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COVID-19: Mobile phone data exposes venues for ‘superspreader’



A SARS-CoV-2 transmission model indicates that the majority of infections are accounted for by a limited number of venue categories, such as restaurants, hotels, and religious venues. The model also helps understand why people live in poorer areas are affected overwhelmingly by infections.

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There is still significant confusion about the best ways to restore economic and social life to something close to normality almost a year after the start of the COVID-19 pandemic in Wuhan, China.

The model offers a method for defining high-risk venues and exploring possible ways out of lockdown, according to the developers of the new model at Stanford University, CA, and Northwestern University in Chicago, IL.

Computer scientists and medical researchers worked on the model, which reported the movements of 98 million citizens in the United States between March 1 and May 2, 2020, using anonymized location data from mobile phone networks.

At about 553,000 venues, the team modelled the number of infections occurring hour by hour, which they divided according to usage into 20 groups. They also took into account each venue’s floor space.

In 10 of the largest metropolitan regions, including Chicago, New York City, and San Francisco, their simulations correctly predicted daily reported infections.

The model indicates that reopening gyms, full-service restaurants, cafes, hotels, and religious venues, due to the high densities of individuals and their long periods of stay, contributes to the greatest rise in infections.

According to the model, a relatively small number of these “superspreader” venues account for the majority of new infections.

For instance, the model found that 85 percent of all infections accounted for 10 percent of all venues in the Chicago metropolitan area.

Capping numbers of visitors

On the upside, the model shows that it is more efficient and less disruptive to limit the number of people allowed into venues at any time than to uniformly reduce the freedom of movement of all.

The model, for instance, predicts that restricting a venue’s occupancy to 20% of its full capacity eliminates new infections by more than 80%.

Since people are likely to respond by spreading their visits more thinly during the day, however the measure reduces by a relatively modest 42 percent the total number of visits.

“The researchers write in their paper explaining the model, which appears in the journal Nature, “[O]one can achieve a disproportionately large reduction in infections with a small reduction in visits. “Precise approaches like these could be more successful than less focused steps, with slightly lower economic costs being incurred.”

“Our study emphasizes that it doesn’t have to be all or nothing,” Stanford University senior author Jure Leskovec said at a press conference to reveal the results.

“We can select different levels for different types of locations, he said and our model offers a tool for policymakers to basically manage and make the right choices for these trade-offs.”

Disadvantaged groups

In racially and socioeconomically deprived communities, the model correctly predicts higher infection rates.

During lockdowns, individuals within these classes have been shown to decrease their mobility levels to a lesser degree, possibly as a result of operating in critical services.

The model also showed that a few types of location, such as full-service restaurants, were driven by high infection rates in deprived areas.

The venues tended to be smaller compared with more affluent places, contributing to higher customer densities. Furthermore, individuals going to these venues appeared to stay longer.

In low-income areas for example, grocery stores had 59 percent more people per square foot than in higher-income areas, and their customers remained, on average 17 percent longer.

As a result, Leskovec said the model showed that the risk of infection was approximately twice as high for a low-income person visiting a grocery store compared to a high-income individual.

Cell phone data

The researchers drew on data from SafeGraph, a company that aggregates anonymized cell phone details.

The hourly movements of 98 million people from 57,000 neighbourhoods, which they call “census block groups,” or CBGs, to 553,000 separate locations, which they call “points of interest,” or POIs, were mapped using this data.

Their basic model of infection known as the SEIR model, predicts how individuals in each neighborhood and location transfer between four categories: vulnerable to infection, exposed to infection, contagious, and removed (recovered, self-isolated, or died).

Importantly, not only the locations of cell phone users are revealed by SafeGraph data, but also the floor space of venues they visit and their purpose, such as a place of worship or grocery store.

By using the local infection and death rates that The New York Times publishes online, the researchers “fine-tuned” their model.

Finally, they reported that the model could probably be used to forecast future rates of infection and death.

Missing groups of people

Dr. Julian Tang, a clinical virologist who was not involved in the research at the University of Leicester in the United Kingdom, welcomed the research but cautioned that its results might not be uniformly applicable.

