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Extremely Rare Phenomenon Sees Babies Inhale Cancer Cells During Vaginal Birth

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It’s not impossible for an infant to get cancer from their mother, but it doesn’t happen very often.

Researchers estimate transmission of maternal cancer to offspring occurs perhaps only twice in every million births for mothers with cancer, with the diseased cells being delivered to the infant via the placenta in these exceedingly rare and unfortunate cases.


But that’s not the only way a mother with cancer might unknowingly infect her child, scientists say.

In a new case study published by researchers in Japan, doctors report what appears to be a medical first: vaginal transmission of cancer cells from mothers with cervical cancer to infants at the moment of their birth.

“Mother-to-infant transmission of tumour in the birth canal during vaginal delivery is also theoretically possible,” the researchers, led by paediatric oncologist Ayumu Arakawa from the National Cancer Centre Hospital in Tokyo, explain in their paper.

“If the mother has cervical cancer, the infant can be exposed to tumour cells in fluids in the birth canal and could aspirate tumour cells into the lungs.”

This obscure and previously unknown vector – inhaling cancer in your very first breaths, ostensibly – appears to be responsible for two otherwise unlinked cases of paediatric lung cancer diagnosed in a pair of young male patients: a 23-month-old and a six-year-old.

In both cases, the patients presented to hospital with symptoms of their illness, the 23-month-old experiencing coughing, and the six-year-old experiencing chest pain.


In each instance, CT scans revealed what eventually turned out to be cancerous tumours in the boys’ lungs, which were successfully treated in both cases – although not easily.

Both the young patients received repeated bouts of chemotherapy, but were only cleared of disease after having operations to remove the cancerous tissue: in the case of the 23-month-old, a cancerous lobe of lung tissue was taken out, while the six-year-old needed his entire left lung removed.

While it’s impossible to know for sure how these boys developed the cancerous growths in their lungs, the researchers say they’ve identified the most probable cause.

In the case of the 23-month-old, his 35-year-old mother, who had not received a vaccination against human papillomavirus (HPV), received a diagnosis of cervical cancer just three months after the infant’s birth, having tested negative seven months before. Eventually, the tumours spread to her lung, liver, and bones, and she died.

However, analysis of the tissue from her cervical tumour and her son’s lung tumour revealed gene profile similarities in the form of certain mutations and alleles, and the lack of the Y chromosome – suggesting the boy’s cancer had come directly from his mother.


The six-year-old’s tumours bore the same genetic signatures of his own mother’s cervical cancer – which was first observed via a tumour that was detected during her pregnancy, but considered, unfortunately incorrectly, to be stable. She later had her uterus removed, along with her fallopian tubes and ovaries, but passed away two years after the surgery from the disease.

Based on all the above – and that both sons’ tumours also bore the hallmarks of the HPV genome – the researchers concluded the lung cancer in the children was caused by transmission of cervical tumours from the children’s mothers.

“The peribronchial [relating to airways of the respiratory system] pattern of tumour growth in both children suggested that the tumours arose from mother-to-infant vaginal transmission through aspiration of tumour-contaminated vaginal fluids during birth,” the team explains.

In most cases involving mother-to-foetus transmission of cancer, the placental delivery of cancerous cells tends to result in the spreading of cancers to the brain, bones, liver, and other tissues, including the lungs. Here, it was just the lungs – which offers a strong clue as to how the disease could have been delivered to the boys’ own bodies.


“In our two patients, tumours were observed only in the lungs and were localised along the bronchi,” the authors write.

“It is likely that maternal tumour cells were present in the amniotic fluid, secretions, or blood from the cervix and were aspirated by the infants during vaginal delivery.”

While the chances of this route of cancerous infection would appear to be incredibly slim for any individual family, the researchers stress that prevention via HPV vaccination would further prevent this method of transmission from occurring – an especially important message in the context of Japan, which has a troubled history with HPV vaccinations.

Further, the researchers suggest caesarean section should be the recommended form of birth for mothers with a history of uterine cervical cancer.

Beyond those takeaways, these grim cases of an extremely rare medical phenomenon serve as a remarkable example of how much we have yet to learn about cancer – and the insidious routes via which the disease appears to spread itself.

“I found it fascinating, personally,” Debbie Saslow, the senior director of HPV-related and women’s cancers at the American Cancer Society, who wasn’t involved with the study, told Health Day.

“I didn’t know this was possible.”

The findings are reported in The New England Journal of Medicine.


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AI Predicts 96% of COVID-19 Pneumonia Cases That Will Require Intensive Care

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As intensive care units hit capacity in many parts of the world, doctors are having to make hard decisions about who gets a bed amid a global pandemic.

While most people who contract COVID-19 ultimately recover, some can go on to develop severe pneumonia at a rapid pace that causes diffuse damage, acute lung failure, and even death.


Now, a new machine learning algorithm could help us figure out who is most at risk, so we can intervene early and hopefully save their lives.

Recent machine learning approaches have tended to rely solely on chest scans to predict who might need a hospital bed. The algorithms search the scans for lung abnormalities and can detect COVID-19-related pneumonia in roughly 90 percent of cases.

But what these scans can’t tell us with nearly as much accuracy is how severe those cases might become, and who is the most vulnerable.

The new algorithm takes things a step further, by combining chest scans with non-imaging data, such as demographic information, vital signs and blood work. And it’s the best we have so far at predicting when someone needs ICU intervention. 

To be fair, the approach has only been tested using health data from 295 patients, hospitalised for COVID-19 either in the United States, Iran or Italy. But even in these early stages, it was able to predict as many as 96 percent of all COVID-19 cases that would require ICU admission, according to a preprint paper.


“As a practitioner of AI, I do believe in its power,” says engineer Pingkun Yan from Rensselaer Polytechnic Institute.

“It really enables us to analyze a large quantity of data and also extract the features that may not be that obvious to the human eye.” 

