{"id":"https://openalex.org/W4382318996","doi":"https://doi.org/10.1609/aaai.v37i13.26855","title":"Phase-Informed Bayesian Ensemble Models Improve Performance of COVID-19 Forecasts","display_name":"Phase-Informed Bayesian Ensemble Models Improve Performance of COVID-19 Forecasts","publication_year":2023,"publication_date":"2023-06-26","ids":{"openalex":"https://openalex.org/W4382318996","doi":"https://doi.org/10.1609/aaai.v37i13.26855"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v37i13.26855","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v37i13.26855","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/26855/26627","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/26855/26627","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5031381738","display_name":"Aniruddha Adiga","orcid":"https://orcid.org/0000-0002-5396-1978"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Aniruddha Adiga","raw_affiliation_strings":["University of Virginia"],"affiliations":[{"raw_affiliation_string":"University of Virginia","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063467309","display_name":"Gursharn Kaur","orcid":"https://orcid.org/0000-0002-0900-0600"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gursharn Kaur","raw_affiliation_strings":["University of Virginia"],"affiliations":[{"raw_affiliation_string":"University of Virginia","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100330304","display_name":"Lijing Wang","orcid":"https://orcid.org/0000-0002-0836-9190"},"institutions":[{"id":"https://openalex.org/I1288882113","display_name":"Boston Children's Hospital","ror":"https://ror.org/00dvg7y05","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1288882113"]},{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lijing Wang","raw_affiliation_strings":["Boston Children\u2019s Hospital and Harvard Medical School"],"affiliations":[{"raw_affiliation_string":"Boston Children\u2019s Hospital and Harvard Medical School","institution_ids":["https://openalex.org/I1288882113","https://openalex.org/I136199984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008261688","display_name":"Benjamin Hurt","orcid":"https://orcid.org/0000-0002-3803-2900"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Benjamin Hurt","raw_affiliation_strings":["University of Virginia"],"affiliations":[{"raw_affiliation_string":"University of Virginia","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017416729","display_name":"Przemyslaw Porebski","orcid":"https://orcid.org/0000-0001-8012-5791"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Przemyslaw Porebski","raw_affiliation_strings":["University of Virginia"],"affiliations":[{"raw_affiliation_string":"University of Virginia","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057315009","display_name":"Srinivasan Venkatramanan","orcid":"https://orcid.org/0000-0002-0874-8692"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Srinivasan Venkatramanan","raw_affiliation_strings":["University of Virginia"],"affiliations":[{"raw_affiliation_string":"University of Virginia","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072570670","display_name":"Bryan Lewis","orcid":"https://orcid.org/0000-0003-0793-6082"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bryan Lewis","raw_affiliation_strings":["University of Virginia"],"affiliations":[{"raw_affiliation_string":"University of Virginia","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020293284","display_name":"Madhav Marathe","orcid":"https://orcid.org/0000-0003-1653-0658"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Madhav V. Marathe","raw_affiliation_strings":["University of Virginia"],"affiliations":[{"raw_affiliation_string":"University of Virginia","institution_ids":["https://openalex.org/I51556381"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5031381738"],"corresponding_institution_ids":["https://openalex.org/I51556381"],"apc_list":null,"apc_paid":null,"fwci":7.4118,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":1.0,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"37","issue":"13","first_page":"15647","last_page":"15653"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10410","display_name":"COVID-19 epidemiological studies","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2611","display_name":"Modeling and Simulation"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10410","display_name":"COVID-19 epidemiological studies","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2611","display_name":"Modeling and Simulation"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9785000085830688,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9668999910354614,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.6633491516113281},{"id":"https://openalex.org/keywords/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.6620564460754395},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6550332903862},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.6356804370880127},{"id":"https://openalex.org/keywords/pandemic","display_name":"Pandemic","score":0.5014774799346924},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.44473010301589966},{"id":"https://openalex.org/keywords/severe-acute-respiratory-syndrome-coronavirus-2","display_name":"Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)","score":0.44111618399620056},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36687877774238586},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36642301082611084},{"id":"https://openalex.org/keywords/operations-research","display_name":"Operations