“The use of cell phone data and modeling are powerful tools to help us understand how the virus spreads, but we need to be cautious about the interpretation as what may apply may not necessarily apply elsewhere in one population,” he said.

Kevin C. Ma and Marc Lipsitch of the Harvard T. H. Chan School of Public Health in Boston, MA, point out in a comment article accompanying the paper that the model does not account for infections among infants, older adults, and those in jail.

They write:

“Further model testing is needed, but given the challenges in gathering and interpreting other relevant data types, these findings could have a valuable role in guiding policy decisions on how to reopen society safely and minimize the harm caused by movement restrictions.”


Is alcohol antiviral? Things to know



Some viruses can be killed by alcohol, but not all. The virus’s efficiency is determined by the concentration and type of alcohol used, as well as the virus’s species.

The Centers for Disease Control and Prevention (CDC) recommend washing hands with soap and water, but this method is not always available. When it isn’t, alcohol-based hand sanitizers can help prevent viral illnesses like SARS-CoV-2, the virus that causes COVID-19, from spreading.

In addition to hand sanitizers, people can disinfect commonly touched devices in the home, such as phones and computer keyboards, with rubbing alcohol.

This page explains how alcohol kills viruses, how it works, and what concentrations to look for while using it. It also explains how to properly use hand sanitizers and rubbing alcohol.

Is alcohol antiviral?

alcohol and virus

A 2020 study found that both isopropyl and ethyl alcohol can kill viruses. Rubbing alcohol contains isopropyl alcohol, while alcoholic beverages include ethyl alcohol.

The efficacy of these alcohols varies with concentration and viral type. Nonenveloped viruses lack a lipid membrane, whereas enveloped viruses do. Encapsulated viruses are more susceptible to disinfectants.

Isopropyl alcohol kills enveloped viruses but not nonenveloped. Ethyl alcohol kills enveloped and non-enveloped viruses. They both have significant antiviral properties against:

These alcohols have little antiviral activity against viruses like polio and hepatitis A.

How does it work?

Few researches on alcohol’s antiviral effects Scientists believe alcohol damages the virus’s cell membrane by altering its protein structure. An essay from 2021 calls this “denaturing and coagulation.” The virus cannot multiply or infect without a functioning membrane.

Adding water to alcohol denaturizes proteins more effectively. Because alcohol evaporates quickly. It takes longer for viruses to digest alcohol in water.

Alcohol and SARS-CoV-2

The virus that caused the COVID-19 pandemic is SARS-CoV-2. Alcohol is beneficial against SARS-CoV-2 because the outermost membrane includes lipids.

According to a study published in 2020, ethyl or isopropyl alcohol at particular doses rendered the virus inactive after 30 seconds. When soap and water are not available, the CDC recommends using alcohol-based hand sanitizers to prevent SARS-CoV-2 transmission.

How strong does the alcohol need to be?

According to a study published in 2021, the recommended alcohol content in sanitizers is either 80 percent ethyl alcohol or 75 percent isopropyl alcohol. According to the CDC, sanitizers containing at least 60% alcohol are also effective.

The influence of hand sanitizer formulations on SARS-CoV-2 was studied in 2020, and it was discovered that concentrations more than or equal to 30% resulted in full viral inactivation.

What is the best way to use alcohol at home?

To clean small things and high-touch surfaces like phones and door handles, people can use alcohol-based sanitizers or rubbing alcohol around the house. To clean these objects, first do the following:

  • Make sure the room is well ventilated.
  • Using a cotton pad, apply rubbing alcohol.
  • To avoid inhaling, replace the cap.
  • Wipe the surface using the pad.
  • Safely dispose of the cotton pad.

Rubbing alcohol, according to the National Capital Poison Center, poses a number of risks. If a person inhales the fumes or drinks any amount of it, even little amounts are dangerous. To lessen the risk, one should:

  • rub alcohol should be kept out of the reach of children
  • It should only be used in well-ventilated areas
  • Keep a safe distance from open flames
  • don’t ever swallow rubbing alcohol

What is the best way to use alcohol on the skin?

