{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T17:56:09Z","timestamp":1791568569577,"version":"4.3.4"},"reference-count":54,"publisher":"Public Library of Science (PLoS)","issue":"10","license":[{"start":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T00:00:00Z","timestamp":1791504000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82472317"],"award-info":[{"award-number":["82472317"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82261128003\/2022YFML1001"],"award-info":[{"award-number":["82261128003\/2022YFML1001"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Key-Area Research and Development Program of Guangdong Province","award":["2025B1111050002"],"award-info":[{"award-number":["2025B1111050002"]}]},{"name":"Key-Area Research and Development Program of Guangdong Province","award":["2022B1111030002"],"award-info":[{"award-number":["2022B1111030002"]}]},{"DOI":"10.13039\/100000009","name":"Foundation for the National Institutes of Health","doi-asserted-by":"publisher","award":["AI136850"],"award-info":[{"award-number":["AI136850"]}],"id":[{"id":"10.13039\/100000009","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.plosntds.org"],"crossmark-restriction":false},"short-container-title":["PLoS Negl Trop Dis"],"abstract":"<jats:sec id=\"sec001\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>\n                      Malaria 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\n                      <jats:italic>Anopheles<\/jats:italic>\n                      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.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec002\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      We developed the \u201cBlack Box,\u201d 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%\u201395.00% for\n                      <jats:italic>Anopheles sinensis<\/jats:italic>\n                      ,\n                      <jats:italic>An. stephensi<\/jats:italic>\n                      , and\n                      <jats:italic>An. anthropophagus<\/jats:italic>\n                      , with data consistency exceeding 97.00%. Semi-field tests yielded trapping rates of 73.60%\u201390.80% and consistency above 92.00%. In field deployments, the device captured 5,109 mosquitoes with a 94.17% consistency rate and captured more\n                      <jats:italic>Anopheles<\/jats:italic>\n                      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\n                      <jats:italic>An. sinensis<\/jats:italic>\n                      , 21 (18.75%; exact 95% CI, 12.60%-26.97%) were blood-fed, indicating that blood-fed mosquitoes may occur in outdoor collections.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec003\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The 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.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1371\/journal.pntd.0014778","type":"journal-article","created":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T17:30:24Z","timestamp":1791567024000},"page":"e0014778","update-policy":"https:\/\/doi.org\/10.1371\/journal.pntd.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["Development and effectiveness test of an internet-based real-time monitoring device for malaria parasite vector mosquitoes"],"prefix":"10.1371","volume":"20","author":[{"given":"Chenyu","family":"Han","sequence":"first","affiliation":[{"name":"Southern Medical University","place":["Guangzhou, Guangdong, China"],"department":["Department of Pathogen Biology, Institute of Tropical Medicine, School of Public 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