Effectiveness of Severe Acute Respiratory Syndrome Coronavirus 2 Messenger RNA Vaccines for Preventing Coronavirus Disease 2019 Hospitalizations in the United States.

BACKGROUND: As severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination coverage increases in the United States, there is a need to understand the real-world effectiveness against severe coronavirus disease 2019 (COVID-19) and among people at increased risk for poor outcomes. METHODS: In a multicenter case-control analysis of US adults hospitalized March 11-May 5, 2021, we evaluated vaccine effectiveness to prevent COVID-19 hospitalizations by comparing odds of prior vaccination with a messenger RNA (mRNA) vaccine (Pfizer-BioNTech or Moderna) between cases hospitalized with COVID-19 and hospital-based controls who tested negative for SARS-CoV-2. RESULTS: Among 1212 participants, including 593 cases and 619 controls, median age was 58 years, 22.8% were Black, 13.9% were Hispanic, and 21.0% had immunosuppression. SARS-CoV-2 lineage B0.1.1.7 (Alpha) was the most common variant (67.9% of viruses with lineage determined). Full vaccination (receipt of 2 vaccine doses ≥14 days before illness onset) had been received by 8.2% of cases and 36.4% of controls. Overall vaccine effectiveness was 87.1% (95% confidence interval [CI], 80.7-91.3). Vaccine effectiveness was similar for Pfizer-BioNTech and Moderna vaccines, and highest in adults aged 18-49 years (97.4%; 95% CI, 79.3-9.7). Among 45 patients with vaccine-breakthrough COVID hospitalizations, 44 (97.8%) were ≥50 years old and 20 (44.4%) had immunosuppression. Vaccine effectiveness was lower among patients with immunosuppression (62.9%; 95% CI,20.8-82.6) than without immunosuppression (91.3%; 95% CI, 85.6-94.8). CONCLUSION: During March-May 2021, SARS-CoV-2 mRNA vaccines were highly effective for preventing COVID-19 hospitalizations among US adults. SARS-CoV-2 vaccination was beneficial for patients with immunosuppression, but effectiveness was lower in the immunosuppressed population.

Duke Scholars

Author Christopher Lindsell Biostatistics & Bioinformatics, Division of Biostatistics