{"id":"https://openalex.org/W3093509097","doi":"https://doi.org/10.1109/tbdata.2020.3032755","title":"An Epidemiological Neural Network Exploiting Dynamic Graph Structured Data Applied to the COVID-19 Outbreak","display_name":"An Epidemiological Neural Network Exploiting Dynamic Graph Structured Data Applied to the COVID-19 Outbreak","publication_year":2020,"publication_date":"2020-10-21","ids":{"openalex":"https://openalex.org/W3093509097","doi":"https://doi.org/10.1109/tbdata.2020.3032755","mag":"3093509097","pmid":"https://pubmed.ncbi.nlm.nih.gov/37981990"},"language":"en","primary_location":{"id":"doi:10.1109/tbdata.2020.3032755","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tbdata.2020.3032755","pdf_url":"https://ieeexplore.ieee.org/ielx7/6687317/9366322/09234698.pdf","source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Big Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://ieeexplore.ieee.org/ielx7/6687317/9366322/09234698.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5038118094","display_name":"Valerio La Gatta","orcid":"https://orcid.org/0000-0002-5941-4684"},"institutions":[{"id":"https://openalex.org/I71267560","display_name":"University of Naples Federico II","ror":"https://ror.org/05290cv24","country_code":"IT","type":"education","lineage":["https://openalex.org/I71267560"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Valerio La Gatta","raw_affiliation_strings":["Department of Electrical and Information TechnologyUniversity of Naples Federico II 80125 Naples Italy","Department of Electrical and Information Technology, University of Naples Federico II, Naples, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Information TechnologyUniversity of Naples Federico II 80125 Naples Italy","institution_ids":[]},{"raw_affiliation_string":"Department of Electrical and Information Technology, University of Naples Federico II, Naples, Italy","institution_ids":["https://openalex.org/I71267560"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081965427","display_name":"Vincenzo Moscato","orcid":"https://orcid.org/0000-0002-0754-7696"},"institutions":[{"id":"https://openalex.org/I71267560","display_name":"University of Naples Federico II","ror":"https://ror.org/05290cv24","country_code":"IT","type":"education","lineage":["https://openalex.org/I71267560"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Vincenzo Moscato","raw_affiliation_strings":["Department of Electrical and Information TechnologyUniversity of Naples Federico II 80125 Naples Italy","Department of Electrical and Information Technology, University of Naples Federico II, Naples, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Information TechnologyUniversity of Naples Federico II 80125 Naples Italy","institution_ids":[]},{"raw_affiliation_string":"Department of Electrical and Information Technology, University of Naples Federico II, Naples, Italy","institution_ids":["https://openalex.org/I71267560"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022700280","display_name":"Marco Postiglione","orcid":"https://orcid.org/0000-0003-1470-8053"},"institutions":[{"id":"https://openalex.org/I71267560","display_name":"University of Naples Federico II","ror":"https://ror.org/05290cv24","country_code":"IT","type":"education","lineage":["https://openalex.org/I71267560"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Marco Postiglione","raw_affiliation_strings":["Department of Electrical and Information TechnologyUniversity of Naples Federico II 80125 Naples Italy","Department of Electrical and Information Technology, University of Naples Federico II, Naples, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Information TechnologyUniversity of Naples Federico II 80125 Naples Italy","institution_ids":[]},{"raw_affiliation_string":"Department of Electrical and Information Technology, University of Naples Federico II, Naples, Italy","institution_ids":["https://openalex.org/I71267560"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080190737","display_name":"Giancarlo Sperl\u00ed","orcid":"https://orcid.org/0000-0003-4033-3777"},"institutions":[{"id":"https://openalex.org/I71267560","display_name":"University of Naples Federico II","ror":"https://ror.org/05290cv24","country_code":"IT","type":"education","lineage":["https://openalex.org/I71267560"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Giancarlo Sperli","raw_affiliation_strings":["Department of Electrical and Information TechnologyUniversity of Naples Federico II 80125 Naples Italy","Department of Electrical and Information Technology, University of Naples Federico II, Naples, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Information TechnologyUniversity of Naples Federico II 80125 Naples