#16,020
In April of last year (see COVID-19: From Here To Immunity) and again in July 2020 (see COVID-19: From here To Immunity (Take Two) we looked at some of the obstacles that might either delay or prevent society from achieving herd immunity - either from natural infection or a vaccine - to the novel coronavirus.
Despite being touted by politicians as being the `way out of the pandemic', achieving herd immunity was always a long shot (see GAO: A Herd Immunity For COVID-19 Primer).
The more likely alternative was - between acquired immunity and (likely) yearly vaccinations - we might eventually be able to `manage' COVID-19 much like we do influenza. It would return on a regular basis, but only spark regional epidemics.
This move - from our current pandemic phase - to endemicity and likely `seasonal' outbreaks, is further complicated by COVID's ability to reinvent itself into new, more transmissible, variants.
Assuming SARS-CoV-2 eventually slows down its generation of new, increasingly dangerous variants (see UK SAGE: Can We Predict the Limits of SARS-CoV-2 Variants and their Phenotypic Consequences?), we should reach some sort of an uneasy truce with the virus in the next year or two.
Exactly what that would look like 5 or 10 years from now is unknown, although it is frequently suggested that COVID could become another in the panoply of seasonal ILI (Influenza-like-illnesses) that return each winter.
In an attempt to predict how endemic COVID might impact society in the short, medium and long term (1, 10 and 20 years, respectively), a team of researchers from the U.S. and Norway have developed extensive mathematical models that - while not set in stone - suggest the burden of COVID will eventually shift more from adults to children.
First, some excerpts from the press release from Pennsylvania State University, then a link and the abstract from the research article.
Will COVID-19 become a mostly childhood disease?
COVID-19 risks may shift from older adults to younger children as the SARS-CoV-2 virus becomes endemic, according to new modeling results Peer-Reviewed Publication
PENN STATE
UNIVERSITY PARK, Pa. — Within the next few years, as the SARS-CoV-2 virus becomes endemic in the global population, COVID-19 may behave like other common-cold coronaviruses, affecting mostly young children who have not yet been vaccinated or exposed to the virus, according to new modeling results. Because COVID-19 severity is generally lower among children, the overall burden from this disease is expected to decline.
“Following infection by SARS-CoV-2, there has been a clear signature of increasingly severe outcomes and fatality with age,” said Ottar Bjornstad. “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.”
Bjornstad explained that such shifts have been observed in other coronaviruses and influenza viruses as they have emerged and then become endemic.
“Historical records of respiratory diseases indicate that age-incidence patterns during virgin epidemics can be very different from endemic circulation,” he said. “For example, ongoing genomic work suggests that the 1889-1890 pandemic, sometimes known as the Asiatic or Russian flu — which killed one 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 7-12 months old.”
Bjornstad cautioned, however, that if immunity to reinfection by SARS-CoV-2 wanes among adults, disease burden could remain high in that group, although previous exposure to the virus would lessen the severity of disease.
“Empirical evidence from seasonal coronaviruses indicates that prior exposure may only confer short-term immunity to reinfection, allowing recurrent outbreaks, this prior exposure may prime the immune system to provide some protection against severe disease,” said Bjornstad. “However, research on COVID-19 shows that vaccination provides stronger protection than exposure to the SARS-CoV-2 virus, so we encourage everyone to get vaccinated as soon as possible.”
The U.S.-Norwegian team developed what is known as a “realistic age-structured (RAS) mathematical model” that integrates demography, degree of social mixing, and duration of infection-blocking and disease-reducing immunity to examine potential future scenarios for age-incidence and burden of mortality for COVID-19.
Specifically, the researchers examined disease burden over immediate, medium and long terms — 1, 10 and 20 years, respectively. They also examined disease burden for 11 different countries — including China, Japan, South Korea, Europe, Spain, United Kingdom, France, Germany, Italy, United States, Brazil and South Africa — that differed widely in their demographics. They used data from the United Nations for each of these countries to parameterize the model.
“Regardless of immunity and mixing, the population-level burden of mortality may differ among countries because of varying demographics,” said Ruiyun Li, postdoctoral fellow, 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.”
According to Li, social distancing is well documented to affect transmissibility, and many countries implemented interventions, such as “shelter in place,” during the build-up of the virgin COVID-19 epidemic. Therefore, the team’s model assumes that the reproduction number (R0) — or the level of transmissibility — on any given day is linked to the amount of mobility on that day. The model also incorporates a variety of scenarios for immunity, including both independence and dependence of disease severity on prior exposure, as well as short- (either three months or one year) and long-term (either 10 years or permanent) immunity.
The team’s results appear today (August 11) in the journal Science Advances.
The full open-access study (warning, heavy math ahead) can be read at the link below. Due to its length, I've only posted the abstract.
RESEARCH ARTICLEHEALTH AND MEDICINE
Abstract
Anticipating the medium- and long-term trajectory of pathogen emergence has acquired new urgency given the ongoing COVID-19 pandemic. For many human pathogens, the burden of disease depends on age and previous exposure. Understanding the intersection between human population demography and transmission dynamics is therefore critical.
Here, we develop a realistic age-structured mathematical model that integrates demography, social mixing, and immunity to establish a plausible range for future age incidence and mortality. With respect to COVID-19, we identify a plausible transition in the age structure of risks once the disease reaches seasonal endemism across a range of immunity durations and relative severity of primary versus subsequent reinfections. We train the model using diverse real-world demographies and age-structured mixing to bound expectations for changing age incidence and disease burden. The mathematical framework is flexible and can help tailor mitigation strategies in countries worldwide with varying demographies and social mixing patterns
