Imuho this is still better than some people who are anti vaxer and yet never give leecomendation and wait to die KNN or worse leecomend you to get covid KNNY ur uncle liddat one?
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IP addresses are NOT logged in this forum so there's no point asking. Please note that this forum is full of homophobes, racists, lunatics, schizophrenics & absolute nut jobs with a smattering of geniuses, Chinese chauvinists, Moderate Muslims and last but not least a couple of "know-it-alls" constantly sprouting their dubious wisdom. If you believe that content generated by unsavory characters might cause you offense PLEASE LEAVE NOW! Sammyboy Admin and Staff are not responsible for your hurt feelings should you choose to read any of the content here. The OTHER forum is HERE so please stop asking.
today 3may2021 how many local community cases?
- Thread starter kaninabuchaojibye
- Start date
For me really not much choice. Anti or not still have to take cos ada hse in JB.:(
Still better than some who said no choice have to take becas want to go holiday KNN that means @ginfreely also need to take
KNNWrong. Again. Call it 0 for 155 tries.
https://www.cnet.com/health/mit-cov...may-be-more-important-than-social-distancing/
MIT COVID study: Masks may be more important indoors than social distancing
Social distancing has its limits, but masks can be "extremely effective," the study's authors find.
Sean Buckley
April 26, 2021 4:41 p.m. PT
- 02:12
New MIT study examines the benefit of wearing masks.
James Martin/CNET
For the most up-to-date news and information about the coronavirus pandemic, visit the WHO website.
Wash your hands. Wear a mask. Stand at least six feet away from others. These are the guidelines many of us have lived by for the past year, all of them suggested in the early days of the COVID-19 pandemic. Now, MIT researchers are taking a closer look at the six-foot recommendation to see how effective social distancing really is.
The short answer? In certain situations, six feet of distance isn't enough to protect you on its own and you should probably still wear a mask.
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The real answer? That's a little complicated. The paper says that in "well-mixed spaces, one is no safer from airborne pathogens at 60 ft than 6ft," but the context of this statement depends on the size of the space, how well ventilated it is and what the persons in the room are doing.
Researchers specifically designed the study to mimic the conditions of certain kinds of indoor "superspreading events," such as the Skagit Valley choir practice that resulted in the infecting 53 of 61 attendees. In other words, researchers were only targeting the transmission of small aerosol droplets in a "well-mixed" indoor space with only moderate ventilation -- one where the air moves around frequently enough that potentially infected particles don't have time to settle.
For example, the formula researchers devised for calculating indoor safety guidelines suggest that if an infected person was riding on a commercial airline with 100 other people, other passengers would be at risk of infection within 70 minutes. If all of the passengers wore masks, however, that space could be safe for up to 54 hours.
With data like that, it's possible to conclude the study says social distancing isn't effective, but the authors are quick to point out that the paper examines only one method of transmission under very specific conditions. In a statement, the researchers said that their findings had been "mischaracterized by some on social media and in the news," stating that the paper makes a point of calling out the benefits of social distancing and mask-wearing in conditions outside of the study's purview.
"The value of social distancing in limiting COVID-19 transmission by respiratory jets is made clear in the last section of our paper, 'Beyond the well-mixed room,'" they said. "Our study highlights that face masks can be an extremely effective indoor safety measure."
The researchers have built an online tool to help readers calculate how their formula estimates risk for differing room sizes, occupancy levels and mask-wearing behavior. For everything else you need to know about COVID-19, be sure to check out CNET's ongoing coverage here.
The information contained in this article is for educational and informational purposes only and is not intended as health or medical advice. Always consult a physician or other qualified health provider regarding any questions you may have about a medical condition or health objectives.
Health and Wellness Sci-Tech Coronavirus
Wrong. Again. Call it 0 for 156 tries. All failed.
https://www.healthsystemtracker.org...-one-cause-of-death-in-the-u-s-in-early-2021/
COVID-19 is the Number One Cause of Death in the U.S. in Early 2021
By Cynthia Cox Twitter and Krutika Amin Twitter KFF
Briefs
Health & Wellbeing
Posted: February 22, 2021
SHARE
In 2020, COVID-19 became the third leading cause of death in the United States, exceeded only by cancer and heart disease. However, that ranking includes months in early 2020 when the pandemic had not fully taken hold in the U.S. The death toll from COVID-19 has risen sharply, particularly since the November and December holidays.