research","score":0.35979944467544556},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1283661127090454},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.0700678825378418}],"concepts":[{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.6633491516113281},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.6620564460754395},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6550332903862},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.6356804370880127},{"id":"https://openalex.org/C89623803","wikidata":"https://www.wikidata.org/wiki/Q12184","display_name":"Pandemic","level":5,"score":0.5014774799346924},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.44473010301589966},{"id":"https://openalex.org/C3007834351","wikidata":"https://www.wikidata.org/wiki/Q82069695","display_name":"Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)","level":5,"score":0.44111618399620056},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36687877774238586},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36642301082611084},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.35979944467544556},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1283661127090454},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0700678825378418},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.0},{"id":"https://openalex.org/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v37i13.26855","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v37i13.26855","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/26855/26627","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v37i13.26855","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v37i13.26855","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/26855/26627","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.8799999952316284,"display_name":"Good health and well-being"}],"awards":[{"id":"https://openalex.org/G1505502640","display_name":null,"funder_award_id":"HDTRA1-19-D-0007","funder_id":"https://openalex.org/F4320332186","funder_display_name":"Defense Threat Reduction Agency"},{"id":"https://openalex.org/G2245754035","display_name":null,"funder_award_id":"CSTE/CDC 5 NU38OT000297","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G2253905536","display_name":"BIGDATA: Collaborative Research: F: Efficient Distributed Computation of Large-Scale Graph Problems in Epidemiology and Contagion Dynamics","funder_award_id":"1633028","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G2372087932","display_name":null,"funder_award_id":"CCF-1918656","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3416031122","display_name":null,"funder_award_id":"R01GM109718","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G3505574271","display_name":null,"funder_award_id":"CNS-2028004","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G3549164809","display_name":null,"funder_award_id":"IIS-1633028","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3611247453","display_name":null,"funder_award_id":"R01GM","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G3706291859","display_name":null,"funder_award_id":"1R01GM109718","funder_id":"https://openalex.org/F4320332186","funder_display_name":"Defense Threat Reduction Agency"},{"id":"https://openalex.org/G3828073557","display_name":null,"funder_award_id":"OAC-1916805","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G3858435652","display_name":null,"funder_award_id":"OAC-2027541","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G3896797137","display_name":null,"funder_award_id":"5 NU38OT000297","funder_id":"https://openalex.org/F4320308644","funder_display_name":"Council of State and Territorial Epidemiologists"},{"id":"https://openalex.org/G3933114365","display_name":null,"funder_award_id":"RAPID","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4656488385","display_name":null,"funder_award_id":"RAPID OAC-2027541","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4894173665","display_name":null,"funder_award_id":"2142997","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4966575984","display_name":null,"funder_award_id":"OAC-1916805","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5024895080","display_name":null,"funder_award_id":"75D30119C05935","funder_id":"https://openalex.org/F4320332162","funder_display_name":"Centers for Disease Control and Prevention"},{"id":"https://openalex.org/G5145214560","display_name":null,"funder_award_id":"VDH-21-501-0141","funder_id":"https://openalex.org/F4320332186","funder_display_name":"Defense Threat Reduction Agency"},{"id":"https://openalex.org/G5260964573","display_name":null,"funder_award_id":"CCF-1918656","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G5817136658","display_name":null,"funder_award_id":"NU38OT000297","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G5845535585","display_name":null,"funder_award_id":"1R01GM109718","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G5921281487","display_name":null,"funder_award_id":"number","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6361321077","display_name":"RAPID: COVID-19 Response Support: Building Synthetic Multi-scale Networks","funder_award_id":"2027541","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6541015203","display_name":null,"funder_award_id":"HDTRA1","funder_id":"https://openalex.org/F4320332186","funder_display_name":"Defense Threat Reduction Agency"},{"id":"https://openalex.org/G6542493234","display_name":null,"funder_award_id":"CCF-1917819","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G6654112443","display_name":null,"funder_award_id":"IIS-1633028","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G7180878835","display_name":null,"funder_award_id":"1917819","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7315863584","display_name":"Collaborative