{"id":"https://openalex.org/W4392922510","doi":"https://doi.org/10.3389/fdata.2024.1298029","title":"The impact of comorbidities and economic inequality on COVID-19 mortality in Mexico: a machine learning approach","display_name":"The impact of comorbidities and economic inequality on COVID-19 mortality in Mexico: a machine learning approach","publication_year":2024,"publication_date":"2024-03-18","ids":{"openalex":"https://openalex.org/W4392922510","doi":"https://doi.org/10.3389/fdata.2024.1298029","pmid":"https://pubmed.ncbi.nlm.nih.gov/38562649"},"language":"en","primary_location":{"id":"doi:10.3389/fdata.2024.1298029","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fdata.2024.1298029","pdf_url":"https://www.frontiersin.org/articles/10.3389/fdata.2024.1298029/pdf?isPublishedV2=False","source":{"id":"https://openalex.org/S4210201220","display_name":"Frontiers in Big Data","issn_l":"2624-909X","issn":["2624-909X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Big Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.frontiersin.org/articles/10.3389/fdata.2024.1298029/pdf?isPublishedV2=False","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5038935486","display_name":"Jorge M\u00e9ndez-Astudillo","orcid":"https://orcid.org/0000-0001-7708-7317"},"institutions":[{"id":"https://openalex.org/I8961855","display_name":"Universidad Nacional Aut\u00f3noma de M\u00e9xico","ror":"https://ror.org/01tmp8f25","country_code":"MX","type":"education","lineage":["https://openalex.org/I8961855"]}],"countries":["MX"],"is_corresponding":true,"raw_author_name":"Jorge M\u00e9ndez-Astudillo","raw_affiliation_strings":["Institute of Economic Research, National Autonomous University of Mexico, Mexico City, Mexico"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Economic Research, National Autonomous University of Mexico, Mexico City, Mexico","institution_ids":["https://openalex.org/I8961855"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5038935486"],"corresponding_institution_ids":["https://openalex.org/I8961855"],"apc_list":{"value":1285,"currency":"USD","value_usd":1285},"apc_paid":{"value":1285,"currency":"USD","value_usd":1285},"fwci":0.8933,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.67286652,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":"7","issue":null,"first_page":"1298029","last_page":"1298029"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10410","display_name":"COVID-19 epidemiological studies","score":0.18000000715255737,"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":0.18000000715255737,"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/T10041","display_name":"COVID-19 Clinical Research Studies","score":0.17419999837875366,"subfield":{"id":"https://openalex.org/subfields/2725","display_name":"Infectious Diseases"},"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/T12246","display_name":"Chronic Disease Management Strategies","score":0.08079999685287476,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/socioeconomic-status","display_name":"Socioeconomic status","score":0.717280387878418},{"id":"https://openalex.org/keywords/comorbidity","display_name":"Comorbidity","score":0.7028868794441223},{"id":"https://openalex.org/keywords/pandemic","display_name":"Pandemic","score":0.6249135732650757},{"id":"https://openalex.org/keywords/inequality","display_name":"Inequality","score":0.6028246879577637},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.5517763495445251},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.5465278029441833},{"id":"https://openalex.org/keywords/epidemiology","display_name":"Epidemiology","score":0.5206283926963806},{"id":"https://openalex.org/keywords/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.5169243216514587},{"id":"https://openalex.org/keywords/demography","display_name":"Demography","score":0.45453813672065735},{"id":"https://openalex.org/keywords/gerontology","display_name":"Gerontology","score":0.34301501512527466},{"id":"https://openalex.org/keywords/environmental-health","display_name":"Environmental health","score":0.33869248628616333},{"id":"https://openalex.org/keywords/disease","display_name":"Disease","score":0.12818971276283264},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10271376371383667},{"id":"https://openalex.org/keywords/psychiatry","display_name":"Psychiatry","score":0.07090386748313904},{"id":"https://openalex.org/keywords/sociology","display_name":"Sociology","score":0.06501027941703796}],"concepts":[{"id":"https://openalex.org/C147077947","wikidata":"https://www.wikidata.org/wiki/Q1515895","display_name":"Socioeconomic status","level":3,"score":0.717280387878418},{"id":"https://openalex.org/C2779159551","wikidata":"https://www.wikidata.org/wiki/Q1414874","display_name":"Comorbidity","level":2,"score":0.7028868794441223},{"id":"https://openalex.org/C89623803","wikidata":"https://www.wikidata.org/wiki/Q12184","display_name":"Pandemic","level":5,"score":0.6249135732650757},{"id":"https://openalex.org/C45555294","wikidata":"https://www.wikidata.org/wiki/Q28113351","display_name":"Inequality","level":2,"score":0.6028246879577637},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.5517763495445251},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.5465278029441833},{"id":"https://openalex.org/C107130276","wikidata":"https://www.wikidata.org/wiki/Q133805","display_name":"Epidemiology","level":2,"score":0.5206283926963806},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.5169243216514587},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.45453813672065735},{"id":"https://openalex.org/C74909509","wikidata":"https://www.wikidata.org/wiki/Q10387","display_name":"Gerontology","level":1,"score":0.34301501512527466},{"id":"https://openalex.org/C99454951","wikidata":"https://www.wikidata.org/wiki/Q932068","display_name":"Environmental