What to Know about the Fast-Spreading Delta Variant
A highly contagious form of the coronavirus known as the Delta variant is spreading rapidly and becoming increasingly prevalent around the world. First identified in India in December, Delta has now been identified in 111 countries.
In the United States, the variant now accounts for 83% of sequenced COVID-19 cases, said Rochelle Walensky, director of the Centers for Disease Control and Prevention, at a July 20 Senate hearing. In May, Delta was responsible for just 3% of U.S. cases. The World Health Organization projects that Delta will become the dominant variant globally over the coming months.
So, how worried should you be about the Delta variant? We asked experts some common questions about Delta.
What is a variant?
To understand Delta, it's helpful to first understand what a variant is. When a virus infects a person, it gets into your cells and makes a copy of its genome so it can replicate and spread throughout your body.
In the process of making new copies of itself, the virus can make a mistake in its genetic code. Because viruses are replicating all the time, these mistakes — also called mutations — happen pretty often. A new variant emerges when a virus acquires one or more new mutations and starts spreading within a population.
There are thousands of SARS-CoV-2 variants, but most of them don't substantially change the way the virus behaves. The variants that scientists are most interested in are known as variants of concern. These are versions of the virus with mutations that allow the virus to spread more easily, evade vaccines, or cause more severe disease.
"The vast majority of the mutations that have accumulated in SARS-CoV-2 don't change the biology as far as we're concerned," said Jennifer Surtees, a biochemist at the University of Buffalo who's studying the coronavirus. "But there have been a handful of key mutations and combinations of mutations that have led to what we're now calling variants of concern."
One of those variants of concern is Delta, which is now driving many new COVID-19 infections.
Why is the Delta variant so concerning?
"The reason why the Delta variant is concerning is because it's causing an increase in transmission," said Alba Grifoni, an infectious disease researcher at the La Jolla Institute for Immunology. "The virus is spreading faster and people — particularly those who are not vaccinated yet — are more prone to exposure."
The Delta variant has a few key mutations that make it better at attaching to our cells and evading the neutralizing antibodies in our immune system. These mutations have changed the virus enough to make it more than twice as contagious as the original SARS-CoV-2 virus that emerged in Wuhan and about 50% more contagious than the Alpha variant, previously known as B.1.1.7, or the U.K. variant.
These mutations were previously seen in other variants on their own, but it's their combination that makes Delta so much more infectious.
Do vaccines work against the Delta variant?
The good news is, the COVID-19 vaccines made by AstraZeneca, Johnson & Johnson, Moderna, and Pfizer still work against the Delta variant. They remain more than 90% effective at preventing hospitalizations and death due to Delta. While they're slightly less protective against disease symptoms, they're still very effective at preventing severe illness caused by the Delta variant.
"They're not as good as they were against the prior strains, but they're holding up pretty well," said Eric Topol, a physician and director of the Scripps Translational Research Institute, during a July 19 briefing for journalists.
Because Delta is better at evading our immune systems, it's likely causing more breakthrough infections — COVID-19 cases in people who are vaccinated. However, breakthrough infections were expected before the Delta variant became widespread. No vaccine is 100% effective, so breakthrough infections can happen with other vaccines as well. Experts say the COVID-19 vaccines are still working as expected, even if breakthrough infections occur. The majority of these infections are asymptomatic or cause only mild symptoms.
Should vaccinated people worry about the Delta variant?
Vaccines train our immune systems to protect us against infection. They do this by spurring the production of antibodies, which stick around in our bodies to help fight off a particular pathogen in case we ever come into contact with it.
But even if the new Delta variant slips past our neutralizing antibodies, there's another component of our immune system that can help overtake the virus: T cells. Studies are showing that the COVID-19 vaccines also galvanize T cells, which help limit disease severity in people who have been vaccinated.
"While antibodies block the virus and prevent the virus from infecting cells, T cells are able to attack cells that have already been infected," Grifoni said. In other words, T cells can prevent the infection from spreading to more places in the body. A study published July 1 by Grifoni and her colleagues found that T cells were still able to recognize mutated forms of the virus — further evidence that our current vaccines are effective against Delta.
