{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,7]],"date-time":"2026-11-07T13:28:30Z","timestamp":1794058110365,"version":"4.8.0"},"reference-count":34,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T00:00:00Z","timestamp":1789516800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004735","name":"Hunan Provincial Natural Science Foundation","doi-asserted-by":"publisher","award":["2024JJ9547"],"award-info":[{"award-number":["2024JJ9547"]}],"id":[{"id":"10.13039\/501100004735","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004735","name":"Hunan Provincial Natural Science Foundation","doi-asserted-by":"publisher","award":["2025JJ80516"],"award-info":[{"award-number":["2025JJ80516"]}],"id":[{"id":"10.13039\/501100004735","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Preventive Medicine Reports"],"published-print":{"date-parts":[[2026,11]]},"DOI":"10.1016\/j.pmedr.2026.103643","type":"journal-article","created":{"date-parts":[[2026,9,17]],"date-time":"2026-09-17T17:38:45Z","timestamp":1789666725000},"page":"103643","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Temporal epidemiology and multi-source forecasting of hemorrhagic fever with renal syndrome and leptospirosis in mainland China: An interpretable machine learning study"],"prefix":"10.1016","volume":"71","author":[{"given":"Meiqian","family":"Gong","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yinzhu","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuilian","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chi","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.pmedr.2026.103643_bb0005","first-page":"451","article-title":"Infectious disease outbreaks in the wake of natural flood disasters: global patterns and local implications","volume":"32","author":"Acosta-Espa\u00f1a","year":"2024","journal-title":"Infez. Med."},{"key":"10.1016\/j.pmedr.2026.103643_bb0010","article-title":"One health field approach applied to leptospirosis: a systematic review and meta-analysis across humans, animals and the environment","volume":"12","author":"Antoniolli","year":"2025","journal-title":"Open Forum Infect. Dis."},{"key":"10.1016\/j.pmedr.2026.103643_bb0015","doi-asserted-by":"crossref","DOI":"10.1016\/j.onehlt.2025.101253","article-title":"Comprehensive review of one health systems for emerging infectious disease detection and management","volume":"21","author":"Basheer","year":"2025","journal-title":"One Health"},{"key":"10.1016\/j.pmedr.2026.103643_bb0020","doi-asserted-by":"crossref","first-page":"1167","DOI":"10.3390\/pathogens12091167","article-title":"Leptospirosis and the environment: a review and future directions","volume":"12","author":"Bradley","year":"2023","journal-title":"Pathogens"},{"key":"10.1016\/j.pmedr.2026.103643_bb0025","series-title":"Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","first-page":"785","article-title":"XGBoost: a scalable tree boosting system","author":"Chen","year":"2016"},{"key":"10.1016\/j.pmedr.2026.103643_bb0030","series-title":"ERA5 Hourly Data on Pressure Levels from 1940 to Present","author":"Copernicus Climate Change Service, Climate Data Store","year":"2023"},{"key":"10.1016\/j.pmedr.2026.103643_bb0035","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pntd.0003898","article-title":"Global morbidity and mortality of leptospirosis: a systematic review","volume":"9","author":"Costa","year":"2015","journal-title":"PLoS Negl. Trop. Dis."},{"key":"10.1016\/j.pmedr.2026.103643_bb0040","article-title":"Epidemiological characteristics and prediction model construction of hemorrhagic fever with renal syndrome in Quzhou city, China, 2005-2022","volume":"11","author":"Gao","year":"2023","journal-title":"Front. Public Health"},{"key":"10.1016\/j.pmedr.2026.103643_bb0045","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.rse.2017.06.031","article-title":"Google Earth Engine: planetary-scale geospatial analysis for everyone","volume":"202","author":"Gorelick","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"10.1016\/j.pmedr.2026.103643_bb0050","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pntd.0012755","article-title":"Spatio-temporal risk prediction of leptospirosis: a machine-learning-based approach","volume":"19","author":"Govan","year":"2025","journal-title":"PLoS Negl. Trop. Dis."