{"doi":"10.1371/journal.ppat.1012288","title":"The role of socio-economic disparities in the relative success and persistence of SARS-CoV-2 variants in New York City in early 2021","abstract":"Socio-economic disparities were associated with disproportionate viral incidence between neighborhoods of New York City (NYC) during the first wave of SARS-CoV-2. We investigated how these disparities affected the co-circulation of SARS-CoV-2 variants during the second wave in NYC. We tested for correlation between the prevalence, in late 2020/early 2021, of Alpha, Iota, Iota with E484K mutation (Iota-E484K), and B.1-like genomes and pre-existing immunity (seropositivity) in NYC neighborhoods. In the context of varying seroprevalence we described socio-economic profiles of neighborhoods and performed migration and lineage persistence analyses using a Bayesian phylogeographical framework. Seropositivity was greater in areas with high poverty and a larger proportion of Black and Hispanic or Latino residents. Seropositivity was positively correlated with the proportion of Iota-E484K and Iota genomes, and negatively correlated with the proportion of Alpha and B.1-like genomes. The proportion of persisting Alpha lineages declined over time in locations with high seroprevalence, whereas the proportion of persisting Iota-E484K lineages remained the same in high seroprevalence areas. During the second wave, the geographic variation of standing immunity, due to disproportionate disease burden during the first wave of SARS-CoV-2 in NYC, allowed for the immune evasive Iota-E484K variant, but not the more transmissible Alpha variant, to circulate in locations with high pre-existing immunity.","journal":"PLoS Pathogens","year":2024,"id":477002,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9591,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":637878,"name":"Jennifer L. Havens","orcid":"0000-0003-3095-5900","position":1,"is_corresponding":false},{"id":637877,"name":"Jade Wang","orcid":"0000-0002-8855-0925","position":2,"is_corresponding":false},{"id":867422,"name":"Elizabeth Luoma","orcid":"0009-0008-8396-269X","position":3,"is_corresponding":false},{"id":803875,"name":"Gabriel W. Hassler","orcid":"0000-0001-6951-5254","position":4,"is_corresponding":false},{"id":868110,"name":"Helly Amin","orcid":null,"position":5,"is_corresponding":false},{"id":1193119,"name":"Steve Di Lonardo","orcid":null,"position":6,"is_corresponding":false},{"id":375889,"name":"Faten Taki","orcid":"0000-0003-1092-3821","position":7,"is_corresponding":false},{"id":1192722,"name":"Enoma Omoregie","orcid":"0000-0002-7701-4182","position":8,"is_corresponding":false},{"id":637880,"name":"Scott Hughes","orcid":"0000-0001-8882-2946","position":9,"is_corresponding":false},{"id":69677,"name":"Joel O. Wertheim","orcid":"0000-0003-4882-5856","position":10,"is_corresponding":false},{"id":329444,"name":"Tetyana I. Vasylyeva","orcid":"0000-0002-9736-7022","position":0,"is_corresponding":true}],"reference_count":27,"raw_metadata":null,"created_at":"2026-07-19T02:06:33.741984Z","pmid":"38900824","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":[]}