{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,2]],"date-time":"2026-11-02T08:29:50Z","timestamp":1793608190810,"version":"4.5.0"},"reference-count":44,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T00:00:00Z","timestamp":1776816000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100018694","name":"European Commission Marie Sklodowska-Curie Actions","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100018694","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001665","name":"French National Research Agency","doi-asserted-by":"publisher","award":["ANR-23-CPJ1\\u20130212\\u201301"],"award-info":[{"award-number":["ANR-23-CPJ1\\u20130212\\u201301"]}],"id":[{"id":"10.13039\/501100001665","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100018693","name":"Horizon Europe","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100018693","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":["Epidemics"],"published-print":{"date-parts":[[2026,6]]},"DOI":"10.1016\/j.epidem.2026.100916","type":"journal-article","created":{"date-parts":[[2026,4,26]],"date-time":"2026-04-26T14:46:38Z","timestamp":1777214798000},"page":"100916","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":5,"special_numbering":"C","title":["Foundation models for time series forecasting and policy evaluation in infectious disease epidemics"],"prefix":"10.1016","volume":"55","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2757-1896","authenticated-orcid":false,"given":"Suprabhath","family":"Kalahasti","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Benjamin","family":"Faucher","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Boxuan","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Claudio","family":"Ascione","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ricardo","family":"Carbajal","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9979-3818","authenticated-orcid":false,"given":"Maxime","family":"Enault","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christophe Vincent","family":"Cassis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Titouan","family":"Launay","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Caroline","family":"Guerrisi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pierre-Yves","family":"Bo\u00eblle","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-1323-4314","authenticated-orcid":false,"given":"Federico","family":"Baldo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eugenio","family":"Valdano","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.epidem.2026.100916_bib1","article-title":"GIFT-eval: a benchmark for general time series forecasting model evaluation","author":"Aksu","year":"2024","journal-title":"Presente NeurIPS Workshop Time Ser. Age Large Models"},{"key":"10.1016\/j.epidem.2026.100916_bib2","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1012523","article-title":"Integrating information from historical data into mechanistic models for influenza forecasting","volume":"20","author":"Andronico","year":"2024","journal-title":"PLOS Comput. Biol."},{"key":"10.1016\/j.epidem.2026.100916_bib3","unstructured":"Ansari, A.F., Stella, L., Turkmen, A.C., Zhang, X., Mercado, P., Shen, H., Shchur, O., Rangapuram, S.S., Arango, S.P., Kapoor, S., Zschiegner, J., Maddix, D.C., Wang, H., Mahoney, M.W., Torkkola, K., Wilson, A.G., Bohlke-Schneider, M., Wang, B., 2024. Chronos: Learning the Language of Time Series. Transactions on Machine Learning Research."},{"key":"10.1016\/j.epidem.2026.100916_bib4","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1038\/s41597-023-02276-y","article-title":"Unified real-time environmental-epidemiological data for multiscale modeling of the COVID-19 pandemic","volume":"10","author":"Badr","year":"2023","journal-title":"Sci. Data"},{"key":"10.1016\/j.epidem.2026.100916_bib5","series-title":"PAIS 2022","first-page":"86","article-title":"Informed Deep Learning for Epidemics Forecasting","author":"Baldo","year":"2022"},{"key":"10.1016\/j.epidem.2026.100916_bib6","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1186\/s12879-016-1669-x","article-title":"Results from the centers for disease control and prevention\u2019s predict the 2013\u20132014 Influenza Season Challenge","volume":"16","author":"Biggerstaff","year":"2016","journal-title":"BMC Infect. Dis."