Looking at the most recent data on deaths from COVID-19 and other causes, it becomes clear that COVID-19 is currently the number one cause of death in the United States. As of February 20, 2021, an average of more than 2,400 people per day died of COVID-19 in the U.S. during February 2021. That number is staggering compared to other leading causes of death and is nearly 20% higher than the next leading cause. Heart disease, which is typically the number one cause of death in the U.S. each year, leads to the death of about 2,000 Americans per day, and cancer claims about 1,600 American lives per day. The cumulative count of deaths attributed to COVID-19 in the U.S. is 497,648 through February 20, 2021, and is expected to exceed 500,000 in the next few days.
The chart above combines data on COVID-19 mortality rates from KFF’s tracker with data from Center for Disease Control (CDC) on weekly counts of death by jurisdiction and cause of death. COVID-19 deaths in the chart represent the average daily deaths thus far in February 2021 (as of February 20, 2021). Deaths from other causes represent the weighted daily mortality rate averaged over MMWR weeks 1-52 during the year 2020. This CDC dataset does not include deaths due to accidents (which, before the pandemic, were typically the third leading cause of death, after heart disease and cancer), nor does it include suicides (which were typically the tenth leading cause of death before the pandemic). To avoid double-counting, the dataset excludes deaths confirmed to have an underlying cause of COVID-19. The chart could, however, understate the severity of COVID-19 because some of those deaths may have been misclassified as other causes. There were many more deaths in 2020 than expected, and confirmed COVID-19 cases only accounted for about two in three excess deaths.
The current wave of COVID-19 has been described as more of a tsunami. The 3,076 COVID-19 deaths per day in January 2021 represent a 29% increase over December. December 2020 may have been the first month in which the COVID-19 mortality rate exceeded that of heart disease, though the margin is narrow and that data may still be preliminary due to reporting delays. In January 2021, the number of deaths from COVID-19 increased so rapidly that it has clearly become the number one cause of death in the U.S. These data are just one more way of illustrating the urgency of expediting COVID-19 vaccination. President Biden has developed a plan to increase vaccine supply, including through use of the Defense Production Act and by purchasing additional doses. In the meantime, other public health measures are crucial to reduce transmission. The number of new COVID-19 cases appears to have taken a turn for the better in the latter half of January, which could lead to declines in the number of new deaths several weeks from now. However, it is difficult to know what the future holds, particularly with the potential spread of new variants.
Thai road death toll tops 12,000 in 2019
Published
1 year ago
on
Thursday, November 7, 2019
By
Jack Burton
PHOTO: Motorcyclist skittled by pick-up and killed in Ranong this week – Daily News
Thai media report 12,304 people have been registered as dying at accident scenes in Thailand so far this year.
Academics caution that this figure only relates to those who die at the scene, and the actual death toll is far higher when when all all data is collated, and when victims succumb to their injuries after leaving the accident scene.
The total annual Thai death toll, over recent years, is between 21,000 – 24,000, making it one of the worst in the world (currently #5 in the world according to World Health Orginisation data).
On Monday this week 62 people died, bringing November’s toll to 144 on just the fourth day of the month.
The Daily News runs an ongoing campaign to raise awareness of the dangers of Thai roads. They report the death toll daily, along with accident reports.
The Daily News reported that a motorcyclist was recently killed outside a chicken rice shop in the southern province of Ranong, north of Phang Nga. The lane-changing motorcyclist was hit by a pickup driver who could not brake in time, and flung the victim into the back of another pickup.
Wrong. Again. Call if 0 for 157 tries. Equating pollution or traffic accidents to Corona deaths just show how stupid you are.
If ask to go for 3rd vaccine jab n border still closed, i will give it a miss!
