The importance of non-pharmaceutical interventions during the COVID-19 vaccine rollout

  1. Nicolò Gozzi
  2. Paolo Bajardi
  3. Nicola Perra

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Abstract

The promise of efficacious vaccines against SARS-CoV-2 is fulfilled and vaccination campaigns have started worldwide. However, the fight against the pandemic is far from over. Here, we propose an age-structured compartmental model to study the interplay of disease transmission, vaccines rollout, and behavioural dynamics. We investigate, via in-silico simulations, individual and societal behavioural changes, possibly induced by the start of the vaccination campaigns, and manifested as a relaxation in the adoption of non-pharmaceutical interventions. We explore different vaccination rollout speeds, prioritization strategies, vaccine efficacy, as well as multiple behavioural responses. We apply our model to six countries worldwide (Egypt, Peru, Serbia, Ukraine, Canada, and Italy), selected to sample diverse socio-demographic and socio-economic contexts. To isolate the effects of age-structures and contacts patterns from the particular pandemic history of each location, we first study the model considering the same hypothetical initial epidemic scenario in all countries. We then calibrate the model using real epidemiological and mobility data for the different countries. Our findings suggest that early relaxation of safe behaviours can jeopardize the benefits brought by the vaccine in the short term: a fast vaccine distribution and policies aimed at keeping high compliance of individual safe behaviours are key to mitigate disease resurgence.

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  1. Version published to 10.1371/journal.pcbi.1009346
  2. ScreenIT

    SciScore for 10.1101/2021.01.09.21249480: (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 epidemic model is implemented using the python library scipy [77] and optimized with numba [78].
    scipy
    suggested: (SciPy, RRID:SCR_008058)
    Visualizations are realized with the python library matplotlib [79].
    python
    suggested: (IPython, RRID:SCR_001658)
    matplotlib
    suggested: (MatPlotLib, RRID:SCR_008624)

    Results from OddPub: Thank you for sharing your code and data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    We acknowledge some limitations in the present study. First, the vaccine is modeled as protective towards infection, without modeling the protection against severe COVID-19 complications and potential reduction of viral shedding in infected vaccinated individuals. At the time of writing, such information are still matters of study even for the vaccines already approved by regulators. For the sake of simplicity, we also considered the vaccines fully working immediately after the first dose. We have also considered two simple vaccination strategies that neglect the complexities of an unprecedented mass vaccination. As result, both the vaccination priorities and rates are an approximation of reality. While the model calibration suggests that our approach can nicely capture the national trend, our model is not meant to provide accurate forecasts of the local unfolding of the disease, but rather to test what-if scenarios in a comparative fashion. We have considered a simple age-structure compartmental model that does not capture spatio-temporal heterogeneity both in terms of spreading and of NPIs implementation which have instead been observed in the countries under investigation. Our model does not include the emergence of a new, more transmissible, strain in the UK. The variant took over in December and led to a significant spike of cases, hospitalizations and deaths. As result, the government imposed a third lock-down in the first days of 2021 which is more restrictive than our...

    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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  3. Version published to 10.1101/2021.01.09.21249480 on medRxiv