Effectiveness of Community-Based Early Warning Systems in Reducing Dengue Incidence in Endemic Regions: A Scoping Review

Abstract

Abstract Dengue fever has become increasingly prevalent and poses a threat to public health worldwide. Despite advances in surveillance and vector control, dengue responses remain largely reactive, relying on passive case reporting systems that limit timely outbreak detection and response(1-3). In addition to improvements in surveillance and vector control, early warning systems have been developed to improve outbreak predictions by integrating data from epidemiology, entomology, and the environment. Recently, there has also been interest in developing community-based early warning systems (CBEWS), which incorporate community knowledge and involvement into surveillance efforts (4). However, the current state of evidence on whether CBEWS can reduce dengue incidence varies widely across studies due to differences in study design and methodology. Methods This review employed a scoping review process. The literature search followed existing methodologies for conducting reviews (5, 6). A comprehensive search of four electronic databases (PubMed, Scopus, Embase, and Medline) was completed to locate all relevant peer-reviewed articles that were published between 2016 and 2026. Eligible studies included observational designs (cross-sectional, cohort, and ecological studies), modelling studies, and evidence syntheses (systematic and scoping reviews) that examined dengue surveillance or early warning systems. Also, experimental and non-randomised intervention studies were considered, where they evaluated intervention components linked to surveillance or response systems. Data extraction focused on information about the characteristics of the early warning system, how the system was implemented, what methods were used to engage communities and the effects of each variable on dengue incidence and response to dengue-related outbreaks. Results Twenty-eight studies met eligibility criteria and demonstrated three key factors that influence the success of CBEWS. First, while many dengue early warning systems demonstrate high predictive value for future dengue activity, few have shown an association with decreased dengue incidence when no prompt response mechanisms exist. Second, when communities are engaged in the surveillance effort through active participation in reporting, in surveillance sensitivity, timeliness of reporting and community awareness of dengue risk were enhanced; however, few studies have found that increased community participation results in measured declines in dengue transmission. Finally, studies where early warning systems were part of larger integrated programmes that included targeted interventions (such as vector control or biological strategies) presented higher rates of dengue incidence reduction than those without integrated components. All three variables impacted by the success of CBEWS show great variability depending on the degree to which system integration occurs with high-quality data and robust governance structures. Conclusion CBEWS provide support to enhance dengue surveillance and improve readiness for dengue outbreak, they represent inadequate stand-alone interventions. Therefore, to be successful CBEWS need to be used in conjunction with swift public health response and functional surveillance-response systems that include continued active community involvement. As identified within this review, there is a clear need to transition from predictive models towards integrated-actionable models for addressing dengue in endemic areas. Keywords: Dengue, Early Warning Systems, Community-Based Surveillance, Vector Control, Public Health, Disease Prevention, Synthesis of Literature