Still better than some who said no choice have to take becas want to go holiday KNN that means @ginfreely also need to take
Holiday can kiv. But hse turned into forest. Chia lat...
Wrong. Again. Call it 0 for 161 tries.
https://www.healthaffairs.org/doi/10.1377/hlthaff.2020.00818
Community Use Of Face Masks And COVID-19: Evidence From A Natural Experiment Of State Mandates In The US
Abstract
State policies mandating public or community use of face masks or covers in mitigating the spread of coronavirus disease 2019 (COVID-19) are hotly contested. This study provides evidence from a natural experiment on the effects of state government mandates for face mask use in public issued by fifteen states plus Washington, D.C., between April 8 and May 15, 2020. The research design is an event study examining changes in the daily county-level COVID-19 growth rates between March 31 and May 22, 2020. Mandating face mask use in public is associated with a decline in the daily COVID-19 growth rate by 0.9, 1.1, 1.4, 1.7, and 2.0 percentage points in 1–5, 6–10, 11–15, 16–20, and 21 or more days after state face mask orders were signed, respectively. Estimates suggest that as a result of the implementation of these mandates, more than 200,000 COVID-19 cases were averted by May 22, 2020. The findings suggest that requiring face mask use in public could help in mitigating the spread of COVID-19.
TOPICS
- COVID-19
- CORONAVIRUS
- STATE MANDATES
- PANDEMICS
- PUBLIC HEALTH
- POPULATIONS
- RESEARCHERS
- EVIDENCE BASED DECISION MAKING
- HEALTH PROFESSIONALS
- DISEASES
- STATE HEALTH POLICIES
Researchers have been reviewing evidence from previous randomized controlled trials for other respiratory illnesses, examining mask use and types among people at higher risk of contracting infections (such as health care workers or people in infected households). Systematic reviews and meta-analyses of such studies have provided suggestive, although generally weak, evidence.6 The estimates from the meta-analyses based on randomized controlled trials suggest declines in transmission risk for influenza or influenza-like illnesses to mask wearers, although estimates are mostly statistically insignificant possibly because of small sample sizes or design limitations, especially those related to assessing compliance.7–9 There is also a relationship between increased adherence to mask use, specifically, and effectiveness of reducing transmission to mask wearers: In one randomized study of influenza transmission in infected households in Australia, transmission risk for mask wearers was lower with greater adherence.10 Further, the evidence is mixed from randomized studies on types of masks and risk for influenza-like illness transmission to mask wearers; for example, a recent systematic review and meta-analysis comparing N-95 respirators versus surgical masks found a statistically insignificant decline in influenza risk with N-95 respirators.11
Positions on widespread face mask use have differed worldwide but are changing over time. In the US, public health authorities did not recommend widespread face mask use in public at the start of the pandemic. The initially limited evidence on asymptomatic transmission and concern about mask shortages for the health care workforce and people caring for patients contributed to that initial decision. On April 3, 2020, the Centers for Disease Control and Prevention (CDC) issued new guidance advising everyone to wear cloth face covers in public areas where close contact with others is unavoidable, citing new evidence on virus transmission from asymptomatic or presymptomatic people.12 Guidelines differ between countries, and some, including Germany, France, Italy, Spain, China, and South Korea, have mandated the use of face masks in public.13–16
This study adds complementary evidence to the literature on the impacts of widespread community use of face masks on COVID-19 spread from a natural experiment based on whether or not US states had mandated the use of face masks in public for COVID-19 mitigation as of May 2020. Fifteen states plus Washington, D.C., issued mandates for face mask use in public between April 8 and May 15.
We identified the effects of state mandates for the use of face masks in public on the daily COVID-19 growth rate, using an event study that examined the effects over different periods. We considered the impact of mandates for mask use targeted only to employees in some work settings, as opposed to communitywide mandates. This evidence is critical, as states and countries worldwide begin to shift to “reopening” their economies and as foot traffic increases. Mandating the public use of masks has become a socially and politically contentious issue, with multiple protests and even acts of violence directed against masked employees and those asking customers to wear face masks.17 Face cover recommendations and mandates are part of the current set of measures, following earlier social distancing measures such as school and nonessential business closures, bans on large gatherings, and shelter-in-place orders being considered by states and local governments, especially as regions of the country reopen. For example, during Virginia’s phase one reopening, begun May 22, 2020, everyone in the state was required to wear a face mask in public where people congregate.18 Even though more states have issued such orders since the study was completed, it is critical to provide direct evidence on this question not only for public health authorities and governments but also for educating the public.
