{"doi":"10.3390/ijerph20186729","title":"Analysis of COVID-19 Case Demographics and Disease Outcomes in Gary, Indiana","abstract":"Background: The COVID-19 pandemic further exposed the prevalence of existing health disparities in Black communities in the U.S. The current study evaluates COVID-19 data collected in Gary, Indiana, from June 2020 to June 2021. We hypothesized that the number of COVID-19 cases, hospitalizations, and deaths were influenced by race and income. Methods: In collaboration with the Gary Health Department (GHD), we analyzed demographic data on COVID-19-positive cases. Results: Compared to Gary’s non-Black population, age- and population-adjusted rates of hospitalizations and deaths in the Black population were 3-fold (p < 0.0001) and 2-fold (p < 0.05) higher, respectively. This is despite a higher infection rate (p < 0.0001) in the non-Black population. The median household income of a zip code was negatively correlated with COVID-19 hospitalizations (R2 = 0.6345, p = 0.03), but did not correlate with infections and deaths. Conclusions: The current study demonstrates clear health disparities of income and race in the context of COVID-19-related infections and outcomes in the city of Gary. Indiana University School of Medicine Northwest and GHD officials can collaborate to utilize these data for the reallocation of resources and health education efforts in Gary’s highly populated, low-income, and predominantly Black neighborhoods. It should also prompt further investigation into national health resource allocation.","journal":"International Journal of Environmental Research and Public Health","year":2023,"id":386685,"datarank":0.11552453009332422,"base_score":0.6931471805599453,"endowment":0.6931471805599453,"self_citation_contribution":0.10397207708399181,"citation_network_contribution":0.011552453009332421,"self_endowment_contribution":0.10397207708399181,"citer_contribution":0.011552453009332421,"corpus_percentile":28.274154869652666,"corpus_rank":9272,"citation_count":1,"citer_count":1,"citers_with_citation_signal":1,"citers_with_endowment":1,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.5599,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":12.5,"fair_percentile":28.767960868236013,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":834165,"name":"Yazan Altarshan","orcid":"0000-0002-2996-321X","position":1,"is_corresponding":false},{"id":1155559,"name":"Cameron Snapp","orcid":null,"position":2,"is_corresponding":false},{"id":1155176,"name":"M. Brown","orcid":"0000-0001-6230-4286","position":3,"is_corresponding":false},{"id":1155560,"name":"Roland Walker","orcid":null,"position":4,"is_corresponding":false},{"id":1155177,"name":"Amy Han","orcid":"0000-0001-6063-7706","position":5,"is_corresponding":false},{"id":1155178,"name":"Tatiana Y. Kostrominova","orcid":"0000-0002-5863-7114","position":6,"is_corresponding":false},{"id":1155175,"name":"Maryam Sabir","orcid":"0000-0002-5415-8917","position":0,"is_corresponding":true}],"reference_count":37,"raw_metadata":null,"created_at":"2026-07-19T01:18:00.717763Z","pmid":"37754588","pmcid":"PMC10531445","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":22.2222,"fair_a":50.0,"fair_i":0.0,"fair_r":16.6667,"fair_zscore":-0.8688,"fair_rationale":{"fair_score":12.5,"has_llm":true,"taxonomy_version":"fair_taxonomy_v5","dimensions":{"F":{"name":"Findable","score":22.22,"criteria":[{"key":"f_dataset_pid","label":"Persistent identifier for the data","kind":"llm","weight":2.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No persistent identifier string for the dataset appears anywhere in the text.","anchors":["RDA-F1-01D — FAIR Data Maturity Model: 'Data is identified by a persistent identifier' (priorit","RDA-F1-02D — FAIR Data Maturity Model: 'Data is identified by a globally unique identifier'","FsF-F1-02D — F-UJI/FAIRsFAIR: 'Data is assigned a persistent identifier'"],"scored":true,"signal":null},{"key":"f_repository_named","label":"Named repository","kind":"llm","weight":2.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No repository is named as the holder of the data; the data are available on request from the corresponding author and the Gary Health Department. 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[majority verdict 'no' (4/5 passes agreed)]","anchors":["RDA-I3-01M — '(meta)data include references to other (meta)data'","RDA-I3-03M — 'metadata includes qualified references to other metadata'","FsF-I3-01M — F-UJI: 'Metadata includes links between the data and its related entities'"],"scored":false,"signal":null}]},"R":{"name":"Reusable","score":16.67,"criteria":[{"key":"r_reuse_license","label":"Reuse licence","kind":"llm","weight":2.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No licence or reuse terms are stated for the dataset; the CC BY licence applies only to the article.","anchors":["RDA-R1.1-01M — 'Metadata includes information about the licence under which the data can be reu","RDA-R1.1-02M — 'Metadata refers to a standard reuse licence'","RDA-R1.1-03M — 'Metadata refers to a machine-understandable reuse licence'"],"scored":true,"signal":null},{"key":"r_provenance_methods","label":"Provenance of the data","kind":"llm","weight":1.0,"fraction":0.5,"verdict":"partial","evidence":"COVID-19 data were collected from the Gary Health Department from 16 June 2020 to 7 June 2021.","grounded":true,"rationale":"The data collection is described in generic terms without naming specific instruments, kits, or software versions. 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