VPDI stands for Vaccine Preventable Disease Incidence, a public health metric that measures how many cases of a disease a vaccine actually prevents in a population. Unlike vaccine efficacy, which is expressed as a percentage, VPDI gives you a concrete number: the difference in disease cases between unvaccinated and vaccinated groups. It was developed as a complementary tool for setting vaccine policy, helping decision-makers compare vaccines against different diseases on more practical terms.
How VPDI Is Calculated
VPDI is calculated by subtracting the incidence of disease in a vaccinated group from the incidence in an unvaccinated group. In a randomized clinical trial, the formula is simply: incidence in the control group minus incidence in the vaccinated group. This is the same number that appears in the numerator of the standard vaccine efficacy formula, but instead of being divided to produce a percentage, it stands on its own as an absolute difference.
A mathematically equivalent way to express it is: incidence in the unvaccinated group multiplied by vaccine efficacy. So if 100 out of every 10,000 unvaccinated people get sick and the vaccine is 80% effective, the VPDI is 80 per 10,000. That number represents 80 cases of disease prevented for every 10,000 people vaccinated.
Why Vaccine Efficacy Alone Falls Short
Vaccine efficacy tells you the proportion of disease a vaccine prevents, but it doesn’t tell you how much disease existed in the first place. A vaccine that is 90% effective against a rare disease prevents far fewer total cases than a vaccine that is 60% effective against a very common one. Efficacy percentages can make both look dramatically different in value, when in practice the less “effective” vaccine might save more lives.
VPDI solves this by folding in the baseline disease burden. It answers the question that matters most for public health planning: how many people will be spared illness if we vaccinate this population? Two vaccines with identical efficacy numbers can have wildly different VPDI values depending on how common the target disease is in a given region. This makes VPDI especially useful when governments are deciding how to allocate limited vaccination budgets across multiple diseases.
How VPDI Is Used in Practice
Researchers calculating VPDI typically focus on severe disease outcomes, since preventing hospitalizations and deaths carries the most weight in policy decisions. When data are available, analysts prefer the most sensitive outcome measure, such as all severe cases regardless of hospitalization, rather than narrower categories. They also tend to use per-protocol analyses and count all disease episodes rather than just the first one, both of which maximize the VPDI estimate and give the clearest picture of a vaccine’s real-world impact.
VPDI can also be applied beyond individual-level trial data. In cluster-randomized trials, where entire communities are vaccinated or left unvaccinated, VPDI can be estimated by comparing disease rates between control and intervention clusters regardless of individual vaccination status. This version of the metric captures indirect protection too: the benefit that unvaccinated people receive when enough of their neighbors are vaccinated to slow transmission. That makes it a powerful tool for evaluating community-wide vaccination campaigns, not just individual shots.
VPDI and Global Health Targets
Metrics like VPDI feed directly into the kind of goal-setting that international health organizations use to track progress. The World Health Organization’s Immunization Agenda 2030 strategy sets specific reduction targets for vaccine-preventable diseases: a 90% reduction in cholera deaths, a 95% reduction in new chronic hepatitis B infections among children, elimination of meningitis epidemics, and zero deaths from dog-mediated rabies, among others. Reaching these targets requires knowing not just whether vaccines work in clinical trials, but how many cases they actually prevent in the populations where they’re deployed.
VPDI provides that bridge between clinical trial data and population-level planning. A country with a high baseline incidence of rotavirus, for example, will see a much larger VPDI from the same vaccine than a country where the disease is already uncommon. This helps health ministries prioritize which vaccines to introduce or expand based on local disease patterns rather than relying solely on global efficacy numbers that may not reflect their specific situation.
Limitations of VPDI
Because VPDI depends on the baseline disease rate, it changes over time and across locations. A vaccine program that dramatically reduces a disease will lower its own VPDI in subsequent years, even though the vaccine is still working just as well. This can create the misleading impression that a vaccine has become less valuable when it has actually been a victim of its own success.
VPDI also requires good surveillance data on disease incidence, which is harder to come by in low-resource settings where vaccination programs are often most needed. And because it is an absolute measure rather than a relative one, comparing VPDI values across diseases with very different severity profiles can be tricky. Preventing 50 cases of a mild illness per 10,000 people is not the same as preventing 50 cases of a fatal one. For that reason, VPDI works best when paired with other measures, including efficacy, cost-effectiveness analyses, and disease severity data, rather than used as a standalone decision tool.