{"doi":"10.1101/2020.09.30.20203315","title":"Widening the gap: greater racial and ethnic disparities in COVID-19 burden after accounting for missing race/ethnicity data","abstract":"Black, Hispanic, and Indigenous persons in the United States have an increased risk of SARS-CoV-2 infection and death from COVID-19, due to persistent social inequities. The magnitude of the disparity is unclear, however, because race/ethnicity information is often missing in surveillance data. In this study, we quantified the burden of SARS-CoV-2 infection, hospitalization, and case fatality rates in an urban county by racial/ethnic group using combined race/ethnicity imputation and quantitative bias-adjustment for misclassification. After bias-adjustment, the magnitude of the absolute racial/ethnic disparity, measured as the difference in infection rates between classified Black and Hispanic persons compared to classified White persons, increased 1.3-fold and 1.6-fold respectively. These results highlight that complete case analyses may underestimate absolute disparities in infection rates. Collecting race/ethnicity information at time of testing is optimal. However, when data are missing, combined imputation and bias-adjustment improves estimates of the racial/ethnic disparities in the COVID-19 burden.","journal":"medRxiv","year":2020,"id":119744,"datarank":0.42498200160843247,"base_score":2.833213344056216,"endowment":2.833213344056216,"self_citation_contribution":0.42498200160843247,"citation_network_contribution":0.0,"self_endowment_contribution":0.42498200160843247,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":16,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9419,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":555745,"name":"Sarah Hamid","orcid":"0000-0001-8164-0656","position":1,"is_corresponding":false},{"id":555746,"name":"Sarita Shah","orcid":"0000-0001-6007-8019","position":2,"is_corresponding":false},{"id":308895,"name":"Neel R. Gandhi","orcid":"0000-0002-1665-299X","position":3,"is_corresponding":false},{"id":376650,"name":"Allison T. Chamberlain","orcid":"0000-0001-6009-537X","position":4,"is_corresponding":false},{"id":556612,"name":"Fazle Khan","orcid":null,"position":5,"is_corresponding":false},{"id":556613,"name":"Shamimul Khan","orcid":null,"position":6,"is_corresponding":false},{"id":555747,"name":"Sasha Smith","orcid":"0000-0001-9843-5368","position":7,"is_corresponding":false},{"id":316803,"name":"Steven Williams","orcid":"0000-0003-4299-1941","position":8,"is_corresponding":false},{"id":387406,"name":"Timothy L. Lash","orcid":"0000-0002-5240-5195","position":9,"is_corresponding":false},{"id":4464,"name":"Lindsay  J. Collin","orcid":"0000-0003-0170-2592","position":10,"is_corresponding":false},{"id":555744,"name":"Katie Labgold","orcid":"0000-0001-6192-5822","position":0,"is_corresponding":true}],"reference_count":12,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-18T23:14:13.002105Z","pmid":"33024980","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}