Seasonal climate synchronizes dengue timing but not spatial risk in subtropical Brazil.

Authors

Renan de Souza Rezende, Franciele Mendonça Ferreira, Cristiano Ilha, Emanuel Rampanelli Cararo, Michele Victória Dalmutt Scarparo, Ana Luiza Caldatto, Laura Jablonski Straube, Amanda Caroline Martinelli Sehn, Adrieli Marsango de Bispo, Cássia Alves Lima-Rezende

Published in

Spatial and spatio-temporal epidemiology. Volume 58. Pages 100831. Epub Jul 10, 2026.

Abstract

Climate-informed early-warning systems are increasingly used to anticipate dengue risk and guide preparedness at regional scales. These frameworks often assume that shared seasonal climate forcing produces spatially coherent epidemic dynamics across connected municipalities. We analyzed a decade-long dengue surveillance dataset from ten major municipalities in southern Brazil, integrating non-linear seasonal modelling, pairwise synchrony metrics, lagged climate-disease associations, and time-frequency coherence analyses. Seasonal temperature forcing strongly synchronized the timing of dengue epidemics across municipalities, with epidemic peaks consistently concentrated within a narrow seasonal window. In contrast, spatial synchrony in epidemic trajectories was weak and heterogeneous, with neighboring municipalities frequently exhibiting asynchronous or negatively correlated dynamics and no evidence of distance-dependent decay. Municipalities were synchronized by distinct temperature-related metrics under a shared thermal regime, indicating locally specific climate-transmission pathways. Climate-informed early-warning systems designed at regional scales may systematically misallocate surveillance and response resources in heterogeneous subtropical settings. Our findings indicate that shared climate seasonality constrains when dengue transmission is possible but does not ensure spatial coherence in epidemic dynamics. Public health preparedness and outbreak response should therefore be locally calibrated, incorporating municipality-specific climatic sensitivities to improve risk stratification and operational targeting in emerging dengue regions.

PMID:
42702490
Bibliographic data and abstract were imported from PubMed on 07 Sep 2026.

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