Alcohol can be applied to the skin in two ways to kill viruses. The first is to use a hand sanitizer gel that is alcohol-based. Applying some gel to the palms and massaging it all over the hands, including between the fingers, is how people can use it. Then wait for it to dry.

Doctors no longer advocate using rubbing alcohol to clean wounds since it can cause more tissue damage. Instead, a person can clean the area under running tap water for 5–10 minutes before gently dabbing or wiping the skin with a gauze pad soaked in saline solution or tap water. They can also use an alcohol-free wipe instead.

Are there any risks associated with using alcohol to eliminate viruses?

Alcohol gels other sterilising treatments are excellent in killing a variety of potentially hazardous microorganisms, but they have some drawbacks.

Inferior to washing with soap and water

When feasible, the CDC recommends washing hands with soap and water. Soap and water, unlike hand sanitizers, can eradicate all types of bacteria from the hands. Bacteria, viruses, and other chemicals, such as pesticides, are all included.

Handwashing with soap and water is required in various conditions for optimal hygiene. These are some of them:

  • before, during, and after food preparation
  • after using the toilet
  • after touching garbage
  • when the hands are visibly greasy or dirty
  • before and after caring for a person who is sick
  • before and after visiting someone with a weakened immune system

If soap and water aren’t available, use a sanitizer with at least 60% alcohol content.

Inferior to other surface cleaners

When it comes to cleaning surfaces or equipment, alcohol is less effective than other disinfectants. In hospitals, for example, instead of using alcohol to clean surfaces like floors, workers often use hydrogen peroxide or other disinfectants.

These compounds can destroy a wider range of germs than alcohol, and because they don’t evaporate as rapidly, they stay in contact with the microbes for longer. They do, however, have their own set of advantages and disadvantages, and they have not completely replaced alcohol.

Alcohol’s rapid evaporation might be beneficial when sanitising noninvasive equipment like thermometers. Alcohol, unlike hydrogen peroxide, does not stain or damage clothing or materials.

Antibiotic resistance

In addition to their antiviral characteristics, alcohol-based sanitizers include antibacterial capabilities. Bacteria, on the other hand, can change over time to the point where compounds no longer damage them. Antibiotic resistance is the term for this.

According to some academics, hand sanitizers may lead to antibiotic resistance. However, according to a study published in 2021, alcohol has not been proved to cause bacterial resistance.

To limit the risk of residual bacteria gaining resistance, some experts recommend using a hand sanitizer for a full 20–30 seconds and then letting it to dry.


Both isopropyl and ethyl alcohol have the ability to destroy viruses with lipid-high cell membranes. SARS-CoV-2, as well as HIV, hepatitis B, and herpes viruses, fall within this category. Alcohol inhibits viral function by altering the structure of the viral membrane.

Using soap and water to wash your hands is preferable to using alcohol-based sanitizers. People can use hand gels containing 60–90 percent Trusted Source alcohol if this alternative is not accessible. 80 percent ethanol or 75 percent isopropyl alcohol are the best amounts.

Rubing alcohol can also be used to clean tiny items around the house, but it is important to use caution when handling it.



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What lies ahead for SARS-CoV-2 variants?



The majority of mutations in the coronavirus that causes severe acute respiratory syndrome (SARS-CoV-2) produce only minor harm. A modest number of alterations, on the other hand, can increase viral pathogenicity and strengthen host-virus interactions, both of which are necessary for viral entrance and infection. Because the spike protein promotes viral attachment to host cell surface receptors, changes in the SARS-CoV-2 spike protein can have a profound impact on viral behavior.

To avoid the formation of new SARS-CoV-2 variations that are resistant to currently existing vaccinations and treatments, it is critical to monitor and limit virus circulation. Despite the efforts of several governments throughout the world, mass vaccination campaigns have not attained the population coverage essential to prevent SARS-CoV-2 transmission,

SARS-CoV-2 variants
Image Credit: Naeblys /

SARS-CoV-2 variant classification

It is critical to examine the emergence and spread of variations, as well as their effects on disease transmission and human health, in order to effectively control the pandemic. SARS-CoV-2 variations with a potential public health risk have been divided into three groups by the World Health Organization (WHO): variants under monitoring (VUMs), variants of interest (VOIs), and variants of concern (VOCs).

