Prevalence of COVID-19 in adolescents and youth compared with older adults in states experiencing surges

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Abstract

There has been considerable controversy regarding susceptibility of adolescents (10–19 years) and youth (15–24 years) to COVID-19. However, a number of studies have reported that adolescents are significantly less susceptible than older adults. Summer 2020 provided an opportunity to examine data on prevalence since after months of lockdowns, with the easing of restrictions, people were mingling, leading to surges in cases.

Methods

We examined data from Departments of Health websites in six U.S. states experiencing surges in cases to determine prevalence of COVID-19, and two prevalence-related measures, in adolescents and youth as compared to older adults. The two other measures related to prevalence were: (Percentage of cases observed in a given age group) ÷ (percentage of cases expected based on population demographics); and percentage deviation, or [(% observed—% expected)/ % expected] x 100.

Results

Prevalence of COVID-19 for adolescents and for youth was significantly greater than for older adults (p < .00001), as was percentage observed ÷ percentage expected (p < .005). The percentage deviation was significantly greater in adolescents/youth than in older adults (p < 0.00001) when there was an excess of observed cases over what was expected, and significantly less when observed cases were fewer than expected (p< 0.00001).

Conclusions

Our results are contrary to previous findings that adolescents are less susceptible than older adults. Possible reasons for the findings are suggested, and we note that public health messaging targeting adolescents and youth might be helpful in curbing the pandemic. Also, the findings of the potential for high transmission among adolescents and youth, should be factored into decisions regarding school reopening.

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  1. SciScore for 10.1101/2020.10.20.20215541: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.


    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).


    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    A limitation of this study is that case data on state website are presumably based on people tested because they were either symptomatic, or they were exposed to someone who was thought to be infected, or they were seeking medical treatment for some other condition and the medical facility required COVID-19 testing. That still leaves some infected individuals who were asymptomatic but did not get tested because they did not fall into the latter two categories. Would their inclusion alter our results? There are two possibilities regarding asymptomatic individuals: (i) Either the number of asymptomatic infections is a constant function of the number of symptomatic ones regardless of age, as the CDC statement on June 25th implied “Our best estimate right now is that for every case that’s reported, there actually are 10 other infections.”16 In such a scenario, the conclusions regarding our prevalence data would be unaffected since the relative proportions would remain the same. (ii) Or that the manifestation of clinical symptoms is age-dependent as Davies et al. maintain in a part of their model that deals with the clinical fraction of cases that are symptomatic vs. asymptomatic. They estimate that clinical symptoms manifest in 21% of adolescents but in 63-69% of older adults ages 60+. This would imply that there are many more asymptomatic adolescents than asymptomatic older adults: Accordingly, if asymptomatic individuals were added to our data set, our conclusions that prevalen...

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

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