Italy","institution_ids":[]},{"raw_affiliation_string":"Department of Electrical and Information Technology, University of Naples Federico II, Naples, Italy","institution_ids":["https://openalex.org/I71267560"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5038118094"],"corresponding_institution_ids":["https://openalex.org/I71267560"],"apc_list":null,"apc_paid":null,"fwci":3.0149,"has_fulltext":true,"cited_by_count":122,"citation_normalized_percentile":{"value":0.9402434,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"7","issue":"1","first_page":"45","last_page":"55"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10410","display_name":"COVID-19 epidemiological studies","score":0.9998000264167786,"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":0.9998000264167786,"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":0.996399998664856,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9919000267982483,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8598728179931641},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6052149534225464},{"id":"https://openalex.org/keywords/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.5693621635437012},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4759366512298584},{"id":"https://openalex.org/keywords/epidemic-model","display_name":"Epidemic model","score":0.46409574151039124},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4610741436481476},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4566243886947632},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.45619896054267883},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45398205518722534},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.4459025263786316},{"id":"https://openalex.org/keywords/temporal-database","display_name":"Temporal database","score":0.42752814292907715},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4029582440853119},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3236543536186218},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.28356027603149414},{"id":"https://openalex.org/keywords/infectious-disease","display_name":"Infectious disease (medical specialty)","score":0.07621389627456665},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.07501402497291565}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8598728179931641},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6052149534225464},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.5693621635437012},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4759366512298584},{"id":"https://openalex.org/C1627819","wikidata":"https://www.wikidata.org/wiki/Q2572354","display_name":"Epidemic model","level":3,"score":0.46409574151039124},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4610741436481476},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4566243886947632},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.45619896054267883},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45398205518722534},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.4459025263786316},{"id":"https://openalex.org/C77277458","wikidata":"https://www.wikidata.org/wiki/Q1969246","display_name":"Temporal database","level":2,"score":0.42752814292907715},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4029582440853119},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3236543536186218},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.28356027603149414},{"id":"https://openalex.org/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.07621389627456665},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.07501402497291565},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"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/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":3,"locations":[{"id":"doi:10.1109/tbdata.2020.3032755","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tbdata.2020.3032755","pdf_url":"https://ieeexplore.ieee.org/ielx7/6687317/9366322/09234698.pdf","source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Big Data","raw_type":"journal-article"},{"id":"pmid:37981990","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37981990","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on big data","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:8769012","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8769012","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Trans Big Data","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1109/tbdata.2020.3032755","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tbdata.2020.3032755","pdf_url":"https://ieeexplore.ieee.org/ielx7/6687317/9366322/09234698.pdf","source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Big