{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,3]],"date-time":"2026-11-03T18:36:12Z","timestamp":1793730972603,"version":"4.6.1"},"reference-count":29,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T00:00:00Z","timestamp":1777852800000},"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>Background<\/jats:title>\n                    <jats:p>Climate change is increasingly recognized as a critical driver affecting the transmission and distribution of parasitic diseases. However, a comprehensive synthesis of the global research landscape in this interdisciplinary field is lacking. This study provides an integrated analysis of research trends, collaborative networks, and emerging themes from 2000 to 2025.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We retrieved relevant articles and reviews from Web of Science and Scopus, analyzing 7,303 publications using visualization and statistical tools. Bibliometric analysis included publication trends, contributions by countries\/institutions, author networks, journal profiles, and keyword evolution.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Annual publications grew steadily at 13.1%. The United States led in output (5,085 papers) and citations (55,533), with strong international collaboration (40.5% cooperation rate). Key journals included\n                      <jats:italic>Veterinary Parasitology<\/jats:italic>\n                      and high-impact journals such as\n                      <jats:italic>Science<\/jats:italic>\n                      and\n                      <jats:italic>Nature<\/jats:italic>\n                      . Authors clustered into five major collaborative groups, with Poulin R. and Johnson P. T. J. as the most productive and influential researchers, respectively. Keyword analysis identified core themes including zoonoses, climate epidemiology, One Health, and specific diseases like malaria and schistosomiasis. Emerging keywords such as \u201cOne Health\u201d and \u201cSurveillance\u201d showed annual growth exceeding 200%.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>By integrating advanced bibliometric analysis, this study provides new insights. Specifically, research on climate change and parasitic diseases is evolving toward interdisciplinary and systems-oriented approaches. Future efforts should prioritize predictive modeling, global health governance, and integrating biodiversity conservation with disease control to mitigate climate-related health risks.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fcimb.2026.1804158","type":"journal-article","created":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T05:32:22Z","timestamp":1777872742000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Global research trends at the intersection of climate change and parasitic diseases: a systematic bibliometric research (2000\u20132025)"],"prefix":"10.3389","volume":"16","author":[{"given":"Maireyamuguli","family":"Nuermaimaiti","sequence":"first","affiliation":[{"name":"Xinjiang Medical University First Affiliated Hospital Medical Laboratory Center","place":["Urumqi, China"]},{"name":"School of Public Health, Xinjiang Medical University","place":["Urumqi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zile","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Anesthesiology, Southern Medical University","place":["Guangzhou, China"]},{"name":"The First Affiliated Medical College, Southern Medical University","place":["Guangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yimei","family":"Xu","sequence":"additional","affiliation":[{"name":"Xinjiang Uyghur Autonomous Region Center for Disease Control and Prevention","place":["Urumqi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinwei","family":"Qi","sequence":"additional","affiliation":[{"name":"Xinjiang Medical University First Affiliated Hospital Medical Laboratory Center","place":["Urumqi, China"]},{"name":"School of Public Health, Xinjiang Medical University","place":["Urumqi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,5,4]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.1016\/j.arr.2024.102285","article-title":"Parkinson's disease diagnosis using deep learning: A bibliometric analysis and literature review","volume":"96","author":"Abumalloh","year":"2024","journal-title":"Ageing Res. 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