Study Data And Methods
Data
We collected information on statewide face cover mandate orders from public data sets on such policies and from searching and reviewing all state orders issued between April 1 and May 21, 2020. Our study focused on state executive orders or directives signed by governors that mandate use. Recommendations or guidelines from state departments of public health were not included, as these largely follow the CDC guidelines and might not necessarily add further information or impact. See online appendix A for a more detailed description of the data sources and measuring of the mandates.19
States differ in whether or not they require their citizens to wear face masks (covers) to limit COVID-19 spread. Between April 8 and May 15, governors of fifteen states and the mayor of Washington, D.C., signed orders mandating all individuals who can medically tolerate the wearing of a face mask do so in public settings (for example, public transportation, grocery stores, pharmacies, or other retail stores) where maintaining six feet of “social distance” might not always be practicable. These sixteen jurisdictions also have specific mandates requiring employees in certain professions to wear masks at all times while working.
In addition to these sixteen jurisdictions, twenty additional states have employee-only mandates (but no community mandate) requiring that some employees (for example, close-contact service providers such as in barber shops and nail salons) wear a face mask at all times while providing services. The face mask defined in these orders primarily refers to cloth face coverings or nonmedical masks. The state orders strongly discourage the use of any medical or surgical masks and N-95 respirators, which should be reserved for health care workers and first responders. The orders also clearly specify that the face masks are not a replacement for any other social distancing protocols. More information on dates and links to these state orders are in appendix exhibit A1 and appendices D and E.19 Fifteen states had not yet issued community or employee mandates when we performed the study.
The main model used publicly available daily county-level data of confirmed COVID-19 cases from March 25 through May 21.20 The data covered all states plus Washington, D.C., and the analytical sample included 2,930 unique counties plus New York City (five boroughs combined). See appendix A for a more detailed description of COVID-19 data.19
Statistical Analysis
We employed an event study, which is generally similar to a difference-in-differences design, to examine whether statewide mandates to wear face masks in public affect the spread of COVID-19 based on the state variations noted earlier. This design allowed us to estimate the effects in the context of a natural experiment, comparing the pre-post mandate changes in COVID-19 spread in the states with mandates versus changes in COVID-19 spread in the states that did not pass these mandates, over time. The model also tested whether states issuing these mandates had differential pre-event trends in COVID-19 rates before they were issued. This is a critical assumption of the validity of an event study that must be upheld under testing. In addition, the model allowed us to control for a wide range of time-invariant differences between states and counties, such as population density and socioeconomic and demographic factors, plus time-variant differences between states and counties, such as other mitigation and social distancing policies, in addition to state-level COVID-19 testing rates.
We estimated the effects of face cover mandates on the daily county-level COVID-19 growth rate, which is the difference in the natural log of cumulative COVID-19 cases on a given day minus the natural log of cumulative cases in the prior day, multiplied by 100.21 This measure gives the daily growth rate in percentage points.
The reference period for estimating the face cover mandate effects was 1–5 days before signing the order. We examined how effects change over five post-event periods: 1–5, 6–10, 11–15, 16–20, and 21 or more days. The model also tested for pre-event trends over the course of 6–10, 11–15, and 16 or more days before signing the mandate. For all counties in the analytical sample, the main model included daily data from March 31 (seven days before the first state signed a face cover mandate) through May 22. The models were estimated by least squares weighted by the county’s 2019 population with heteroscedasticity-robust and state-clustered standard errors.
As noted earlier, all of the fifteen states plus Washington, D.C., that mandated face cover use in public also mandated employee mask use. To assess the effects of employee face cover mandates, we employed another event study model that focused solely on the employee face cover mandate as the policy intervention. In this analysis, we excluded the sixteen jurisdictions that enacted both public and employee face cover mandates and focused on the twenty states that enacted an employee-only mandate and the fifteen states with neither a public nor an employee mandate.
