Authors
Gian Marco Ludovici, Alba Iannotti, Colomba Russo, Francesco Gargallo di Castel Lentini, Manousos E Kambouris, Mostafa Mohammed Atiyah, Sijo Asokan, Andrea Malizia, Marta Giovanetti
Published in
Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology]. Volume 57. Issue 1. Sep 09, 2026. Epub Sep 09, 2026.
Abstract
Arboviral diseases are undergoing substantial epidemiological changes driven by climate change, urbanization, global mobility, vector expansion, and evolving ecological conditions. These processes increasingly favor the geographic overlap and co-circulation of multiple arboviruses, including in regions previously considered at limited risk. In this review, we describe this broader process as epidemiological convergence, referring to the progressive overlap of arboviral transmission systems across shared geographic, ecological, vector, host, and public health contexts. Such convergence creates interconnected challenges for clinical recognition, laboratory diagnosis, surveillance, and outbreak response. Diagnostic uncertainty is further amplified by overlapping clinical presentations, serological cross-reactivity, previous arboviral exposure, and co-infections or sequential infections. At the same time, pathogen-specific surveillance systems may inadequately capture increasingly complex transmission patterns, highlighting the need for integrated and interoperable approaches. One Health provides an essential framework for integrating human, animal, vector, and environmental dimensions of arboviral transmission. Complementarily, selected principles derived from Chemical, Biological, Radiological, Nuclear, and Explosive (CBRNE) preparedness may strengthen operational coordination, contingency planning, biosafety, risk communication, and response capacity during complex arboviral scenarios. However, their added value in arboviral settings requires further empirical evaluation. Addressing epidemiological convergence will ultimately require adaptable systems linking epidemiological understanding, diagnostic capacity, integrated surveillance, and operational preparedness.
PMID:
42714752
Bibliographic data and abstract were imported from PubMed on 10 Sep 2026.
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