{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T18:38:26Z","timestamp":1792607906435,"version":"4.5.0"},"reference-count":80,"publisher":"Public Library of Science (PLoS)","issue":"10","license":[{"start":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T00:00:00Z","timestamp":1792540800000},"content-version":"am","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100013037","name":"Department of Agriculture, Environment and Rural Affairs, UK Government","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100013037","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:p>\n                    Reliable early warning of infectious disease outbreaks remains a major challenge for surveillance systems, particularly for vector-borne pathogens whose transmission depends on interactions among hosts, vectors, and climate-sensitive environmental conditions. Data-driven forecasting offers a promising approach for predicting outbreak risk using surveillance and environmental data. This study develops a logit-weighted ensemble (LWE), a machine-learning framework that predicts outbreak occurrence 1\u20136 months ahead at the administrative unit\u2013month scale using routinely available outbreak notifications and gridded climate data. Bluetongue virus (BTV), an arbovirus of ruminants transmitted by\n                    <jats:italic>Culicoides<\/jats:italic>\n                    biting midges, provides a well-characterised system in which transmission is strongly shaped by climate, making it a useful system for applying and testing this approach. The framework is evaluated using surveillance data collected between 2005 and 2024 from France, Greece, and Italy, selected for their long-running and high-quality outbreak surveillance records. Across all three countries, the LWE achieved the strongest and most stable predictive performance under a recall-focused evaluation that prioritises correctly identifying outbreak months. It outperformed or matched 14 benchmark models, with differences becoming more pronounced at longer lead times (month +3 onward), when predictions are more uncertain and outbreaks are relatively rare. Predictability varied across countries, with the highest performance in Greece, strong performance in France, and lower, more variable performance in Italy, reflecting differences in how consistently outbreaks occur and spread across regions. Overall, the results demonstrate that horizon-aware, climate-informed forecasting can reliably identify months and locations at elevated risk of outbreak occurrence up to six months in advance, supporting surveillance planning and preparedness across heterogeneous European settings. The ensemble framework provides a robust and portable strategy for outbreak prediction using routinely collected surveillance and environmental data.\n                  <\/jats:p>","DOI":"10.1371\/journal.pcbi.1014870","type":"journal-article","created":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T17:45:26Z","timestamp":1792604726000},"page":"e1014870","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["Spatio-temporal machine learning for multi-horizon prediction of bluetongue outbreaks"],"prefix":"10.1371","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-4493-3669","authenticated-orcid":true,"given":"Lucy M.","family":"Devlin","sequence":"first","affiliation":[{"name":"Queen\u2019s University Belfast","place":["Belfast, United Kingdom"],"department":["Institute for Global Food Security, School of Biological Sciences"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Phi H.","family":"Nguyen","sequence":"additional","affiliation":[{"name":"Queen\u2019s University Belfast","place":["Belfast, United Kingdom"],"department":["School of Electronics, Electrical Engineering and Computer Science"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ross N.","family":"Cuthbert","sequence":"additional","affiliation":[{"name":"Queen\u2019s University Belfast","place":["Belfast, United Kingdom"],"department":["Institute for Global Food Security, School of Biological Sciences"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Phu Ngoc","family":"Doan","sequence":"additional","affiliation":[{"name":"Queen\u2019s University Belfast","place":["Belfast, United Kingdom"],"department":["School of Electronics, Electrical Engineering and Computer Science"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Viet Hung","family":"Tran","sequence":"additional","affiliation":[{"name":"Queen\u2019s University Belfast","place":["Belfast, United Kingdom"],"department":["School of Electronics, Electrical Engineering and Computer Science"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zichi","family":"Zhang","sequence":"additional","affiliation":[{"name":"Queen\u2019s University Belfast","place":["Belfast, United Kingdom"],"department":["School of Electronics, Electrical Engineering and Computer Science"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Archie K.","family":"Murchie","sequence":"additional","affiliation":[{"name":"Agri-Food and Biosciences Institute (AFBI)","place":["Belfast, United Kingdom"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Connor G. G.","family":"Bamford","sequence":"additional","affiliation":[{"name":"Queen\u2019s University Belfast","place":["Belfast, United Kingdom"],"department":["Institute for Global Food Security, School of Biological Sciences"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jaimie T. A.","family":"Dick","sequence":"additional","affiliation":[{"name":"Queen\u2019s University Belfast","place":["Belfast, United Kingdom"],"department":["Institute for Global Food Security, School of Biological Sciences"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eric R.","family":"Morgan","sequence":"additional","affiliation":[{"name":"Queen\u2019s University Belfast","place":["Belfast, United Kingdom"],"department":["Institute for Global Food Security, School of Biological Sciences"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thai S.","family":"Mai","sequence":"additional","affiliation":[{"name":"Queen\u2019s University Belfast","place":["Belfast, United Kingdom"],"department":["School of Electronics, Electrical Engineering and Computer Science"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2026,10,21]]},"reference":[{"key":"pcbi.1014870.ref001","doi-asserted-by":"crossref","first-page":"513","DOI":"10.3389\/fvets.2020.00513","article-title":"Prediction models in veterinary and human epidemiology: Our experience with modeling Sars-CoV-2 spread","volume":"7","author":"T Halasa","year":"2020","journal-title":"Front Vet Sci"},{"issue":"2","key":"pcbi.1014870.ref002","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3708549","article-title":"Disease outbreak detection and forecasting: A review of methods and data sources","volume":"6","author":"G Babanejaddehaki","year":"2025","journal-title":"ACM Trans Comput Healthcare"},{"key":"pcbi.1014870.ref003","doi-asserted-by":"crossref","unstructured":"Xie L, Zhang MJ, Tan JL, Ling YX, Xue ZQ, Huang JJ, et al. 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