Limitations
We were unable to measure face cover use in the community (that is, compliance with the mandate). As such, the estimates represent the intent-to-treat effects of these mandates—that is, their effects as passed and not the individual-level effect of wearing a face mask in public on one’s own COVID-19 risk. Related, we did not measure enforcement of the mandates, which might affect compliance. We also did not have data on county-level mandates for wearing face masks in public. In some states without state-level mandates at the time of our study, such as California,22 Texas,23 and Colorado,24 multiple counties had enacted such mandates. These county-level mandates did not bias the intent-to-treat estimates of effects of state-level mandates as actually passed, but they added local-level heterogeneity not directly accounted for in the model. We did examine the robustness of estimates to the exclusion of some of these states. Finally, we were able to examine only confirmed COVID-19 cases. However, there is evidence of a higher infection rate in the community than is reflected in the number of confirmed cases.25
Study Results
Effects Of Mandates For Face Covering In Public
Exhibit 1 plots the event study estimates of effects of state mandates for community face covering in public on the county-level daily growth rate of COVID-19 cases, with 95 percent confidence intervals, obtained from the main regression model (in appendix B),19 using county-level daily data from March 31 through May22; appendix exhibit C1 (column 1) reports the exact estimates. The effects are shown over the course of five periods after signing the orders, relative to the five days before signing (which is the reference period). Also shown are estimated differences in daily COVID-19 growth rates between states with and without the mandates over the course of three periods before the reference period.
Exhibit 1 Event study estimates of the effects of states mandating community face mask use in public on the daily county-level growth rate of COVID-19 cases, 2020
SOURCE Authors’ analysis of US county-level COVID-19 case data between March 31 and May 22, 2020. NOTES Event study estimates (dots) and 95% confidence intervals (bars) of the effects of states mandating community use of face covers or masks when people are in public on the county-level daily growth rate of COVID-19 cases over different periods before and after the mandate order was signed. The reference period was the first five days before the mandate order was signed. The model controlled for major COVID-19 mitigation policies as time-varying (closure of K–12 schools, county-level or statewide shelter-in-place orders, nonessential business closure, closure of restaurants for dining in, closure of gyms or movie theaters), COVID-19 tests per 100,000 people, county fixed effects, and day fixed effects. The model was estimated by least squares weighted by the county 2019 population, and the standard errors were robust to heteroscedasticity and clustered at the state level.
There was a significant decline in daily COVID-19 growth rate after the mandating of face covers in public, with the effect increasing over time after the orders were signed. Specifically, the daily case rate declined by 0.9, 1.1, 1.4, 1.7, and 2.0 percentage points within 1–5, 6–10, 11–15, 16–20, and 21 or more days after signing, respectively. All of these declines were statistically significant (p<0.05 or less). In contrast, the pre-event trends in COVID-19 case growth rates were small and statistically insignificant.
We also projected the number of averted COVID-19 cases with the mandates for face mask use in public by comparing actual cumulative daily cases with daily cases predicted by the model if none of the states had enacted the public face cover mandate at the time they did (see details in appendix B).19 The main model estimates suggested that because of these mandates, 230,000–450,000 cases may have been averted by May 22. Estimates of averted cases should be viewed cautiously and only as general approximations.
Robustness Checks
We estimated multiple extensions of the main event study model to assess the robustness of estimates to different model specifications and sample choices. These checks started the event study on March 26; added flexible controls for social distancing measures, state reopening measures, employee face mask use mandates, and county-specific time trends; and allowed time trends to vary by sociodemographic indicators. Other checks used the mandate effective date instead of the signing date, used hyperbolic sine transformation to account for zero cases, included states as the unit instead of counties, included only urban counties, and excluded some states without state-level mandates but with multiple counties having local mandates. The detailed description and results of these robustness checks are in appendix C.19 The results were robust across these checks; effects were smaller when we used the effective dates instead of the signing dates, which differ by about two to three days, on average, suggesting earlier compliance, and when we used states as the unit of analysis. But the estimates remained meaningful and statistically significant in all checks.
