{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T04:56:25Z","timestamp":1781067385165,"version":"3.54.1"},"reference-count":37,"publisher":"Cambridge University Press (CUP)","license":[{"start":{"date-parts":[[2020,3,17]],"date-time":"2020-03-17T00:00:00Z","timestamp":1584403200000},"content-version":"unspecified","delay-in-days":76,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["cambridge.org"],"crossmark-restriction":true},"short-container-title":["Epidemiol. Infect."],"published-print":{"date-parts":[[2020]]},"abstract":"<jats:title>Abstract<\/jats:title>\n\t  <jats:p>Chlamydia trachomatis (CT) infection has been a major public health threat globally. Monitoring and prediction of CT epidemic status and trends are important for programme planning, allocating resources and assessing impact; however, such activities are limited in China. In this study, we aimed to apply a seasonal autoregressive integrated moving average (SARIMA) model to predict the incidence of CT infection in Shenzhen city, China. The monthly incidence of CT between January 2008 and June 2019 in Shenzhen was used to fit and validate the SARIMA model. A seasonal fluctuation and a slightly increasing pattern of a long-term trend were revealed in the time series of CT incidence. The monthly CT incidence ranged from 4.80\/100 000 to 21.56\/100 000. The mean absolute percentage error value of the optimal model was 8.08%. The SARIMA model could be applied to effectively predict the short-term CT incidence in Shenzhen and provide support for the development of interventions for disease control and prevention.<\/jats:p>","DOI":"10.1017\/s0950268820000680","type":"journal-article","created":{"date-parts":[[2020,3,16]],"date-time":"2020-03-16T23:00:00Z","timestamp":1584399600000},"update-policy":"https:\/\/doi.org\/10.1017\/policypage","source":"Crossref","is-referenced-by-count":15,"title":["Time series analysis and forecasting of chlamydia trachomatis incidence using surveillance data from 2008 to 2019 in Shenzhen, China"],"prefix":"10.1017","volume":"148","author":[{"given":"R. X.","family":"Weng","sequence":"first","affiliation":[{"name":"Shenzhen Center for Chronic Disease Control"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"H. L.","family":"Fu","sequence":"additional","affiliation":[{"name":"Shenzhen Center for Chronic Disease Control"},{"name":"Central South University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"C. L.","family":"Zhang","sequence":"additional","affiliation":[{"name":"Shenzhen Center for Chronic Disease Control"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"J. B.","family":"Ye","sequence":"additional","affiliation":[{"name":"Shenzhen Center for Chronic Disease Control"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"F. C.","family":"Hong","sequence":"additional","affiliation":[{"name":"Shenzhen Center for Chronic Disease Control"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"X. S.","family":"Chen","sequence":"additional","affiliation":[{"name":"Chinese Academy of Medical Sciences & Peking Union Medical College Institute of Dermatology"},{"name":"China Center for Disease Control and Prevention"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8098-8244","authenticated-orcid":false,"given":"Y. M.","family":"Cai","sequence":"additional","affiliation":[{"name":"Shenzhen Center for Chronic Disease Control"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"56","published-online":{"date-parts":[[2020,3,17]]},"reference":[{"key":"S0950268820000680_ref20","volume-title":"China Statistical Yearbook 2015","year":"2015"},{"key":"S0950268820000680_ref31","first-page":"e149401","article-title":"Time series modelling of syphilis incidence in China from 2005 to 2012","volume":"11","author":"Zhang","year":"2016","journal-title":"PLoS One"},{"key":"S0950268820000680_ref17","doi-asserted-by":"publisher","DOI":"10.1097\/MD.0000000000003929"},{"key":"S0950268820000680_ref26","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/65.2.297"},{"key":"S0950268820000680_ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.fertnstert.2008.06.051"},{"key":"S0950268820000680_ref21","unstructured":"21. 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Published by Cambridge University Press","name":"copyright","label":"Copyright","group":{"name":"copyright_and_licensing","label":"Copyright and Licensing"}},{"value":"This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http:\/\/creativecommons.org\/licenses\/by\/4.0\/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.","name":"license","label":"License","group":{"name":"copyright_and_licensing","label":"Copyright and Licensing"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}],"article-number":"e76"}}