Brazil’s dengue immunity map points vaccine supply toward geography, age, and history
Brazil’s dengue burden in 2024 was severe enough to force a harder question than case counts alone can answer: where is population immunity already depleted, and where would a limited vaccine supply do the most good? This preprint approaches that problem by reconstructing state- and age-specific immune profiles across Brazil and then testing how different allocation strategies could change projected disease burden.
The work begins with a simple epidemiologic premise. Where past transmission has been lower, more people remain susceptible; where transmission has been higher, immunity has accumulated unevenly across age groups and states. Those differences are not academic bookkeeping. They determine where a vaccine can avert the largest number of infections, how many severe outcomes can be prevented, and whether a dose placed in one setting yields more benefit than the same dose placed elsewhere.
Catalytic modeling rebuilt immunity from two and a half decades of surveillance
Investigators fit an age-structured catalytic model to dengue surveillance data spanning 2000 to 2025 to infer immune profiles by state and age. The inferred immunity was then fed into an SIR-type transmission model to project burden under multiple vaccination scenarios. This design matters because surveillance counts alone do not reveal the size of the susceptible pool; a region with modest recent incidence may still contain a large fraction of people who have never encountered the virus.
The modeling framework also reflects dengue’s biological reality. Prior exposure shapes future risk, and that risk is distributed unevenly across Brazil’s states and age strata. A vaccine strategy built without that information can easily miss the target: doses may be concentrated where recent transmission has already burned through much of the susceptible population, while places with larger vulnerable pools remain exposed.
Spatial heterogeneity emerged as a central finding. The reconstructed immunity profile varied substantially across Brazil, and those differences closely tracked projected burden and the optimal vaccine allocation pattern. States with lower historical incidence and larger susceptible populations stood out as higher-priority targets because they offered more room for intervention to change the epidemic curve.
The biggest gains came from targeting children under constrained supply
Under limited vaccine supply, prioritizing children produced the largest reductions in DALYs. That result fits the logic of cumulative exposure: immunizing earlier can prevent a long chain of future infections and downstream disability across many years of life. A vaccine administered in childhood can interrupt transmission before repeated exposure compounds population-level burden.
A different pattern emerged when the allocation goal shifted from total health loss to mortality. Targeting elderly populations produced smaller reductions in DALYs but larger reductions in deaths. Severe dengue rises with age in the setting described here, and the 2024 epidemic was marked by worse outcomes among older adults. In a system where the oldest groups bear a disproportionate share of fatal events, a mortality-focused strategy naturally pulls doses toward those patients even when the total DALY effect is smaller.
One sentence captures the tension plainly: the same dose can avert more life-years lost in children or more deaths in older adults, depending on how the program is designed.
Vaccination strategy changed with supply, but geography kept its weight
Accelerated vaccine supply increased the overall impact of vaccination markedly. More supply expanded the number of people who could be reached before infection, which is the most direct route to reducing population burden in any transmission model. Yet allocation decisions remained critical when availability was constrained, because the marginal value of a dose depended on local susceptibility and prior transmission history.
This is where the epidemiologic structure does the heavy lifting. If one state has accumulated broad immunity through repeated outbreaks and another retains a large susceptible pool, equal distribution is not equal benefit. The model suggests that vaccine placement should follow the underlying ecology of risk rather than a simple headcount approach.
The findings also help explain why dengue policy cannot rely on a single national average. Brazil is large, heterogeneous, and epidemiologically uneven. A vaccine program that ignores those differences may still deliver protection, but it will leave preventable burden on the table.
Public health planning depends on exposure history, not just incidence headlines
The preprint argues for a more granular framework for dengue vaccination in Brazil, one built on reconstructed immunity rather than recent incidence alone. Historical incidence is informative, but it is not a complete proxy for who remains susceptible. An area that has been quieter for years may in fact be carrying a larger pool of people at risk for the next surge.
That insight has immediate implications for planning. Vaccine strategy becomes a balancing act between preventing illness, limiting deaths, and working within supply constraints. If the objective is to reduce overall disease burden, the model favors children. If the objective is to reduce mortality, older adults become more attractive targets. If supply expands, the field shifts again, but the need to match doses to local immunity remains.
The study is also explicit about its limits. It is a preprint and has not undergone peer review. Its projections depend on the assumptions built into the catalytic and transmission models, and those assumptions deserve careful scrutiny before any policy translation. Even so, the central message is hard to miss: in dengue control, where immunity has accumulated unevenly, the value of a vaccine is shaped as much by geography and age structure as by the number of doses on hand.