During a global pandemic, that sort of insight is invaluable and potentially life-saving. Those who develop the most severe cases of COVID-19 pneumonia should have a number of common features; finding the right ones is a lot quicker for a clever machine than it is for a human.

Already, machine learning tools have been used to assess which signs are most likely to predict COVID-19 mortality. 

Initial findings suggest ventilator use and potassium levels are the most important non-imaging variables, although other contributors have also been identified, including lymphocyte percentage, total bilirubin, creatinine, and albumin levels to name a few.

One study even found non-imaging data alone, including age, fever, and abnormal breathing could predict whether patients with COVID-19 need to be admitted to the ICU. 

The new algorithm combines both approaches. First, it quantifies the extent and volume of lung features. Then, it focuses on those features that are most important in predicting COVID-19 pneumonia. Lastly, it uses other contextual factors to predict which cases will turn out the most severe.


“To the best of our knowledge, this is the first study that uses holistic information of a patient including both imaging and non-imaging data for outcome prediction,” the authors claim.

The team hopes with further refinement, the tool can one day be used to screen for high-risk patients with COVID-19 pneumonia, who require closer monitoring and care.

While the team didn’t test how COVID-19 pneumonia compares to other respiratory diseases, the broad similarities in lung distress suggest the algorithm might prove useful even when the pandemic is over.

“We actually are seeing that the impact could go well beyond COVID diseases. For example, patients with other lung diseases,” Yan says.

“Assessing their heart disease condition, together with their lung condition, could better predict their mortality risk so that we can help them to manage their condition.” 

The preprint study was published in Medical Image Analysis.


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A Day-by-Day Breakdown of Coronavirus Symptoms Shows How The Disease Progresses

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As doctors observe a growing number of coronavirus patients, they have identified a few patterns in how typical symptoms progress.

As many as 40 percent of coronavirus cases are asymptomatic, according to the Centres for Disease Control and Prevention. And 20 percent of symptomatic cases become severe or critical.


Among patients who develop symptoms, a fever and cough are usually the first to arrive. They’re often followed by a sore throat, headache, muscle aches and pains, nausea, or diarrhoea (though in severe cases, gastrointestinal issues can appear earlier in the course of an infection).

Patients with severe infections tend to develop difficulty breathing – one of the virus‘ hallmark symptoms – around five days after symptoms start.

But symptoms generally don’t appear right after a person has been infected. The virus’ median incubation period is about four to five days, according to the Centres for Disease Control and Prevention.

During that time, an infected person likely won’t yet know they’re sick, but evidence shows they could transmit the virus during the presymptomatic phase.

A day-by-day breakdown

After observing thousands of patients during China’s outbreak earlier this year, hospitals there identified a pattern of symptoms among COVID-19 patients:


  • Day 1: Symptoms start off mild. Patients usually experience a fever, followed by a cough. A minority may have had diarrhoea or nausea one or two days before this, which could be a sign of a more severe infection.
  • Day 3: This is how long it took, on average, before patients in Wenzhou were admitted to the hospital after their symptoms started. A study of more than 550 hospitals across China also found that hospitalized patients developed pneumonia on the third day of their illness.
  • Day 5: In severe cases, symptoms could start to worsen. Patients may have difficulty breathing, especially if they are older or have a preexisting health condition.
  • Day 7: This is how long it took, on average, for some patients in Wuhan to be admitted to the hospital after their symptoms started. Other Wuhan patients developed shortness of breath on this day.
  • Day 8: By this point, patients with severe cases will have most likely developed shortness of breath, pneumonia, or acute respiratory distress syndrome (ARDS), an illness that may require intubation. ARDS is often fatal.
  • Day 9: Some Wuhan patients developed sepsis, an infection caused by an aggressive immune response, on this day.
  • Days 10-11: If patients have worsening symptoms, this is the time in the disease’s progression when they’re likely to be admitted to the ICU. These patients probably have more abdominal pain and appetite loss than patients with milder cases.
  • Day 12: In some cases, patients don’t develop ARDS until nearly two weeks after their illness started. One Wuhan study found that it took 12 days, on average, before patients were admitted to the ICU. Recovered patients may see their fevers resolve after 12 days.
  • Day 16: Patients may see their coughs resolve on this day, according to a Wuhan study.
  • Day 17-21: On average, people in Wuhan either recovered from the virus and were discharged from the hospital or passed away after 2.5 to 3 weeks.
  • Day 19: Patients may see their shortness of breath resolve on this day, according to a Wuhan study.
  • Day 27: Some patients stay in the hospital for longer. The average stay for Wenzhou patients was 27 days.

5f7dee2b94fce90018f7ba8d(Shayanne Gal/Insider)

Just because patients leave the hospital, though, doesn’t mean their symptoms are fully gone. Some coronavirus patients report having symptoms for months, including chest pain, shortness of breath, nausea, heart palpitations, and loss of taste and smell.

People who got sick and were never hospitalized can have lingering symptoms, too.


July report from CDC researchers found that among nearly 300 symptomatic patients, 35 percent had not returned to their usual state of health two to three weeks after testing positive.

Patients who felt better after a few weeks said their symptoms typically resolved four to eight days after getting tested. Loss of taste and smell usually took the longest to get back to normal, they said: around eight days, on average.

COVID-19 may be a vascular disease more than a respiratory one

Though the coronavirus attacks the lungs first, it can infect the heart, kidneys, liver, brain, and intestines as well. Some research has suggested that COVID-19 is a vascular disease instead of a respiratory one, meaning it can travel through the blood vessels. This is the reason for additional complications like heart damage or stroke.

Scientists have a few theories about why some coronavirus patients take a rapid turn for the worse. One is that immune systems overreact by producing a “cytokine storm” – a release of chemical signals that instruct the body to attack its own cells.


