Modelling the effect of the interaction between vaccination and non-pharmaceutical measures on COVID-19 incidence

  1. Atsegine Canga
  2. Gorka Bidegain

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Abstract

Since December 2019, the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread rapidly from Wuhan (China) across the globe, affecting more than 200 countries by mid-2021, with over 190 M reported cases and around 4 M fatalities. During the first year of the pandemic, affected countries implemented a variety of non-pharmaceutical interventions to control virus transmission. In December 2020, countries started administering several authorised vaccines under a limited supply scenario. In this context, the aim of this study was to develop a SEIR-type continuous-time deterministic disease model, to determine the impact of interaction between different vaccination scenarios and levels of protection measures on disease incidence. For this, the model incorporates (i) a protection measure including low (self-protection), medium (mobility limitation), high (closure of indoor facilities) and very high (lockdown) protection levels, (ii) quarantine for confirmed cases, and (iii) vaccination rate and efficacy of four type of vaccines (Pfizer, Moderna, Astra Zeneca or Janssen). The model was verified and evaluated using the response timeline and vaccination strategies and rates in the Basque Country (N. Spain). Once the model performance was validated, different initial phase (when 30% of the population is vaccinated) vaccination scenarios were simulated, including (i) a realistic vaccine limited supply scenario, and (ii) four potential full vaccine supply scenarios where a unique vaccine type is administered. Some differences in disease incidence were found between vaccination scenarios for low and medium-level protection measures. However, regardless of the administered vaccine, a high-level protection scenario is the most effective to control the virus transmission and disease mortality in the studied initial phase of vaccination. The results obtained here may vary in further studies since there may be some unpredictable factors/covariates. With this in mind, the model here could be easily applied to other regions or countries, modifying the strategies implemented and initial conditions.

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  1. Version published to 10.1101/2021.11.29.21266986v2 on medRxiv
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    SciScore for 10.1101/2021.11.29.21266986: (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 numerical model for this ODE system is programmed in Matlab R2018a.
    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:
    This result is consistent with the fact that confirmed cases may be undercounted (Giattino, 2020) since one of the key limitations when modelling this disease is that the reported cases only become confirmed cases by a test, and there are a substantial proportion of infected people that never get tested because they were asymptomatic or never sought medical assistance. The model here, as well as others of this type or more sophisticated ones, use confirmed cases and deaths, testing rates, and a range of assumptions and epidemiological knowledge to estimate this proportion and consequently show a higher number of cases compared to the reported data (Giattino, 2020). This is also consistent with the seroprevalence study carried out in Spain, where around 33% of the infected cases were asymptomatic (Pollán et al., 2020). The simulation explored here for the limited vaccine supply scenario confirms that the model is correctly validated against the real data. The performance when increasing the protection measures from low-level to high-level non-pharmaceutical protection measures, follows the expected decreasing trend of COVID-19 cases and cumulative mortality. Comparing this scenario to the full vaccine supply scenarios results suggest that the Pfizer vaccine scenario is the one that maintains daily positive cases and deaths at the lowest levels even when the protection rate is low. Nevertheless, there is not a big variation between vaccines in terms of cases and cumulative mort...

    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.

    Results from scite Reference Check: We found no unreliable references.

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  3. Version published to 10.1101/2021.11.29.21266986v1 on medRxiv