ArticleMicrobiology spectrum2025
Molecular xenosurveillance of
Article in Microbiology spectrum, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
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 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
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