Skip to main content

Italy

Public Health Policies Have Prevented Hundreds of Millions of Coronavirus Infections

Posted on by

Touchless carryout
Credit: Stock photo/Juanmonino

The alarming spread of coronavirus disease 2019 (COVID-19) last winter presented a profound threat to nations around the world. Many government leaders responded by shutting down all non-essential activities, implementing policies that public health officials were hopeful could slow the highly infectious SARS-CoV-2, the novel coronavirus that causes COVID-19.

But the shutdown has come at a heavy cost for the U.S. and global economies. It’s also taken a heavy personal toll on many of us, disrupting our daily routines—getting children off to school, commuting to the office or lab, getting together with friends and family, meeting face to face to plan projects, eating out, going to the gym—and causing lots of uncertainty and frustration.

As difficult as the shutdowns have been, new research shows that without these public health measures, things would have been much, much worse. According to a study published recently in Nature [1], the implementation of containment and mitigation strategies across the globe prevented or delayed about 530 million coronavirus infections across six countries—China, South Korea, Iran, Italy, France, and the United States. Take a moment to absorb that number—530 million. Right now, there are 8.8 million cases documented across the globe.

Estimates of the benefits of anti-contagion policies have drawn from epidemiological models that simulate the spread of COVID-19 in various ways, depending on assumptions built into each model. But models are sophisticated ways of guessing. Back when decisions about staying at home had to be made, no one knew for sure if, or how well, such approaches to limit physical contact would work. What’s more, the only real historical precedent was the 1918 Spanish flu pandemic in a very different, much-less interconnected world.

That made it essential to evaluate the pros and cons of these public health strategies within a society. As many people have rightfully asked: are the health benefits really worth the pain?

Recognizing a pressing need to answer this question, an international team of scientists dropped everything that they were doing to find out. Led by Solomon Hsiang, director of the University of California, Berkeley’s Global Policy Laboratory and Chancellor’s Professor at the Goldman School of Public Policy, a research group of 15 researchers from China, France, South Korea, New Zealand, Singapore, and the United States evaluated 1,717 policies implemented in all six countries between January 2020, when the virus began its global rise, and April 6, 2020.

The team relied on econometric methods that use statistics and math to uncover meaningful patterns hiding in mountains of data. As the name implies, these techniques are used routinely by economists to understand, in a before-and-after way, how certain events affect economic growth.

In this look-back study, scientists compare observations before and after an event they couldn’t control, such as a natural disaster or disease outbreak. In the case of COVID-19, these researchers compared public health datasets in multiple localities (e.g., states or cities) within each of the six countries before and several weeks after lockdowns. For each data sample from a given locality, the time period right before a policy deployment was the experimental “control” for the same locality several weeks after it received one or more shutdown policy “treatments.”

Hsiang and his colleagues measured the effects of all the different policies put into place at local, regional, and national levels. These included travel restrictions, business and school closures, shelter-in-place orders, and other actions that didn’t involve any type of medical treatment for COVID-19.

Because SARS-CoV-2 is a new virus, the researchers knew that early in the pandemic, everyone was susceptible, and the outbreak would grow exponentially. The scientists could then use a statistical method designed to estimate how the daily growth rate of infections changed over time within a location after different combinations of large-scale policies were put into place.

The result? Early in the pandemic, coronavirus infection rates grew 38 percent each day, on average, across the six countries: translating to a two-day doubling time. Applying all policies at once slowed the daily COVID-19 infection rate by 31 percentage points! Policies having the clearest benefit were business closures and lockdowns, whereas travel restrictions and bans on social gatherings had mixed results. Without more data, the analysis can’t specify why, but the way different countries enacted those policies might be one reason.

As we continue to try to understand and thwart this new virus and its damage to so many aspects of our personal and professional lives, these new findings add context, comfort, and guidance about the present circumstances. They tell us that individual sacrifices from staying home and canceled events contributed collectively to a huge, positive impact on the world.

Now, as various communities start cautiously to open up, we should continue to practice social distancing, mask wearing, and handwashing. This is not the time to say that the risk has passed. We are all tired of the virus and its consequences for our personal lives, but the virus doesn’t care. It’s still out there. Stay safe, everyone!

Reference:

[1] The effect of large-scale anti-contagion policies on the COVID-19 pandemic. Hsiang S, Allen D, Annan-Phan S, et al. Nature. 2020 June 8 [published online ahead of print].

Links:

Coronavirus (NIH)

Global Policy Lab: Effect of Anti-Contagion Policies (University of California, Berkeley)

Video: How much have policies to slow COVID-19 worked? (UC Berkeley)

Hsiang Lab (UC Berkeley)

Global Policy Lab Rallies for COVID-19 Research,” COVID-19 News, Goldman School of Public Policy, June 5, 2020.


