Evaluating the number of unvaccinated people needed to exclude to prevent SARS-CoV-2 transmissions

  1. Aaron Prosser
  2. Bartosz Helfer
  3. David L. Streiner

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Abstract

Background

Vaccine mandates and vaccine passports (VMVP) for SARS-CoV-2 are thought to be a path out of the pandemic by increasing vaccination through coercion and excluding unvaccinated people from different settings because they are viewed as being at significant risk of transmitting SARS-CoV-2. While variants and waning efficacy are relevant, SARS-CoV-2 vaccines reduce the risk of infection, transmission, and severe illness/hospitalization in adults. Thus, higher vaccination levels are beneficial by reducing healthcare system pressures and societal fear. However, the benefits of excluding unvaccinated people are unknown.

Methods

A method to evaluate the benefits of excluding unvaccinated people to reduce transmissions is described, called the number needed to exclude (NNE). The NNE is analogous to the number needed to treat (NNT=1/ARR), except the absolute risk reduction (ARR) is the baseline transmission risk in the population for a setting (e.g., healthcare). The rationale for the NNE is that exclusion removes all unvaccinated people from a setting, such that the ARR is the baseline transmission risk for that type of setting, which depends on the secondary attack rate (SAR) typically observed in that type of setting and the baseline infection risk in the population. The NNE is the number of unvaccinated people who need to be excluded from a setting to prevent one transmission event from unvaccinated people in that type of setting. The NNE accounts for the transmissibility of the currently dominant Delta (B.1.617.2) variant to estimate the minimum NNE in six types of settings: households, social gatherings, casual close contacts, work/study places, healthcare, and travel/transportation. The NNE can account for future potentially dominant variants (e.g., Omicron, B.1.1.529). To assist societies and policymakers in their decision-making about VMVP, the NNEs were calculated using the current (mid-to-end November 2021) baseline infection risk in many countries.

Findings

The NNEs suggest that at least 1,000 unvaccinated people likely need to be excluded to prevent one SARS-CoV-2 transmission event in most types of settings for many jurisdictions, notably Australia, California, Canada, China, France, Israel, and others. The NNEs of almost every jurisdiction examined are well within the range of the NNTs of acetylsalicylic acid (ASA) in primary prevention of cardiovascular disease (CVD) (≥ 250 to 333). This is important since ASA is not recommended for primary prevention of CVD because the harms outweigh the benefits. Similarly, the harms of exclusion may outweigh the benefits. These findings depend on the accuracy of the model assumptions and the baseline infection risk estimates.

Conclusions

Vaccines are beneficial, but the high NNEs suggest that excluding unvaccinated people has negligible benefits for reducing transmissions in many jurisdictions across the globe. This is because unvaccinated people are likely not at significant risk – in absolute terms – of transmitting SARS-CoV-2 to others in most types of settings since current baseline transmission risks are negligible. Consideration of the harms of exclusion is urgently needed, including staffing shortages from losing unvaccinated healthcare workers, unemployment/unemployability, financial hardship for unvaccinated people, and the creation of a class of citizens who are not allowed to fully participate in many areas of society.

Registration

CRD42021292263

Funding

This study received no grant from any funding agency, commercial, or not-for-profit sectors. It has also received no support of any kind from any individual or organization. BH is supported by a personal research grant from the University of Wroclaw within the “Excellence Initiative – Research University” framework and by a scholarship from the Polish Ministry of Education and Science. None of these institutions were involved in this research and did not fund it directly.

Competing interests

The authors have no competing interests to declare.

Ethical approval

Not applicable. All the work herein was performed using publicly available data.

Data reporting

The data used in this work are available at https://tinyurl.com/4m8mm4jh and https://decision-support-tools.com/ .

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  1. ScreenIT

    SciScore for 10.1101/2021.12.08.21267162: (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
    To identify these meta-analyses, we searched PubMed from inception to November 26, 2021, with no language restrictions.
    PubMed
    suggested: (PubMed, RRID:SCR_004846)

    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:
    Notwithstanding this limitation, we have provided a ‘proof of concept’ of how baseline infection risk data can be used to calculate the NNE to evaluate the benefits of excluding unvaccinated people to reduce SARS-CoV-2 transmissions. Future research should focus on developing an online interactive global database of the NNEs and baseline infection risks in each region which is regularly updated. Furthermore, this interactive database should be linked to regional vaccination rates, SARS-CoV-2-related hospitalizations/deaths, hospital/ICU occupancy, and the basic and effective reproduction number to contextualize the NNEs within other important metrics. This would be helpful for societies and policymakers to evaluate in real-time the harms vs. benefits of excluding unvaccinated people. Health economic analyses are also needed to analyze the cost-effectiveness and cost-benefits of excluding unvaccinated people. Future studies could incorporate vaccine/natural immunity data into the model to explore the impact of herd immunity on the NNE. Finally, when new variants emerge (e.g., Omicron) and potentially outcompete the Delta variant, the NNEs should be updated with the transmissibility data of future dominant variants.

    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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  2. Version published to 10.1101/2021.12.08.21267162 on medRxiv