Protection of hybrid immunity against SARS-CoV-2 reinfection and severe COVID-19 during periods of Omicron variant predominance in Mexico
Notice bibliographique
Résumé
ABSTRACT BACKGROUND With widespread transmission of the Omicron SARS-CoV-2 variant, reinfections have become increasingly common. Here, we explored the role hybrid immunity, primary infection severity, and variant predominance on the risk of reinfection and severe COVID-19 during periods of Omicron predominance in Mexico. METHODS We analyzed reinfections in Mexico in individuals with ≥90 days from a previous primary infection using a national surveillance registry of SARS-CoV-2 cases from March 3 rd , 2020, until August 13 th , 2022. Immunity-generating events included primary infection, partial or full vaccination and vaccine boosting. Reinfections were matched by age and sex with controls with primary SARS-CoV-2 infection and negative RT-PCR or antigen test ≥90 days after infection to explore risk factors for reinfection and reinfection-associated severe COVID-19. We also explored the protective role of heterologous vs. homologous vaccine boosters against reinfection or severe COVID-19 in fully vaccinated individuals. RESULTS We detected 231,202 SARS-CoV-2 reinfections in Mexico, with most occurring in unvaccinated individuals (41.55%). Over 207,623 reinfections occurred during periods of Omicron (89.8%), BA.1 (36.74%) and BA.5 (33.67%) subvariant predominance and a case-fatality rate of 0.22%. Vaccination protected against reinfection, without significant influence of the order of immunity-generating events and provided >90% protection against severe reinfections. Heterologous booster schedules were associated with ∼11% and ∼54% lower risk for reinfection and reinfection-associated severe COVID-19 respectively, modified by time-elapsed since the last immunity-generating event. CONCLUSIONS SARS-CoV-2 reinfections have increased during periods of Omicron predominance. Hybrid immunity provides protection against reinfection and reinfection-associated severe COVID-19, with potential benefit from heterologous booster schemes. RESEARCH IN CONTEXT Evidence before this study We searched PubMed for the terms “SARS-CoV-2” AND “reinfection” AND “hybrid immunity” until November 20 th , 2022, and identified a few population studies previously conducted in Israel, Sweden, Qatar, United States and Canada which explored risk of reinfection and the protective role of hybrid immunity in individuals with one, two or three doses of COVID-19 vaccines, predominantly during periods of predominance of Omicron BA.1 and BA.2 subvariants. Notably, no studies were conducted in any Latin American country or reported on the benefit of heterologous booster schemes or the order of immunity-generating events. Added value of this study We report the results of nation-wide study in Mexico of over 230,000 SARS-CoV-2 reinfections, with ∼90% occurring during periods of Omicron predominance. We identified that vaccination provided additional benefit on reducing the risk of SARS-CoV-2 reinfection, with the highest benefit observed in individuals with complete vaccination and booster protocols prior to primary infection or with primary infection during periods of BA.1 and BA.2 subvariant predominance. Hybrid immunity also provides a substantial reduction in the risk of reinfection-associated severe COVID-19, with >90% reduction in risk compared to unvaccinated individuals with previous SARS-CoV-2 infection, regardless of the order of immunity-generating events. Finally, heterologous COVID-19 booster schedules were associated with ∼11% and ∼54% lower risk for reinfection and reinfection-associated severe COVID-19 respectively, modified by time-elapsed since the last immunity-generating event. Implications of all the available evidence Our results support that COVID-19 vaccination and boosters provide additional benefit to protect against SARS-CoV-2 reinfection and reinfection-associated severe COVID-19. The use of heterologous boosters appears to provide additional protection in previously infected individuals and such schemes may prove beneficial to increase vaccination coverage as newer, more transmissible variants emerge.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».