Dr. Panagis Galiatsatos, a pulmonary physician at Johns Hopkins Bayview Medical Centre, compared that process to an earthquake – generally, it’s the falling buildings that kill someone, not the quake itself.

“Your infection is a rattling of your immune system,” he said. “If your immune system is just not well structured, it’s just going to collapse.”

The most concerning symptom: shortness of breath

Once symptoms appear, some early signs should be treated with more caution than others.

“I would of course always ask about shortness of breath before anything, because that’s somebody who has to be immediately helped,” Megan Coffee, an infectious-disease clinician who analysed the Wenzhou data, told Business Insider.

Patients who develop ARDS may need to be put on a ventilator in ICU. Coffee estimated that one in four hospitalized COVID-19 patients wind up on the ICU track. Those who are ultimately discharged, she added, should expect another month of rest, rehabilitation, and recovery.

But viewing coronavirus infections based on averages can hide the fact that the disease often doesn’t progress in a linear fashion.

“Courses can step by step worsen progressively. They can wax and wane, doing well one day, worse the next,” Coffee said.

“An 80-year-old man with medical issues can do quite well. Sometimes a 40-year-old woman with no medical issues doesn’t.”

This story was originally published February 21, 2020. It has been updated over time with additional research findings.

This article was originally published by Business Insider.

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The US Could Begin Coronavirus Vaccinations Within Weeks, Official Says

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The United States hopes to begin coronavirus vaccinations in early December, a top government health official said Sunday, the latest positive news to emerge even as cases surge across the worst-hit nation and elsewhere around the globe.


The beginning of vaccinations could be a crucial shift in the battle against a virus that has claimed more than 1.4 million lives worldwide, including 255,000 just in the US, since emerging from China late last year.

Encouraging results from vaccine trials have bolstered hopes for an end to the pandemic, as nations reimpose restrictions and lockdowns that slowed the spread earlier this year but turned lives and economies upside down across the globe.

Two leading vaccine candidates – one by Pfizer and German partner BioNTech and another by US firm Moderna – have been shown to be 95 percent effective in trials, and Pfizer has already applied for emergency use approval from US health authorities.

“Our plan is to be able to ship vaccines to the immunization sites within 24 hours of approval” by the US Food and Drug Administration, Moncef Slaoui, head of the US government virus vaccine effort, told CNN, pointing to possible dates of December 11-12.

FDA vaccine advisors will meet December 10 to discuss approval.

Slaoui estimated that 20 million people across the US could be vaccinated in December, with 30 million per month after that.


But top US infectious disease official Anthony Fauci, who said “maybe 20 million people will be able to get vaccinated by the middle to the end of December,” warned the situation could get worse before getting better if people fail to take precautions in the coming holiday season.

“We’re in a very difficult situation at all levels,” he told CBS’s “Face the Nation.”

Vaccines for all?

With cases surpassing 12 million in the United States, the highest in the world, many Americans were nonetheless heading to airports to travel for this week’s Thanksgiving holiday, despite health officials’ warnings to stay home.

Some US states were imposing new restrictions, including California, where a 10:00 pm to 5:00 am curfew took effect Saturday. New York city has closed schools again.

US drug regulators on Saturday already gave emergency approval to a Covid-19 antibody therapy – one used by US President Donald Trump – that could help treat those infected.

However, G20 nations were pushing for “equitable” global access to vaccines, with worries poorer nations will be left behind.

German Chancellor Angela Merkel said more needed to be done, since no major vaccine agreements had been struck yet for poorer nations.


“We will now speak with (global vaccine alliance group) GAVI about when these negotiations will begin because I am somewhat worried that nothing has been done on that yet,” Merkel told reporters on Sunday in Berlin after a virtual G20 summit hosted by Saudi Arabia.

There were signs that restrictions being imposed in certain countries were helping slow infections.

Spanish Prime Minister Pedro Sanchez, whose country has been badly hit by the pandemic, said Sunday that a strategy to curb infections was working.

Spain declared a state of emergency last month, which allowed regional governments to impose virus restrictions such as nighttime curfews.

The country has recorded fewer than 400 Covid-19 cases per 100,000 inhabitants over the last two weeks, compared to nearly 530 cases at the start of the month, he told a news conference after the G20 summit.

‘A mockery’

But the restrictions and mask-wearing rules have led to pushback and protests in some countries, particularly the United States, where Trump supporters have railed against closures.

Similar pushback has been seen elsewhere, and German Foreign Minister Heiko Maas lashed out Sunday at anti-mask protesters comparing themselves to Nazi victims, accusing them of trivializing the Holocaust and “making a mockery” of the courage shown by resistance fighters.


The harsh words came after a young woman took to the stage at a protest against coronavirus restrictions in Hanover Saturday saying she felt “just like Sophie Scholl,” the German student executed by the Nazis in 1943 for her role in the resistance.

Government measures introduced to halt the spread of the coronavirus have triggered large protests in Germany, drawing in people from the far-left, conspiracy theorists and right-wing extremists who claim the curbs infringe on their civil rights.

While necessary to stop the spread of the virus, restrictions have taken a heavy toll on economies across the world.

The latest warning came on Sunday from Britain’s finance minister Rishi Sunak, who said the country’s economy was under “enormous strain and stress.”

Britain has suffered more than any other country in Europe from the coronavirus, recording more than 54,000 deaths from 1.4 million cases.

In November, Prime Minister Boris Johnson’s government imposed a four-week lockdown to stop the spread of the disease. That is due to be partially lifted on December 2, giving some relief to businesses.

© Agence France-Presse


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Superspreader Events Played a Key Role in Igniting The Current Pandemic Globally

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At churches, on cruise ships, and even in the White House, superspreading events that can sicken dozens, even hundreds, of people have illustrated the potential for the coronavirus to infect in dramatic bursts.​


Experts say these large clusters are more than just extreme outliers, but rather the pandemic‘s likely main engine of transmission.

