A girl with a face mask against COVID-19 plays with the waters of an urban outdoor fountain.Share on Pinterest
The COVID-19 pandemic could be shifting towards becoming a disease of the young. Nina Westervelt/Bloomberg via Getty Images
  • A new computer model suggests that SARS-CoV-2, the virus that causes COVID-19, could one day be just another cold-like coronavirus.
  • COVID-19 is likely to become a primarily children’s disease if adults acquire long-term immunity from natural infection or vaccination.
  • The purpose of the model is to provide health planners with an additional tool to anticipate future needs.

Since Medical News Today published this article, the paper in question has come under scrutiny. The journal in which it appears — PLOS ONE — has issued an “expression of concern.” The journal’s editors explain that “Concerns were raised about the validity of results and conclusions reported in the article and about undisclosed competing interests.” Read more here.

Some experts believe that the SARS-CoV-2 virus, which causes COVID-19, will eventually become endemic, finding its place among common cold viruses.

A team of researchers from the United States and Norway has published a glimpse into that future based on a model of likely outcomes.

The model predicts that COVID-19 will primarily affect the young if there is long-lasting immunity in other age groups or the symptoms become less severe in adults when they acquire the infection.

According to senior author Ottar Bjornstad, Ph.D., Professor of Entomology and Biology at Penn State University:

“Following infection by SARS-CoV-2, there has been a clear signature of increasingly severe outcomes and fatality with age. Yet, our modeling results suggest that the risk of infection will likely shift to younger children as the adult community becomes immune, either through vaccination or exposure to the virus.”

The research appears in Science Advances.

The researchers’ expectations are in line with what experts have seen before. “Historical records of respiratory diseases indicate that age-incidence patterns during virgin epidemics can be very different from endemic circulation,” says Bjornstad.

Bjornstad suggests, as an illustration, the 1889–1890 epidemic, which people often refer to as the Asiatic or Russian flu. In its early days, it killed a million individuals, primarily over the age of 70 years.

Bjornstad says the deadly outbreak “may have been caused by the emergence of HCoV-OC43 virus, which is now an endemic, mild, repeat-infecting cold virus affecting mostly children aged 7–12 months old.”

“We know of a few respiratory viruses that were introduced into the human population, swept across the globe, and transitioned to endemic circulation, usually with annual wintertime peaks in incidence,” says Harvard’s Associate Professor Yonatan Grad, speaking to the university’s T.H. Chan School of Public Health News.

He notes that although the 1918 flu caused by the A/H1N1 virus is a commonly cited example, “there are other more recent examples from influenza: the 1957 flu pandemic caused by an A/H2N2 influenza virus, the 1968 flu pandemic from an A/H3N2 influenza virus, and the 2009 “swine flu” pandemic, from an A/H1N1 influenza virus.”

The researchers’ prediction that the disease will affect younger age groups in the future depends on adults developing long-term or permanent immunity to SARS-CoV-2 from vaccinations or prior exposure to the virus. If this does not occur, the primary burden of COVID-19 will remain among older adults.

Bjornstad and his colleagues encourage people to get vaccinated as soon as possible since prior exposure to the virus does not reliably promote as robust an immune response.

“Empirical evidence from seasonal coronaviruses indicates that prior exposure may only confer short-term immunity to reinfection, allowing recurrent outbreaks,” he says. However, he added that “this prior exposure may prime the immune system to provide some protection against severe disease.”

The researchers developed a “realistic age-structured (RAS)” mathematical model as a means of projecting COVID-19’s future history over the short, medium, and long term.

The model considers and allows for the modification of a range of variables, including demography, the amount of social interaction, and the duration of immunity that either blocks infection or reduces its severity.

“For many infectious respiratory diseases, prevalence in the population surges during a virgin epidemic but then recedes in a diminishing wave pattern, as the spread of the infection unfolds over time toward an endemic equilibrium,” says lead author Ruiyun Li.

Some experts have suggested an endemic future for SARS-CoV-2 for a while. Speaking to the National Security Strategy Committee in London in October 2020, the United Kingdom’s chief scientific advisor, Patrick Vallance, said:

“I think if you speak with most epidemiologists and most public health workers, they would say today that they believe this disease will become endemic, at least in the short term and most likely in the long term.”

“Depending on immunity and demography,” says Li, “our RAS model supports this observed trajectory — it predicts a strikingly different age structure at the start of the COVID-19 epidemic compared to the eventual endemic situation. In a scenario of long-lasting immunity, either permanent or at least 10 years, the young are predicted to have the highest rates of infection as older individuals are protected from new infections by prior infection.”

Researchers designed the model to project outcomes in 11 countries according to their differing demographics: China, Japan, South Korea, Spain, the U.K., France, Germany, Italy, United States, Brazil, and South Africa.

The eventual progress of the virus varies from country to country.

Li says, “Regardless of immunity and mixing, the population-level burden of mortality may differ among countries because of varying demographics.”

For example, co-author Prof. Nils Chr. Stenseth says, “Given the marked increase of the infection-fatality ratio with age, countries with older population structures would be expected to have a larger fraction of deaths than those with relatively younger population structures.”

Prof. Stenseth offers South Africa as an example. “South Africa — likely due, in part, to its younger population structure — has a lower number of deaths compared to older populations, such as Italy. We found that such ‘death disparities’ are heavily influenced by demographics. However, regardless of demographics, we predict a consistent shift of the risk to the young.”

The researchers intend to make their model accessible to health authorities as a powerful and flexible tool that can help them prepare for future developments and better predict the required deployment of interventions.

Dr. Bjornstad says, “The mathematical framework we built is flexible and can help in tailoring mitigation strategies for countries worldwide with varying demographics and social mixing patterns, thus providing a critical tool for policy decision-making.”