Can fully vaccinated people spread the Delta variant?
Previously, scientists believed it was unlikely for fully vaccinated individuals with asymptomatic infections to spread Covid-19. But the Delta variant causes the virus to make so many more copies of itself inside the body, and high viral loads have been found in the respiratory tracts of people who are fully vaccinated. This suggests that vaccinated people may be able to spread the Delta variant to some degree.
If you have COVID-19 symptoms, even if you're fully vaccinated, you should get tested and isolate from friends and family because you could spread the virus.
What risk does Delta pose to unvaccinated people?
The Delta variant is behind a surge in cases in communities with low vaccination rates, and unvaccinated Americans currently account for 97% of hospitalizations due to COVID-19, according to Walensky. The best thing you can do right now to prevent yourself from getting sick is to get vaccinated.
Gigi Gronvall, an immunologist and senior scholar at the Johns Hopkins Center for Health Security, said in this week's "Making Sense of Science" podcast that it's especially important to get all required doses of the vaccine in order to have the best protection against the Delta variant. "Even if it's been more than the allotted time that you were told to come back and get the second, there's no time like the present," she said.
With more than 3.6 billion COVID-19 doses administered globally, the vaccines have been shown to be incredibly safe. Serious adverse effects are rare, although scientists continue to monitor for them.
Being vaccinated also helps prevent the emergence of new and potentially more dangerous variants. Viruses need to infect people in order to replicate, and variants emerge because the virus continues to infect more people. More infections create more opportunities for the virus to acquire new mutations.
Surtees and others worry about a scenario in which a new variant emerges that's even more transmissible or resistant to vaccines. "This is our window of opportunity to try to get as many people vaccinated as possible and get people protected so that so that the virus doesn't evolve to be even better at infecting people," she said.
Does Delta cause more severe disease?
While hospitalizations and deaths from COVID-19 are increasing again, it's not yet clear whether Delta causes more severe illness than previous strains.
How can we protect unvaccinated children from the Delta variant?
With children 12 and under not yet eligible for the COVID-19 vaccine, kids are especially vulnerable to the Delta variant. One way to protect unvaccinated children is for parents and other close family members to get vaccinated.
It's also a good idea to keep masks handy when going out in public places. Due to risk Delta poses, the American Academy of Pediatrics issued new guidelines July 19 recommending that all staff and students over age 2 wear face masks in school this fall, even if they have been vaccinated.
Parents should also avoid taking their unvaccinated children to crowded, indoor locations and make sure their kids are practicing good hand-washing hygiene. For children younger than 2, limit visits with friends and family members who are unvaccinated or whose vaccination status is unknown and keep up social distancing practices while in public.
While there's no evidence yet that Delta increases disease severity in children, parents should be mindful that in some rare cases, kids can get a severe form of the disease.
"We're seeing more children getting sick and we're seeing some of them get very sick," Surtees said. "Those children can then pass on the virus to other individuals, including people who are immunocompromised or unvaccinated."
Two years, six million deaths and still counting, scientists are searching for answers to prevent another COVID-19-like tragedy from ever occurring again. And it’s a gargantuan task.
Our disturbed ecosystems are creating more favorable conditions for the spread of infectious disease. Global warming, deforestation, rising sea levels and flooding have contributed to a rise in mosquito-borne infections and longer tick seasons. Disease-carrying animals are in closer range to other species and humans as they migrate to escape the heat. Bats are thought to have carried the SARS-CoV-2 virus to Wuhan, either directly or through another host animal, but thousands of novel viruses are lurking within other wild creatures.
Understanding how climate change contributes to the spread of disease is critical in predicting and thwarting future calamities. But the problem is that predictive models aren’t yet where they need to be for forecasting with certainty beyond the next year, as we could for weather, for instance.
The association between climate and infectious disease is poorly understood, says Irina Tezaur, a computational scientist at Sandia National Laboratories. “Correlations have been observed but it’s not known if these correlations translate to causal relationships.”
