{"id":"https://openalex.org/W4312401089","doi":"https://doi.org/10.1145/3565291.3565350","title":"Regression Study on Influencing Factors of COVID-19 Diagnosis Rate and Mortality: A Global Perspective","display_name":"Regression Study on Influencing Factors of COVID-19 Diagnosis Rate and Mortality: A Global Perspective","publication_year":2022,"publication_date":"2022-09-23","ids":{"openalex":"https://openalex.org/W4312401089","doi":"https://doi.org/10.1145/3565291.3565350"},"language":"en","primary_location":{"id":"doi:10.1145/3565291.3565350","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3565291.3565350","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th International Conference on Big Data Technologies","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065259477","display_name":"Yiheng Niu","orcid":"https://orcid.org/0000-0003-0645-7354"},"institutions":[{"id":"https://openalex.org/I165859042","display_name":"Huaibei Normal University","ror":"https://ror.org/03ek23472","country_code":"CN","type":"education","lineage":["https://openalex.org/I165859042"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yiheng Niu","raw_affiliation_strings":["College of Computer Science and Technology, College of Computer Science and Technology, Huaibei Normal University, Huaibei, Anhui, China, China"],"raw_orcid":"https://orcid.org/0000-0003-0645-7354","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, College of Computer Science and Technology, Huaibei Normal University, Huaibei, Anhui, China, China","institution_ids":["https://openalex.org/I165859042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039109899","display_name":"Dashuang Zhu","orcid":"https://orcid.org/0000-0001-6424-7422"},"institutions":[{"id":"https://openalex.org/I165859042","display_name":"Huaibei Normal University","ror":"https://ror.org/03ek23472","country_code":"CN","type":"education","lineage":["https://openalex.org/I165859042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dashuang Zhu","raw_affiliation_strings":["College of Computer Science and Technology, Huaibei Normal University, China"],"raw_orcid":"https://orcid.org/0000-0001-6424-7422","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Huaibei Normal University, China","institution_ids":["https://openalex.org/I165859042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071511611","display_name":"Lisai Liu","orcid":"https://orcid.org/0000-0002-9600-8730"},"institutions":[{"id":"https://openalex.org/I165859042","display_name":"Huaibei Normal University","ror":"https://ror.org/03ek23472","country_code":"CN","type":"education","lineage":["https://openalex.org/I165859042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lisai Liu","raw_affiliation_strings":["College of Computer Science and Technology, Huaibei Normal University, China"],"raw_orcid":"https://orcid.org/0000-0002-9600-8730","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Huaibei Normal University, China","institution_ids":["https://openalex.org/I165859042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010287808","display_name":"Weibiao Tan","orcid":"https://orcid.org/0000-0002-7087-4059"},"institutions":[{"id":"https://openalex.org/I165859042","display_name":"Huaibei Normal University","ror":"https://ror.org/03ek23472","country_code":"CN","type":"education","lineage":["https://openalex.org/I165859042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weibiao Tan","raw_affiliation_strings":["College of Computer Science and Technology, Huaibei Normal University, China"],"raw_orcid":"https://orcid.org/0000-0002-7087-4059","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Huaibei Normal University, China","institution_ids":["https://openalex.org/I165859042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077159831","display_name":"Wenqian Zhao","orcid":"https://orcid.org/0000-0001-5464-1178"},"institutions":[{"id":"https://openalex.org/I165859042","display_name":"Huaibei Normal University","ror":"https://ror.org/03ek23472","country_code":"CN","type":"education","lineage":["https://openalex.org/I165859042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenqian Zhao","raw_affiliation_strings":["College of Computer Science and Technology, Huaibei Normal University, China"],"raw_orcid":"https://orcid.org/0000-0001-5464-1178","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Huaibei Normal University, China","institution_ids":["https://openalex.org/I165859042"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100320010","display_name":"Sheng Liu","orcid":"https://orcid.org/0000-0003-2731-9591"},"institutions":[{"id":"https://openalex.org/I165859042","display_name":"Huaibei Normal University","ror":"https://ror.org/03ek23472","country_code":"CN","type":"education","lineage":["https://openalex.org/I165859042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sheng Liu","raw_affiliation_strings":["College of Computer Science and Technology, College of Computer Science and Technology, Huaibei Normal University, Huaibei, Anhui, China, China"],"raw_orcid":"https://orcid.org/0000-0003-2731-9591","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, College of Computer Science and