{"doi":"10.1093/cid/ciaa1547","title":"The Potential Epidemiological Impact of Coronavirus Disease 2019 (COVID-19) on the Human Immunodeficiency Virus (HIV) Epidemic and the Cost-effectiveness of Linked, Opt-out HIV Testing: A Modeling Study in 6 US Cities","abstract":"BACKGROUND: Widespread viral and serological testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may present a unique opportunity to also test for human immunodeficiency virus (HIV) infection. We estimated the potential impact of adding linked, opt-out HIV testing alongside SARS-CoV-2 testing on the HIV incidence and the cost-effectiveness of this strategy in 6 US cities. METHODS: Using a previously calibrated dynamic HIV transmission model, we constructed 3 sets of scenarios for each city: (1) sustained current levels of HIV-related treatment and prevention services (status quo); (2) temporary disruptions in health services and changes in sexual and injection risk behaviors at discrete levels between 0%-50%; and (3) linked HIV and SARS-CoV-2 testing offered to 10%-90% of the adult population in addition to Scenario 2. We estimated the cumulative number of HIV infections between 2020-2025 and the incremental cost-effectiveness ratios of linked HIV testing over 20 years. RESULTS: In the absence of linked, opt-out HIV testing, we estimated a total of a 16.5% decrease in HIV infections between 2020-2025 in the best-case scenario (50% reduction in risk behaviors and no service disruptions), and a 9.0% increase in the worst-case scenario (no behavioral change and 50% reduction in service access). We estimated that HIV testing (offered at 10%-90% levels) could avert a total of 576-7225 (1.6%-17.2%) new infections. The intervention would require an initial investment of $20.6M-$220.7M across cities; however, the intervention would ultimately result in savings in health-care costs in each city. CONCLUSIONS: A campaign in which HIV testing is linked with SARS-CoV-2 testing could substantially reduce the HIV incidence and reduce direct and indirect health care costs attributable to HIV.","journal":"Clinical Infectious Diseases","year":2020,"id":66137,"datarank":0.5983476069846413,"base_score":3.9889840465642745,"endowment":3.9889840465642745,"self_citation_contribution":0.5983476069846413,"citation_network_contribution":0.0,"self_endowment_contribution":0.5983476069846413,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":53,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9495,"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":311284,"name":"Emanuel Krebs","orcid":"0000-0002-6590-8728","position":1,"is_corresponding":false},{"id":350504,"name":"Siyuan Chen","orcid":"0009-0001-8475-0305","position":2,"is_corresponding":false},{"id":352108,"name":"Micah Piske","orcid":null,"position":3,"is_corresponding":false},{"id":350505,"name":"Wendy S. Armstrong","orcid":"0000-0002-7316-2276","position":4,"is_corresponding":false},{"id":311286,"name":"Czarina N. Behrends","orcid":"0000-0003-3885-088X","position":5,"is_corresponding":false},{"id":294608,"name":"Carlos del Rı́o","orcid":"0000-0002-0153-3517","position":6,"is_corresponding":false},{"id":311288,"name":"Daniel J. Feaster","orcid":"0000-0002-6172-7460","position":7,"is_corresponding":false},{"id":270176,"name":"Brandon D. L. Marshall","orcid":"0000-0002-0134-7052","position":8,"is_corresponding":false},{"id":228276,"name":"Shruti H. Mehta","orcid":"0000-0002-2523-0959","position":9,"is_corresponding":false},{"id":350506,"name":"Jonathan Mermin","orcid":"0000-0001-9022-4961","position":10,"is_corresponding":false},{"id":284211,"name":"Lisa R. Metsch","orcid":"0000-0001-5966-3982","position":11,"is_corresponding":false},{"id":311290,"name":"Bruce R. Schackman","orcid":"0000-0002-1132-2932","position":12,"is_corresponding":false},{"id":301815,"name":"Steffanie A. Strathdee","orcid":"0000-0002-7724-691X","position":13,"is_corresponding":false},{"id":311282,"name":"Bohdan Nosyk","orcid":"0000-0003-2513-3718","position":14,"is_corresponding":false},{"id":352109,"name":"Localized HIV Modeling Study","orcid":null,"position":15,"is_corresponding":false},{"id":311287,"name":"Julia C. Dombrowski","orcid":"0000-0003-1907-9428","position":16,"is_corresponding":false},{"id":311291,"name":"Kelly A. Gebo","orcid":"0000-0003-4010-398X","position":17,"is_corresponding":false},{"id":240255,"name":"Gregory D. