University of Florida biostatisticians conclude in a recent paper that current COVID vaccines are effective against severe infection and disease from the Omicron viral variant. In the new work, the researchers made a series of estimates of vaccine efficacy. This describes how effective a vaccine is at preventing infection and disease.
Their results reinforce the idea that while COVID vaccines may not always block infection with Omicron, they still offer substantial benefits. Specifically, COVID vaccines and boosters protect people from severe illness and disease. The new paper is published on the pre-print server MedRxiv.
UF biostatistician Ira Longini, Ph.D., is a co-senior author of the work and says the research was needed because: “We need continuing evidence that COVID vaccines administered as an original vaccination and as boosters are holding up as protection against the evolving SARS-CoV-2 virus, including the Omicron subvariants.”
Longini is a professor in the UF department of biostatistics in the College of Public Health and Health Professions and the College of Medicine. He is an expert in estimating vaccine efficacy, is a consultant for the World Health Organization, and is a member of the UF Emerging Pathogens Institute.
“In this latest work, we show that these vaccines still provide substantial protection against infection and severe disease, and that their continued use is essential to protect the world’s populations,” Longini said.
Additional research team members of the paper are first author Shangchen Son, who is a Ph.D. student in biostatistics at the UF; Mingjin Liu, postdoctoral fellow in biostatistics at UF; Zachary J. Madewell, public health analytics and modeling fellow at the Centers for Disease Control and Prevention; and Yang Yang, Ph.D., formerly with UF and now a professor of statistics at the University of Georgia.
In the new work, the team performed a meta-analysis, which is a systematic way of analyzing results published by others. This type of study is useful for looking at broad trends in evidence-based health research while also scrutinizing the strength of data from each paper.
A special kind of figure called a forest plot is used to report findings from meta-analyses. (Unfamiliar with forest plots? here is a resource on how to interpret them.)
Vaccine efficacy meta-analysis models
Figure 1 from the paper shows that when people received full doses of COVID-19 vaccines, the effects prevented infection either with or without symptoms. If the vaccines were ineffective, data points would be plotted to the left of the vertical line. These studies included both Omicron and earlier viral variants. When the results of all studies were pooled, the vaccine efficacy, or VE, was calculated as 0.24, which is interpreted as 24%, for adults across all vaccine types, and 0.29 for all age groups across all vaccine types. What this means is that researchers can expect to find a 24% reduction in the risk of illness in vaccinated people compared to unvaccinated people at the same level of risk.
Figure 2 from the paper shows the additional protection against infection that people obtain when they get a single booster shot. Notice that the data points fall even further to the right of the vertical line. This indicates a stronger effect against infection (either with or without symptoms) from the vaccine plus a booster than just the vaccine alone, shown in the preceding figure. These studies included both Omicron and earlier viral variants. When pooled together, the VE was calculated as 0.53 for adults across all vaccine types, and also for all age groups across all vaccine types. So in this case, researchers can expect to find a 53% reduction in illness in vaccinated and boosted people compared to unvaccinated people at the same level of risk.
Figure 3 from the paper evaluates vaccine efficacy only for studies focused on Omicron viral variants. It shows the additional protection against severe infection and illness that people obtain when they get two booster shots. These studies included only Omicron viral variants. When pooled together, the shorterm VE was calculated as 0.86 for adults across all age groups and vaccine types. In this case, researchers can expect to find an 86% reduction in illness in vaccinated and twice-boosted people compared to unvaccinated people at the same level of risk.
Figure 4 from the paper evaluates vaccine efficacy against severe outcomes for several viral variants when someone gets only a full dose of vaccine. When pooled together, the VE was calculated as 0.58 for adults across all age groups and vaccine types, and 0.57 for all age groups across all vaccine types. In this case, researchers can expect to find a 57 to 58% reduction in severe illness in full-dose vaccinated people compared to unvaccinated people at the same level of risk.
Figure 5 from the paper evaluates vaccine efficacy against severe outcomes for several viral variants when someone gets received a full dose of vaccine plus a booster. When pooled together, the VE was calculated as 0.82 for adults across all age groups and vaccine types, and 0.83 for all age groups across all vaccine types. In this case, researchers can expect to find an 82-83% reduction in severe outcomes in vaccinated and boosted people compared to unvaccinated people at the same level of risk.
What is the take-home message?
Taken as a whole, the new meta-analysis shows that when people receive a full dose of vaccine plus one or two boosters, they get significantly more protection than someone who is not vaccinated. This holds true for Omicron variants too. And while it is usual for the efficacy of a vaccine to decline after a few months, the researchers say that getting a second booster offers the most sustainable protection.
Dr. Longini received his Ph.D. in Biometry at the University of Minnesota in 1977. He began his career with the International Center for Medical Research and Training and the Universidad del Valle in Cali, Colombia, where he worked on tropical infectious disease problems and taught courses in biomathematics. Following that, he was a professor biostatistics at the University of Michigan, Emory University and the University of Washington. He currently is a professor of biostatistics at the University of Florida and Director of the Center for Statistical and Quantitative Infectious Diseases (CSQUID), the Emerging Pathogens Institute, at the University of Florida. His research interests are in the area of stochastic processes applied to epidemiological problems. He has specialized in the mathematical and statistical theory of epidemics–a process that involves constructing and analyzing mathematical models of disease transmission, disease progression and the analysis of infectious disease data based on these models. He works extensively in the design and analysis of vaccine and infectious disease prevention trials and observational studies. Dr. Longini has worked on the analysis of epidemics of COVID-19, Ebola, influenza, HIV, tuberculosis, cholera, dengue fever, malaria, rhinovirus, rotavirus, measles and other infectious agents. Dr. Longini is also working with the Department of Health and Human Services, the World Health Organization, the CDC and other public health organizations on mathematical and statistical models for the control of a possible bioterrorist attack with an infectious agent such as smallpox, and other natural infectious disease threats such as COVID-19, pandemic influenza or another SARS-like infectious agent. Dr. Longini is author or coauthor of over 245 scientific papers and he has won a number of awards for excellence in research, including the Howard M. Temin Award in Epidemiology for “Scientific Excellence in the Fight against HIV/AIDS,” two CDC Statistical Science Awards for both “Best Theoretical and Applied Papers,” the CDC James H. Nakano Citation “for an outstanding scientific publications” the Science Magazine, one of the top 10 “Breakthrough of the Year” for 2015, Guinea Ebola ring vaccination trial, the Aspen Institute Italia Award for scientific research and collaboration between Italy and the United States, 2016, and the David A. Paulus Lifetime Achievement Award, College of Medicine, University of Florida. April 25, 2022. He is a Fellow of the American Statistical Association and a Fellow of the American Association for the Advancement of Science. Dr. Longini has Erdős number = 3.