VUMs are viral variations having genetic alterations that change viral properties, but their phenotypic or epidemiological significance is unknown. Mutations in VOIs can influence infectivity, disease progression, and diagnostic or therapeutic escape, potentially resulting in community transmission and a global public health issue. VOCs have been linked to higher transmissibility, virulence, or disease severity, as well as the ability to reduce the efficacy of interventions, diagnostics, therapies, and vaccinations.

Because the virus is constantly evolving, these varieties may need to be categorized in the future. Quantifying the number of variations that could constitute a public health risk is essential for future planning in the battle against viral outbreaks.

About the study

Researchers used a function that solely rely on the global number of infected cases since the start of the pandemic to fit data on the most important SARS-CoV-2 variants according to the WHO in a new study published on the preprint platform medRxiv*. Their match allows for a fairly accurate estimate of the number of SARS-CoV-2 variants that could emerge for a given number of infected people around the world. In every epidemiological circumstance, our novel technique can also anticipate the amount of new relevant variations per 10 million instances.

The researchers gathered data on SARS-CoV-2 variants, including WHO-reported variant characteristics, PANGO (Phylogenetic Assignment of Named Global Outbreak) classification, current relevance (VOC, VOI, or VUM), date and country of first detection, total number of global cases at the end of the month of detection, and a cumulative number of variants. PANGO is a nomenclature method for recognizing and tracking SARS-CoV-2 genomic lineages. The WHO data was numerically fit using the function v(N) = k x Nlog N, where k is the numerical fit constant and is equal to 3.35 x 10−6.

“Our method depends critically on the WHO efficiency in tracking the most relevant SARS-CoV-2 variants.”

Study findings

According to the study’s findings, there were almost 44 SARS-CoV-2 subtypes that were relevant until November 2021. In November 2021, the number of new relevant variants per ten million cases was 1.64, decreasing 28.4 percent from 2.29 in March 2020.

Cumulative number of relevant SARS-CoV-2 variants
Cumulative number of relevant SARS-CoV-2 variants versus the cumulative number of cases in the world. The dots from 1 to 10 indicate the data reported by WHO [12] from March 2020 to May 2021; the solid line represents the numerical fit υ = k · N/log N obtained with Wolfram Mathematica

Until November 2021, there were around 252 million COVID-19 instances worldwide, which corresponded to 43.7 relevant variants. This is nearly 19 variations more than what the WHO published in May 2021.


The number of new significant variations per ten million instances fell relatively slowly as the total number of cases increased, according to the findings of this study. As a result, new SARS-CoV-2 variations will continue to evolve as long as the virus is in circulation.

Using the cumulative global number of infected cases, the scientists developed a mathematical model to calculate the number of relevant SARS-CoV-2 variants. This model simply looked at the relationship between the number of virus replications and the appearance of important variants, ignoring all other parameters that affect the spread of new variants.

The capacity to anticipate the frequency of new relevant SARS-CoV-2 variations will be critical in the future for effective vaccination campaign planning, as novel variants can change viral properties and have a significant impact on global pandemic management.

*Important notice

Preliminary scientific papers published on medRxiv are not peer-reviewed and should not be regarded as conclusive, should not be used to influence clinical practice or health-related behavior, and should not be recognized as established information.

Journal reference:

Littera, R., & Melis, M. (2021). How many relevant SARS-CoV-2 variants might we expect in the future? medRixv.

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COVID-19 boosters to prevent SARS-CoV-2 infections in adults



Since it was initially announced on March 11, 2020, the unusual coronavirus disease 2019 (COVID-19) pandemic produced by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has posed a threat to world health. Since then, the BNT162b2/Pfizer and mRNA-1273/Moderna messenger ribonucleic acid (mRNA) vaccines against SARS-CoV-2 have been rolled out in two-dose regimens in the United States, with a December 2020 deadline. Both of these vaccines provide at least six months of protection against COVID-19-related hospitalization and mortality.