Technology, Huaibei Normal University, Huaibei, Anhui, China, China","institution_ids":["https://openalex.org/I165859042"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5065259477"],"corresponding_institution_ids":["https://openalex.org/I165859042"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.32590653,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"363","last_page":"372"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11711","display_name":"COVID-19 Pandemic Impacts","score":0.9983000159263611,"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"}},"topics":[{"id":"https://openalex.org/T11711","display_name":"COVID-19 Pandemic Impacts","score":0.9983000159263611,"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"}},{"id":"https://openalex.org/T10410","display_name":"COVID-19 epidemiological studies","score":0.998199999332428,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9830999970436096,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/life-expectancy","display_name":"Life expectancy","score":0.7452071905136108},{"id":"https://openalex.org/keywords/per-capita","display_name":"Per capita","score":0.6858292818069458},{"id":"https://openalex.org/keywords/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.6146201491355896},{"id":"https://openalex.org/keywords/human-development-index","display_name":"Human Development Index","score":0.5465160012245178},{"id":"https://openalex.org/keywords/public-health","display_name":"Public health","score":0.5443238615989685},{"id":"https://openalex.org/keywords/environmental-health","display_name":"Environmental health","score":0.5019023418426514},{"id":"https://openalex.org/keywords/transmission","display_name":"Transmission (telecommunications)","score":0.49093011021614075},{"id":"https://openalex.org/keywords/gross-domestic-product","display_name":"Gross domestic product","score":0.4756811857223511},{"id":"https://openalex.org/keywords/global-health","display_name":"Global health","score":0.4672061800956726},{"id":"https://openalex.org/keywords/demography","display_name":"Demography","score":0.45882725715637207},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.45225194096565247},{"id":"https://openalex.org/keywords/mortality-rate","display_name":"Mortality rate","score":0.44469571113586426},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4326220750808716},{"id":"https://openalex.org/keywords/pandemic","display_name":"Pandemic","score":0.42524275183677673},{"id":"https://openalex.org/keywords/pneumonia","display_name":"Pneumonia","score":0.42392468452453613},{"id":"https://openalex.org/keywords/economic-growth","display_name":"Economic growth","score":0.3095487356185913},{"id":"https://openalex.org/keywords/human-development","display_name":"Human development (humanity)","score":0.27262818813323975},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.20064851641654968},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.18412411212921143},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.17927080392837524},{"id":"https://openalex.org/keywords/disease","display_name":"Disease","score":0.1557999849319458},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.13499024510383606},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.10586294531822205},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09810873866081238},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.08809918165206909}],"concepts":[{"id":"https://openalex.org/C133925201","wikidata":"https://www.wikidata.org/wiki/Q188419","display_name":"Life expectancy","level":3,"score":0.7452071905136108},{"id":"https://openalex.org/C127598652","wikidata":"https://www.wikidata.org/wiki/Q558635","display_name":"Per capita","level":3,"score":0.6858292818069458},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.6146201491355896},{"id":"https://openalex.org/C2779735493","wikidata":"https://www.wikidata.org/wiki/Q38994","display_name":"Human Development Index","level":3,"score":0.5465160012245178},{"id":"https://openalex.org/C138816342","wikidata":"https://www.wikidata.org/wiki/Q189603","display_name":"Public health","level":2,"score":0.5443238615989685},{"id":"https://openalex.org/C99454951","wikidata":"https://www.wikidata.org/wiki/Q932068","display_name":"Environmental health","level":1,"score":0.5019023418426514},{"id":"https://openalex.org/C761482","wikidata":"https://www.wikidata.org/wiki/Q118093","display_name":"Transmission (telecommunications)","level":2,"score":0.49093011021614075},{"id":"https://openalex.org/C114350782","wikidata":"https://www.wikidata.org/wiki/Q12638","display_name":"Gross domestic product","level":2,"score":0.4756811857223511},{"id":"https://openalex.org/C46578552","wikidata":"https://www.wikidata.org/wiki/Q2725393","display_name":"Global health","level":3,"score":0.4672061800956726},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.45882725715637207},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.45225194096565247},{"id":"https://openalex.org/C179755657","wikidata":"https://www.wikidata.org/wiki/Q58702","display_name":"Mortality