In a recent article published in BMC Public Health, researchers analyzed the relationship between time-varying vaccination rates against coronavirus disease 2019 (COVID-19) and the COVID-19 case hospitalization risk (CHR), an indicator of disease severity at the individual level and the burden of illness on population-level health systems during different severe waves of the variant of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the United States (USA).
By March 1, 2023, there were 1.1 million deaths due to COVID-19 in the USA. COVID-19 vaccines have been most effective in curbing the disease and its impact, including the socioeconomic burden on the population and the country’s health system.
However, studies evaluating the effectiveness of COVID-19 vaccines have relied on individual-level data that have been distorted by unquantified factors and inconsistent quality.
Therefore, high-resolution population-level data reflecting the real relative relationships between available COVID-19 vaccines and COVID-19 CHR over time were not available for the USA.
Über die Studie
The present study examined the relationship between COVID-19 vaccination rates and CHR in 48 US states from April 19, 2021, to March 1, 2022, using Generalized Additive Models (GAMs).
The study model captured nonlinear dynamics and considered dynamic (time-varying) and static (time-constant) factors that may contribute to COVID-19 CHR and disease transmission.
Among the former, natural immunity resulting from a previous infection with SARS-CoV-2, government policies, population activity-related engagement, and local health infrastructure were considered.
In contrast, the latter included the Social Vulnerability Index (SVI), race/ethnicity, comorbidities, and state healthcare expenditures, all of which have been considered significant in previous studies.
The study period spanned the pre-Delta, Delta, and Omicron waves of COVID-19, with each independently evaluated in this study.
The study findings indicate several key insights into the effects of COVID-19 vaccination at the population level in the USA.
The GAMs using relative COVID-19 CHR (RCHR) as an outcome variable showed explained deviation values between 46.8% and 72.3% for variant waves.
In addition, the correlation between observed and predicted RCHRs showed strong positive correlations in the range of 0.67 to 0.81.
Population-level vaccination was significantly associated with reduced COVID-19 CHR.
Furthermore, previous SARS-CoV-2 infections (aged one to four months) across different waves showed strong negative associations with RCHR; however, this effect remained inconsistent at both individual and population levels.
Population engagement levels (e.g., gym visits), state policies, and local health infrastructure contributed to the explanatory power of the study model, favoring the importance of considering these factors in the outcomes of COVID-19 vaccines at the population level. However, their associations were inconsistent over time and across different variants.
Furthermore, the observed correlation between the relative weekly test rate and RCHR was negative and decreased from the pre-Delta wave to the Omicron wave.
In addition, US states with higher SVIs consistently showed higher RCHR, and Medicaid expenditures per person showed consistently negative associations with RCHR.
The GAMs using relative COVID-19 incidence rates (RCIR) as an outcome variable showed lower performance, indicating a more dynamic relationship regarding COVID-19 transmission, especially during the Omicron wave.
The explained deviation for the Omicron-Booster-RCIR model was 17%, suggesting that booster vaccination during the Omicron waves provided additional protection against severe COVID-19. However, its effect on Omicron infection itself was limited.
The study provides robust evidence for the effectiveness of COVID-19 vaccines against COVID-19 CHR across different variant waves in the United States.
Despite the emergence of new variants, the vaccines remained effective and significantly mitigated the negative consequences of COVID-19 and its socioeconomic burden on health systems. This data could help shape future health policies in the USA.
Future studies should identify other factors that could capture the dynamics of COVID-19 transmission during the Omicron period.
Furthermore, studies should explore the complex and evolving nature of COVID-19 transmission.