Brazil experienced a large dengue epidemic during the 2024 season, with almost 5.7 million total cases (compared to under 1.3 million in 2023), raising questions about underlying drivers, including rising temperatures, expansion into susceptible populations, changes in reporting, and novel strains. We compared state-level 2024 incidence with 2000 - 2023 data to quantify anomalies. Nine of 27 states, primarily in the Southeast, recorded their highest incidence in 25 years, accounting for 97% of cases while comprising only 67% of the population. In contrast, nine states (mostly in the North and Northeast) reported below-average incidence. Counterintuitively, the correlation between state-level temperature and incidence declined significantly over the study period, turning negative by 2024 (r = -0.72), a reversal from the positive correlations observed at the start. To determine whether this pattern was driven by northern temperatures being too high for transmission, or by spatial variation in immunity, we fit generalized additive models to effective reproductive numbers. Transmission remained substantial at the highest temperatures, while reproductive numbers declined with lagged cumulative incidences, indicating susceptibility depletion was important. We then estimated state-level susceptibility using a mechanistic SEIR-SEI model, describing a trade-off: high temperatures supported high transmission rates, but were associated with reduced susceptibility. Linear regression models confirmed both temperature and susceptibility were necessary to predict the 2024 outbreaks, suggesting that immunity plays an important role in modulating temperature's effect on incidence. Future surveillance integrating measures of immunity could enhance forecasts and early-warning systems, particularly as climate change expands dengue into immunologically naive populations.