And understanding where, when, and why they happen could help us tame the spread of the virus in the period before a vaccine may be widely available.

Research increasingly suggests that the coronavirus SARS-CoV-2 does not fan out evenly across the population, but spreads at the extremes in an almost “all or nothing” pattern.

Many studies now suggest the majority of people with COVID-19 barely pass it on to anyone else, but when infections happen, they can be explosive and supercharge an outbreak.

Then the virus can infect “10, 20, 50, or even more people”, said Benjamin Althouse, research scientist at the Institute for Disease Modeling.

This corresponds to the “80/20 rule” of epidemiology, where 80 percent of cases come from only 20 percent of those infected, but Althouse said this coronavirus may be even more extreme, with 90 percent of cases coming from potentially just 10 percent of carriers.

This transmission pattern is like “throwing matches on a pile of kindling”, he told AFP.


“You throw one match, it doesn’t ignite. You throw another match, it doesn’t ignite. You throw yet another match, and this time you see flames blaze up,” he said.​

“For SARS-CoV-2, this means that while it is difficult to establish in new places, once established, it can spread rapidly and far.”

Virus ‘hallmark’

Superspreading events have grabbed headlines, looming large in the narrative of the unfolding pandemic.​

In February, the Diamond Princess and its 4,000 passengers spent weeks in quarantine at port in Japan as the number of infections on board climbed, reaching 700.​

The same month a 61-year-old woman, known as “Patient 31”, attended several church services of the Shincheonji Church of Jesus in the South Korean city of Daegu.​

The Korea Centers for Disease Control and Prevention has since linked more than 5,000 infections to Shincheonji.

More recently the virus managed to infiltrate the White House despite a host of measures to keep it out.

Political gatherings, business conferences, and sports tournaments have all acted as infection incubators, but these high profile events could just be the tip of the iceberg.


A study by US researchers, based on one of the world’s largest contact tracing operations and published in Science in September, found that “superspreading predominated” in transmission.

Analysing data from the first four months of the pandemic in the states of Tamil Nadu and Andhra Pradesh in India, the authors found that just eight percent of infected individuals accounted for 60 percent of new cases, while 71 percent of people with the virus did not pass it on to any of their contacts.

Perhaps this should not be a surprise.

Maria Van Kerkhove, an infectious disease epidemiologist at the heart of the World Health Organization‘s pandemic response, tweeted in October that “superspreading is a hallmark” of coronaviruses.

Indeed, it has been observed in many infectious diseases.

One of the most famous superspreaders was Mary Mallon, a cook working in New York in the early 1900s who was the first documented healthy carrier of typhoid bacteria in the US.

Blamed for giving the illness to dozens of people, she was given the unsympathetic label “Typhoid Mary” and forcibly confined for years.

Measles, smallpox and Ebola also see clustering patterns, as did the other coronaviruses, SARS and MERS.


K factor

Early in the pandemic, much attention was focused on the basic reproduction number (R0) of SARS-CoV-2.

This helps calculate the speed a disease can spread by looking at the average number of others a person with the virus infects.

But looking at transmission through this metric alone often “fails to tell the whole story”, said Althouse, who co-authored a paper on the limitations of R0 in the Journal of the Royal Society Interface this month.

For instance, he said Ebola, SARS-CoV-2, and influenza, all have an R0 value of around two to three.

But while people with the flu tend to infect two or three others “consistently”, the transmission pattern for those with Ebola and SARS-CoV-2 is overdispersed, meaning most will hardly spread it and some will give rise to tens of other cases.

A different metric – “k” – is used to capture this clustering behaviour, although it usually requires “more detailed data and methodology”, said Akira Endo, a research student at the London School of Hygiene and Tropical Medicine.

His modelling from the early international spread of the virus, published in Wellcome Open Research, suggested SARS-CoV-2 could be highly overdispersed.

A telltale clue, he said, was that some countries reported numerous imported cases but no signs of sustained transmission – like the match analogy – while others reported large local outbreaks with only a few imported cases.

But even k may not give the full picture, said Felix Wong, a postdoctoral fellow at the Massachusetts Institute of Technology.

His research analysing known COVID-19 superspreading events, published this month in the journal PNAS, found that they were happening even more frequently than predicted by traditional epidemiological models.

They are “extreme, yet probable occurrences”, Wong told AFP.

Biology vs opportunity

So why does superspreading occur?

We don’t know definitively whether biological factors, such as viral load, play much of a role.

But what we do know is people can spread SARS-CoV-2 without symptoms and given a poorly-ventilated, crowded space – particularly where people talk, shout, or sing – the virus can run rampant.​

This could be why a study in Nature this month found that restaurants, gyms, and cafes account for most COVID-19 infections in the United States.​

Using the mobile phone data of 98 million people, researchers found about 10 percent of venues accounted for over 80 percent of cases.

Given this, experts say the focus should be on these types of spaces – and reducing opportunities for the virus to access large numbers of people.

Wong said his modelling showed that if each individual was limited to ten transmissible contacts, “viral transmission would quickly die down”.

Tracking back

Overdispersed spread also means that most people testing positive for the virus are likely to be part of a cluster.

This opens up another way to trace infections: backwards.​

“The idea being that it could be more efficient to trace back, and isolate, superspreaders than it is to trace downstream and isolate individuals who, even if they were infected, might transmit the virus to very few people,” said Wong.

Both Japan and South Korea have used backwards contact tracing, which has been credited with helping them curb their epidemics, along with other control measures.

Masks, social distancing and reducing contacts are all ways to limit transmission opportunities, Althouse said, adding that even characterising people as “superspreaders” is misleading.

“There are vast differences in biology between individuals – I may have a million times more virus in my nose than you – but if I am a recluse, I can infect no one,” he said.

