Vaccine efficacy or vaccine effectiveness is the percentage reduction of disease cases in a vaccinated group of people compared to an unvaccinated group. For example, a vaccine efficacy or effectiveness of 80% indicates an 80% decrease in the number of disease cases among a group of vaccinated people compared to a group in which nobody was vaccinated. When a study is carried out using the most favorable, ideal or perfectly controlled conditions, such as those in a clinical trial, the term vaccine efficacy is used. On the other hand, when a study is carried out to show how well a vaccine works when they are used in a bigger, typical population under less-than-perfectly controlled conditions, the term vaccine effectiveness is used. Vaccine efficacy was designed and calculated by Greenwood and Yule in 1915 for the cholera and typhoid vaccines. It is best measured using double-blind, randomized, clinical controlled trials, such that it is studied under "best case scenarios." Vaccine efficacy studies are used to measure several important and critical outcomes of interest such as disease attack rates, hospitalizations due to the disease, deaths due to the disease, asymptomatic infection, serious adverse events due to vaccination, vaccine reactogenicity, and cost effectiveness of the vaccine. Vaccine efficacy is calculated on a set population (and therefore is not a constant value when counting in other populations), and may be misappropriated to be how efficacious a vaccine is in all populations.
Testing Vaccine efficacy differs from vaccine effectiveness in the same way that an explanatory clinical trial differs from an intention-to-treat trial: vaccine efficacy shows how effective a vaccine could be given ideal circumstances and 100% vaccine uptake (such as the conditions within a controlled clinical trial); vaccine effectiveness measures how well a vaccine performs when it is used in routine circumstances in the community. What makes vaccine efficacy relevant is that it shows the disease attack rates as well as a tracking of vaccination status. Vaccine effectiveness is relatively inexpensive to measure than vaccine efficacy. The measurement of vaccine effectiveness relies on observational studies which are usually easier to perform, whereas a vaccine efficacy measurement requires randomized controlled trials which are time and capital intensive. Because a clinical trial is based on people who are taking the vaccine and those who are not, there is a risk for disease, and optimal treatment is needed for those who become infected. The advantages of measuring vaccine efficacy is having the ability to control for selection bias, as well as prospective, active monitoring for disease attack rates, and careful tracking of vaccination status for a study population there is normally a subset as well; laboratory confirmation of the infectious outcome of interest and a sampling of vaccine immunogenicity. The major disadvantages of vaccine efficacy trials are the complexity and expense of performing them, especially for relatively uncommon infectious outcomes of diseases for which the sample size required is driven up to achieve clinically useful statistical power. Vaccine effectiveness estimates obtained from observational studies are usually subject to selection bias. Since 2014, epidemiologists have used quasi-experimental designs to obtain unbiased estimates of vaccine effectiveness. Standardized statements of efficacy may be parametrically expanded to include multiple categories of efficacy in a table format. While conventional efficacy/effectiveness data typically shows the ability to prevent a symptomatic infection, this expanded approach could include prevention of outcomes categorized to include symptom class, viral damage minor/serious, hospital admission, ICU admission, death, various viral shedding levels, etc. Capturing effectiveness at preventing each of these "outcome categories" is typically part of any study and could be provided in a table with clear definitions instead of being inconsistently presented in study discussion as is typically done in past practice.
Biological factors Biological exposures such as parasites affect the immune responses after vaccination. This can be seen in areas with a high burden of parasitic infections where vaccine responses are low for vaccines such as BCG. Infections like malaria suppress immune responses to polysaccharide vaccines. A potential solution is to give curative treatment before vaccination in areas where malaria is present. The effect of parasites on vaccine response has also been observed in individuals infected by helminths in areas that have a high burden of infectious diseases. Established helminth infections at the time of vaccination affect vaccine responses. Other biological factors such as smoking, age, sex, and nutrition also affect vaccine responses. In the case of hepatitis B vaccine, for example, increasing age, being male, having a body mass index > 25, and smoking can result in lower seroprotection rates. The composition of the gut microbiota might impact responses to vaccination, although there is insufficient evidence for the gut microbiota directly affecting vaccine efficacy.
Formula
The outcome data (vaccine efficacy) generally are expressed as a proportionate reduction in disease attack rate (AR) between the unvaccinated (ARU) and vaccinated (ARV), or can be calculated from the relative risk (RR) of disease among the vaccinated group. The basic formula is written as: V E = A R U − A R V A R U × 100 % , {\displaystyle VE={\frac {ARU-ARV}{ARU}}\times 100\%,} with
V E {\textstyle VE} = Vaccine efficacy,
A R U {\displaystyle ARU} = Attack rate of unvaccinated people,
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