A mathematical model for estimating the age-specific transmissibility of a novel coronavirus

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Abstract

Background

A novel coronavirus named as “SARS-CoV-2” has spread widely in many countries since December 2019, especially in China. This study aimed to quantify the age-specific transmissibility by using a mathematical model.

Methods

An age-specific susceptible – exposed – symptomatic – asymptomatic – recovered – seafood market (SEIARW) model was developed based on two suspected transmission routes (from market to person and person to person). The susceptible people from Wuhan City were divided into different age groups. We used the subscript i and j to represent age group 1 to 4 ( ij ; 1: ≤ 14 years; 2: 15-44 years; 3: 45-64 years; 4: ≥ 65 years) and 1 to 5 ( ij ; 1: ≤ 5 years; 2: 6-14 years; 3: 15-24 years; 4: 25-59 years; 4: ≥ 60 years), respectively. Data of reported COVID-19 cases were collected from one published literature from 26 November to 22 December, 2019 in Wuhan City, China. The age-specific transmissibility of the virus was estimated accordingly secondary attack rate ( SAR ).

Results

The age-specific SEIARW model fitted with the reported data well by dividing the population into four age groups ( χ 2 = 4.99 × 10 −6 , P > 0.999), and five age groups ( χ 2 = 4.85 × 10 −6 , P > 0.999). Based on the four-age-group SEIARW model, the highest transmissibility occurred from age group 2 to 3 ( SAR 23 = 17.56 per 10 million persons), followed by from age group 3 to 2 ( SAR 32 = 10.17 per 10 million persons). The lowest transmissibility occurred from age group 1 to 2 ( SAR 12 = 0.002 per 10 million persons). Based on the five-age-group SEIARW model, the highest transmissibility occurred from age group 4 to 5 ( SAR 45 = 12.40 per 10 million persons), followed by from age group 5 to 4 ( SAR 54 = 6.61 per 10 million persons). The lowest transmissibility occurred from age group 3 to 4 ( SAR 34 = 0.0002 per 10 million persons).

Conclusions

SARS-CoV-2 has high transmissibility among adults and elder people but low transmissibility among children and young people.

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  1. SciScore for 10.1101/2020.03.05.20031849: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Parameters estimation: The mean incubation period was 5.2 days (95% confidence interval [CI]: 4.1‒7.0) [2].
    CI]
    suggested: None
    The data was analyzed and figured by using Microsoft Office Excel 2010
    Microsoft Office Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)
    (Microsoft, Redmond, WA, USA) and GraphPad Prism 7.0 (GraphPad Software, La Jolla, CA).
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)
    The goodness of fit was judged by coefficient of determination (R2) and Chi-square (χ2) value calculated by SPSS 21.0 (IBM Corp, Armonk, NY, USA).
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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.

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