},{"key":"10.1016\/j.pmedr.2026.103643_bb0055","doi-asserted-by":"crossref","first-page":"561","DOI":"10.5194\/npg-11-561-2004","article-title":"Application of the cross wavelet transform and wavelet coherence to geophysical time series","volume":"11","author":"Grinsted","year":"2004","journal-title":"Nonlinear Process. Geophys."},{"key":"10.1016\/j.pmedr.2026.103643_bb0060","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1038\/s41586-024-08328-6","article-title":"Accurate predictions on small data with a tabular foundation model","volume":"637","author":"Hollmann","year":"2025","journal-title":"Nature"},{"key":"10.1016\/j.pmedr.2026.103643_bb0065","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1038\/s41746-023-00751-9","article-title":"Explainable artificial intelligence for mental health through transparency and interpretability for understandability","volume":"6","author":"Joyce","year":"2023","journal-title":"NPJ Digit. Med."},{"key":"10.1016\/j.pmedr.2026.103643_bb0070","doi-asserted-by":"crossref","first-page":"623","DOI":"10.1038\/s41586-024-08564-w","article-title":"Artificial intelligence for modelling infectious disease epidemics","volume":"638","author":"Kraemer","year":"2025","journal-title":"Nature"},{"key":"10.1016\/j.pmedr.2026.103643_bb0075","doi-asserted-by":"crossref","first-page":"3029","DOI":"10.7189\/jogh.13.03029","article-title":"Predicting the daily counts of COVID-19 infection using temporal convolutional networks","volume":"13","author":"Li","year":"2023","journal-title":"J. Glob. Health"},{"key":"10.1016\/j.pmedr.2026.103643_bb0080","doi-asserted-by":"crossref","DOI":"10.1002\/sim.70374","article-title":"Extended joinpoint regression methodology for complex survey data","volume":"45","author":"Liu","year":"2026","journal-title":"Stat. Med."},{"key":"10.1016\/j.pmedr.2026.103643_bb0085","series-title":"Proceedings of the 31st International Conference on Neural Information Processing Systems","first-page":"4768","article-title":"A unified approach to interpreting model predictions","author":"Lundberg","year":"2017"},{"key":"10.1016\/j.pmedr.2026.103643_bb0090","doi-asserted-by":"crossref","first-page":"839","DOI":"10.1186\/s12879-021-06503-y","article-title":"Time series analysis of hemorrhagic fever with renal syndrome in mainland China by using an XGBoost forecasting model","volume":"21","author":"Lv","year":"2021","journal-title":"BMC Infect. Dis."},{"key":"10.1016\/j.pmedr.2026.103643_bb0095","doi-asserted-by":"crossref","first-page":"e699","DOI":"10.1016\/S2589-7500(22)00167-4","article-title":"Real-time COVID-19 forecasting: challenges and opportunities of model performance and translation","volume":"4","author":"Nixon","year":"2022","journal-title":"Lancet Digit. Health"},{"key":"10.1016\/j.pmedr.2026.103643_bb0105","doi-asserted-by":"crossref","first-page":"6713","DOI":"10.1038\/s41598-021-85987-9","article-title":"Forecasting influenza-like illness trends in Cameroon using Google Search Data","volume":"11","author":"Nsoesie","year":"2021","journal-title":"Sci. Rep."},{"key":"10.1016\/j.pmedr.2026.103643_bb0110","doi-asserted-by":"crossref","first-page":"1644","DOI":"10.1038\/s41467-025-56826-6","article-title":"Advancing adoptability and sustainability of digital prediction tools for climate-sensitive infectious disease prevention and control","volume":"16","author":"Phung","year":"2025","journal-title":"Nat. Commun."},{"key":"10.1016\/j.pmedr.2026.103643_bb0115","doi-asserted-by":"crossref","DOI":"10.1111\/cts.70056","article-title":"Practical guide to SHAP analysis: explaining supervised machine learning model predictions in drug development","volume":"17","author":"Ponce-Bobadilla","year":"2024","journal-title":"Clin. Transl. Sci."