{"id":"https://openalex.org/W3045488076","doi":"https://doi.org/10.48550/arxiv.2007.11103","title":"A Comparison of Aggregation Methods for Probabilistic Forecasts of COVID-19 Mortality in the United States","display_name":"A Comparison of Aggregation Methods for Probabilistic Forecasts of COVID-19 Mortality in the United States","publication_year":2020,"publication_date":"2020-07-21","ids":{"openalex":"https://openalex.org/W3045488076","doi":"https://doi.org/10.48550/arxiv.2007.11103","mag":"3045488076"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2007.11103","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2007.11103","pdf_url":"https://arxiv.org/pdf/2007.11103","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2007.11103","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5048147657","display_name":"Kathryn Taylor","orcid":"https://orcid.org/0000-0001-6589-5456","observed_orcids":["https://orcid.org/0000-0001-6589-5456"]},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Taylor, Kathryn S.","raw_affiliation_strings":["University of Oxford"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Oxford","institution_ids":["https://openalex.org/I40120149"]}]},{"author_position":"last","author":{"id":null,"display_name":"Taylor, James W.","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Taylor, James W.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.9520999789237976,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.9520999789237976,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10410","display_name":"COVID-19 epidemiological studies","score":0.03779999911785126,"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/T14374","display_name":"Statistical Methods in Epidemiology","score":0.0005000000237487257,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/forecast-aggregation","display_name":"forecast aggregation","score":0.7459999918937683},{"id":"https://openalex.org/keywords/probabilistic-forecasting","display_name":"probabilistic forecasting","score":0.9330000281333923},{"id":"https://openalex.org/keywords/covid-19-mortality","display_name":"COVID-19 mortality","score":0.9259999990463257},{"id":"https://openalex.org/keywords/prediction-intervals","display_name":"prediction intervals","score":0.9100000262260437},{"id":"https://openalex.org/keywords/forecast-combination","display_name":"forecast combination","score":0.6320000290870667},{"id":"https://openalex.org/keywords/median-aggregation","display_name":"median aggregation","score":0.5180000066757202},{"id":"https://openalex.org/keywords/forecast-accuracy","display_name":"forecast accuracy","score":0.4490000009536743},{"id":"https://openalex.org/keywords/wisdom-of-crowds","display_name":"wisdom of crowds","score":0.6140000224113464},{"id":"https://openalex.org/keywords/forecast-confidence","display_name":"forecast confidence","score":0.3089999854564667},{"id":"https://openalex.org/keywords/united-states","display_name":"United States","score":0.47099998593330383}],"concepts":[{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.8258605003356934},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5362616777420044},{"id":"https://openalex.org/C3006700255","wikidata":"https://www.wikidata.org/wiki/Q81068910","display_name":"2019-20 coronavirus outbreak","level":3,"score":0.535132110118866},{"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":0.509833037853241},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.4386083781719208},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.34123921394348145},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.3378744125366211},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.33089715242385864},{"id":"https://openalex.org/C159047783","wikidata":"https://www.wikidata.org/wiki/Q7215","display_name":"Virology","level":1,"score":0.24487492442131042},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.187151700258255},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1729356050491333},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.1729259192943573},{"id":"https://openalex.org/C116675565","wikidata":"https://www.wikidata.org/wiki/Q3241045","display_name":"Outbreak","level":2,"score":0.16706028580665588},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.055385053157806396},{"id":"https://openalex.org/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