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Researcher profile

Maíra Aguiar

Maíra Aguiar contributes to research discovery and scholarly infrastructure.

ResearcherAffiliation not importedOpen to collaborate
Biological Physicsmath.DSnlin.CDphysics.soc-phPopulations and Evolution

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Published work

2 published item(s)

preprint2026arXiv

Climate and dengue synchronization in southern Brazil: a municipal analysis with cross-state validation

Dengue transmission is rapidly expanding beyond its historical tropical range, raising concerns about how climate change may alter the collective dynamics of epidemics. While most studies focus on transmission risk, much less is known about how climate affects the synchronization of outbreaks. In this work, we investigate dengue synchronization using epidemiological and climate data from 74 municipalities in the state of Paraná (southern Brazil) between 2010 and 2024. We quantify outbreak coherence using the Event Synchronization (ES) method. Our results reveal a transition from a low-transmission regime to a high-transmission regime accompanied by a marked increase in synchronization across cities. We also show that climate anomalies increase the number of permissive days for dengue transmission. Our results suggest that such days are significantly associated with outbreak synchronization. We identify a two-stage climate mechanism: conducive climatic conditions first reduce the probability of asynchronous states and coincide with the emergence of synchronized outbreaks, and subsequently sustain higher synchronization levels. Extending the analysis through comparative analyses in Ceará and Minas Gerais, we uncover that climate consistently amplifies synchronization, although its role in the onset of synchronization depends on regional climatic regimes. These findings highlight climate-driven synchronization as an emerging feature shaping dengue dynamics.

0 citations0 reviewsNo code linkedOpen access
preprint2011arXiv

Irregularity in dengue fever epidemics: difference between first and secondary infections drives the rich dynamics more than the detailed number of strains

Different extensions of the classical single-strain SIR model for the host population, motivated by modeling dengue fever epidemiology, have reported a rich dynamic structure including deterministic chaos which was able to explain the large fluctuations of disease incidences. A comparison between the basic two-strain dengue model, which already captures differences between primary and secondary infections, with the four-strain dengue model, that introduces the idea of competition of multiple strains in dengue epidemics shows that the difference between first and secondary infections drives the rich dynamics more than the detailed number of strains to be considered in the model structure. Chaotic dynamics were found to happen at the same parameter region of interest, for both the two and the four-strain models, able to explain the fluctuations observed in empirical data and showing a qualitatively good agreement between empirical data and model simulation. Since the law of parsimony favors the simplest of two competing models, the two-strain model would be the better candidate to be analyzed, giving the expected complex behavior to explain the fluctuations observed in empirical data, and indeed the better option for estimating all initial conditions as well as the few model parameters based on the available incidence data.

0 citations0 reviewsNo code linkedOpen access