Data","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.8700000047683716}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3093509097.pdf","grobid_xml":"https://content.openalex.org/works/W3093509097.grobid-xml"},"referenced_works_count":63,"referenced_works":["https://openalex.org/W950853366","https://openalex.org/W1525783482","https://openalex.org/W1606697907","https://openalex.org/W1899504021","https://openalex.org/W1969378369","https://openalex.org/W2002944058","https://openalex.org/W2004882990","https://openalex.org/W2046111848","https://openalex.org/W2064675550","https://openalex.org/W2064867497","https://openalex.org/W2104595316","https://openalex.org/W2107975333","https://openalex.org/W2136325354","https://openalex.org/W2136848157","https://openalex.org/W2143612262","https://openalex.org/W2148301044","https://openalex.org/W2157331557","https://openalex.org/W2161728228","https://openalex.org/W2163966557","https://openalex.org/W2525984666","https://openalex.org/W2554640988","https://openalex.org/W2565330852","https://openalex.org/W2579549467","https://openalex.org/W2606780347","https://openalex.org/W2610034660","https://openalex.org/W2886970679","https://openalex.org/W2913820390","https://openalex.org/W2918342466","https://openalex.org/W2950145354","https://openalex.org/W2952254971","https://openalex.org/W2963858333","https://openalex.org/W2964015378","https://openalex.org/W2964054289","https://openalex.org/W2964113829","https://openalex.org/W2998313947","https://openalex.org/W2999612210","https://openalex.org/W3004705239","https://openalex.org/W3008119221","https://openalex.org/W3008827533","https://openalex.org/W3009876049","https://openalex.org/W3009951436","https://openalex.org/W3010699833","https://openalex.org/W3010921212","https://openalex.org/W3011133285","https://openalex.org/W3013603216","https://openalex.org/W3014995088","https://openalex.org/W3018782651","https://openalex.org/W3019418590","https://openalex.org/W3041250660","https://openalex.org/W3043277778","https://openalex.org/W3100347265","https://openalex.org/W3105080728","https://openalex.org/W4288419263","https://openalex.org/W4297733535","https://openalex.org/W6685350579","https://openalex.org/W6726873649","https://openalex.org/W6736685754","https://openalex.org/W6736880317","https://openalex.org/W6760045743","https://openalex.org/W6761150088","https://openalex.org/W6774121290","https://openalex.org/W6775371796","https://openalex.org/W6776453626"],"related_works":["https://openalex.org/W2811185723","https://openalex.org/W2547829566","https://openalex.org/W2050347474","https://openalex.org/W2541259009","https://openalex.org/W638142098","https://openalex.org/W1975124777","https://openalex.org/W2019425806","https://openalex.org/W2991945580","https://openalex.org/W4385335406","https://openalex.org/W146849528"],"abstract_inverted_index":{"With":[0],"the":[1,9,16,23,30,37,54,108,117,124,132,135,142],"recent":[2],"COVID-19":[3,125],"outbreak,":[4],"we":[5,43,77,130],"have":[6],"assisted":[7],"to":[8,21,27,52,106,123],"development":[10],"of":[11,18,56,73,110,134],"new":[12],"epidemic":[13,38,143],"models":[14],"or":[15],"application":[17],"existing":[19],"methodologies":[20],"predict":[22],"virus":[24],"spread":[25],"and":[26,64,70,87,99,112,129],"analyze":[28],"how":[29],"different":[31],"lock-down":[32],"strategies":[33],"can":[34],"effectively":[35],"influence":[36],"diffusion.":[39],"In":[40,75],"this":[41],"paper,":[42],"propose":[44],"a":[45,82],"novel":[46],"machine":[47],"learning":[48],"based":[49,67],"framework":[50],"able":[51],"estimate":[53],"parameters":[55,109],"any":[57],"epidemiological":[58],"model,":[59],"such":[60],"as":[61],"contact":[62],"rates":[63],"recovery":[65],"rates,":[66],"on":[68],"static":[69],"dynamic":[71],"features":[72,89],"places.":[74],"particular,":[76],"model":[78,137],"mobility":[79],"data":[80,121,140],"through":[81],"graph":[83],"series":[84],"whose":[85],"spatial":[86],"temporal":[88],"are":[90],"investigated":[91],"by":[92],"combining":[93],"Graph":[94],"Convolutional":[95],"Neural":[96],"Networks":[97],"(GCNs)":[98],"Long":[100],"short-term":[101],"memories":[102],"(LSTMs)":[103],"in":[104,127],"order":[105],"infer":[107],"SIR":[111],"SIRD":[113],"models.":[114],"We":[115],"evaluate":[116],"proposed":[118],"approach":[119],"using":[120],"related":[122],"dynamics":[126],"Italy":[128],"compare":[131],"forecasts":[133],"trained":[136],"with":[138],"available":[139],"about":[141],"spread.":[144]},"counts_by_year":[{"year":2025,"cited_by_count":24},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":27},{"year":2022,"cited_by_count":28},{"year":2021,"cited_by_count":31}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}