Effects of previous infection, vaccination, and hybrid immunity against symptomatic Alpha, Beta, and Delta SARS-CoV-2 infections: an observational study. Academic Article uri icon

Overview

abstract

  • BACKGROUND: Protection against SARS-CoV-2 symptomatic infection and severe COVID-19 of previous infection, mRNA two-dose vaccination, mRNA three-dose vaccination, and hybrid immunity of previous infection and vaccination were investigated in Qatar for the Alpha, Beta, and Delta variants. METHODS: Six national, matched, test-negative, case-control studies were conducted between January 18 and December 18, 2021 on a sample of 239,120 PCR-positive tests and 6,103,365 PCR-negative tests. FINDINGS: Effectiveness of previous infection against Alpha, Beta, and Delta reinfection was 89.5% (95% CI: 85.5-92.3%), 87.9% (95% CI: 85.4-89.9%), and 90.0% (95% CI: 86.7-92.5%), respectively. Effectiveness of two-dose BNT162b2 vaccination against Alpha, Beta, and Delta infection was 90.5% (95% CI, 83.9-94.4%), 80.5% (95% CI: 79.0-82.0%), and 58.1% (95% CI: 54.6-61.3%), respectively. Effectiveness of three-dose BNT162b2 vaccination against Delta infection was 91.7% (95% CI: 87.1-94.7%). Effectiveness of hybrid immunity of previous infection and two-dose BNT162b2 vaccination was 97.4% (95% CI: 95.4-98.5%) against Beta infection and 94.5% (95% CI: 92.8-95.8%) against Delta infection. Effectiveness of previous infection and three-dose BNT162b2 vaccination was 98.1% (95% CI: 85.7-99.7%) against Delta infection. All five forms of immunity had >90% protection against severe, critical, or fatal COVID-19 regardless of variant. Similar effectiveness estimates were observed for mRNA-1273. A mathematical model accurately predicted hybrid immunity protection by assuming that the individual effects of previous infection and vaccination acted independently. INTERPRETATION: Hybrid immunity, offering the strongest protection, was mathematically predicted by assuming that the immunities obtained from previous infection and vaccination act independently, without synergy or redundancy. FUNDING: The Biomedical Research Program and the Biostatistics, Epidemiology, and the Biomathematics Research Core, both at Weill Cornell Medicine-Qatar, Ministry of Public Health, Hamad Medical Corporation, Sidra Medicine, Qatar Genome Programme, Qatar University Biomedical Research Center, and Qatar University Internal Grant ID QUCG-CAS-23/24-114.

authors

  • Altarawneh, Heba N
  • Chemaitelly, Hiam Souheil
  • Ayoub, Houssein H
  • Tang, Patrick
  • Hasan, Mohammad R
  • Yassine, Hadi M
  • Al-Khatib, Hebah A
  • Al Thani, Asmaa A
  • Coyle, Peter
  • Al-Kanaani, Zaina
  • Al-Kuwari, Einas
  • Jeremijenko, Andrew
  • Kaleeckal, Anvar Hassan
  • Latif, Ali Nizar
  • Shaik, Riyazuddin Mohammad
  • Abdul-Rahim, Hanan F
  • Nasrallah, Gheyath K
  • Al-Kuwari, Mohamed Ghaith
  • Butt, Adeel A
  • Al-Romaihi, Hamad Eid
  • Al-Thani, Mohamed H
  • Al-Khal, Abdullatif
  • Bertollini, Roberto
  • Abu-Raddad, Laith Jamal

publication date

  • July 27, 2023

Research

keywords

  • COVID-19
  • Hepatitis D

Identity

Digital Object Identifier (DOI)

  • 10.1016/j.ebiom.2023.104734

PubMed ID

  • 37515986

Additional Document Info

volume

  • 95