Study: COVID-19 to become endemic and primarily a childhood disease

alopah Date:2021-08-18 11:44:32
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According to new modeling results, COVID-19 is likely to behave like other common cold coronaviruses in the coming years as the SARS-CoV-2 virus becomes endemic in the global population, primarily affecting young children who have not yet been vaccinated or exposed to the virus, according to foreign media reports. Because the severity of COVID-19 is generally lower in children, the overall burden of the disease is expected to decline.


The increasing severity of outcome and mortality with age after SARS-CoV-2 infection is a clear indication,” said researcher Ottar Bjornstad. However, our modeling results suggest that as the adult community becomes immune through vaccination or exposure to the virus, the risk of infection may transfer to younger children.”


Bjornstad explained that this change was also observed when other coronaviruses and influenza viruses emerged and subsequently became endemic.


“The historical record of respiratory disease suggests that age-incidence patterns during initial epidemics may be very different from those of endemic disease. For example, ongoing genomic studies suggest that the 1889 – 1890 pandemic that killed one million people, primarily adults over the age of 70, may have been due to the emergence of the HCoV-OC43 virus, which now becomes an epidemic, mild, recurrent influenza virus in most children between 7 and 12 months of age.”


However, Bjornstad warned that if adults become less immune to re-infection with SARS-CoV-2, the disease burden in this group may remain high despite prior exposure to the virus reducing the severity of the disease.


Empirical evidence from seasonal coronaviruses suggests that prior exposure may result in only short-term immunity to reinfection, leading to recurrent outbreaks, and that such prior exposure may initiate the immune system and thus provide some protection against severe disease,” Bjornstad said. However, studies of COVID-19 have shown 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.-Norway team developed a mathematical model known as the Realistic Age Structure (RAS) model, which integrates demographics, social mixing, infection blockade and duration of disease-reducing immunity to examine potential future scenarios of age-specific morbidity and mortality burden for COVID-19.


Specifically, the researchers examined the short-, medium- and long-term burden of disease – 1, 10 and 20 years, respectively. They also looked at the burden of disease in 11 different countries, including China, Japan, Korea, Europe, Spain, the United Kingdom, France, Germany, Italy, the United States, Brazil and South Africa, which have widely varying demographics. They parameterized the model for each country using data from the United Nations.




Regardless of immunization and mixing, the burden of population mortality may vary across countries due to differences in demographics,” said Ruiyun Li, a postdoctoral fellow at the University of Oslo. Our general modeling framework allows for robust prediction of age-dependent risk in the face of short-term or long-term protective immunization, taking into account reduced severity of previously exposed diseases and accounting for a range of countries with different demographics and social mixing patterns.”


Li said there is strong evidence that social distance affects transmission, and many countries implemented interventions such as “shelter-in-place” during the development of the first COVID-19 outbreak. Therefore, the team’s model assumes that the number of reproductions (R0) – or level of transmission – on any given day is related to the mobility of that day. The model also covers a variety of immunization scenarios, including independence and dependence of disease severity on prior exposure and short-term (three months or one year) and long-term (10 years or permanent) immunization.


The team’s findings were published in Science Advances on Aug. 11, 2021.


“For many infectious respiratory diseases, population prevalence spikes during the initial epidemic, but declines in a decreasing wave pattern as the spread of infection gradually unfolds over time toward endemic equilibrium,” Li said, “Based on immunity and demographics, our Our RAS model supports this observed trajectory; it predicts that the age structure at the start of the COVID-19 epidemic is very different from the eventual prevalence. In the case of long-term immunization, either permanent or for at least 10 years, the infection rate is expected to be highest in younger people, as older people are protected from new infections by previous infections.”


Jessica Metcalf, associate professor of ecology, evolutionary biology and public affairs at Princeton University, noted that this prediction could hold true only if reinfection produced only mild disease. However, she said, if primary infections do not prevent reinfection or mitigate serious illness in older adults, the burden of mortality may not change over time. “In this most pessimistic scenario, additional deaths from persistent severe reinfection due to decreased immunity will persist until more effective pharmacologic tools become available.”


Interestingly, the model predicts different results for different countries due to differences in demographics.


Given the significant increase in mortality from infection with age, countries with older demographics are expected to have a larger proportion of deaths than countries with relatively younger demographics,” said Nils Chr. Stenseth, professor of ecology and evolution at the University of Oslo. Consistent with this, South Africa, for example – probably due in part to its young demographics – has fewer deaths compared to older populations such as Italy. We find that this ‘death differential’ is heavily influenced by demographics. Yet regardless of demographics, we expect the risk to continue to shift to younger people.”


The researchers said they designed the model to give health authorities a powerful and flexible tool that can be used to examine the future age cycle of COVID-19 and thus enhance prevention and deployment of interventions.


Bjornstad said, “The mathematical framework we have developed is flexible and can help countries around the world with different demographics and social mixing patterns to adapt mitigation strategies thus providing a key tool for policy decisions.”


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