To make accurate longer-term predictions, scientists need more empirical data, multiple datasets specific to locations and diseases, and the ability to calculate risks that depend on unpredictable nature and human behavior. Another obstacle is that climate scientists and epidemiologists are not collaborating effectively, so some researchers are calling for a multidisciplinary approach, a new field called Outbreak Science.
Climate scientists are far ahead of epidemiologists in gathering essential data.
Earth System Models—combining the interactions of atmosphere, ocean, land, ice and biosphere—have been in place for two decades to monitor the effects of global climate change. These models must be combined with epidemiological and human model research, areas that are easily skewed by unpredictable elements, from extreme weather events to public environmental policy shifts.
“There is never just one driver in tracking the impact of climate on infectious disease,” says Joacim Rocklöv, a professor at the Heidelberg Institute of Global Health & Heidelberg Interdisciplinary Centre for Scientific Computing in Germany. Rocklöv has studied how climate affects vector-borne diseases—those transmitted to humans by mosquitoes, ticks or fleas. “You need to disentangle the variables to find out how much difference climate makes to the outcome and how much is other factors.” Determinants from deforestation to population density to lack of healthcare access influence the spread of disease.
Even though climate change is not the primary driver of infectious disease today, it poses a major threat to public health in the future, says Rocklöv.
The promise of predictive modeling
“Models are simplifications of a system we’re trying to understand,” says Jeremy Hess, who directs the Center for Health and the Global Environment at University of Washington in Seattle. “They’re tools for learning that improve over time with new observations.”
Accurate predictions depend on high-quality, long-term observational data but models must start with assumptions. “It’s not possible to apply an evidence-based approach for the next 40 years,” says Rocklöv. “Using models to experiment and learn is the only way to figure out what climate means for infectious disease. We collect data and analyze what already happened. What we do today will not make a difference for several decades.”
To improve accuracy, scientists develop and draw on thousands of models to cover as many scenarios as possible. One model may capture the dynamics of disease transmission while another focuses on immunity data or ocean influences or seasonal components of a virus. Further, each model needs to be disease-specific and often location-specific to be useful.
“All models have biases so it’s important to use a suite of models,” Tezaur stresses.
The modeling scientist chooses the drivers of change and parameters based on the question explored. The drivers could be increased precipitation, poverty or mosquito prevalence, for instance. Later, the scientist may need to isolate the effect of one driver so that will require another model.
There have been some related successes, such as the latest models for mosquito-borne diseases like Dengue, Zika and malaria as well as those for flu and tick-borne diseases, says Hess.
Rocklöv was part of a research team that used test data from 2018 and 2019 to identify regions at risk for West Nile virus outbreaks. Using AI, scientists were able to forecast outbreaks of the virus for the entire transmission season in Europe. “In the end, we want data-driven models; that’s what AI can accomplish,” says Rocklöv. Other researchers are making an important headway in creating a framework to predict novel host–parasite interactions.
Modeling studies can run months, years or decades. “The scientist is working with layers of data. The challenge is how to transform and couple different models together on a planetary scale,” says Jeanne Fair, a scientist at Los Alamos National Laboratory, Biosecurity and Public Health, in New Mexico.
Disease forecasting will require a significant investment into the infrastructure needed to collect data about the environment, vectors, and hosts a tall spatial and temporal resolutions.
And it’s a constantly changing picture. A modeling study in an April 2022 issue of Nature predicted that thousands of animals will migrate to cooler locales as temperatures rise. This means that various species will come into closer contact with people and other mammals for the first time. This is likely to increase the risk of emerging infectious disease transmitted from animals to humans, especially in Africa and Asia.
Other things can happen too. Global warming could precipitate viral mutations or new infectious diseases that don’t respond to antimicrobial treatments. Insecticide-resistant mosquitoes could evolve. Weather-related food insecurity could increase malnutrition and weaken people’s immune systems. And the impact of an epidemic will be worse if it co-occurs during a heatwave, flood, or drought, says Hess.
The devil is in the climate variables
Solid predictions about the future of climate and disease are not possible with so many uncertainties. Difficult-to-measure drivers must be added to the empirical model mix, such as land and water use, ecosystem changes or the public’s willingness to accept a vaccine or practice social distancing. Nor is there any precedent for calculating the effect of climate changes that are accelerating at a faster speed than ever before.
