{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T18:33:26Z","timestamp":1792002806568,"version":"4.4.0"},"reference-count":26,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T00:00:00Z","timestamp":1768780800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Cell. Infect. Microbiol."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>HIV molecular network technology can identify HIV transmission hotspots and individuals at risk of HIV transmission, facilitating precise and targeted interventions. This study explored the molecular network parameters, namely degree centrality (DC) and betweenness centrality (BC), to effectively pinpoint individuals at high risk of HIV transmission within the network.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A previous whole-population sampling cohort comprising all newly diagnosed people living with HIV (PLWH) in Shenyang, from 2016 to 2019, was analyzed. Molecular networks based pol gene were constructed, the DC and BC of each node were calculated, and six groups of nodes were identified based on DC, BC, and DC+BC: high DC group, low DC group, high BC group, low BC group, high DC+BC group, and non-high DC+BC group. The average risk of HIV transmission in each group was calculated by dividing the total probability of recent HIV infection (identified by HIV-1 LAg-Avidity EIA) by the number of cases in each group. A multivariate logistic regression analysis was conducted to identify the characteristics of the high-risk group.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Of the 2882 PLWH, 1162 were included in the molecular network. The mean DC and the mean BC of all nodes were 2.6 (range: 1-29) and 0.09 (range: 0-1), respectively. The top three groups with the highest average risk of HIV transmission were the high DC+BC group at 0.62, followed by the high BC group at 0.56, and the high DC group at 0.53. The characteristics of the high DC+BC group were low education levels, Housekeeping, housework, and unemployment, and high baseline viral load (\u226510\n                      <jats:sup>5<\/jats:sup>\n                      copies\/mL) (P&amp;lt;0.05).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>The combined utilization of DC and BC can effectively identify individuals at high risk of HIV transmission, enabling precisely targeted interventions using molecular network technology.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fcimb.2025.1695049","type":"journal-article","created":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T06:31:53Z","timestamp":1768804313000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Combining degree centrality and betweenness centrality of molecular networks can effectively pinpoint individuals at high risk of HIV transmission within the network"],"prefix":"10.3389","volume":"15","author":[{"given":"Wen","family":"Gan","sequence":"first","affiliation":[{"name":"State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Laboratory Medicine, The First Hospital of China Medical University, China Medical University","place":["Shenyang, China"]},{"name":"NHC Key Laboratory of AIDS Prevention and Treatment, National Clinical Research Center for Laboratory Medicine, The First Hospital of China Medical University, China Medical University","place":["Shenyang, China"]},{"name":"Key Laboratory of AIDS Immunology, Chinese Academy of Medical Sciences","place":["Shenyang, Liaoning, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bin","family":"Zhao","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Diagnosis and Treatment of 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