Correlation-weighted communicability curvature as a structural driver of dengue spread: A Bayesian spatial analysis of Recife (2015–2024)

Marcílio Ferreira dos Santos, Cleiton de Lima Ricardo and Andreza dos Santos Rodrigues de Melo

Chaos, Solitons & Fractals, 2026, vol. 208, issue P1

Abstract: We investigate whether functional connectivity in urban road networks explains dengue incidence in Recife, Brazil (2015–2024), beyond traditional adjacency-based spatial dependence. For each neighborhood, we compute the average communicability curvature, a graph-theoretic measure capturing multiscale accessibility through redundant network paths. The curvature metric is incorporated into Negative Binomial models, fixed-effects regressions, SAR/SAC spatial models, and a hierarchical INLA/BYM2 specification. Across all frameworks, curvature emerges as the strongest and most stable predictor of dengue risk. In the BYM2 model, the structured spatial component collapses (ϕ≈0), indicating that spatial variation traditionally attributed to CAR adjacency effects is largely absorbed by functional network connectivity. Rather than eliminating spatial dependence, the results suggest a reparametrization of space: dengue diffusion in Recife is structured less by geometric contiguity and more by network-mediated urban connectivity.

Keywords: Dengue; Spatial epidemiology; Correlation-weighted communicability curvature; Network science; Bayesian hierarchical models; INLA (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:208:y:2026:i:p1:s0960077926002304

DOI: 10.1016/j.chaos.2026.118089

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