{"id":"https://openalex.org/W3137821106","doi":"https://doi.org/10.1109/bigdata50022.2020.9378174","title":"Describing and Predicting COVID19 Evolution Using Pandemic Equation","display_name":"Describing and Predicting COVID19 Evolution Using Pandemic Equation","publication_year":2020,"publication_date":"2020-12-10","ids":{"openalex":"https://openalex.org/W3137821106","doi":"https://doi.org/10.1109/bigdata50022.2020.9378174","mag":"3137821106"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata50022.2020.9378174","is_oa":true,"landing_page_url":"https://doi.org/10.1109/bigdata50022.2020.9378174","pdf_url":"https://ieeexplore.ieee.org/ielx7/9377717/9377728/09378174.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/9377717/9377728/09378174.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070091935","display_name":"M. S. Shur","orcid":"https://orcid.org/0000-0003-0976-6232"},"institutions":[{"id":"https://openalex.org/I165799507","display_name":"Rensselaer Polytechnic Institute","ror":"https://ror.org/01rtyzb94","country_code":"US","type":"education","lineage":["https://openalex.org/I165799507"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Michael Shur","raw_affiliation_strings":["Rensselaer Polytechnic Institute,Department of Electrical, Computer, and Systems Engineering,Troy,NY,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rensselaer Polytechnic Institute,Department of Electrical, Computer, and Systems Engineering,Troy,NY,USA","institution_ids":["https://openalex.org/I165799507"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5070091935"],"corresponding_institution_ids":["https://openalex.org/I165799507"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.26992288,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"3","issue":null,"first_page":"5822","last_page":"5824"},"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/T12261","display_name":"Statistical Mechanics and Entropy","score":0.9469000101089478,"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"}},{"id":"https://openalex.org/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9408000111579895,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pandemic","display_name":"Pandemic","score":0.8002896308898926},{"id":"https://openalex.org/keywords/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.5866923332214355},{"id":"https://openalex.org/keywords/structural-equation-modeling","display_name":"Structural equation modeling","score":0.5658102631568909},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4711410403251648},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3608752191066742},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3415840268135071},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3381654918193817},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.24953439831733704},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.075876384973526}],"concepts":[{"id":"https://openalex.org/C89623803","wikidata":"https://www.wikidata.org/wiki/Q12184","display_name":"Pandemic","level":5,"score":0.8002896308898926},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.5866923332214355},{"id":"https://openalex.org/C71104824","wikidata":"https://www.wikidata.org/wiki/Q1476639","display_name":"Structural equation modeling","level":2,"score":0.5658102631568909},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4711410403251648},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3608752191066742},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3415840268135071},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3381654918193817},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.24953439831733704},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.075876384973526},{"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/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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata50022.2020.9378174","is_oa":true,"landing_page_url":"https://doi.org/10.1109/bigdata50022.2020.9378174","pdf_url":"https://ieeexplore.ieee.org/ielx7/9377717/9377728/09378174.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1109/bigdata50022.2020.9378174","is_oa":true,"landing_page_url":"https://doi.org/10.1109/bigdata50022.2020.9378174","pdf_url":"https://ieeexplore.ieee.org/ielx7/9377717/9377728/09378174.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.8500000238418579,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3137821106.pdf","grobid_xml":"https://content.openalex.org/works/W3137821106.grobid-xml"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W224340457","https://openalex.org/W568941435","https://openalex.org/W944707096","https://openalex.org/W2001930367","https://openalex.org/W2028568622","https://openalex.org/W2991614892","https://openalex.org/W3010020071","https://openalex.org/W3013080757","https://openalex.org/W3013360115","https://openalex.org/W3016460100","https://openalex.org/W3020878652","https://openalex.org/W3040339974","https://openalex.org/W3045441399","https://openalex.org/W3081037176","https://openalex.org/W3118585142","https://openalex.org/W6781242588","https://openalex.org/W6787736586","https://openalex.org/W6856241678"],"related_works":["https://openalex.org/W2024934382","https://openalex.org/W2303173273","https://openalex.org/W2513767888","https://openalex.org/W3147308590","https://openalex.org/W1528049813","https://openalex.org/W1968285868","https://openalex.org/W2364043478","https://openalex.org/W4388140417","https://openalex.org/W3153451317","https://openalex.org/W3046517191"],"abstract_inverted_index":{"The":[0,50,71],"COVID-19":[1],"pandemic":[2,20,91],"evolution":[3,92],"is":[4,13],"accurately":[5],"described":[6],"by":[7],"the":[8,14,19,26,31,36,40,67,75,81,95],"new":[9],"Pandemic":[10,51,76],"Equation,":[11],"which":[12],"generalized":[15],"rate":[16],"equation":[17],"describing":[18],"curve":[21],"flattening":[22],"and":[23,38,47],"accounting":[24],"for":[25,39,55,66],"mitigation":[27,96],"measures,":[28],"such":[29],"as":[30],"introduction":[32],"or":[33,44],"removal":[34],"of":[35,42,74],"quarantine,":[37],"effect":[41],"vaccination":[43],"drugs,":[45],"when":[46],"if":[48],"introduced.":[49],"Equation":[52,77],"model":[53,65],"allows":[54],"an":[56],"easy":[57],"parameter":[58,69,82],"extraction":[59],"amenable":[60],"to":[61],"training":[62],"Artificial":[63],"Intelligence":[64],"automatic":[68],"extraction.":[70],"predictive":[72],"capabilities":[73],"are":[78],"based":[79],"on":[80],"ranges":[83],"extracted":[84],"from":[85],"multiple":[86],"localities":[87],"with":[88,94],"well":[89],"advanced":[90],"correlated":[93],"measures.":[97]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