Effects Of Employee-Only Face Cover Mandates
As noted earlier, we also directly assessed the effects of states mandating only that certain employees wear face masks. Twenty states issued employee use mandates but not community use mandates. We reestimated the event study model described earlier for an employee-only mandate including those twenty states (issued between April 17 and May 9) and the fifteen states without mandates, and excluding the sixteen jurisdictions that issued both public and employee use mandates. Exhibit 2 plots the event study estimates of changes in county-level daily COVID-19 growth rates with the employee-only face cover mandates and their 95 percent confidence intervals. All pre- and postmandate estimates were small and insignificant. Overall, these results indicate no evidence of declines in daily COVID-19 growth rates with employee-only mandates.
Exhibit 2 Event study estimates of effects of states mandating only employee use of face masks during working time on daily county-level growth rate of COVID-19 cases
SOURCE Authors’ analysis of US county-level COVID-19 case data between March 31 and May 22, 2020. NOTES Event study estimates (dots) and 95% confidence intervals (bars) of the effects of states mandating employee use of face covers or masks on the county-level daily growth rate of COVID-19 cases over different periods before and after the mandate order was signed. This model excluded fifteen states plus Washington, D.C., that made the use of face covering mandatory for both the general public and employees. The reference period was the first five days before the mandate order was signed. The model controlled for major COVID-19 mitigation policies as time-varying (closure of K–12 schools, county-level or statewide shelter-in-place orders, nonessential business closure, closure of restaurants for dining in, and closure of gyms or movie theaters), COVID-19 tests per 100,000 people, county fixed effects, and day fixed effects. The model was estimated by least squares weighted by the county 2019 population, and the standard errors were robust to heteroscedasticity and clustered at state level.
Discussion
Around the world, governments have been fighting COVID-19 spread through a mix of policies and mitigation measures such as school and nonessential business closures and shelter-in-place orders. Some countries have also recommended or mandated widespread community use of face masks as a mitigation measure. However, the effectiveness of this measure is highly debated. The debate and uncertainty are fueled by the limited direct empirical evidence available on the magnitude of the effects of widespread face mask use in public on COVID-19 mitigation. There is a critical need for empirical evidence on the magnitude of these effects from natural experiments.8 This evidence is especially relevant as governments reopen their economies and loosen social distancing restrictions while new infections continue to occur and while there is no vaccine or widely accessible or effective treatments in sight.
The study provides direct evidence on the effectiveness of widespread community use of face masks from a natural experiment that evaluated the effects of state government mandates in the US for face mask use in public on COVID-19 spread. Fifteen states plus Washington, D.C., mandated face mask use between April 8 and May 15. Using an event study that examined daily changes in county-level COVID-19 growth rates, the study found that mandating public use of face masks was associated with a reduction in the COVID-19 daily growth rate. Specifically, we found that the average daily county-level growth rate decreases by 0.9, 1.1, 1.4, 1.7, and 2.0 percentage points in 1–5, 6–10, 11–15, 16–20, and 21 or more days after signing, respectively.
These estimates are not small; they represent nearly 16 percent to 19 percent of the effects of other social distancing measures (school closures; bans on large gatherings; shelter-in-place orders; and closures of restaurants, bars, and entertainment venues) after similar periods from their enactment.21 The estimates suggest that the effectiveness of and benefits from these mandates increase over time. By May 22, 2020, the estimates suggest that 230,000–450,000 COVID-19 cases may have been averted on the basis of when states passed these mandates. Again, the estimates of averted cases should be viewed cautiously, as they are sensitive to assumptions and different approaches to transforming the changes in the daily growth rate estimates to cases.
The early declines in the daily growth rate over the course of five days after signing the order are broadly consistent with the timing of the effects of other social distancing measures such as business closures.21 Although the median incubation period is estimated to be around five days,26 there is a wide range from 2.2 days (2.5th percentile) to 11.5 days (97.5th percentile), which suggests that for many people, symptoms may appear relatively early. Further, people may become aware of the mandates early through governors’ briefings and related media reports, or they may be anticipating them.
