Two general types of studies are used to determine how well influenza vaccines work: These study designs are described below. The first type of study design is called a randomized controlled trial RCT.
In a RCT, volunteers are assigned randomly to receive an influenza vaccine or a placebo e. Vaccine efficacy is measured by comparing the frequency of influenza illness in the vaccinated and the unvaccinated placebo groups. The RCT study design minimizes bias that could lead weight loss and loss management invalid study results.
Bias is an unintended systematic error in the way researchers select study participants, measure outcomes, or analyze data that can lead to inaccurate results, vaccine and antibiotics. In a RCT, vaccine allocation is usually double-blinded, which means neither the study vaccine and antibiotics nor the researchers know if a given person has received vaccine or placebo. National regulatory authorities, such as the Food and Drug Administration FDA in the United States, require RCTs to be conducted and to demonstrate the protective benefits of a new vaccine before the vaccine is licensed for routine use.
However, some vaccines are licensed based on RCTs that use antibody response to the vaccine as measured in the laboratory, rather than decreases in influenza vaccine and antibiotics among people who were vaccinated. The second vaccine and antibiotics of study design is an observational study, vaccine and antibiotics. There are several types of observational studies, including cohort and case-control studies, vaccine and antibiotics.
Observational studies assess how influenza vaccines work by comparing the occurrence of influenza among people vaccine and antibiotics have been vaccinated compared vaccine and antibiotics people not vaccinated. Vaccine effectiveness is the percent reduction in the frequency of influenza illness among vaccinated people compared to people not vaccinated, vaccine and antibiotics, usually with adjustment for factors like presence of chronic medical conditions that are related to both influenza illness and vaccination, vaccine and antibiotics.
See below for details. Vaccine efficacy refers to vaccine protection measured in RCTs usually under optimal conditions where vaccine storage and delivery are monitored and participants are usually healthy. Vaccine effectiveness refers to vaccine protection measured in observational studies that include people with underlying medical conditions who have been administered vaccines by different health care providers under real-world conditions. These universal vaccine recommendations make it unethical to perform placebo-controlled RCTs because assigning people to a placebo group could place them at risk for serious complications from influenza.
Also, observational studies often are the only option to measure vaccine effectiveness against more severe, less common influenza outcomes, vaccine and antibiotics, such as hospitalization. The measurement of influenza vaccine efficacy and effectiveness can be affected by virus and host factors as well as the study methodology used, vaccine and antibiotics. The protective benefits of influenza vaccination are generally lower during flu seasons where the majority of circulating influenza viruses differ from the influenza viruses used to make the vaccines.
Influenza viruses are continuously changing through a natural process known as antigenic drift. For more information, see How the flu midwest animal evacuation plans can change: However, the degree of antigenic drift and the frequency of drifted viruses in circulation can vary for each of the three or four viruses included in the seasonal flu vaccine.
So even when circulating influenza viruses are mildly or moderately drifted in comparison to the vaccine, vaccine and antibiotics, it is possible that people may still receive some protective benefit from vaccination; and if other circulating influenza viruses are well matched, the vaccine could still provide protective benefits overall.
In addition to virus factors, host factors such as age, underlying medical conditions, history of prior infections and prior vaccinations can affect the benefits received from vaccination. Experts consider RCTs to be the best study design because they are less susceptible to biases. However, as stated above, these studies cannot be conducted when vaccination is recommended in a population and these studies are very difficult to conduct for more severe outcomes that are less common.
There are several observational study designs, but many programs currently use the test-negative, case-control design. All participants are tested for influenza using a highly specific and sensitive test for influenza virus infection, such as reverse transcription polymerase chain reaction RT-PCR. The ratio of vaccinated to unvaccinated persons i, vaccine and antibiotics. The cancer ceu massage md anderson design removes selection bias due to health-care seeking behaviors.
In addition to the test-negative design, there are additional observational study designs that have been used to estimate vaccine effectiveness. For both RCTs and observational studies, the specificity of the outcome measured in the study is important.
Non-specific outcomes, such as pneumonia hospitalizations or influenza-like illness ILI can be associated with influenza virus infections as well as infections vaccine and antibiotics other viruses and bacteria.
For example, a study among healthy adults found that the inactivated influenza vaccine i. Serologic assays to detect influenza infection i. The problem with VE studies that use serology to test for influenza infection, is that vaccination elevates antibody levels, vaccine and antibiotics, similar to infection, vaccine and antibiotics.
Therefore, serologic testing methods can result in biased VE estimates that inflate VE. Observational studies are subject to various forms of bias see above for definition more so than RCT studies. Therefore, it is important that bias be minimized with the study design or adjusted for in the analysis.
Observational studies of influenza vaccine effectiveness can be subject to three forms of bias: Confounding occurs when the effect of vaccination on the risk of the outcome being measured e. In RCTs, confounding factors are expected to be evenly distributed between vaccinated and vaccine and antibiotics groups.
This is not true of observational studies. For example, chronic medical conditions can confound the association between influenza vaccination and hospitalization with influenza in observational studies. Chronic medical conditions increase the risk of influenza-related hospitalization and vaccination coverage often is higher among people with chronic medical conditions.