© Agence France-Presse


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Actual COVID-19 Cases Could Be 6 Times Greater Than Official Figures

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The true number of COVID-19 infections is probably much higher than what’s being reported in many high-income nations around the world.

A newly modelled estimate from the United States, Australia, Canada, South Korea and 11 countries in Europe suggests official figures could be struggling to capture the full scale of the outbreak. 


The new model from scientists in Australia employs a ‘backcasting’ method, which projects the number of new daily fatalities in reverse, from the time of death to the time of infection. This allows scientists to avoid using epidemiological and serological data, which comes with testing limitations.

Comparing the new estimates with official confirmed cases, the team was able to predict the ‘true’ infection rate for each country. According to their results, at the end of August the population infection rate was, on average, six times higher than reported cases.

“Unlike reported infections based on RNA tests, backcasting is not dependent on the coverage or efficacy of testing regimes, which can be very different across jurisdictions and over time,” the authors write.

That means it’s much easier to use on a regional, national or even international level than other methods. What’s more, because it doesn’t rely on a nation having widespread testing, it can help public health experts prepare in areas that have limited testing capacity. 

“Simply put, we analysed statistics on how many people had died from COVID-19 in a given country and then worked backwards to see how many people would have to have been infected to arrive at that number of deaths,” says data scientist Steven Phipps from Ikigai Research in Australia.


“Our method is a novel and easy-to-use method for estimating the true infection rate wherever there is reliable data on the number of fatalities attributable to COVID-19.”

Some nations were better at reporting these infections than others. In South Korea, the actual number of  infections was found to be 2.6 times higher than reported figures, whereas in Italy, the ‘backcasted’ number of cases was a startling 17.5 times higher.

In general, since March, countries around the world have gotten better at rolling out COVID-19 testing, educating the public on symptoms, and coming up with more and more accurate ways to detect and track the infection. 

Despite that improvement, international numbers continue to lag behind the likely reality. Even in Australia, which has one of the best levels of detection among all 15 countries studied, researchers say the rate of infection could still be nearly five times higher than what’s being reported.

“We found COVID-19 infections are much higher than confirmed cases across many countries, and this has important implications for both control and the probability of infection,” says economist Quentin Grafton from the Australian National University. 


“These findings raise serious questions about how we deal with all facets of the coronavirus pandemic, including ongoing morbidity and life-long health impacts for people who have been infected, how we implement and manage lockdowns, and how we make sure we are on top of this pandemic more broadly.”

This isn’t the first time scientists have found a discrepancy between actual COVID-19 cases and reported infections. Pretty much since the beginning, experts have warned we are likely underestimating the true extent of viral spread.

Determining a cause of death from the novel coronavirus is no easy matter when testing is limited, symptoms often overlap with other illnesses, and those who are most vulnerable have pre-existing medical conditions.

Many estimates to date have compared the total death rate in 2020 to what it would usually be in any other given year, or they’ve used antibody testing to go back and identify individuals who were not included in initial case figures, possibly because they showed little to no symptoms. 

Most epidemiological models agree that actual infections far outnumber confirmed cases, but exactly to what extent and how that changes over time is less clear.


Epidemiological data are limited by the level of a nation’s testing, and antibody testing comes with some false positives and false negatives, which means that if the number of cases is low, on a population level even a handful of false results can skew the data.

An estimate by a different study in the US found the number of infections in April was 3 to 20 times higher than the number of confirmed cases, and most of that was due to incomplete testing and, to a lesser extent, imperfect test accuracy.

Another estimate using antibody data in the US found there were 10 times more SARS-CoV-2 infections than reported in May. 

The new model is only based on high-income countries that have relatively widespread testing regimes. Most nations, however, have taken far fewer tests among their populations, which suggests the number of people globally who have been infected with COVID-19 is likely several times greater than official figures.

Some countries like Belgium, France, Italy and the United Kingdom were found to have very low true detection rates. As of 31 August 2020, official figures in these nations represented only 10 percent of all actual COVID-19 cases, according to the new analysis. 

At this point, however, no estimate is perfect, and this new method shouldn’t replace existing ones, it should merely complement them.

Epidemiological models are still much better at predicting future hospitalisations than backcasting methods, and the authors wholly admit this.

It’s also important to note that for backcasting to be accurate, the age distribution across those infected with COVID-19 has to be broadly similar, because older people have a higher chance of death once infected. This may skew the results in places like Australia where around 75 percent of the deaths have occurred in aged care

Finding the best way to estimate past, current and future COVID-19 cases will take time, and to a certain point, it might be impossible to ever truly know exactly how many people will be sickened by the current pandemic.

That said, accurate estimates of the real COVID-19 burden will be crucial in determining how to respond to the global tragedy on our hands.

The study was published in the Royal Society Open Science.


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Moderna Says Its COVID-19 Vaccine Is 94.5% Effective. Here’s What You Need to Know

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We just took another big step forward in fighting the coronavirus pandemic.

Moderna on Monday said that its experimental vaccine was effective at preventing COVID-19, the disease caused by the novel coronavirus. The findings come from a massive and well-designed study, but they haven’t been reviewed by outside experts or by regulators.


The news comes just one week after Pfizer shared that its vaccine was effective in preventing COVID-19, sending markets soaring on the hope that an effective vaccine would help end the pandemic.

There’s a lot to keep in mind about what the results mean for the pandemic and for when Americans might be able to get a shot now that two vaccines have proven successful.

Here’s what you need to know.

1. Moderna’s vaccine is 94.5 percent effective

As of Moderna’s initial analysis of its late-stage, 30,000-person trial, its vaccine is 94.5 percent effective. Pfizer reported that its vaccine was more than 90 percent effective.

Those numbers may change as we get more data on trial participants who’ve gotten infected with COVID-19.