},{"key":"10.1016\/j.epidem.2026.100916_bib7","doi-asserted-by":"crossref","first-page":"1180","DOI":"10.1038\/s41586-025-09005-y","article-title":"A foundation model for the Earth system","volume":"641","author":"Bodnar","year":"2025","journal-title":"Nature"},{"key":"10.1016\/j.epidem.2026.100916_bib8","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1008618","article-title":"Evaluating epidemic forecasts in an interval format","volume":"17","author":"Bracher","year":"2021","journal-title":"PLOS Comput. Biol."},{"key":"10.1016\/j.epidem.2026.100916_bib9","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1038\/s41586-021-03694-x","article-title":"Thinking clearly about social aspects of infectious disease transmission","volume":"595","author":"Buckee","year":"2021","journal-title":"Nature"},{"key":"10.1016\/j.epidem.2026.100916_bib10","doi-asserted-by":"crossref","first-page":"730","DOI":"10.1016\/S2352-4642(24)00171-8","article-title":"Real-world effectiveness of nirsevimab immunisation against bronchiolitis in infants: a case\u2013control study in Paris, France","volume":"8","author":"Carbajal","year":"2024","journal-title":"Lancet Child Adolesc. Health"},{"key":"10.1016\/j.epidem.2026.100916_bib11","doi-asserted-by":"crossref","first-page":"850","DOI":"10.1038\/s41591-024-02857-3","article-title":"Towards a general-purpose foundation model for computational pathology","volume":"30","author":"Chen","year":"2024","journal-title":"Nat. Med."},{"key":"10.1016\/j.epidem.2026.100916_bib12","doi-asserted-by":"crossref","first-page":"639","DOI":"10.1126\/science.adj4427","article-title":"Indian Ocean temperature anomalies predict long-term global dengue trends","volume":"384","author":"Chen","year":"2024","journal-title":"Science"},{"key":"10.1016\/j.epidem.2026.100916_bib13","doi-asserted-by":"crossref","first-page":"296","DOI":"10.1038\/s41597-024-03120-7","article-title":"A global dataset of publicly available dengue case count data","volume":"11","author":"Clarke","year":"2024","journal-title":"Sci. Data"},{"key":"10.1016\/j.epidem.2026.100916_bib14","doi-asserted-by":"crossref","DOI":"10.1073\/pnas.2113561119","article-title":"Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States","volume":"119","author":"Cramer","year":"2022","journal-title":"Proc. Natl. Acad. Sci."},{"key":"10.1016\/j.epidem.2026.100916_bib15","author":"Das","year":"2024","journal-title":"A Decod. -only Found. Model Time-Ser. Forecast."},{"key":"10.1016\/j.epidem.2026.100916_bib16","article-title":"Attitudes towards booster, testing and isolation, and their impact on COVID-19 response in winter 2022\/2023 in France, Belgium, and Italy: a cross-sectional survey and modelling study","volume":"28","author":"de Meijere","year":"2023","journal-title":"Lancet Reg. Health - Eur."},{"key":"10.1016\/j.epidem.2026.100916_bib17","article-title":"Collaborative forecasting of influenza-like illness in Italy: the Influcast experience","author":"Fiandrino","year":"2024","journal-title":"medRxiv 2024"},{"key":"10.1016\/j.epidem.2026.100916_bib18","doi-asserted-by":"crossref","first-page":"413","DOI":"10.1177\/0962280206071639","article-title":"Virtual surveillance of communicable diseases: a 20-year experience in France","volume":"15","author":"Flahault","year":"2006","journal-title":"Stat. Methods Med Res"},{"key":"10.1016\/j.epidem.2026.100916_bib19","first-page":"1","author":"Garza","year":"2024","journal-title":"TimeGPT"},{"key":"10.1016\/j.epidem.2026.100916_bib20","doi-asserted-by":"crossref","first-page":"871","DOI":"10.1016\/S0140-6736(20)30411-6","article-title":"Preparedness