{"id":"https://openalex.org/W4292641496","doi":"https://doi.org/10.1137/21m1435033","title":"Analysis of Spatial and Spatiotemporal Anomalies Using Persistent Homology: Case Studies with COVID-19 Data","display_name":"Analysis of Spatial and Spatiotemporal Anomalies Using Persistent Homology: Case Studies with COVID-19 Data","publication_year":2022,"publication_date":"2022-08-22","ids":{"openalex":"https://openalex.org/W4292641496","doi":"https://doi.org/10.1137/21m1435033"},"language":"en","primary_location":{"id":"doi:10.1137/21m1435033","is_oa":true,"landing_page_url":"https://doi.org/10.1137/21m1435033","pdf_url":null,"source":{"id":"https://openalex.org/S4210229561","display_name":"SIAM Journal on Mathematics of Data Science","issn_l":"2577-0187","issn":["2577-0187"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Mathematics of Data Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1137/21m1435033","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062343449","display_name":"Abigail Hickok","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Abigail Hickok","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024153474","display_name":"Deanna Needell","orcid":"https://orcid.org/0000-0002-8058-8638"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Deanna Needell","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-8058-8638","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5058684689","display_name":"Mason A. Porter","orcid":"https://orcid.org/0000-0002-5166-0717"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mason A. Porter","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-5166-0717","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5062343449"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.8102,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.86968694,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"4","issue":"3","first_page":"1116","last_page":"1144"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12536","display_name":"Topological and Geometric Data Analysis","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12536","display_name":"Topological and Geometric Data Analysis","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/persistent-homology","display_name":"Persistent homology","score":0.9523066282272339},{"id":"https://openalex.org/keywords/topological-data-analysis","display_name":"Topological data analysis","score":0.8069474101066589},{"id":"https://openalex.org/keywords/geospatial-analysis","display_name":"Geospatial analysis","score":0.6908997297286987},{"id":"https://openalex.org/keywords/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.5585934519767761},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4867141544818878},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.46083882451057434},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.43978869915008545},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.43782585859298706},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4299119710922241},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.4229303002357483},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2883467674255371},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.18203383684158325},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.11261790990829468},{"id":"https://openalex.org/keywords/infectious-disease","display_name":"Infectious disease (medical specialty)","score":0.10004952549934387}],"concepts":[{"id":"https://openalex.org/C2874115","wikidata":"https://www.wikidata.org/wiki/Q17099562","display_name":"Persistent homology","level":2,"score":0.9523066282272339},{"id":"https://openalex.org/C2776477805","wikidata":"https://www.wikidata.org/wiki/Q4460773","display_name":"Topological data analysis","level":2,"score":0.8069474101066589},{"id":"https://openalex.org/C9770341","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Geospatial analysis","level":2,"score":0.6908997297286987},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.5585934519767761},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4867141544818878},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.46083882451057434},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43978869915008545},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.43782585859298706},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4299119710922241},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.4229303002357483},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2883467674255371},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.18203383684158325},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.11261790990829468},{"id":"https://openalex.org/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.10004952549934387},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.0},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1137/21m1435033","is_oa":true,"landing_page_url":"https://doi.org/10.1137/21m1435033","pdf_url":null,"source":{"id":"https://openalex.org/S4210229561","display_name":"SIAM