{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,3]],"date-time":"2026-11-03T23:14:11Z","timestamp":1793747651081,"version":"4.6.1"},"reference-count":47,"publisher":"Cambridge University Press (CUP)","license":[{"start":{"date-parts":[[2024,10,24]],"date-time":"2024-10-24T00:00:00Z","timestamp":1729728000000},"content-version":"unspecified","delay-in-days":297,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42201448"],"award-info":[{"award-number":["42201448"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82273689"],"award-info":[{"award-number":["82273689"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003819","name":"Natural Science Foundation of Hubei Province","doi-asserted-by":"publisher","award":["2022CFB610"],"award-info":[{"award-number":["2022CFB610"]}],"id":[{"id":"10.13039\/501100003819","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["cambridge.org"],"crossmark-restriction":true},"short-container-title":["Epidemiol. Infect."],"published-print":{"date-parts":[[2024]]},"abstract":"<jats:title>Abstract<\/jats:title>\n\t  <jats:p>As one of the most neglected zoonotic diseases, brucellosis has posed a serious threat to public health worldwide. This study is purposed to apply different machine learning models to improve the prediction accuracy of human brucellosis (HB) in Shaanxi, China from 2008 to 2020, under livestock husbandry intensification from a spatiotemporal perspective. We quantitatively evaluated the performance and suitability of ConvLSTM, RF, and LSTM models in epidemic forecasting, and investigated the spatial heterogeneity of how different factors drive the occurrence and transmission of HB in distinct sub-regions by using Kernel Density Analysis and Shapley Additional Explanations. Our findings demonstrated that ConvLSTM network yielded the best predictive performance with the lowest average RMSE of 13.875 and MAE values of 18.393. RF model generated an underestimated outcome while LSTM model had an overestimated one. In addition, climatic conditions, intensification of livestock keeping and socioeconomic status were identified as the dominant factors that drive the occurrence of HB in Shaanbei Plateau, Guanzhong Plain, and Shaannan Region, respectively. This work provided a comprehensive understanding of the potential risk of HB epidemics in Northwest China driven by both anthropogenic activities and natural environment, which can support further practice in disease control and prevention.<\/jats:p>","DOI":"10.1017\/s0950268824001018","type":"journal-article","created":{"date-parts":[[2024,10,24]],"date-time":"2024-10-24T08:12:16Z","timestamp":1729757536000},"update-policy":"https:\/\/doi.org\/10.1017\/policypage","source":"Crossref","is-referenced-by-count":14,"title":["Spatiotemporal risk of human brucellosis under intensification of livestock keeping based on machine learning techniques in Shaanxi, China"],"prefix":"10.1017","volume":"152","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9078-9353","authenticated-orcid":false,"given":"Li","family":"Shen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chenghao","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fangting","family":"Weng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Minghao","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chenxi","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ting","family":"Fu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cuihong","family":"An","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhongjun","family":"Shao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kun","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"56","published-online":{"date-parts":[[2024,10,24]]},"reference":[{"key":"S0950268824001018_r22","doi-asserted-by":"publisher","DOI":"10.1186\/s12889-020-08607-7"},{"key":"S0950268824001018_r12","doi-asserted-by":"publisher","DOI":"10.12980\/apjtd.7.2017D6-353"},{"key":"S0950268824001018_r35","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"S0950268824001018_r31","doi-asserted-by":"publisher","DOI":"10.1016\/j.rse.2017.01.005"},{"key":"S0950268824001018_r5","doi-asserted-by":"publisher","DOI":"10.1016\/S1473-3099(06)70382-6"},{"key":"S0950268824001018_r17","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pntd.0007757"},{"key":"S0950268824001018_r11","doi-asserted-by":"publisher","DOI":"10.1016\/j.onehlt.2022.100449"},{"key":"S0950268824001018_r26","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0232910"},{"key":"S0950268824001018_r27","first-page":"1","article-title":"Comparison of ARIMA and GM(1,1) models for prediction of hepatitis B in China","volume":"13","author":"Wang","year":"2018","journal-title":"PLoS One"},{"key":"S0950268824001018_r8","first-page":"1","article-title":"Epidemiological characteristics and spatiotemporal trend analysis of human brucellosis in China, 1950\u20132018","volume":"17","author":"Yang","year":"2020","journal-title":"International Journal of Environmental Research and Public Health"},{"key":"S0950268824001018_r23","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pntd.0007091"},{"key":"S0950268824001018_r39","doi-asserted-by":"publisher","DOI":"10.1186\/s12889-020-08599-4"},{"key":"S0950268824001018_r40","doi-asserted-by":"publisher","DOI":"10.1155\/2016\/5103718"},{"key":"S0950268824001018_r44","doi-asserted-by":"publisher","DOI":"10.1186\/s12879-016-2086-x"},{"key":"S0950268824001018_r36","first-page":"4768","article-title":"A unified approach to interpreting model predictions","volume":"30","author":"Lundberg","year":"2017","journal-title":"Advances in Neural Information Processing Systems"},{"key":"S0950268824001018_r25","doi-asserted-by":"crossref","first-page":"1680","DOI":"10.1017\/S0950268818002030","article-title":"Spatiotemporal analysis and forecasting model of hemorrhagic fever with renal syndrome in mainland China","volume":"146","author":"Sun","year":"2018","journal-title":"Epidemiology and Infection"},{"key":"S0950268824001018_r7","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijfoodmicro.2018.12.009"},{"key":"S0950268824001018_r41","doi-asserted-by":"publisher","DOI":"10.1007\/s11356-022-22831-1"},{"key":"S0950268824001018_r34","first-page":"802","volume-title":"Proceedings of the 28th International Conference on Neural Information Processing Systems","author":"Shi","year":"2015"},{"key":"S0950268824001018_r15","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pntd.0002260"},{"key":"S0950268824001018_r30","doi-asserted-by":"publisher","DOI":"10.3390\/rs9070673"},{"key":"S0950268824001018_r33","unstructured":"[33] Pei, C (2014) Research on Principal Component Analysis and Its Application in Feature Extraction. 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