Spatial model of Dengue Hemorrhagic Fever (DHF) risk: scoping review

Pakaya, Ririn and Daniel, D. and Widayani, Prima and Utarini, Adi (2023) Spatial model of Dengue Hemorrhagic Fever (DHF) risk: scoping review. BMC Public Health, 23 (1). ISSN 14712458

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Abstract

Background: Creating a spatial model of dengue fever risk is challenging duet to many interrelated factors that could affect dengue. Therefore, it is crucial to understand how these critical factors interact and to create reliable predictive models that can be used to mitigate and control the spread of dengue. Methods: This scoping review aims to provide a comprehensive overview of the important predictors, and spatial modelling tools capable of producing Dengue Haemorrhagic Fever (DHF) risk maps. We conducted a methodical exploration utilizing diverse sources, i.e., PubMed, Scopus, Science Direct, and Google Scholar. The following data were extracted from articles published between January 2011 to August 2022: country, region, administrative level, type of scale, spatial model, dengue data use, and categories of predictors. Applying the eligibility criteria, 45 out of 1,349 articles were selected. Results: A variety of models and techniques were used to identify DHF risk areas with an arrangement of various multiple-criteria decision-making, statistical, and machine learning technique. We found that there was no pattern of predictor use associated with particular approaches. Instead, a wide range of predictors was used to create the DHF risk maps. These predictors may include climatology factors (e.g., temperature, rainfall, humidity), epidemiological factors (population, demographics, socio-economic, previous DHF cases), environmental factors (land-use, elevation), and relevant factors. Conclusions: DHF risk spatial models are useful tools for detecting high-risk locations and driving proactive public health initiatives. Relying on geographical and environmental elements, these models ignored the impact of human behaviour and social dynamics. To improve the prediction accuracy, there is a need for a more comprehensive approach to understand DHF transmission dynamics. © 2023, The Author(s).

Item Type: Article
Additional Information: Cited by: 3; All Open Access, Gold Open Access, Green Open Access
Uncontrolled Keywords: Dengue; Disease Outbreaks; Humans; Risk Factors; Severe Dengue; Temperature; dengue; epidemic; human; risk factor; severe dengue; temperature
Subjects: R Medicine > RP Public Health and Nutrition
Divisions: Faculty of Geography > Departemen Sains Informasi Geografi
Depositing User: Sri Purwaningsih Purwaningsih
Date Deposited: 03 Sep 2024 07:39
Last Modified: 03 Sep 2024 07:39
URI: https://ir.lib.ugm.ac.id/id/eprint/6226

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