and vulnerability of African countries against importations of COVID-19: a modelling study","volume":"395","author":"Gilbert","year":"2020","journal-title":"Lancet"},{"key":"10.1016\/j.epidem.2026.100916_bib21","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1186\/s13071-022-05630-y","article-title":"Evaluation of an open forecasting challenge to assess skill of West Nile virus neuroinvasive disease prediction","volume":"16","author":"Holcomb","year":"2023","journal-title":"Parasites & Vectors"},{"key":"10.1016\/j.epidem.2026.100916_bib22","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.epidem.2026.100916_bib23","unstructured":"Hoo, S.B., M\u00fcller, S., Salinas, D., Hutter, F., 2024. The Tabular Foundation Model TabPFN Outperforms Specialized Time Series Forecasting Models Based on Simple Features. Presented at the NeurIPS 2024 Third Table Representation Learning Workshop."},{"key":"10.1016\/j.epidem.2026.100916_bib24","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v027.i03","article-title":"Automatic Time Series Forecasting: The forecast Package for R","volume":"27","author":"Hyndman","year":"2008","journal-title":"J. Stat. Softw."},{"key":"10.1016\/j.epidem.2026.100916_bib25","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pntd.0007451","article-title":"A systematic review and evaluation of Zika virus forecasting and prediction research during a public health emergency of international concern","volume":"13","author":"Kobres","year":"2019","journal-title":"PLOS Negl. Trop. Dis."},{"key":"10.1016\/j.epidem.2026.100916_bib26","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.epidem.2026.100916_bib27","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1016\/j.ijforecast.2019.04.014","article-title":"The M4 Competition: 100,000 time series and 61 forecasting methods","volume":"36","author":"Makridakis","year":"2020","journal-title":"Int. J. Forecast. M4 Comp\u00e9t."},{"key":"10.1016\/j.epidem.2026.100916_bib28","doi-asserted-by":"crossref","unstructured":"Mills, C., Falconi-Agapito, F., Carrera, J.-P., Munayco, C.V., Kraemer, M.U.G., Donnelly, C.A., 2025. Multi-model approach to understand and predict past and future dengue epidemic dynamics. https:\/\/doi.org\/10.1101\/2024.10.18.24315690.","DOI":"10.1101\/2024.10.18.24315690"},{"key":"10.1016\/j.epidem.2026.100916_bib29","author":"Olivares","year":"2022","journal-title":"Neural. Use Friendly State---Art. Neural.Forecast. Models"},{"key":"10.1016\/j.epidem.2026.100916_bib30","doi-asserted-by":"crossref","DOI":"10.1126\/sciadv.abc0764","article-title":"Mobile phone data for informing public health actions across the COVID-19 pandemic life cycle","volume":"6","author":"Oliver","year":"2020","journal-title":"Sci. Adv."},{"issue":"10429","key":"10.1016\/j.epidem.2026.100916_bib31","doi-asserted-by":"crossref","first-page":"789","DOI":"10.1016\/S0140-6736(23)02758-7","article-title":"How modelling can better support public health policy making: the Lancet Commission on Strengthening the Use of Epidemiological Modelling of Emerging and Pandemic Infectious Diseases","volume":"403","year":"2024","journal-title":"Lancet"},{"key":"10.1016\/j.epidem.2026.100916_bib32","article-title":"Integrating dynamical modeling and phylogeographic inference to characterize global influenza circulation","volume":"4","author":"Parino","year":"2025","journal-title":"PNAS Nexus"},{"key":"10.1016\/j.epidem.2026.100916_bib33","doi-asserted-by":"crossref","first-page":"e353","DOI":"10.1016\/S2352-3018(22)00029-7","article-title":"Cost-effectiveness of easy-access, risk-informed oral pre-exposure prophylaxis in HIV epidemics in sub-Saharan Africa: a modelling study","volume":"9","author":"Phillips","year":"2022","journal-title":"Lancet HIV"},{"key":"10.1016\/j.epidem.2026.100916_bib34","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1038\/s41586-020-03095-6","article-title":"Underdetection