The coronavirus may eventually become a childhood infection, research suggests.
Young people rarely become seriously unwell with the coronavirus. In May, 2020, scientists from University College London even reported children are around half as likely to catch the infection in the first place.
Writing in the journal Science Advances, a team of US and Norwegian experts has now predicted the coronavirus will shift towards predominantly infecting younger people, who then endure mild symptoms or none at all.
The team has put this down to adults developing some degree of immunity after overcoming the coronavirus naturally or being vaccinated against it.
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Children are not routinely being immunised in the UK. On 4 August, the Joint Committee on Vaccination and Immunisation (JCVI) recommended that people aged 16 to 17 be offered a first dose of the Pfizer-BioNTech jab.
The JCVI already advised that children aged 12 to 15 who are at risk of coronavirus complications, or those aged 12 or over who live with a vulnerable person, be vaccinated.
"Following infection by [the coronavirus] there has been a clear signature of increasingly severe outcomes and fatality with age," said study author Dr Ottar Bjornstad, from Pennsylvania State University in the US.
"Yet, our modelling results suggest 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 model took into account the degree of social mixing, duration of "infection blocking" and any disease-preventing immunity in different groups of people.
United Nations data allowed the scientists to model the coronavirus's burden over one, 10 or 20 years in 11 countries, including the UK and US.
"Regardless of immunity and mixing, the population-level burden of mortality may differ among countries because of varying demographics,” said co-author Ruiyun Li, from the University of Oslo.
"Our general model framework allows for robust predictions of age-dependent risk in the face of either short or long-term protective immunity, reduction of severity of disease given previous exposure, and consideration of the range of countries with their different demographics and social mixing patterns."
Many countries have introduced "stay at home" restrictions at various points of the pandemic. The model therefore assumes the coronavirus' reproduction (R) number, a measure of its transmission, is linked to the movement of residents within a given country on a set day.
The model also accounts for various immunity scenarios, including whether the severity of the infection influences a person's subsequent protection and how long immunity may last, from as little as three months to forever.
"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," said Li.
"Depending on immunity and demography, our model supports this observed trajectory – it predicts a strikingly different age-structure at the start of the COVID-19 [the disease caused by the coronavirus] 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."
The coronavirus is one of seven strains of a virus class that are known to infect humans. Some of the other strains disproportionately infect children, who rarely become seriously ill.
"Historical records of respiratory diseases indicate age-incidence patterns during virgin epidemics can be very different from endemic circulation," said Dr Bjornstad.
"For example, ongoing genomic work suggests the 1889-1890 pandemic, sometimes known as the Asiatic or Russian flu – which killed 1 million people, primarily adults over age 70 – may have been caused by the emergence of HCoV-OC43 virus, which is now an endemic, mild, repeat-infecting cold virus affecting mostly children ages seven–12 months old."
Nevertheless, if coronavirus immunity wanes among adults, they could still be at high risk of infection.
The extent to which an individual is protected after overcoming the coronavirus naturally, or being immunised against it, has long been debated, particularly with the emergence of new variants.
"Empirical evidence from seasonal coronaviruses indicates that prior exposure may only confer short-term immunity to reinfection, allowing recurrent outbreaks," said Dr Bjornstad.
"This prior exposure may prime the immune system to provide some protection against severe disease, however, research on COVID-19 shows vaccination provides stronger protection than exposure to the [corona]virus, so we encourage everyone to get vaccinated as soon as possible."
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If previous infections do not protect against subsequent coronavirus exposure or prevent severe disease among older people, deaths may remain high.
"In this bleakest scenario, excess deaths due to continual severe reinfections that result from waning immunity will continue until more effective pharmaceutical tools are available," said co-author Dr Jessica Metcalf, from Princeton University.
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Perhaps surprisingly, variations in the population make-up of different countries suggest the coronavirus' severity may vary worldwide.
"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," said co-author Dr Jessica Metcalf, from Princeton University.
"Consistent with this, for 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 such 'death disparities' are heavily influenced by demographics, however, regardless of demographics, we predict a consistent shift of the risk to the young."
The scientists hope their model will help health officials predict how the coronavirus will circulate in different age groups going forward.
"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," added Dr Bjornstad.