Even so, the results are better than many experts expected. Prior to Moderna and Pfizer’s announcements, Dr Paul Offit, a vaccine expert, told Business Insider he hoped to see a shot that reduced the chances of getting moderate or severe disease by 70 percent, adding that anything more than 50 percent would be valuable.

Vaccine effectiveness varies. Some, like the seasonal flu vaccine can be as low as 44 percent effective, while shots that prevent polio and measles are 99 percent and 97 percent effective, respectively.

Up next, Moderna plans to submit the vaccine to the Food and Drug Administration for emergency authorization. It’s waiting on key safety data before submitting.


2. Having two effective vaccines is great news for society

Stopping the spread of the novel coronavirus will require wide-scale vaccination efforts around the world.

Should the FDA authorise the vaccines made by Moderna and Pfizer, we will have a limited supply of shots at first.

Having two effective vaccines, however, should help increase distribution. Moncef Slaoui, the head of Operation Warp Speed, said he anticipates 20 million Americans will get coronavirus vaccines in December, if both vaccines are approved.

Dr Anthony Fauci, the director of the National Institute of Allergy and Infectious Diseases, on Sunday said he anticipates a return to “relative normal” in 2021 if the majority of Americans get vaccinated.

Both vaccines are given as two doses. Pfizer’s regimen is space out by 21 days, while Moderna’s second dose comes 28 days after the first.

3. The pandemic’s end could be in sight, but a vaccine’s impact won’t be immediate

Success on vaccines is reason for celebration. But it will still take many months to roll out a vaccine to everyone, and people need to continue wearing masks and social distancing.

The pandemic is raging across the US with surges in new cases, hospitalizations, and deaths. The shots are still experimental and the process to authorise a shot will likely take weeks, Peter Marks, the FDA’s director of the Centre for Biologics Evaluation and Research, told Business Insider in a November 13 interview.


“We all need to still be very focused,” Moderna CEO Stephane Bancel said, emphasising that masks and social-distancing are the best tools we have.

Bancel, for instance, said he won’t see his in-laws in Seattle or any friends for Thanksgiving, as he typically does.

“That’s just the price we going to have to pay to play our role so that we minimise the risk of contamination and we protect those who are at highest risk,” Bancel said in a Sunday evening interview.

4. Moderna’s vaccine can be stored in standard refrigerators for up to 30 days

Moderna’s vaccine won’t require a deep-freeze, unlike Pfizer’s shot.

Pfizer’s vaccine needs to be shipped and stored at negative 94 degrees Fahrenheit, a temperature colder than what’s needed to store most other vaccines. That can be challenging in the US and presents even more of an obstacle in some other countries.

Pfizer will ship the vaccine by air and land using dry ice, along with reusable GPS temperature-monitoring devices.

Moderna’s meanwhile can be stored using standard refrigeration for up to 30 days, the company said on Monday. That greatly simplifies the distribution challenge compared to Pfizer’s shot.


The shot is stable for a month at anywhere from 36 degrees Fahrenheit to 46 degrees Fahrenheit, which is the standard temperatures of refrigerators.

Moderna’s vaccine can also be stored for up to six months at -4 degrees Fahrenheit, a typical temperature requirement that hospitals and clinics are used to.

Pfizer is already working on a next-generation version of its shot that wouldn’t need to kept at extremely cold temperatures, the company’s chief scientific officer told Business Insider.

5. Moderna’s success signals that Pfizer’s vaccine results weren’t a fluke

Pfizer and Moderna both developed messenger-RNA vaccines, which require just the genetic code of the virus to engineer an experimental vaccine. Pfizer’s results in November were the first data from a large-scale study to indicate that the technology works in humans.

While it might not necessarily signal success for other coronavirus vaccines in development, it does mean that Pfizer’s success wasn’t a one-off incident.

The successful results from Pfizer and Moderna should also validate the target that all the frontrunners are going after. All these shots target the same portion of the coronavirus: its spike protein.

Finally, the findings are a huge moment for mRNA as a platform. Moderna is working on several other vaccine candidates for Zika, influenza, cytomegalovirus or CMV, and respiratory syncytial virus or RSV. Bancel said he now has greater confidence in finding success against other diseases.

“It’s copy and paste,” Bancel said. “So the Zika vaccine, the CMV vaccine, if this vaccine shows high efficacy, they are going to have high efficacy. It’s just science.”

6. All 11 severe cases of COVID-19 in Moderna’s trial happened in participants who received a placebo shot

Moderna noted in its release that it has recorded 11 severe cases of COVID-19 among trial participants.

All of the participants who had severe cases of COVID-19 were a part of the placebo arm, Moderna said.

This is the piece of data that excited Moderna’s CEO the most, Bancel said. While he emphasised these aren’t the final study results, the early findings mean “we might have a chance to prevent severe disease.”

That means they hadn’t received the experimental vaccine.

Moderna also broke down the 95 COVID-19 cases it documented by age and background. Among the cases, 15 were in adults 65 and older, and 20 participants who got COVID-19 identified themselves as being part of a diverse community.

7. Nearly 10 percent of participants experienced fatigue that was severe enough to interfere with daily life

Moderna’s vaccine comes with some notable side effects.

While most side effects from Moderna’s shots were mild or moderate, some volunteers did have severe side effects, which are medically significant but not immediately life-threatening.

These mainly happened after the second injection. Even so, the most common severe side effects were fatigue in 9.7 percent of participants, and severe muscle pains or aches, which occured in 8.9 percent of participants. Known as Grade 3 events, these are side effects so severe that they interfere with daily life or activities for a period of time. Moderna said they were mostly “short-lived.”

5.2 percent of participants experienced severe joint pain, 4.5 percent had bad headaches, 4.1 percent experienced injection-site pain, and 2.0 percent had redness at the injection site.

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Here’s How a COVID-19 Vaccine Might Work in The Real World, According to The Numbers

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Pfizer and BioNTech have just released interim results of their COVID-19 vaccine trial.