There is no evidence of differential premandate COVID-19 trends with respect to issuing these mandates. The estimates represent the intent-to-treat effects of the statewide face cover mandates as passed, conditional on other national and local measures. In that way, the effects are independent of the CDC national guidance to wear face masks that was issued April 3, 2020.12 These effects were robust to several model checks. The study provides evidence from a natural experiment on the effectiveness of mandating public use of face masks in mitigating the spread of COVID-19. We found no evidence for effects of states mandating employee face mask use, perhaps because many businesses themselves already required their employees to wear masks.27,28 In that case, mandating employee mask use reinforce what many businesses already choose to do on their own.
Although the intent-to-treat estimates are of interest for understanding the effectiveness of these policies in limiting COVID-19 spread at the community and population levels, understanding how their effects change with compliance and enforcement strategies is important for designing effective policies. Our study has built the first step in estimating the overall effect of these policies as enacted. However, these policies vary in their strictness and the consequences of noncompliance. The mandates generally require wearing a face mask in public whenever the social distance cannot be maintained. States such as Delaware, Maryland, Massachusetts, and Maine clarify what “public” areas are (for example, indoor space in retail establishments, outdoor space in busy parking lots and waiting areas for take-out services, semi-enclosed areas such as at public transportation stops, and enclosed spaces such as in taxis and other public transportation). The language on enforcement and penalties for noncompliance also vary. In states such as Delaware, Hawaii, Maryland, and Massachusetts, the face mask orders state that they have the force and effect of law, with a willful violation subject to a criminal offense with penalties. For example, the order in Maryland states that “a person who knowingly and willfully violates this order is guilty of a misdemeanor and on conviction is subject to imprisonment not exceeding one year or a fine not exceeding $5,000 or both.”29 In contrast, the orders of other states such as Connecticut, Maine, and Pennsylvania, although clearly mandating the wearing of a face mask in public, do not appear to clearly specify that violations of the order are subject to criminal offense or penalties. Future work should examine whether and how differences in strictness and enforcement modify the effects of these mandates.
Compliance and enforcement may also differ across contextual factors (such as other social distancing measures, workforce distribution, population demographics, and socioeconomic and cultural factors). In that regard, it is important to clarify that the suggested benefits from mandating face mask use are not substitutes for other social distancing measures; the effects are conditional on the other enacted social distancing measures and how communities are complying with them. It is also important to extend the evidence into additional measures of exposure to the virus in the community as data become available, such as from serological testing for antibodies. Finally, future work can examine effects on deaths, which lag cases and change not only with the number of cases but also with case severity.
Conclusion
The study provides evidence that US states mandating the use of face masks in public had a greater decline in daily COVID-19 growth rates after issuing these mandates compared with states that did not issue mandates. These effects were observed conditional on other existing social distancing measures and were independent of the CDC recommendation to wear face covers issued April 3, 2020. As international and state governments begin to relax social distancing restrictions, and considering the high likelihood of a second COVID-19 wave in the fall and winter of 2020,30 requiring the use of face masks in public could help in reducing COVID-19 spread.
ACKNOWLEDGMENTS
An unedited version of this article was published online June 16, 2020, as a Fast Track Ahead Of Print article. That version is available in the online appendix.
NOTES
- 1
Wrong. Again. Call it 0 for 161 tries.
https://www.cbsnews.com/video/covid-deaths-and-cases-surge-in-new-peak-worldwide/
COVID deaths and cases surge in new peak worldwide
The coronavirus continues to devastate many countries worldwide, especially in India, where hospitals are at capacity and are facing an oxygen shortage. Elizabeth Palmer reports.MAY 2, 2021
LOL! Now change story from Anti-vaxxer to pro vax LOL! flip flop ADMIN So funny
When cornered with the facts and there is no more argument, they tend to admit they were wrong all along.
Seen it many times.
All I have to do is keep on presenting the facts to counter and ridiculous opinion.
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