A Computer Simulation Study on novel Corona Virus Transmission among the People in a Queue

  1. Santhosh Samuel Mathews

Reviewed by

Read the full article

Listed in

Log in to save this article

Abstract

The World Health Organization (WHO) on March 11, 2020, has declared the novel Corona virus (COVID-19) outbreak a global pandemic. It is essential to understand how coronavirus transmits from one person to another and this knowledge will help protect the vulnerable and limit the spread of the Corona virus. The mode of respiratory transmission of Corona virus is not completely understood as of date. Using a computer simulation, this paper analyses the probability of spreading of Corona virus through air among the people who are standing in a queue. The parameters such as the diameter of the virus particle, room temperature, relative humidity, height of the person, distance between the people and the waiting time in the queue are considered in the computer model to determine the distribution of Corona virus and hence identify the risk factor of spreading the Covid-19. This paper describes the possibilities of getting infectious when a Covid-19 infected person present in a queue and the impact on the waiting time and the position in the queue on the transmission of Corona virus.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.05.16.20104489: (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
    The Python libraries are extensively used for this computer model.
    Python
    suggested: (IPython, RRID:SCR_001658)

    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: Please consider improving the rainbow (“jet”) colormap(s) used on page 11. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.

    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 10.1101/2020.05.16.20104489v2 on medRxiv
  3. Version published to 10.1101/2020.05.16.20104489v1 on medRxiv