Modeling the potential impact of indirect transmission on COVID-19 epidemic

  1. Jummy David
  2. Sarafa A. Iyaniwura
  3. Pei Yuan
  4. Yi Tan
  5. Jude Kong
  6. Huaiping Zhu

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Abstract

The spread of SARS-CoV-2 through direct transmission (person-to-person) has been the focus of most studies on the dynamics of COVID-19. The efficacy of social distancing and mask usage at reducing the risk of direct transmission of COVID-19 has been studied by many researchers. Little or no attention is given to indirect transmission of the virus through shared items, commonly touch surfaces and door handles. The impact of the persistence of SARS-CoV-2 on hard surfaces and in the environment, on the dynamics of COVID-19 remain largely unknown. Also, the current increase in the number of cases despite the strict non-pharmaceutical interventions suggests a need to study the indirect transmission of COVID-19 while incorporating testing of infected individuals as a preventive measure. Assessing the impact of indirect transmission of the virus may improve our understanding of the overall dynamics of COVID-19. We developed a novel deterministic susceptible-exposed-infected-removed-virus-death compartmental model to study the impact of indirect transmission pathway on the spread of COVID-19, the sources of infection, and prevention/control. We fitted the model to the cumulative number of confirmed cases at episode date in Toronto, Canada using a Markov Chain Monte Carlo optimization algorithm. We studied the effect of indirect transmission on the epidemic peak, peak time, epidemic final size and the effective reproduction number, based on different initial conditions and at different stages. Our findings revealed an increase in cases with indirect transmission. Our work highlights the importance of implementing additional preventive and control measures involving cleaning of surfaces, fumigation, and disinfection to lower the spread of COVID-19, especially in public areas like the grocery stores, malls and so on. We conclude that indirect transmission of SARS-CoV-2 has a significant effect on the dynamics of COVID-19, and there is need to consider this transmission route for effective mitigation, prevention and control of COVID-19 epidemic.

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  1. ScreenIT

    SciScore for 10.1101/2021.01.28.20181040: (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
    Main Outcomes: We give numerical results of the SEIRVD model (1) computed using the MATLAB numerical ODE solver ODE45 [34].
    MATLAB
    suggested: (MATLAB, RRID:SCR_001622)

    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:
    As a limitation, the model is developed for a region or geographical area where the testing of individuals is readily available. This model does not consider heterogeneous mixing between two or more populations/regions. An extension of the model to include heterogeneous mixing of individuals consisting of multiple populations should be straightforward. Our work considered a general population and our results are generated as crude estimates. Projects on model stratification according to age, gender, region, socio-economic status are underway. We did not look into the impact of opinion and individual behaviour known to significantly modify the risk of COVID-19 transmission [49–51]. Therefore we could not evaluate the effect of indirect transmission for different opinion and behaviour, and the complexities that exist in behavioural changes. Even though, these conditions are somewhat important factors in modeling the transmission of COVID-19, modeling their effects would make the model more complicated, which is beyond the scope of this study, and therefore considered as one of the future works we intend to explore. Despite these limitations, our findings show that reducing the transmission of the virus through indirect route would significantly decrease the spread of the disease, especially when efforts are concentrated more on the symptomatic individuals through further isolation and/or hospitalization. We believe that models that do not consider indirect transmission of the v...

    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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  2. Version published to 10.1101/2021.01.28.20181040 on medRxiv