ArticlePLoS neglected tropical diseases2026
Development and effectiveness test of an internet-based real-time monitoring device for malaria parasite vector mosquitoes.
Article in PLoS neglected tropical diseases, 2026. 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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Abstract
backgroundMalaria remains a major global health threat, and effective vector surveillance is essential for timely vector control. However, surveillance systems are challenged by behavioral shifts in Anopheles mosquitoes, labor-intensive procedures, and delays in real-time data transmission. Existing electronic monitoring tools often suffer from low sensitivity and specificity, creating an urgent need for automated, high-precision alternatives.
methodsWe developed the "Black Box," a 3D-printed, internet-enabled device integrating multispectral light, thermal simulation, chemical attractants, and photocatalytic materials with automated counting and wireless data transmission. Laboratory trials demonstrated trapping rates of 94.00%-95.00% for Anopheles sinensis, An. stephensi, and An. anthropophagus, with data consistency exceeding 97.00%. Semi-field tests yielded trapping rates of 73.60%-90.80% and consistency above 92.00%. In field deployments, the device captured 5,109 mosquitoes with a 94.17% consistency rate and captured more Anopheles than the light trap during the field observation period. Real-time data revealed distinct bimodal activity peaks at dawn and dusk. Among the 112 field-captured female An. sinensis, 21 (18.75%; exact 95% CI, 12.60%-26.97%) were blood-fed, indicating that blood-fed mosquitoes may occur in outdoor collections.
conclusionsThe Black Box provides a highly efficient, automated solution for real-time malaria vector surveillance. By delivering accurate, timely ecological data, it supports dynamic risk assessment and enables targeted interventions, addressing key limitations of current control programs.
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