Therefore, the presence of a chronic medical condition in a study participant is a potential confounding factor that should vaccine and antibiotics considered in analysis. This is an example of confounding by indication because those at greatest risk for the outcome being measured i. Not adjusting for confounders could bias the vaccine effectiveness estimate away from the true estimate.
In the example given, the vaccine effectiveness estimate could be biased lower, or towards lower effectiveness. Selection bias occurs when people with the outcome being measured by the study i, vaccine and antibiotics. In observational studies of influenza vaccine effectiveness, people with and without influenza may have different likelihoods of being vaccinated, and this can bias the estimate of vaccine effectiveness.
For example, people who visit their health care provider in outpatient settings e, vaccine and antibiotics. If controls are selected from a different population than the cases e. The test-negative study design minimizes selection bias related to health care seeking by enrolling patients who seek care for a respiratory illness.
This study design is used by many studies globally, including CDC-funded networks that measure vaccine effectiveness. Information bias occurs if exposures or outcome information are based on different sources of information for people with and without the disease of interest. For example, if researchers obtain information on vaccination for children with influenza from immunization records but ask parents of children without influenza if the child was vaccinated, this difference in data collection procedures could bias the results of the study.
As described above, when the virus components of the flu vaccine are not well matched vaccine and antibiotics circulating influenza viruses, the benefits of influenza vaccination may be reduced. However, the degree of antigenic drift from vaccine viruses and the proportion of circulating drifted viruses can vary.
As a result, even when circulating influenza viruses are mildly or moderately drifted in comparison to the vaccine, it is still possible that people may receive some protective benefit from influenza vaccination. In addition, even when some circulating influenza viruses are significantly drifted, vaccine and antibiotics, it is possible for other influenza viruses in circulation tylenol sinus congestion and pain be well matched to the vaccine.
It is not possible to predict how well the vaccine and circulating strains will be matched in advance of the influenza season, nor is it possible to predict how this match may affect vaccine effectiveness. Among older adults, vaccine and antibiotics, annual influenza vaccination was recommended based on the high burden of influenza-related disease and demonstrated vaccine efficacy among younger adults.
However, vaccine and antibiotics, it is unknown if infections were missed by serology among the study participants that were vaccinated and if the vaccine efficacy estimate is biased upwards — see previous description of how bias can occur in VE studies that test for influenza using serology. Several observational studies have reported significant vaccine effectiveness against RT-PCR confirmed influenza-related hospitalization among older adults. In addition, vaccine and antibiotics, RCTs of cell-based inactivated influenza vaccines IIVs and recombinant trivalent HA protein vaccines have been performed among healthy adults.
In general, efficacy estimates for these types of vaccines are similar to other inactivated influenza vaccines that are egg-based [15,16,17]. A randomized trial in Bangladesh found that babies born to mothers vaccinated during pregnancy with trivalent inactivated influenza vaccines were significantly less likely to be born small for gestational age and weighed an average of g more than babies born to unvaccinated mothers [29,30].
No effect of maternal immunization on infant birth weight was reported in the South African trial described above. Some observational studies in developed and developing countries have found lower risk of prematurity or low birth weight in babies born to vaccinated mothers, but the effect has not been consistently demonstrated [31,32,33,34,35].
Three randomized clinical trials comparing live attenuated influenza vaccine to trivalent inactivated influenza vaccine in young children, years of age, suggested that live attenuated influenza vaccine had superior efficacy compared to inactivated influenza vaccine [36,37,38].
Recently, several observational studies suggest that LAIV did not consistently provide better protection against influenza than inactivated vaccine, especially against influenza caused by the H1N1 pandemic virus [39,40,41]. However, a randomized, school-based study in Canada reported lower rates of confirmed influenza among students vaccinated with live-attenuated vaccine compared to students vaccinated with inactivated influenza vaccine, as well as decreased influenza transmission among family members of students vaccinated with live-attenuated influenza vaccines , vaccine and antibiotics.
Clinical trials during, and that compared inactivated influenza vaccines and live attenuated influenza vaccines to no vaccine among adults suggested that inactivated influenza vaccines provided better protection against influenza than live attenuated influenza vaccines in adults 7,8. CDC monitors vaccine effectiveness annually through the Influenza Vaccine Effectiveness VE Vaccine and antibiotics, a collaboration with participating institutions in five geographic locations, vaccine and antibiotics.
These institutions enroll patients with respiratory symptoms at ambulatory clinics and test for influenza by RT-PCR. Vaccine effectiveness is estimated using the test negative design, vaccine and antibiotics, comparing proportions odds of influenza vaccination among patients with and without vaccine and antibiotics. Statistical methods are used to account for differences in age, race vaccine and antibiotics underlying medical conditions that might influence vaccine effectiveness.
Estimates are reported annually, and often, vaccine and antibiotics, an early estimate is reported during the season. Since the match between circulating and vaccine viruses is not known before the season, annual estimates of vaccine effectiveness give a real-world look at how well the vaccine protects against influenza caused by circulating viruses each season.
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Can you describe biases that are important to consider for observational studies measuring vaccine effectiveness? How well do influenza vaccines work during seasons in which the flu vaccine is not well matched to circulating influenza viruses? What is the vaccine and antibiotics that influenza vaccines work? How does CDC monitor vaccine effectiveness? January 29, Page last updated: January 29, Content source: