利用数学模型重建巴西登革热暴露动态并评估疫苗接种情景的公共卫生影响

Abstract

Brazil experienced its worst dengue epidemic in 2024, with an increase in severe outcomes among elderly individuals, highlighting the need for vaccination strategies informed by population immunity. We reconstructed state- and age-specific immune profiles by fitting an age-structured catalytic model to dengue surveillance data from 2000-2025. This inferred immune profile was incorporated into an SIR-type transmission model to project disease burden and to evaluate the public health impact of vaccine allocation strategies. We observed substantial spatial heterogeneity in accumulated immunity, which was closely associated with projected burden and optimal allocation. Strategies prioritizing states with lower historical incidence and larger susceptible populations yielded greater benefits. Under limited vaccine supply, targeting children resulted in the greatest reductions in DALYs, whereas targeting elderly populations achieved smaller DALY reductions but larger reductions in mortality. We further showed that accelerated vaccine supply markedly increased impact, while allocation choices remained critical when availability was constrained.

Competing Interest Statement

The authors have declared no competing interest.

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Funder Information Declared

National Institutes of Health, AI174105

Wellcome Trust, https://ror.org/029chgv08, Harnessing prospective studies to delineate the interplay of immunity and pathogen genetics in Zika and dengue

Raj and Indra Nooyi Professorship

Sendas Family Fund