A system dynamics modelling and analytical framework for imported dengue outbreak surveillance and risk mapping.

Autor: Del-Águila-Mejía J; Departamento de Medicina Preventiva y Salud Pública y Microbiología, Facultad de Medicina, Universidad Autónoma de Madrid, C. Arzobispo Morcillo, 4, Madrid 28029, Spain; Servicio de Medicina Preventiva, Hospital Universitario de Móstoles, C. Dr. Luis Montes s/n, Madrid, Móstoles 28935, Spain. Electronic address: javier.delaguila@estudiante.uam.es., Morilla F; Departamento de Informática y Automática, Universidad Nacional de Educación a Distancia, Juan del Rosal 16, Madrid 28040, Spain., Donado-Campos JM; Departamento de Medicina Preventiva y Salud Pública y Microbiología, Facultad de Medicina, Universidad Autónoma de Madrid, C. Arzobispo Morcillo, 4, Madrid 28029, Spain; Consorcio de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Calle Monforte de Lemos 3-5, Madrid 28029, Spain; Departamento de Medicina, Facultad de Ciencias Biomédicas y de la Salud, Universidad Europea de Madrid, C. Tajo, s/n, Madrid, Villaviciosa de Odón 28670, Spain; Instituto de Investigación Sanitaria del Hospital Universitario La Paz (IdiPAZ), Universidad Autónoma de Madrid, C. Arzobispo Morcillo 4, Madrid 28029, Spain.
Jazyk: angličtina
Zdroj: Acta tropica [Acta Trop] 2024 Sep; Vol. 257, pp. 107304. Date of Electronic Publication: 2024 Jun 26.
DOI: 10.1016/j.actatropica.2024.107304
Abstrakt: System Dynamics (SD) models have been used to understand complex, multi-faceted dengue transmission dynamics, but a gap persists between research and actionable public health tools for decision-making. Spain is an at-risk country of imported dengue outbreaks, but only qualitative assessments are available to guide public health action and control. We propose a modular SD model combining temperature-dependent vector population, transmission parameters, and epidemiological interactions to simulate outbreaks from imported cases accounting for heterogeneous local climate-related transmission patterns. Under our assumptions, 15 provinces sustain vector populations capable of generating outbreaks from imported cases, with heterogeneous risk profiles regarding seasonality, magnitude and risk window shifting from late Spring to early Autum. Results being relative to given vector-to-human populations allow flexibility when translating outcomes between geographic scales. The model and the framework are meant to serve public health by incorporating transmission dynamics and quantitative-qualitative input to the evidence-based decision-making chain. It is a flexible tool that can easily adapt to changing contexts, parametrizations and epidemiological settings thanks to the modular approach.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)
Databáze: MEDLINE
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