Research: Framework: Software: CINES: A Scalable Cyberinfrastructure for Sustained Innovation in Network Engineering and Science","funder_award_id":"1916805","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7568272315","display_name":null,"funder_award_id":"US-CDC 75D30119C05935","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G775681259","display_name":null,"funder_award_id":"75D30119C0593","funder_id":"https://openalex.org/F4320332162","funder_display_name":"Centers for Disease Control and Prevention"},{"id":"https://openalex.org/G8034655586","display_name":null,"funder_award_id":"CNS-2028004","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8146162564","display_name":null,"funder_award_id":"CCF-1917819","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8473960026","display_name":null,"funder_award_id":"214299","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8754932706","display_name":null,"funder_award_id":"NU38OT000297","funder_id":"https://openalex.org/F4320332162","funder_display_name":"Centers for Disease Control and Prevention"},{"id":"https://openalex.org/G887741455","display_name":null,"funder_award_id":"1918656","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8980456122","display_name":null,"funder_award_id":"NU38OT000297","funder_id":"https://openalex.org/F4320308644","funder_display_name":"Council of State and Territorial Epidemiologists"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320308644","display_name":"Council of State and Territorial Epidemiologists","ror":"https://ror.org/03ax9j741"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320332162","display_name":"Centers for Disease Control and Prevention","ror":"https://ror.org/042twtr12"},{"id":"https://openalex.org/F4320332186","display_name":"Defense Threat Reduction Agency","ror":"https://ror.org/04tz64554"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4382318996.pdf"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W2150657679","https://openalex.org/W2158840489","https://openalex.org/W2515822248","https://openalex.org/W2748268306","https://openalex.org/W2767745493","https://openalex.org/W2896605639","https://openalex.org/W2909758842","https://openalex.org/W3005699652","https://openalex.org/W3015438442","https://openalex.org/W3031381838","https://openalex.org/W3038075184","https://openalex.org/W3038787377","https://openalex.org/W3040134252","https://openalex.org/W3046978353","https://openalex.org/W3082591845","https://openalex.org/W3091413779","https://openalex.org/W3096046600","https://openalex.org/W3097661700","https://openalex.org/W3111459367","https://openalex.org/W3125676075","https://openalex.org/W3137647102","https://openalex.org/W3138337437","https://openalex.org/W3187294826","https://openalex.org/W4200194600","https://openalex.org/W4289261700","https://openalex.org/W6755313938","https://openalex.org/W6789427365"],"related_works":["https://openalex.org/W2407375987","https://openalex.org/W2505726097","https://openalex.org/W2950975704","https://openalex.org/W3049691116","https://openalex.org/W2010643158","https://openalex.org/W2106867672","https://openalex.org/W4310268968","https://openalex.org/W3081214562","https://openalex.org/W2753713401","https://openalex.org/W2053745677"],"abstract_inverted_index":{"Despite":[0],"hundreds":[1],"of":[2,28,39,63,97,158,188],"methods":[3,81,122],"published":[4],"in":[5,50,73,182],"the":[6,22,37,124,146,151,159,165,186,192],"literature,":[7],"forecasting":[8,78,116,194],"epidemic":[9,29,77,91],"dynamics":[10,30,92],"remains":[11],"challenging":[12],"yet":[13,87],"important.":[14],"The":[15,43,155],"challenges":[16],"stem":[17],"from":[18,191],"multiple":[19],"sources,":[20],"including:":[21],"need":[23],"for":[24,132],"timely":[25],"data,":[26],"co-evolution":[27],"with":[31,101,144],"behavioral":[32],"and":[33,36,127,150,174],"immunological":[34],"adaptations,":[35],"evolution":[38],"new":[40],"pathogen":[41],"strains.":[42],"ongoing":[44],"COVID-19":[45,152],"pandemic":[46,166],"highlighted":[47],"these":[48,64],"challenges;":[49],"an":[51],"important":[52],"article,":[53],"Reich":[54],"et":[55],"al.":[56],"did":[57],"a":[58,85,95,106],"comprehensive":[59],"analysis":[60],"highlighting":[61],"many":[62],"challenges.":[65],"In":[66],"this":[67,102],"paper,":[68],"we":[69,104],"take":[70],"another":[71],"step":[72],"critically":[74],"evaluating":[75],"existing":[76],"methods.":[79],"Our":[80],"are":[82],"based":[83],"on":[84],"simple":[86],"crucial":[88],"observation":[89],"-":[90],"go":[93],"through":[94],"number":[96],"phases":[98,181],"(waves).":[99],"Armed":[100],"understanding,":[103],"propose":[105],"modification":[107],"to":[108],"our":[109,141],"deployed":[110,148],"Bayesian":[111],"ensembling":[112,121],"case":[113],"time":[114],"series":[115],"framework.":[117],"We":[118,139],"show":[119],"that":[120],"employing":[123],"phase":[125,134],"information":[126],"using":[128],"different":[129],"weighting":[130],"schemes":[131],"each":[133],"can":[135],"produce":[136],"improved":[137],"forecasts.":[138],"evaluate":[140],"proposed":[142,160],"method":[143],"both":[145],"currently":[147],"model":[149,161],"forecasthub":[153],"models.":[154],"overall":[156],"performance":[157,187],"is":[162,171],"consistent":[163],"across":[164],"but":[167],"more":[168],"importantly,":[169],"it":[170],"ranked":[172],"third":[173],"first":[175],"during":[176],"two":[177],"critical":[178],"rapid":[179],"growth":[180],"cases,":[183],"regimes":[184],"where":[185],"most":[189],"models":[190],"CDC":[193],"hub":[195],"dropped":[196],"significantly.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}