Journal on Mathematics of Data Science","issn_l":"2577-0187","issn":["2577-0187"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Mathematics of Data Science","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1137/21m1435033","is_oa":true,"landing_page_url":"https://doi.org/10.1137/21m1435033","pdf_url":null,"source":{"id":"https://openalex.org/S4210229561","display_name":"SIAM Journal on Mathematics of Data Science","issn_l":"2577-0187","issn":["2577-0187"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Mathematics of Data Science","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.46000000834465027,"display_name":"Climate action","id":"https://metadata.un.org/sdg/13"}],"awards":[{"id":"https://openalex.org/G1366356479","display_name":null,"funder_award_id":"1922952","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G138482151","display_name":null,"funder_award_id":"DMS-2011140","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G461241202","display_name":null,"funder_award_id":"DMS-2027438","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1830471444","https://openalex.org/W1991288592","https://openalex.org/W2044207839","https://openalex.org/W2115445832","https://openalex.org/W2153986241","https://openalex.org/W2224675575","https://openalex.org/W2751441808","https://openalex.org/W2783014944","https://openalex.org/W2799174785","https://openalex.org/W2913946465","https://openalex.org/W2951377931","https://openalex.org/W2962849396","https://openalex.org/W2963336247","https://openalex.org/W2991962490","https://openalex.org/W2999323139","https://openalex.org/W3003630168","https://openalex.org/W3009313293","https://openalex.org/W3021693646","https://openalex.org/W3022529094","https://openalex.org/W3049730228","https://openalex.org/W3087311875","https://openalex.org/W3091692300","https://openalex.org/W3099391356","https://openalex.org/W3117547876","https://openalex.org/W3127037230","https://openalex.org/W3141649405","https://openalex.org/W3161177018","https://openalex.org/W3194725275","https://openalex.org/W3215014341","https://openalex.org/W4206116286","https://openalex.org/W4213002438","https://openalex.org/W4213033583","https://openalex.org/W4251980118","https://openalex.org/W4285367599"],"related_works":["https://openalex.org/W4303685620","https://openalex.org/W2329652450","https://openalex.org/W2567191849","https://openalex.org/W4310838936","https://openalex.org/W3193988670","https://openalex.org/W3027964864","https://openalex.org/W4311527157","https://openalex.org/W4296836279","https://openalex.org/W2952699330","https://openalex.org/W109218057"],"abstract_inverted_index":{"We":[0,45,83,112],"develop":[1],"a":[2,35,135,143],"method":[3],"for":[4,98],"analyzing":[5],"spatial":[6],"and":[7,38],"spatiotemporal":[8],"anomalies":[9,108],"in":[10,34,57,61,127,138,151],"geospatial":[11],"data":[12,15,36,145],"using":[13,117],"topological":[14],"analysis":[16],"(TDA).":[17],"To":[18],"do":[19],"this,":[20],"we":[21,123,141],"use":[22,84],"persistent":[23],"homology":[24],"(PH),":[25],"which":[26,86],"allows":[27],"one":[28,87],"to":[29,101],"algorithmically":[30],"detect":[31],"geometric":[32],"voids":[33,56],"set":[37,146],"quantify":[39],"the":[40,55,65,79,104,107,154],"persistence":[41,92],"of":[42,106,147,153,156],"such":[43,53],"voids.":[44],"construct":[46],"an":[47,96],"efficient":[48],"filtered":[49],"simplicial":[50],"complex":[51],"(FSC)":[52],"that":[54],"our":[58],"FSC":[59],"are":[60,95],"one-to-one":[62],"correspondence":[63],"with":[64,110],"anomalies.":[66,82],"Our":[67],"approach":[68,97],"goes":[69],"beyond":[70],"simply":[71],"identifying":[72],"anomalies;":[73],"it":[74],"also":[75],"encodes":[76],"information":[77],"about":[78],"relationships":[80],"between":[81],"vineyards,":[85],"can":[88],"interpret":[89],"as":[90],"time-varying":[91],"diagrams":[93],"(which":[94],"visualizing":[99],"PH),":[100],"track":[102],"how":[103],"locations":[105],"change":[109],"time.":[111,139],"conduct":[113],"two":[114],"case":[115,149],"studies":[116],"spatially":[118],"heterogeneous":[119],"COVID-19":[120,148],"data.":[121],"First,":[122],"examine":[124],"vaccination":[125],"rates":[126,150],"New":[128],"York":[129],"City":[130],"by":[131],"zip":[132],"code":[133],"at":[134],"single":[136],"point":[137],"Second,":[140],"study":[142],"year-long":[144],"neighborhoods":[152],"city":[155],"Los":[157],"Angeles.":[158]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}