Genes, Blood Type Tied to Risk of Severe COVID-19

Posted on by

SARS-CoV-2 virus particles
Caption: Micrograph of SARS-CoV-2 virus particles isolated from a patient.
Credit: National Institute of Allergy and Infectious Diseases, NIH

Many people who contract COVID-19 have only a mild illness, or sometimes no symptoms at all. But others develop respiratory failure that requires oxygen support or even a ventilator to help them recover [1]. It’s clear that this happens more often in men than in women, as well as in people who are older or who have chronic health conditions. But why does respiratory failure also sometimes occur in people who are young and seemingly healthy?

A new study suggests that part of the answer to this question may be found in the genes that each one of us carries [2]. While more research is needed to pinpoint the precise underlying genes and mechanisms responsible, a recent genome-wide association (GWAS) study, just published in the New England Journal of Medicine, finds that gene variants in two regions of the human genome are associated with severe COVID-19 and correspondingly carry a greater risk of COVID-19-related death.

The two stretches of DNA implicated as harboring risks for severe COVID-19 are known to carry some intriguing genes, including one that determines blood type and others that play various roles in the immune system. In fact, the findings suggest that people with blood type A face a 50 percent greater risk of needing oxygen support or a ventilator should they become infected with the novel coronavirus. In contrast, people with blood type O appear to have about a 50 percent reduced risk of severe COVID-19.

These new findings—the first to identify statistically significant susceptibility genes for the severity of COVID-19—come from a large research effort led by Andre Franke, a scientist at Christian-Albrecht-University, Kiel, Germany, along with Tom Karlsen, Oslo University Hospital Rikshospitalet, Norway. Their study included 1,980 people undergoing treatment for severe COVID-19 and respiratory failure at seven medical centers in Italy and Spain.

In search of gene variants that might play a role in the severe illness, the team analyzed patient genome data for more than 8.5 million so-called single-nucleotide polymorphisms, or SNPs. The vast majority of these single “letter” nucleotide substitutions found all across the genome are of no health significance, but they can help to pinpoint the locations of gene variants that turn up more often in association with particular traits or conditions—in this case, COVID-19-related respiratory failure. To find them, the researchers compared SNPs in people with severe COVID-19 to those in more than 1,200 healthy blood donors from the same population groups.

The analysis identified two places that turned up significantly more often in the individuals with severe COVID-19 than in the healthy folks. One of them is found on chromosome 3 and covers a cluster of six genes with potentially relevant functions. For instance, this portion of the genome encodes a transporter protein known to interact with angiotensin converting enzyme 2 (ACE2), the surface receptor that allows the novel coronavirus that causes COVID-19, SARS-CoV-2, to bind to and infect human cells. It also encodes a collection of chemokine receptors, which play a role in the immune response in the airways of our lungs.

The other association signal popped up on chromosome 9, right over the area of the genome that determines blood type. Whether you are classified as an A, B, AB, or O blood type, depends on how your genes instruct your blood cells to produce (or not produce) a certain set of proteins. The researchers did find evidence suggesting a relationship between blood type and COVID-19 risk. They noted that this area also includes a genetic variant associated with increased levels of interleukin-6, which plays a role in inflammation and may have implications for COVID-19 as well.

These findings, completed in two months under very difficult clinical conditions, clearly warrant further study to understand the implications more fully. Indeed, Franke, Karlsen, and many of their colleagues are part of the COVID-19 Host Genetics Initiative, an ongoing international collaborative effort to learn the genetic determinants of COVID-19 susceptibility, severity, and outcomes. Some NIH research groups are taking part in the initiative, and they recently launched a study to look for informative gene variants in 5,000 COVID-19 patients in the United States and Canada.

The hope is that these and other findings yet to come will point the way to a more thorough understanding of the biology of COVID-19. They also suggest that a genetic test and a person’s blood type might provide useful tools for identifying those who may be at greater risk of serious illness.

References:

[1] Characteristics of and important lessons from the Coronavirus Disease 2019 (COVID-19) outbreak in China: Summary of a report of 72 314 cases from the Chinese Center for Disease Control and Prevention. Wu Z, McGoogan JM, et. al. 2020 Feb 24. [published online ahead of print]

[2] Genomewide association study of severe Covid-19 with respiratory failure. Ellinghaus D, Degenhardt F, et. a. NEJM. June 17, 2020.

Links:

The COVID-19 Host Genetics Initiative

Andre Franke (Christian-Albrechts-University of Kiel, Germany)

Tom Karlsen (Oslo University Hospital Rikshospitalet, Norway)


Revisiting Resveratrol’s Health Claims

Posted on by

Photo of red wine and dark chocolate

Credit: Jill George, NIH

Over the past decade or so, a lot of us have been led to believe that certain indulgences—such as a glass of Pinot noir or a piece of dark chocolate—can actually be health-promoting. That’s because a number of studies had suggested that red wine, chocolate, and other foods containing the antioxidant resveratrol might lower the risk of heart disease, cancer, and other age-related maladies. But now comes word that a diet rich in resveratrol may not automatically translate into better health.