{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T03:41:18Z","timestamp":1764906078599,"version":"build-2065373602"},"reference-count":33,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2022,5,29]],"date-time":"2022-05-29T00:00:00Z","timestamp":1653782400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Science and Technology Major Project \u201cStudy on the Source Spectrum and Epidemic Law of Infectious Diseases in Yunnan and Surrounding Provinces\u201d","award":["2017ZX10103010003"],"award-info":[{"award-number":["2017ZX10103010003"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJERPH"],"abstract":"<jats:p>(1) Background: To explore whether meteorological factors have an impact on the prevalence of mumps, and to make a short\u2013term prediction of the case number of mumps in Chongqing. (2) Methods: K\u2013means clustering algorithm was used to divide the monthly mumps cases of each year into the high and low case number clusters, and Student t\u2013test was applied for difference analysis. The cross\u2013correlation function (CCF) was used to evaluate the correlation between the meteorological factors and mumps, and an ARIMAX model was constructed by additionally incorporating meteorological factors as exogenous variables in the ARIMA model, and a short\u2013term prediction was conducted for mumps in Chongqing, evaluated by MAE, RMSE. (3) Results: All the meteorological factors were significantly different (p &lt; 0.05), except for the relative humidity between the high and low case number clusters. The CCF and ARIMAX model showed that monthly precipitation, temperature, relative humidity and wind velocity were associated with mumps, and there were significant lag effects. The ARIMAX model could accurately predict mumps in the short term, and the prediction errors (MAE, RMSE) were lower than those of the ARIMA model. (4) Conclusions: Meteorological factors can affect the occurrence of mumps, and the ARIMAX model can effectively predict the incidence trend of mumps in Chongqing, which can provide an early warning for relevant departments.<\/jats:p>","DOI":"10.3390\/ijerph19116625","type":"journal-article","created":{"date-parts":[[2022,5,29]],"date-time":"2022-05-29T08:50:51Z","timestamp":1653814251000},"page":"6625","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Association between Meteorological Factors and Mumps and Models for Prediction in Chongqing, China"],"prefix":"10.3390","volume":"19","author":[{"given":"Hong","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Public Health and Management, Chongqing Medical University, Chongqing 400016, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kun","family":"Su","sequence":"additional","affiliation":[{"name":"School of Public Health and Management, Chongqing Medical University, Chongqing 400016, China"},{"name":"Chongqing Municipal Center for Disease Control and Prevention, Chongqing 400042, China"},{"name":"Chongqing Public Health Medical Center, Chongqing 400036, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoni","family":"Zhong","sequence":"additional","affiliation":[{"name":"School of Public Health and Management, Chongqing Medical University, Chongqing 400016, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,5,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1002\/rmv.1819","article-title":"Genomic diversity of mumps virus and global distribution of the 12 genotypes","volume":"25","author":"Jin","year":"2014","journal-title":"Rev. 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