Preliminary epidemiological analysis on children and adolescents with novel coronavirus disease 2019 outside Hubei Province, China: an observational study utilizing crowdsourced data

  1. Brandon Michael Henry
  2. Maria Helena Santos de Oliveira

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Abstract

Background

The outbreak of coronavirus disease 2019 (COVID-19) continues to expand across the world. Though both the number of cases and mortality rate in children and adolescents is reported to be low in comparison to adults, limited data has been reported on the outbreak with respect to pediatric patients. To elucidate information, we utilized crowdsourced data to perform a preliminary epidemiologic analysis of pediatric patients with COVID-19

Methods

In this observational study, data was collected from two open-access, line list crowdsourced online databases. Pediatric cases of COVID-19 were defined as patients ≤19 years of age with a laboratory confirmed diagnosis. The primary outcomes were case counts and cumulative case counts. Secondary outcomes included days between symptoms onset and first medical care and days between first medical care and reporting. Tertiary outcomes were rate of travel to Wuhan, rate of infected family members and rates of symptoms.

Results

A total of 82 patients were included. The median age was 10 [IQR: 5-15] years. Patients from mainland China (outside Hubei) accounted for 46.3% of cases, while the remaining 53.7% of cases were international. Males and females accounted for 52.4% and 32.9% of cases, respectively, with the remaining 14.6% being designated as unknown. A male skew persisted across subgroup analyses by age group (p=1.0) and location (inside/outside China) (p=0.22). While the number of reported international cases has been steadily increasing over the study period, the number of reported cases in China rapidly decreased from the start point. The median reporting delay was 3 [IQR: 2-4.8] days. The median delay between symptom onset and first seeking medical care was 1 [IQR: 0-3.25] day. In international cases, time to first seeking medical care was a median of 2.5 days longer than in China (p=0.04). When clinical features were reported, fever was the most common presentation (68.0%), followed by cough (36.0%).

Conclusions

The number of reported international pediatric COVID-19 cases is rapidly increasing. COVID-19 infections are, to-date, more common in males than females in both the children and adolescent age groups. Additionally, this male predominance remains the case both inside and outside of China. Crowdsourced data enabled early analysis of epidemiologic variables in pediatric patients with COVID-19. Further data sharing is required to enable analyses that are required to understand the course of this infection in children.

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  1. ScreenIT

    SciScore for 10.1101/2020.03.01.20029884: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: As only de-identified patient data from publicly available databases was used in this study, no patient consent was obtained, and no ethical approval was required.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line AuthenticationAuthentication: 5 Each report is linked to an original source to allow for authentication.

    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:
    This study has several limitations. First, it presents data from a limited sample of total pediatric cases of COVID-19. As noted by Sun et al., line list data is available for only a small number of Chinese provinces, while aggregated data on number of cases and mortality is provided by all.5 As such, cases from some provinces, including Hubei which is the center of the initial outbreak, were not able to be included. Cases in this study may also be those in whom the disease was severe enough to seek medical attention or identified by contact tracing, and as such, many minor cases may have been missed and symptomatology data skewed.5 Additionally, crowdsourced data would be less likely to capture mild cases as curated via the applied data collection modalities.5 Missing data was common for many of the included variables. Further efforts should be made to collect follow up data on patient outcomes. Limited data in children with respect to travel history or exposure prevented any estimation of incubation time. Sun et al. reported a median incubation time of 4.5 days [IQR: 3.0.5.5]5, while others using their data and other data sets have reported incubation rates of 5-6 days.21,32–34 In a case series of 10 children, Cai et al. observed a longer incubation than observed in adults, with a mean of 6.5 days (range 2-10 days) from exposure to symptoms.16 Further efforts should be made in the coming weeks to study transmission and estimate incubation time in pediatric patients to impro...

    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

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.03.01.20029884 on medRxiv