},{"key":"10.1016\/j.pmedr.2026.103643_bb0120","first-page":"130","article-title":"2010\u20142022\u5e74\u6211\u56fd\u94a9\u7aef\u87ba\u65cb\u4f53\u75c5\u6d41\u884c\u75c5\u5b66\u7279\u5f81 (Epidemiological characteristics of leptospirosis in China from 2010 to 2022)","volume":"36","author":"Shi","year":"2024","journal-title":"Chin. J. Schistosomiasis Control"},{"key":"10.1016\/j.pmedr.2026.103643_bb0125","doi-asserted-by":"crossref","first-page":"145","DOI":"10.3390\/v16010145","article-title":"Epidemiology of hemorrhagic fever with renal syndrome and host surveillance in Zhejiang Province, China, 1990-2021","volume":"16","author":"Su","year":"2024","journal-title":"Viruses"},{"key":"10.1016\/j.pmedr.2026.103643_bb0130","doi-asserted-by":"crossref","DOI":"10.1080\/21505594.2025.2553784","article-title":"Pathogenicity and virulence of rodent-borne orthohantaviruses","volume":"16","author":"Taylor","year":"2025","journal-title":"Virulence"},{"key":"10.1016\/j.pmedr.2026.103643_bb0135","doi-asserted-by":"crossref","DOI":"10.1016\/j.scitotenv.2023.168700","article-title":"Rainfall-driven resuspension of pathogenic Leptospira in a leptospirosis hotspot","volume":"911","author":"Thibeaux","year":"2024","journal-title":"Sci. Total Environ."},{"key":"10.1016\/j.pmedr.2026.103643_bb0140","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1175\/1520-0477(1998)079<0061:APGTWA>2.0.CO;2","article-title":"A practical guide to wavelet analysis","volume":"79","author":"Torrence","year":"1998","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"10.1016\/j.pmedr.2026.103643_bb0145","doi-asserted-by":"crossref","first-page":"6440","DOI":"10.1038\/s41467-021-26742-6","article-title":"Spatiotemporal prediction of COVID-19 cases using inter- and intra-county proxies of human interactions","volume":"12","author":"Vahedi","year":"2021","journal-title":"Nat. Commun."},{"key":"10.1016\/j.pmedr.2026.103643_bb0150","article-title":"Spatiotemporal trends of hemorrhagic fever with renal syndrome (HFRS) in China under climate variation","volume":"121","author":"Wang","year":"2024","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"10.1016\/j.pmedr.2026.103643_bb0155","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1186\/s40249-025-01284-x","article-title":"Changing epidemiology of leptospirosis in China from 1955 to 2022","volume":"14","author":"Wang","year":"2025","journal-title":"Infect. Dis. Poverty"},{"key":"10.1016\/j.pmedr.2026.103643_bb0160","article-title":"Integrating artificial intelligence with mechanistic epidemiological modeling: a scoping review of opportunities and challenges","volume":"16","author":"Ye","year":"2025","journal-title":"Nat. Commun."},{"key":"10.1016\/j.pmedr.2026.103643_bb0165","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1111\/zph.70014","article-title":"Epidemiological features and spatial\u2013temporal distribution of hemorrhagic fever with renal syndrome\u2014China, 2004\u20132023","volume":"73","author":"Zhai","year":"2026","journal-title":"Zoonoses Public Health"},{"key":"10.1016\/j.pmedr.2026.103643_bb0170","doi-asserted-by":"crossref","DOI":"10.1016\/j.soh.2023.100061","article-title":"Modern technologies and solutions to enhance surveillance and response systems for emerging zoonotic diseases","volume":"3","author":"Zhang","year":"2024","journal-title":"Sci. One Health"},{"key":"10.1016\/j.pmedr.2026.103643_bb0175","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2023.106157","article-title":"Improved LSTM-based deep learning model for COVID-19 prediction using optimized approach","volume":"122","author":"Zhou","year":"2023","journal-title":"Eng. Appl. Artif. Intell."}],"container-title":["Preventive Medicine Reports"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S221133552600272X?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S221133552600272X?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,11,7]],"date-time":"2026-11-07T13:12:24Z","timestamp":1794057144000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S221133552600272X"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,11]]},"references-count":34,"alternative-id":["S221133552600272X"],"URL":"https:\/\/doi.org\/10.1016\/j.pmedr.2026.103643","relation":{},"ISSN":["2211-3355"],"issn-type":[{"value":"2211-3355","type":"print"}],"subject":[],"published":{"date-parts":[[2026,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Temporal epidemiology and multi-source forecasting of hemorrhagic fever with renal syndrome and leptospirosis in mainland China: An interpretable machine learning study","name":"articletitle","label":"Article Title"},{"value":"Preventive Medicine Reports","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.pmedr.2026.103643","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Authors. Published by Elsevier Inc.","name":"copyright","label":"Copyright"}],"article-number":"103643"}}