Bibliometric Analysis Of Dengue Fever For Spatial-Temporal Predictions Using A Geographical Information System

Abstract

This study mapped the development of dengue fever research at the intersection of spatiotemporal analysis, prediction, and geographic information system-based surveillance during 2020–2025. A descriptive bibliometric design with a science mapping approach was used. Data were retrieved from Scopus using search terms related to dengue fever, spatial or spatiotemporal analysis, prediction or forecasting, and geographic information systems. After title, keyword, abstract screening, metadata cleaning, and harmonization, 360 documents were analyzed using Biblioshiny, Co-occurence network, thematic mapping, trend topic analysis, and author collaboration network analysis. The corpus showed steady scientific activity, with 175 sources, 1,945 authors, 312 articles, 48 reviews, an average of 11.75 citations per document, and an international collaboration rate of 42.5%. Indonesia, Brazil, China, the United States, and Thailand contributed strongly to publication output, while citation impact varied by country. The conceptual structure showed mature themes in dengue epidemiology, spatial analysis, spatiotemporal modeling, and prediction, but weak operational translation into web-based geographic information systems and early warning systems. These findings highlighted the need for validated, interoperable, and decision-oriented geospatial surveillance tools for dengue control.