Molecular xenosurveillance of mosquitoes reveals dengue virus serotype-2 during an outbreak in Dhaka, Bangladesh.

UNLABELLED

The increased risk of emerging infectious diseases is particularly pronounced in resource-constrained regions with limited capacity to undertake surveillance, presenting a global challenge for the timely identification and mitigation of disease threats. Consequently, the development and implementation of feasible, cost-effective, and sustainable surveillance strategies are essential. Molecular xenosurveillance (MX) represents an innovative approach for arbovirus monitoring, including dengue surveillance, which utilizes field-collected mosquito specimens to detect circulating pathogens and provide early outbreak warnings. Bangladesh is highly endemic for dengue, and with limited resources, the implementation of MX will add value to ongoing efforts to scale up surveillance. This study aimed to test the suitability of MX in detecting dengue viruses in vectors and recommend its integration into the existing surveillance system. Adult mosquitoes were collected using BG-Sentinel traps during pre-monsoon dengue vector surveys in Dhaka city. mosquitoes were identified morphologically and screened in pools using real-time RT-PCR. Infection prevalence was estimated using the PoolTestR program. Out of 228 mosquitoes distributed across 26 pools, one pool with 10 mosquitoes tested positive for the dengue virus. The estimated infection prevalence was 0.450% (95% CI: 0.026%-1.960%) and 0.510% (95% CI: 0.053%-2.100%) using maximum likelihood and Bayesian estimates, respectively. The DENV-2 serotype was detected in the positive pool. This study presents the first successful implementation of the MX methodology to detect dengue virus presence in field-collected specimens from Dhaka, Bangladesh. These findings provide empirical support for enhanced vector surveillance protocols and offer valuable insights for strengthening comprehensive dengue control efforts.

IMPORTANCE

The timely detection of arboviral pathogens like dengue virus, through surveillance is critical for developing early warning systems and preventing outbreaks. However, limited surveillance capacity in resource-constrained settings creates gaps that can be addressed by implementing sustainable and cost-effective surveillance strategies. This study demonstrates the feasibility of molecular xenosurveillance (MX), which is a vector-based, non-invasive surveillance method for dengue virus surveillance in mosquitoes in Dhaka, Bangladesh. By detecting and identifying dengue virus serotype-2 (DENV-2) using real-time RT-PCR, this study also provides evidence of the method's potential for generating deeper epidemiological insights. These findings highlight the value of MX as a complementary tool to existing surveillance systems. Integrating MX into routine entomological surveillance could significantly enhance national preparedness and response to dengue outbreaks.