.044658005237579346}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2007.11103","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2007.11103","pdf_url":"https://arxiv.org/pdf/2007.11103","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2007.11103","doi":"https://doi.org/10.48550/arxiv.2007.11103","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2007.11103","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2007.11103","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2007.11103","pdf_url":"https://arxiv.org/pdf/2007.11103","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.4043000042438507,"id":"https://metadata.un.org/sdg/3"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1986528915","https://openalex.org/W2033501063","https://openalex.org/W2065089656","https://openalex.org/W2107609023","https://openalex.org/W2130715829","https://openalex.org/W2138241424","https://openalex.org/W2804689380","https://openalex.org/W3003749070","https://openalex.org/W3013080757","https://openalex.org/W3031845223","https://openalex.org/W3038501713","https://openalex.org/W3122054577","https://openalex.org/W3140139051"],"related_works":["https://openalex.org/W3174685221","https://openalex.org/W4220757792","https://openalex.org/W3127292647","https://openalex.org/W4223487063","https://openalex.org/W3092058378","https://openalex.org/W4297973287","https://openalex.org/W4306850832","https://openalex.org/W3080387602","https://openalex.org/W4414546704","https://openalex.org/W4283745601"],"abstract_inverted_index":{"The":[0],"COVID-19":[1,41,210],"pandemic":[2,255],"has":[3,203],"placed":[4],"forecasting":[5,34,94,119,192],"models":[6],"at":[7,42],"the":[8,32,36,43,49,84,99,103,106,114,118,143,163,166,169,180,185,191,209,214,220,229,236,251,254],"forefront":[9],"of":[10,15,35,56,105,117,134,145,158,165,187],"health":[11],"policy":[12],"making.":[13],"Predictions":[14],"mortality":[16,38,222,240],"and":[17,23,45,78,96,156,171,178,231,238],"hospitalization":[18],"help":[19],"governments":[20],"meet":[21],"planning":[22],"resource":[24],"allocation":[25],"challenges.":[26],"In":[27,137],"this":[28,138,249],"paper,":[29,140],"we":[30,97,121,141,224],"consider":[31,83,122],"weekly":[33],"cumulative":[37],"due":[39],"to":[40,101,183,194,246],"national":[44],"state":[46],"level":[47],"in":[48],"U.S.":[50],"Optimal":[51],"decision-making":[52],"requires":[53],"a":[54,57,63,132,188],"forecast":[55,182],"probability":[58,159],"distribution,":[59],"rather":[60],"than":[61],"just":[62],"single":[64],"point":[65],"forecast.":[66],"Interval":[67],"forecasts":[68,88,100,155],"are":[69],"also":[70],"important,":[71],"as":[72,253],"they":[73],"can":[74],"support":[75],"decision":[76],"making":[77],"provide":[79],"situational":[80],"awareness.":[81],"We":[82,199],"case":[85,252],"where":[86],"probabilistic":[87],"have":[89,149],"been":[90,150,204],"provided":[91],"by":[92],"multiple":[93],"teams,":[95,120],"aggregate":[98,181],"extract":[102],"wisdom":[104],"crowd.":[107],"With":[108],"only":[109],"limited":[110],"information":[111],"available":[112,207],"regarding":[113],"historical":[115],"accuracy":[116,144,227],"aggregation":[123,146],"(i.e.":[124],"combining)":[125],"methods":[126,147,234],"that":[127,148,202],"do":[128],"not":[129],"rely":[130],"on":[131],"record":[133],"past":[135],"accuracy.":[136],"empirical":[139],"evaluate":[142],"previously":[151],"proposed":[152],"for":[153,190,219,235],"interval":[154],"predictions":[157],"distributions.":[160],"These":[161],"include":[162],"use":[164,200],"simple":[167,215],"average,":[168],"median,":[170],"trimming":[172,233],"methods,":[173],"which":[174],"enable":[175],"robust":[176],"estimation":[177],"allow":[179],"reduce":[184],"impact":[186],"tendency":[189],"teams":[193],"be":[195,244],"under-":[196],"or":[197],"overconfident.":[198],"data":[201],"made":[205],"publicly":[206],"from":[208],"Forecast":[211],"Hub.":[212],"While":[213],"average":[216],"performed":[217],"well":[218],"high":[221],"series,":[223],"obtained":[225],"greater":[226],"using":[228],"median":[230],"certain":[232],"low":[237],"medium":[239],"series.":[241],"It":[242],"will":[243],"interesting":[245],"see":[247],"if":[248],"remains":[250],"evolves.":[256]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":3}],"updated_date":"2026-10-08T09:06:37.294493","created_date":"2020-07-29T00:00:00"}