The most critical climate variables thought to influence disease spread are temperature, precipitation, humidity, sunshine and wind, according to Tezaur’s research. And then there are variables within variables. Influenza scientists, for example, found that warm winters were predictors of the most severe flu seasons in the following year.
The human factor may be the most challenging determinant. To what degree will people curtail greenhouse gas emissions, if at all? The swift development of effective COVID-19 vaccines was a game-changer, but will scientists be able to repeat it during the next pandemic? Plus, no model could predict the amount of internet-fueled COVID-19 misinformation, Fair noted. To tackle this issue, infectious disease teams are looking to include more sociologists and political scientists in their modeling.
Addressing the gaps
Currently, researchers are focusing on the near future, predicting for next year, says Fair. “When it comes to long-term, that’s where we have the most work to do.” While scientists cannot foresee how political influences and misinformation spread will affect models, they are positioned to make headway in collecting and assessing new data streams that have never been merged.
Disease forecasting will require a significant investment into the infrastructure needed to collect data about the environment, vectors, and hosts at all spatial and temporal resolutions, Fair and her co-authors stated in their recent study. For example real-time data on mosquito prevalence and diversity in various settings and times is limited or non-existent. Fair also would like to see standards set in mosquito data collection in every country. “Standardizing across the US would be a huge accomplishment,” she says.
Understanding how climate change contributes to the spread of disease is critical for thwarting future calamities.
Jeanne Fair
Hess points to a dearth of data in local and regional datasets about how extreme weather events play out in different geographic locations. His research indicates that Africa and the Middle East experienced substantial climate shifts, for example, but are unrepresented in the evidentiary database, which limits conclusions. “A model for dengue may be good in Singapore but not necessarily in Port-au-Prince,” Hess explains. And, he adds, scientists need a way of evaluating models for how effective they are.
The hope, Rocklöv says, is that in the future we will have data-driven models rather than theoretical ones. In turn, sharper statistical analyses can inform resource allocation and intervention strategies to prevent outbreaks.
Most of all, experts emphasize that epidemiologists and climate scientists must stop working in silos. If scientists can successfully merge epidemiological data with climatic, biological, environmental, ecological and demographic data, they will make better predictions about complex disease patterns. Modeling “cross talk” and among disciplines and, in some cases, refusal to release data between countries is hindering discovery and advances.
It’s time for bold transdisciplinary action, says Hess. He points to initiatives that need funding in disease surveillance and control; developing and testing interventions; community education and social mobilization; decision-support analytics to predict when and where infections will emerge; advanced methodologies to improve modeling; training scientists in data management and integrated surveillance.
Establishing a new field of Outbreak Science to coordinate collaboration would accelerate progress. Investment in decision-support modeling tools for public health teams, policy makers, and other long-term planning stakeholders is imperative, too. We need to invest in programs that encourage people from climate modeling and epidemiology to work together in a cohesive fashion, says Tezaur. Joining forces is the only way to solve the formidable challenges ahead.
This article originally appeared in One Health/One Planet, a single-issue magazine that explores how climate change and other environmental shifts are increasing vulnerabilities to infectious diseases by land and by sea. The magazine probes how scientists are making progress with leaders in other fields toward solutions that embrace diverse perspectives and the interconnectedness of all lifeforms and the planet.
Scientists use AI to predict how hospital stays will go
The Friday Five covers five stories in research that you may have missed this week. There are plenty of controversies and troubling ethical issues in science – and we get into many of them in our online magazine – but this news roundup focuses on scientific creativity and progress to give you a therapeutic dose of inspiration headed into the weekend.
Here are the promising studies covered in this week's Friday Five:
- The problem with bedtime munching
- Scientists use AI to predict how stays in hospitals will go
- How to armor the shields of our livers against cancer
- One big step to save the world: turn one kind of plastic into another
- The perfect recipe for tiny brains
And an honorable mention this week: Bigger is better when it comes to super neurons in super agers