Although it is not the only vaccine in the late stages of testing, the large size and careful design of the trial, not to mention the promising results, have caused understandable enthusiasm around the world.


As we get nearer the long-awaited start of a COVID-19 vaccine roll-out, it is worth looking at how statisticians help medics establish the safety of vaccines.

How effective is the vaccine?

It is not easy to find out how effective a vaccine is. First, researchers need to know whether just an act of injecting somebody can help. The trials involve a large number of people, with half of them given a vaccine and the other half a placebo.

Then the participants need to be exposed to the infection with the expectation that most of those in the control group become ill, but vaccination protects at least some in the treated group.

In some cases, such as for HIV or Ebola, even giving a placebo can be ethically controversial as they have such a high death rate.

For coronavirus, the researchers need to rely on natural infection because no study, at the moment, intentionally exposes participants to the coronavirus. As a result, the efficacy calculation is based on a relatively small number of those who caught COVID-19 by contact with other infected people.


Vaccine efficacy reflects a proportion of the number of those who became ill in the vaccinated group and in the non-vaccinated group. The Pfizer/BioNTech trial involved nearly 44,000 participants, with 21,999 given the vaccine.

The researchers use statistical analysis to set up milestones at which they can be increasingly confident that the vaccine works – or it does not – as the cases trickle in.

If the numbers are small, it would not be clear whether the difference in the outcomes between the placebo and the treated groups is real or just a result of a random fluke.

Statisticians use the so-called “power analysis” to discover how many cases we need to observe. For the Pfizer and BioNTech vaccine, the target was 164 cases when the final estimation of efficacy can be made, but this was based on the assumption that the vaccine is only 60 percent effective.

This was based on the seasonal flu vaccine efficacy. However, with the numbers exceeding expectations, the company decided to release the results at one of the interim analysis points.

Ninety-four cases were reported and the split of about 86 cases in the placebo group and eight cases among vaccinated yielded 90 percent efficacy. This level of protection against infection is remarkable.


Even though the study is based on a relatively small number of cases, statistical analysis allows the researchers to extrapolate to what might happen when the vaccine is rolled out.

The trial included different ages as well as people from different ethnic minority groups, but more studies would be needed to assess how the most vulnerable groups are protected.

The final efficacy is likely to be lower, as administering the treatment is difficult for many logistical reasons, including the requirement of mRNA-based vaccines, of which the Pfizer vaccine is one, to be stored at very low temperatures.

In the real world, the vaccine might not be stored at the correct temperature and hence may spoil.

How safe is the vaccine?

If the vaccine is to be widely applied, the medical community and the public need to be reassured about its safety.

The Pfizer vaccine was administered to 21,999 people. Some people reported a reaction similar to the one after the seasonal flu vaccination, but so far no serious side-effects have been reported. But how can we be sure that this holds if the treatment is rolled out to millions of people?


Statisticians came up with the “rule of three”. The rule tells us that if 21,999 participants were treated with no side-effects, then with 95% confidence, the probability of a side-effect from the vaccine is expected to be less than three (hence the name) divided by 21,999 and so less than one in 10,000.

The chance of these side-effects is probably even lower, but the researchers will be keen to extend the trials further to confirm this.

Safety is just as important as efficacy. If you take a probability of one in 10,000 and extrapolate that out to the 300 million population slated for vaccination in the US alone, the number of people with side effects could be as high as 30,000.

Clearly, the doctors need to ensure they are not causing harm, but also any serious side-effect attributable to the vaccine would damage the reputation and significantly affect the take-up.

How to use the vaccine so it is effective and safe?

Medical authorities are now designing ways to implement vaccination in nationwide programmes, but the details on how to do this depend on several factors.

The UK government has ordered 40 million doses of the Pfizer vaccine, which – with two-dose treatment – would vaccinate 20 million people, that is, everyone aged 55 and up. However, the roll-out will not be fast since production and delivery will take time.

The strategy also depends on what the vaccination programme is supposed to achieve. Childhood vaccines, such as measles, are given to newborns to maintain herd immunity. In this case, only a relatively small proportion of the population needs to be vaccinated. With the rapid spread of COVID-19 – and high levels of existing infection – the proportion would need to be much higher.

Predictions for the level of immunity required to reach herd immunity depend on our estimate of the COVID-19 basic reproductive number, R. In absence of any control measures, R is estimated to be around 3 and so at least 67 percent of the public need to be fully immune just for the epidemic to stop growing.

Higher values would need to be achieved if the aim is to eradicate the virus.

This level will hardly be achievable with 60 percent efficacy, even if the whole population is vaccinated. The value of R=3 assumes the return to the behaviour before the pandemic. If we keep some level of restrictions and use masks, R could be lower and the herd immunity easier to achieve.

On the positive side, our simple models might be too pessimistic about the herd immunity levels. Additionally, if perhaps as many as 20 percent of the public already have had COVID-19, the required level of vaccination might be much easier to achieve.

Alternatively, vaccination can be applied to these segments of the society who are either at high risk of infection (healthcare and care home workers) or high risk of death (vulnerable, care home residents). This is the recommended strategy in the UK.

Are we there yet?

The results of the Pfizer vaccine trial are highly promising. But the road to eradicating the coronavirus is likely to be long and difficult.

Besides establishing the potential for the vaccine to protect against the virus, we also need to know whether it gives a lasting immunity or whether it would need to be applied repeatedly, for example, as with tetanus or seasonal flu vaccines.

But the policymakers and researchers also need to balance the requirement for stopping the pandemic with the fears of side-effects and the resulting vaccine hesitancy.

While it is easy to dismiss these concerns, they need to be taken seriously if the vaccination is to be successful. The Conversation

Adam Kleczkowski, Professor of Mathematics and Statistics, University of Strathclyde.

This article is republished from The Conversation under a Creative Commons license. Read the original article.