of cases of COVID-19 in France threatens epidemic control","volume":"590","author":"Pullano","year":"2021","journal-title":"Nature"},{"key":"10.1016\/j.epidem.2026.100916_bib35","article-title":"Lag-Llama: Towards Foundation Models for Time Series Forecasting. Presented at the R0-FoMo:Robustness of Few-shot and Zero-shot","author":"Rasul","year":"2023","journal-title":"Learn. Large Found. Models"},{"key":"10.1016\/j.epidem.2026.100916_bib36","doi-asserted-by":"crossref","first-page":"1465","DOI":"10.1126\/science.abc5096","article-title":"Assessing the impact of coordinated COVID-19 exit strategies across Europe","volume":"369","author":"Ruktanonchai","year":"2020","journal-title":"Science"},{"key":"10.1016\/j.epidem.2026.100916_bib37","doi-asserted-by":"crossref","first-page":"465","DOI":"10.1016\/S1473-3099(23)00816-2","article-title":"The public health impact and cost-effectiveness of the R21\/Matrix-M malaria vaccine: a mathematical modelling study","volume":"24","author":"Schmit","year":"2024","journal-title":"Lancet Infect. Dis."},{"key":"10.1016\/j.epidem.2026.100916_bib38","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1080\/00031305.2017.1380080","article-title":"Forecasting at Scale","volume":"72","author":"Taylor","year":"2018","journal-title":"Am. Stat."},{"key":"10.1016\/j.epidem.2026.100916_bib39","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1186\/1741-7015-10-165","article-title":"Real-time numerical forecast of global epidemic spreading: case study of 2009 A\/H1N1pdm","volume":"10","author":"Tizzoni","year":"2012","journal-title":"BMC Med."},{"key":"10.1016\/j.epidem.2026.100916_bib40","unstructured":"US COVID-19 Forecasting Hub evaluation scores URL \u3008https:\/\/www.cmu.edu\/delphi-web\/forecast-eval-scores\/\u3009 (accessed 9.11.25)."},{"key":"10.1016\/j.epidem.2026.100916_bib41","unstructured":"Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, \u0141., Polosukhin, I., 2017. Attention is All you Need.31st Conference on Neural Information Processing Systems (NIPS 2017), Long Beach, CA, USA."},{"key":"10.1016\/j.epidem.2026.100916_bib42","first-page":"13","article-title":"The RAPIDD ebola forecasting challenge: Synthesis and lessons learnt","volume":"22","author":"Viboud","year":"2018","journal-title":"Epidemics RAPIDD Ebola Forecast. Chall."},{"key":"10.1016\/j.epidem.2026.100916_bib43","doi-asserted-by":"crossref","first-page":"1293","DOI":"10.1016\/S1473-3099(22)00320-6","article-title":"Global impact of the first year of COVID-19 vaccination: a mathematical modelling study","volume":"22","author":"Watson","year":"2022","journal-title":"Lancet Infect. Dis."},{"key":"10.1016\/j.epidem.2026.100916_bib44","doi-asserted-by":"crossref","first-page":"581","DOI":"10.1038\/s41467-024-55461-x","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."}],"container-title":["Epidemics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1755436526000320?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1755436526000320?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,11,2]],"date-time":"2026-11-02T08:13:28Z","timestamp":1793607208000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1755436526000320"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6]]},"references-count":44,"alternative-id":["S1755436526000320"],"URL":"https:\/\/doi.org\/10.1016\/j.epidem.2026.100916","relation":{},"ISSN":["1755-4365"],"issn-type":[{"value":"1755-4365","type":"print"}],"subject":[],"published":{"date-parts":[[2026,6]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Foundation models for time series forecasting and policy evaluation in infectious disease epidemics","name":"articletitle","label":"Article Title"},{"value":"Epidemics","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.epidem.2026.100916","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Author(s). Published by Elsevier B.V.","name":"copyright","label":"Copyright"}],"article-number":"100916"}}