JMIR Publications

ABSTRACT

Background:

In recent years, the rapid emergence and global spread of dengue (DEN) has become a public health burden. Clinical surveillance alone has limited capacity with delayed detection of upcoming outbreaks. Hence, the potential use of wastewater-based surveillance (WBS) for early detection of incoming surges in DEN cases could complement proactive public health action. However, there are still substantial gaps in the standard approach for sampling and detection methods in dengue WBS.

Objective:

This review aims to determine the current methodological approach for the detection of dengue virus (DENV) in wastewater across geographical areas.

Methods:

The review will be conducted systematically following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. In the initial stage, peer-reviewed publications from PubMed, Embase, Scopus, and WOS will be searched using predefined terms such as “Dengue” and “WBS”. Keywords will be adjusted to suit each database to identify studies related to DENV WBS from inception until June 2025. Subsequently, the references from relevant articles will be screened for eligibility. All data will be extracted from full-text articles highlighting the characteristics and methodological context of the investigated DENV WBS using a standardized form. The risk of bias in non-randomized studies of Interventions (ROBINS – I) tool and the GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) systems will be used for study bias and quality assessment of the evidence. Further descriptive and meta-analysis will be applied to evaluate the methodologies for DENV WBS.

Results:

The data on DENV detection in wastewater will be synthesized by analysing sampling techniques, viral detection method, study sites, geographic locations, dengue serotype and seasonality. A meta-analysis will be conducted using a random-effects model if data are sufficiently homogeneous, with pooled estimates reported as 95% confidence intervals (CIs). Heterogeneity will be assessed using the I² and Chi² tests, with subgroup and sensitivity analyses conducted as needed. Findings will be reported in accordance with PRISMA 2020.

Conclusions:

This protocol outlines a systematic approach to identifying and evaluating existing methods for detecting DENV in wastewater. It aims to provide valuable insights into best practices for DEN surveillance and offer guidance for future research by highlighting current strengths and limitations in the field.