rate","level":2,"score":0.44469571113586426},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4326220750808716},{"id":"https://openalex.org/C89623803","wikidata":"https://www.wikidata.org/wiki/Q12184","display_name":"Pandemic","level":5,"score":0.42524275183677673},{"id":"https://openalex.org/C2777914695","wikidata":"https://www.wikidata.org/wiki/Q12192","display_name":"Pneumonia","level":2,"score":0.42392468452453613},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.3095487356185913},{"id":"https://openalex.org/C2781089502","wikidata":"https://www.wikidata.org/wiki/Q2917873","display_name":"Human development (humanity)","level":2,"score":0.27262818813323975},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.20064851641654968},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.18412411212921143},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.17927080392837524},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.1557999849319458},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.13499024510383606},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.10586294531822205},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09810873866081238},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.08809918165206909},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"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/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3565291.3565350","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3565291.3565350","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th International Conference on Big Data Technologies","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.4399999976158142,"display_name":"Good health and well-being"}],"awards":[{"id":"https://openalex.org/G4423544424","display_name":null,"funder_award_id":"No. 2021sykf041","funder_id":"https://openalex.org/F4320328705","funder_display_name":"Huaibei Normal University"}],"funders":[{"id":"https://openalex.org/F4320328705","display_name":"Huaibei Normal University","ror":"https://ror.org/03ek23472"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1985327665","https://openalex.org/W1988790447","https://openalex.org/W2145073242","https://openalex.org/W2295598076","https://openalex.org/W2523513879","https://openalex.org/W2567881713","https://openalex.org/W3005119027","https://openalex.org/W3024894164","https://openalex.org/W3036760274","https://openalex.org/W3080103188","https://openalex.org/W3080995561","https://openalex.org/W3084916260","https://openalex.org/W3085640916","https://openalex.org/W3112119732","https://openalex.org/W3118577658","https://openalex.org/W3124607975","https://openalex.org/W3182406050","https://openalex.org/W3186728370","https://openalex.org/W3188347082","https://openalex.org/W4212883601","https://openalex.org/W6681651645"],"related_works":["https://openalex.org/W4388292402","https://openalex.org/W2885178679","https://openalex.org/W2932409583","https://openalex.org/W4312190046","https://openalex.org/W4226161467","https://openalex.org/W2886718573","https://openalex.org/W2188932524","https://openalex.org/W4200541242","https://openalex.org/W2965062853","https://openalex.org/W2782780157"],"abstract_inverted_index":{"The":[0],"novel":[1,13],"coronavirus":[2,14],"pneumonia":[3],"(COVID-19)":[4],"refers":[5],"to":[6,31,35,149,167,179,181],"the":[7,12,38,42,48,58,151,159,163,177],"pulmonary":[8],"infection":[9,54],"caused":[10],"by":[11],"(2019-nCoV),":[15],"which":[16],"has":[17],"become":[18],"an":[19],"urgent":[20],"public":[21,183],"health":[22,65,184],"event":[23],"of":[24,44,60,94,113,135,153,165],"global":[25],"concern":[26],"at":[27],"present.":[28],"In":[29],"order":[30],"help":[32],"local":[33],"governments":[34],"find":[36],"out":[37],"factors":[39,50,155],"that":[40,51,74,110],"curb":[41],"spread":[43],"COVID-19,":[45],"we":[46,72],"explored":[47],"influence":[49],"cause":[52],"COVID-19":[53,75,125,157],"and":[55,64,77,96,103,118,127,137,143,170,175],"death":[56],"in":[57,66,158,173],"fields":[59],"economy,":[61],"society,":[62],"life,":[63],"this":[67],"paper.":[68],"Through":[69],"correlation":[70],"analysis,":[71],"found":[73],"transmission":[76,126],"mortality":[78,171],"are":[79],"relatively":[80],"strongly":[81],"associated":[82],"with":[83,129,133],"human":[84,90],"development":[85,164],"index":[86],"(HDI),":[87],"Median":[88,119],"Age,":[89],"life":[91],"expectancy,":[92],"proportion":[93,112],"smokers,":[95,114],"GDP":[97,115],"per":[98,116,139],"capita.":[99],"Further":[100],"regression":[101,106],"analysis":[102],"machine":[104],"learning":[105],"algorithms":[107],"also":[108],"confirmed":[109,141],"HDI,":[111],"capita,":[117],"Age":[120],"have":[121],"significant":[122],"effects":[123],"on":[124,156],"mortality,":[128],"GBDT":[130],"performing":[131],"best":[132],"R\u00b2":[134],"0.585":[136],"0.415":[138],"million":[140],"cases":[142],"deaths,":[144],"respectively.":[145],"This":[146],"study":[147],"aims":[148],"explore":[150],"impact":[152],"relevant":[154],"international":[160],"community,":[161],"inform":[162],"measures":[166],"reduce":[168],"diagnosis":[169],"rates":[172],"countries,":[174],"improve":[176],"capacity":[178],"respond":[180],"such":[182],"emergencies.":[185]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
