{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T13:51:08Z","timestamp":1790171468534,"version":"4.1.0"},"reference-count":30,"publisher":"Public Library of Science (PLoS)","issue":"12","license":[{"start":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T00:00:00Z","timestamp":1766102400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Xinjiang Uygur Autonomous Region Key Research and Development Project","award":["2022B03013-1"],"award-info":[{"award-number":["2022B03013-1"]}]}],"content-domain":{"domain":["www.plosntds.org"],"crossmark-restriction":false},"short-container-title":["PLoS Negl Trop Dis"],"abstract":"<jats:sec id=\"sec001\">\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study investigated the epidemiological characteristics of echinococcosis in Xinjiang, aiming to provide evidence for evaluating prevention and control progress and guiding future strategies.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec002\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Reported echinococcosis incidence data from Xinjiang during 2005\u20132023 were obtained from the China Infectious Disease Surveillance and Reporting System. Temporal trends and spatial distributionwere analyzed using joinpoint regression and spatial autocorrelation methods. Additionally, a linear regression model (LR), spatial autoregressive model (SAR), and spatiotemporal autoregressive model (STAR) were constructed to quantitatively assess the impact of factors such as year, spatial lag, and temporal lag on incidence rates.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec003\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The reported incidence ranged from 1.95 per 100,000 in 2005 to 10.85 per 100,000 in 2017, followed by a gradual decline, though levels in 2023 (8.12 per 100,000) remained higher than those in 2005. Spatially, incidence exhibited significant positive spatial correlation (Moran\u2019s\n                      <jats:italic>I<\/jats:italic>\n                      : 0.097 in 2008 to 0.400 in 2010, all P-values\u2009&lt;\u20090.001), with high-incidence counties concentrated in northern and central Xinjiang, while low-incidence counties were mainly located in the south. Northern Xinjiang, particularly areas centered around Tacheng Prefecture, Bortala Prefecture, and Ili Prefecture, was identified as a hotspot, whereas Kashgar and Hotan Prefectures in southern Xinjiang formed cold spots. Model analysis indicated that the STAR model provided the best fit (residuals range: 0.020 [\u22120.292, 0.317], AIC\u2009=\u20092,549.4), with year, spatial lag (\n                      <jats:italic>\u03b2\u2009<\/jats:italic>\n                      =\u20090.323), and temporal lag (\n                      <jats:italic>\u03b2\u2009<\/jats:italic>\n                      =\u20090.420) significantly affecting incidence rates (\n                      <jats:italic>P<\/jats:italic>\n                      \u2009&lt;\u20090.05). The findings suggest that echinococcosis incidence in Xinjiang exhibits temporal continuity and spatial spillover effects.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec004\">\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Echinococcosis in Xinjiang exhibited marked spatiotemporal heterogeneity during 2005\u20132023. While national and regional prevention programs contributed to reducing incidence after 2017, the burden remains substantial. These findings underscore the need for sustained and regionally coordinated prevention and control strategies to prevent potential resurgence.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1371\/journal.pntd.0013775","type":"journal-article","created":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T18:40:37Z","timestamp":1766169637000},"page":"e0013775","update-policy":"https:\/\/doi.org\/10.1371\/journal.pntd.corrections_policy","source":"Crossref","is-referenced-by-count":2,"title":["Spatiotemporal distribution and control of echinococcosis in Xinjiang, 2005\u20132023"],"prefix":"10.1371","volume":"19","author":[{"given":"Zhe","family":"Yin","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guangzhong","family":"Shi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yalikun","family":"Maimaitiyiming","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qi","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kaisaer","family":"Tuerxunjiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adili","family":"Simayi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-5874-780X","authenticated-orcid":true,"given":"Jiangshan","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2025,12,19]]},"reference":[{"issue":"4","key":"pntd.0013775.ref001","doi-asserted-by":"crossref","first-page":"87","DOI":"10.3390\/tropicalmed9040087","article-title":"Global, Regional and National Burden of Human Cystic Echinococcosis from 1990 to 2019: A Systematic Analysis for the Global Burden of Disease Study 2019","volume":"9","author":"T Tian","year":"2024","journal-title":"Trop Med Infect Dis"},{"key":"pntd.0013775.ref002","unstructured":"WHO.Echinococcosis. 2020. 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