COVID-19 booster vaccine

Because of the weakened immunity, the transmission of the SARS-CoV-2 B.1.617.2 (Delta) variant increased, resulting in a larger number of COVID-19 cases in the summer of 2021. Booster vaccines for higher-risk persons were approved by the US Food and Drug Administration in response to the abrupt surge in illnesses.

Serological studies have since showed that the antibody response increases significantly from the first to the second dosage of the mRNA vaccines. However, after six months of full vaccination, the duration and amount of antibody response to booster doses are uncertain.

Understanding COVID-19 booster antibody responses

Researchers measured anti-receptor-binding domain (RBD) immunoglobulin G (IgG) and surrogate virus neutralization of the interaction between the SARS-CoV-2 spike protein and the human angiotensin-converting enzyme (ACE2) receptor before and after vaccination with boosters in 33 healthy adults in a recent study published on the medRxiv* preprint server. Participants were requested to fill out an e-consent form and complete online surveys about their COVID-19 vaccination status and history.

Before receiving the booster dose, the subjects supplied finger stick dried blood spot samples, which were collected 6-10 days later. The study’s findings were compared to data from a previous community-based study that followed the identical protocols.

The antibody responses were assessed in a prior community-based trial after SARS-CoV-2 infection or after receiving the second dose of the mRNA vaccine. The presence of anti-RBD IgG before vaccination was used to classify the participants as seropositive or seronegative.

Findings of the research

The study’s findings revealed that antibody responses after 6-10 days of receiving the booster dose are higher than natural SARS-CoV-2 infection, after two doses of the mRNA vaccine, and after both natural infection and immunization. Notably, females’ post-booster IgG levels were greater than men’ and were adversely associated to age.

In addition, the SARS-CoV-2 Delta variant displayed strong surrogate neutralization, but this response was still lower than that shown after exposure to the wild-type SARS-CoV-2 strain. There were no differences in SARS-CoV-2 Delta variant neutralization between males and females, although the inhibitory concentration of 50% (IC50) was adversely related to age.

COVID-19 boosters to prevent SARS-CoV-2 infections in adults
A) Response to COVID-19 mRNA vaccine and booster was measured as anti-RBD IgG antibodies from dried blood spots. Median IgG concentration (black dashed line) increased from 4.4µg/ml pre-booster to 101.6µg/ml post-booster (*p<0.001). Grey dotted lines represents paired samples. n=33. B) There was a median 25-fold change post-booster. C) Median anti-RBD IgG concentration (black dashed line) are shown. Individuals with outpatient COVID-19 had a median of 1.92 µg/ml (n=76) 14-42 days after infection, while individuals with a history of COVID-19 followed by vaccination were higher (60.61µg/ml, n=73, 5-42 days after 2nd dose). Individuals without a known history of COVID-19 who were either seropositive or seronegative and then 2-dose vaccinated had median IgG of 34.15µg/ml (n=181) and 33.09µg/ml (n=687), respectively. Pre-booster levels mean 237.9 days after 2-doses of vaccine were 4.4 µg/ml (n=33) compared to post-booster vaccination level of 101.6 µg/ml (n=33). Dotted lines represent the 25th and 75th percentiles. (*p<0.001).


The findings suggested that giving BNT162b2/Pfizer or mRNA-1273/Moderna boosters to healthy adults could prevent infections from progressing due to the production of significant antibody responses. Furthermore, when compared to antibody-mediated immunity created after the second vaccine dosage, antibody-mediated immunity may be sustained for a longer period of time.

The study has several drawbacks, including a short timeframe, a small sample size, and the lack of cellular immunity tests. Future research can look into the impact of boosters on cell-mediated immunity.

“These data support the use of boosters to prevent breakthrough infections and suggest that antibody-mediated immunity may last longer than after the second vaccine dose.”

*Important notice

Preliminary scientific papers published on medRxiv are not peer-reviewed and should not be regarded as conclusive, should not be used to influence clinical practice or health-related behavior, and should not be recognized as established information.

Journal reference:

  • Demonbreun, A. R., Sancilio, A., Vaught, L. A., et al. (2021). Antibody titers before and after booster doses of SARS-CoV-2 mRNA vaccines in healthy adults. medRxiv.

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