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Enregistrement W4200419868 · doi:10.1101/2021.12.08.21267162

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

2021· preprint· en· W4200419868 sur OpenAlexaffabout
Aaron Prosser, Bartosz Helfer, David L. Streiner

Notice bibliographique

RevuemedRxiv · 2021
Typepreprint
Langueen
DomaineMathematics
ThématiqueCOVID-19 epidemiological studies
Établissements canadiensMcMaster University
Organismes subventionnairesnon disponible
Mots-clésPandemicTransmission (telecommunications)MedicineVaccinationPopulationAbsolute risk reductionNumber needed to treatSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Relative riskDemographyCoronavirus disease 2019 (COVID-19)Environmental healthDiseaseVirologyConfidence intervalInternal medicineInfectious disease (medical specialty)

Résumé

récupéré en direct d'OpenAlex

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/ .

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,020
score de la tête « metaresearch » (Gemma)0,061
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,020
Score d'incertitude au seuil0,105

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0200,061
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0020,005
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,001
Communication savante0,0010,002
Science ouverte0,0010,001
Intégrité de la recherche0,0020,002
Charge utile insuffisante (le modèle a refusé de juger)0,0060,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,413
Tête enseignante GPT0,525
Écart entre enseignants0,113 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSimulation ou modélisation
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations3
Publié2021
Routes d'admission2
Résumé présentoui

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