, we estimate less than 1–2 log 10 reduction factors for normal mask wearing in public. The log reduction factor translates into less than 90% virus removal effectiveness. We assume Mred, the base aerosol reduction percentage of face masks (commercial medical products) in a public setting, to be approximately 60% [60] and estimate the range from 40% to 75%, assuming the best reduction rate is 99% for a NOISH-certified N-95 type respirator [53, 57, 58, 61].

The percentage of people wearing a mask during a pandemic depends on several factors. First, culture plays a very important role in determining mask coverage around the world [62]. In East Asia, wearing a mask is common and has long been culturally acceptable [62].

People wear masks for many different reasons, such as pollution, allergies, and winter protection, not just when they are sick. According to a recent Mintel report, 63% of Japanese wore face masks in public during the spread of COVID-19 [63]. However, in North America and Europe, public health officials have discouraged healthy people from wearing masks [62].

Previous studies across five countries suggested a significant gap between willingness (71%) and real action (8%) to wear a mask in the US [64]. The awareness of wearing a mask during the COVID-19 pandemic recently became more popular in the US, and the percentage of Americans wearing masks increased to approximately 12% by the end of March 2020 [65].

Therefore, we expect Mcov to be higher in East Asian countries and lower in North America and Europe. Second, the pandemic’s severity could potentially change the mask coverage dynamics in a short period. Based on an online (February 11 to 13, 2020) survey in South Korea, 79% of the participants started wearing masks compared to only 19% who wore masks prior to the outbreak.

Third, public health advocacy and government policies or recommendations could have a significant impact on mask coverage. To simulate the mask coverage impact on R0, we assume Mcov to be in a range of 8% to 100%.

Most countries were not prepared for the COVID-19 outbreak and are universally short of PPE supplies. Abramovich et al. utilized a computer simulation to model the benefits of stockpiling PPE based on disease profile variables.

The simulation variables provided a wide range that covered the current COVID-19 outbreak, whose disease parameters fall into the higher end of the range. The authors suggested diminishing patient care benefits of stockpiling on the high side of the range [66].

However, the study pointed out the importance of having modest stockpiles of critical resources. Carias et al. estimated in a hypothetical influenza outbreak that 1.7 to 3.5 billion respirators would be needed in the base case scenario, 2.6 to 4.3 billion in the intermediate demand scenario, and up to 7.3 billion in the maximum demand scenario for an outbreak with 20% to 30% of the population infected.

Among all of the scenarios, between 0.1 and 0.4 billion surgical masks would be needed for patients [67]. Moreover, the production of N95 respirators and other surgical masks has increased since the COVID-19 outbreak. As of February 3, 2020, it was estimated that China was producing approximately 14.8 million medical masks daily, a production capacity utilization rate of nearly 67% [68].

The future trend will follow the market needs, government agency public health policies, and supportive programs [69]. Given the limited data and vast uncertainty of future mask production, we estimate Mava varies significantly across countries and regions.

In countries with a large mask production capacity such as China [70], Mava is on the higher end, approximately 90%. However, countries that rely heavily on importing face masks, such as Switzerland, are more likely to face shortages because of the surging global demand and disrupted global supply chain [18]. As a result, Mava for these countries could be on the lower end, approximately 30%. Moreover, we project that mask availability will increase as the pandemic peaks and production continues to rise.

We used the following table for the Rint simulation of the mask features. We set Mred at 57.5% and considered two parameters for Mcov and Mava individually for the simulation. We set the baseline scenario of 8% for Mcov [64] and 100% as the best scenario. Given the shortages in the PPE market, we used 5% as the baseline scenario and 100% as the best scenario. We simulated seven scenarios (Table 2) and discuss the details.

Table 2. Parameters for reproduction number, infection attack rate, and infected cases in seven scenarios (S1 to S7).

Effects of mask-wearing on reproduction number and infection attack rate

Based on the reported studies, we set R0 at 2.3 to evaluate the mask impact. As previously mentioned, we exclude homemade face masks from this evaluation as the mask material and quality cannot be guaranteed. T

o show how the reproduction number Rint and infection attack rate a are impacted by mask-wearing, we plot the change in Rint and a with mask availability Mava under seven scenarios. We report the values of Mred and Mcov for these seven scenarios (S1 to 7) in Table 2. Fig 1 shows that Rint decreases with mask availability in all of the scenarios.

Specifically, in scenarios 2 and 5, when everyone is willing to wear a mask (Mcov = 100%), Rint is among the lowest (that is, Rint2 and Rint5). It can be less than 1 when mask availability is close to 100%. Moreover, even a moderate level of mask coverage (Mcov = 54%, scenarios 3 and 7) can help substantially reduce Rint (i.e., Rint3 and Rint7) compared with low mask coverage (Mcov = 8%, Rint1, Rint4, and Rint6). We observe a similar pattern in the infection attack rate a graph (Fig 1). These results indicate the significance of mask-wearing, demonstrating considerable promise to contain the pandemic.

Fig 1. Rint and attack rate dependence on mask availability.
The Rint and attack rate a values are simulated based seven scenarios in Table 2. Rint 1 is calculated based on scenarios 1. The same annotation principle applies to all other Rint calculations.

reference link :

More information: Modeling COVID-19 scenarios for the United States, Nature Medicine (2020). DOI: 10.1038/s41591-020-1132-9 ,


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