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A Record Number of People in The US Are Currently Hospitalised With COVID-19

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More people than ever are currently hospitalized in the US due to the coronavirus, and a record of 150,526 new cases were reported on Thursday, according to data from The COVID Tracking Project.


This week alone, one in 378 US residents has tested positive for COVID-19, the group said.

Over 1,100 new deaths were also reported on November 12. Over the last week, an average of 1,052 people died each day from COVID-19.

This number of people currently hospitalized, as reported by The COVID Tracking Project, 67,096, is nearly double what it was two weeks ago.

“The current national case surge has been underway for nine weeks,” The COVID Tracking Project said in a blog post explaining the new data, “hospitalizations have risen for seven weeks, and deaths have risen for five.”

Cases are also increasing at the fastest rate since the pandemic began, and not just because there is more testing.

Indeed, the number of cases reported this week is up 41 percent from last, compared to a 13 percent increase in new tests.

Over 234,000 people have now died from the coronavirus. By December 5, that number could be as high as 282,000, according to an analysis by the US Centres for Disease Control and Prevention.

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US Could Have 1 Million Daily Virus Cases by The End of The Year, Report Finds

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In March, when New York City hospitals were reeling from an overwhelming surge of coronavirus cases, the US was only catching a glimpse of the bigger crisis to come.

The highest number of cases ever recorded in one day this spring was around 35,000, though many went uncounted. Now, the US has recorded an average of more than 112,000 daily cases over the last seven days. Cases reached an all-time peak of more than 132,000 on Friday.


On Monday, the US surpassed 10 million total cases – just 10 days after cases topped 9 million. Before that, it took two weeks for cases to rise from 8 million to 9 million, and three weeks for cases to jump from 7 million to 8 million.

The nation’s weekly per cent positivity rate – the share of coronavirus tests that come back positive – has reached 9 percent. Anthony Fauci, director of the National Institute of Allergy and Infectious Diseases, has said the rate should ideally sit below 3 percent. Only six states and Washington, DC, currently meet that threshold. Half of states have test-positivity rates in the double digits. South Dakota’s rate is highest, at around 54 percent.

Experts predict this fall-winter surge will be the largest, and perhaps deadliest, yet. Indeed, the second surge the country experienced over the summer, from June through August, resulted in nearly 4.2 million cases. Since September, the US has already recorded about 4 million more.

According to a recent prediction from Pantheon Macroeconomics, the US could be on track to record 1 million daily coronavirus cases by the end of 2020 if average cases continue to grow 34 percent from week to week, as they are currently.

new daily cases bi chart

The US is ‘about to enter COVID hell’

Other models offer more conservative, albeit still troubling, estimates.

The University of Washington’s Institute for Health Metrics and Evaluation, for instance, predicts that daily cases could peak at nearly 306,000 on December 31. (The institute defines daily cases as all infections on a given day, not just new cases identified through testing.)


If states continue to relax restrictions, the model suggests the fall-winter surge could be even worse, reaching a peak of nearly 793,000 daily cases on January 23. The institute’s model predicts that 160,000 more people in the US could die of the coronavirus from now through February 1.

“I am tremendously concerned,” Megan Ranney, an emergency-medicine physician at Brown University, told Business Insider.

“The other surges were very localised,” she added. “This is different because it is truly nationwide.”

Weekly hospitalizations have also risen about 18 percent from week to week. If that trend continues, daily hospitalizations could triple to 180,000 by the end of the year.

On Monday, Dr. Michael Osterholm, a recent appointee to President-elect Joe Biden’s coronavirus advisory board, told CNBC that the US was “about to enter COVID hell.”

But public-experts say the US can lower daily cases – and consequently, deaths – this winter, before a vaccine hits the market. The solution would involve more lockdown restrictions.

Lockdown measures could prevent a worst-case scenario

In a Monday report, Pantheon Macroeconomics’ chief economist, Ian Sherpherdson, warned that the US should brace for the worst-case scenario of 1 million daily cases this winter. The longer states and cities wait to impose lockdown restrictions, he added, the more likely that scenario becomes.

“When it gets as bad as it appears to be in some parts of the country, and potentially others in the weeks to come, you really have little choice left than to do a short-term lockdown, trying to get the numbers down to a point where testing and contact tracing can actually have an impact,” Marissa Levine, a public-health professor at the University of South Florida, told Business Insider. “I hate to say that because we didn’t necessarily have to be in this position.”


Many states are taking the opposite approach, however.

In October, Texas began allowing counties with relatively few coronavirus hospitalizations to reopen bars and other businesses at limited capacity. Pennsylvania, too, started permitting venues like concerts and stadiums to operate at 10 percent to 25 percent occupancy. Restaurants in South Carolina have been able to operate at full capacity since October 2.

Other states have reinstated some restrictions, but not nearly to the extent that they did in the spring.

Illinois, Massachussetts, and New Mexico recently imposed curfews that limit how late certain businesses can remain open. Illinois began prohibiting indoor dining in bars and restaurants earlier this month. And at the end of October, Michigan reduced the maximum capacity at indoor venues from 500 people to 50.

Some other states – including Delaware, Louisiana, Maine, and North Carolina – have simply put their reopening plans on pause.

Public-health experts say it’s likely that under a Biden administration, states may get more concrete guidelines as to when they can safely reopen or should enact new restrictions. Biden’s campaign website at one time stated that if elected, he would tailor reopening guidelines to individual communities based on their levels of transmission.


But any lockdown is likely to be met with some opposition, due to a combination of pandemic fatigue and politics.

“Even if we make it completely clear: ‘This is the line, if you cross this line, you should shut down,’ it’s still ultimately a political decision,” Ingrid Katz, an assistant professor at Harvard Medical School, told Business Insider. “If decisions are being driven by forces other than science, then they are not always going to be decisions that are in people’s best interests.”

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