health","level":1,"score":0.33869248628616333},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.12818971276283264},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10271376371383667},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.07090386748313904},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.06501027941703796},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"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/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3389/fdata.2024.1298029","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fdata.2024.1298029","pdf_url":"https://www.frontiersin.org/articles/10.3389/fdata.2024.1298029/pdf?isPublishedV2=False","source":{"id":"https://openalex.org/S4210201220","display_name":"Frontiers in Big Data","issn_l":"2624-909X","issn":["2624-909X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Big Data","raw_type":"journal-article"},{"id":"pmid:38562649","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38562649","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":"Frontiers in big data","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:10982366","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10982366","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10982366/pdf/fdata-07-1298029.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Front Big Data","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:cfe5e349d8004dfa9503e0378586c1eb","is_oa":false,"landing_page_url":"https://doaj.org/article/cfe5e349d8004dfa9503e0378586c1eb","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Frontiers in Big Data, Vol 7 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3389/fdata.2024.1298029","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fdata.2024.1298029","pdf_url":"https://www.frontiersin.org/articles/10.3389/fdata.2024.1298029/pdf?isPublishedV2=False","source":{"id":"https://openalex.org/S4210201220","display_name":"Frontiers in Big Data","issn_l":"2624-909X","issn":["2624-909X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Big Data","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5,"id":"https://metadata.un.org/sdg/1","display_name":"No poverty"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4392922510.pdf"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W1872185361","https://openalex.org/W2084884579","https://openalex.org/W2168759057","https://openalex.org/W2266821176","https://openalex.org/W2295598076","https://openalex.org/W2766640405","https://openalex.org/W2911964244","https://openalex.org/W2972869264","https://openalex.org/W3008928028","https://openalex.org/W3023759297","https://openalex.org/W3036174218","https://openalex.org/W3037515314","https://openalex.org/W3037523062","https://openalex.org/W3093183334","https://openalex.org/W3112471780","https://openalex.org/W3134088423","https://openalex.org/W3135617626","https://openalex.org/W3136471166","https://openalex.org/W3138319424","https://openalex.org/W3155919847","https://openalex.org/W3162535866","https://openalex.org/W3183165119","https://openalex.org/W4281931238","https://openalex.org/W4282919394","https://openalex.org/W4285087054","https://openalex.org/W4307242100","https://openalex.org/W4322718320","https://openalex.org/W7019633904"],"related_works":["https://openalex.org/W1978188354","https://openalex.org/W3141224953","https://openalex.org/W2155091457","https://openalex.org/W4240532399","https://openalex.org/W2765738011","https://openalex.org/W4387318495","https://openalex.org/W2157868280","https://openalex.org/W2002142585","https://openalex.org/W2795699014","https://openalex.org/W2125404607"],"abstract_inverted_index":{"Introduction:":[0],"Studies":[1],"from":[2,98],"different":[3,27],"parts":[4],"of":[5,18,24,45,77,84,117,165,221],"the":[6,21,29,43,73,94,115,118,133,139,144,159,163,175,204],"world":[7],"have":[8],"shown":[9],"that":[10,154],"some":[11],"comorbidities":[12,25,74,161,201],"are":[13,26],"associated":[14,80],"with":[15,81,181,218],"fatal":[16,82],"cases":[17,83],"COVID-19.":[19],"However,":[20],"prevalence":[22,44],"rates":[23],"around":[28],"world,":[30],"therefore,":[31,47],"their":[32],"contribution":[33],"to":[34,71,101,190,202,208,214],"COVID-19":[35,52,85,122],"mortality":[36,164],"is":[37,188],"different.":[38],"Socioeconomic":[39],"factors":[40],"may":[41,49],"influence":[42,51],"comorbidities;":[46],"they":[48],"also":[50,171],"mortality.":[53,176],"Methods:":[54],"This":[55],"study":[56],"conducted":[57],"feature":[58],"analysis":[59,152],"using":[60,132],"two":[61],"supervised":[62],"machine":[63],"learning":[64],"classification":[65],"algorithms,":[66],"Random":[67,182],"Forest":[68,183],"and":[69,75,104,111,143,156,184],"XGBoost,":[70],"examine":[72],"level":[76],"economic":[78],"inequalities":[79,129,169,196],"in":[86],"Mexico.":[87],"The":[88,151,211],"dataset":[89],"used":[90],"was":[91],"collected":[92],"by":[93,138,148],"National":[95,140],"Epidemiology":[96],"Center":[97],"February":[99],"2020":[100],"November":[102],"2022,":[103],"includes":[105],"more":[106,206],"than":[107],"20":[108],"million":[109],"observations":[110],"40":[112],"variables":[113],"describing":[114],"characteristics":[116,173],"individuals":[119],"who":[120],"underwent":[121],"testing":[123],"or":[124,216,223],"treatment.":[125],"In":[126],"addition,":[127],"socioeconomic":[128,168],"were":[130,158,170,179],"measured":[131],"normalized":[134],"marginalization":[135],"index":[136,146],"calculated":[137,147],"Population":[141],"Council":[142],"deprivation":[145],"NASA.":[149],"Results:":[150],"shows":[153],"diabetes":[155],"hypertension":[157],"main":[160],"defining":[162,174],"COVID-19,":[166],"furthermore,":[167],"important":[172],"Similar":[177],"features":[178],"found":[180],"XGBoost.":[185],"Discussion:":[186],"It":[187],"imperative":[189],"implement":[191],"programs":[192],"aimed":[193],"at":[194],"reducing":[195],"as":[197,199],"well":[198],"preventable":[200],"make":[203],"population":[205],"resilient":[207],"future":[209],"pandemics.":[210],"results":[212],"apply":[213],"regions":[215],"countries":[217],"similar":[219],"levels":[220],"inequality":[222],"comorbidity":[224],"prevalence.":[225]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}
