Individuals aged 20-49 is the only groups sustaining COVID-19 transmission with reproduction numbers well above 1 in the US

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As of October 2020, individuals aged 20-49 were the only groups sustaining COVID-19 transmission with reproduction numbers well above 1 in the US, according to the latest publication in Science today by the Imperial College COVID-19 Response team.

Following initial declines, numbers of COVID-19 cases started to rise again halfway through 2020 in the United States and Europe. In September the team published report 32, using age-specific mobility data from across the United states and linking these to age-specific COVID-19 mortality.

Their findings pointed out that targeting interventions to adults aged 20-49 could facilitate safe reopening of schools and kindergartens.

The peer reviewed publication in Science today includes new data up to October 2020. The updated analysis of aggregated age-specific mobility data from more than 10 million individuals in the US, shows that 65 of 100 COVID-19 infections still originated from individuals aged 20-49 in the US.

Across the US as a whole, the mobility trends indicate substantial initial declines in venue visits (such as visit by an individual to locations like supermarkets and restaurants) followed by a subsequent rebound for all age groups.

In contrast with the large fluctuations in the share of age groups among reported COVID-19 cases, the study describes the share of age groups among the observed COVID-19 deaths remarkably constant.

The researchers find that in locations where novel highly-transmissible SARS-CoV-2 lineages have not yet established, additional interventions among adults aged 20-49, such as mass vaccination with transmission-blocking vaccines, could bring resurgent COVID-19 epidemics under control and avert deaths.

The work is presented in the latest report from Imperial’s Department of Mathematics and the WHO Collaborating Centre for Infectious Disease Modelling within the MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College London.

Since the emergence of the new coronavirus (COVID-19) in December 2019, the Imperial College COVID-19 Response Team has adopted a policy of immediately sharing research findings on the developing pandemic.

Dr. Samir Bhatt, from Imperial College London, said, “This work is a big step in understanding how age affects the dynamics of COVID-19 epidemics. We would like thank in particular all epidemiologists at state Departments of Health who work tirelessly to update data on the evolving COVID19 epidemics. Without this effort, this study would not have been possible.”

Dr. Melodie Monod, from Imperial College London, said, “We find adults aged 20-49 are a main driver of the COVID-19 epidemic in the United State and are the only age groups contributing disproportionally to onward spread, relative to their population size.

While children and teens contribute more to COVID19 spread since school closure mandates have been lifted in fall 2020, we find these dynamics have not changed substantially since school re-opening.”

Dr. Oliver Ratmann, from Imperial College London, concluded, “We believe this study is important because we demonstrate that adults aged 20-49 are the only age groups that have consistently sustained COVID-19 spread across the US, despite large variations in the scale and timing of local epidemics.

Thus—at least where highly transmissible variants have not established—additional interventions targeting the 20-49 age group could bring resurgent epidemics under control and avert deaths.”


Coronavirus disease 2019 (COVID-19) is caused by the infection of a novel severe acute respiratory syndrome-associated coronavirus (SARS-CoV-2) [1,2]. Since December 2019, over 11 million people have been infected with SARS-CoV-2 and over 528,000 people have died of coronavirus infection (https://coronavirus.jhu.edu/map.html, accessed on 4 July 2020).

Of them, elderly people and people with underlying chronic conditions suffered the heaviest disease burden [3,4,5]. For example, in the US, as reported by the US Center for Disease Control and Intervention, about 80% of deaths were people aged 65 or above (https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/cases-in-us.html), and 43.4% of hospitalizations were people aged 65 or above [6,7].

On the other hand, the case fatality rate of COVID-19 in South Korea was about 2.1% as of 16 July 2020, according to the Korea Center for Disease Control report (http://ncov.mohw.go.kr/en/).

The reasons for the disproportional burden among elderly people were unclear [8]. Elderly people generally have weaker immune systems than younger people due to aging, and they are also more likely to have multiple chronic conditions [9,10]. Thus, elderly people may have severe symptoms if infected with coronavirus [11,12].

On the other hand, elderly people may have been exposed to myriads of infections over their lifetime which may provide partial immunity against new virus infection. Although cross-reaction of antibodies between SARS-CoV and SARS-CoV-2 was observed, cross-neutralization was rare [13]. Thus, it was unlikely elderly people might have any effective immunity against SARS-CoV-2.

Epidemic data of high quality are essential to understand the mechanism of an epidemic and compare the courses of epidemic and risk patterns of infection across different groups. Unfortunately, due to insufficient testing kits, heterogeneous diagnosis criteria, and varied implementation of different interventions, epidemiological data on COVID-19 pandemic among different countries (and even within a country) and during different periods were often noncomparable [14].

One notable exception is South Korea, where extensive contact tracing and mass testing not only curtailed the epidemic but also generated high-quality data. In South Korea, both asymptomatic and symptomatic cases were identified promptly from the very beginning of the epidemic [15,16]. Thus, depicting a complete picture of the epidemic process was possible in South Korea.

In South Korea, the first case of COVID-19 occurred on 20 January 2020 and the major outbreak started on 19 February 2020. The COVID-19 pandemic was waning down since 10 March 2020 (see Figure 1) [17,18]. However, potential rebounds of new cases have been warned by many public health experts [19].

This is reflected in an epidemic curve with a long tail and occasional spikes, which is demonstrated in the epidemic process in South Korea (https://www.kcdc.info/covid-19/) [15,16]. In addition, if the seasonality, immunity, and cross-immunity of SARS-CoV-2 behave like previous coronaviruses, a recent study predicted that a long-lasting and multi-wave epidemic was possible [20].

Furthermore, after the first epidemic peak is passed, which suggests mitigating interventions are likely effective, the society is expected to gradually return to normalcy [21]. Strategies for re-opening the society should be evaluated, and exploring risk patterns of infection during the post-peak period will provide important evidence for decision-making.

In the COVID-19 epidemic, given the disproportional disease burden born by elderly people, it is imperative to examine risk patterns of coronavirus infection among elderly people after the peak of the epidemic.

Epidemic data from South Korea will allow us to examine the risk interactions among different age groups, which can serve as an exemplary reference model for other countries.

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Figure 1
Observed daily new cases of COVID-19 and predicted epidemic curve from the generalized additive model, South Korea, from 10 March to 30 April 2020, by age groups.

In this study, we will examine how risks of coronavirus infection interact across age groups using time series analysis. Using the high-quality data from South Korea, we will focus on the post-peak period of the epidemic process to evaluate the risk of infection among elderly people during the period of society re-opening.

reference link: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7400465/


More information: “Age groups that sustain resurging COVID-19 epidemics in the United States,” Science (2021). science.sciencemag.org/cgi/doi … 1126/science.abe8372

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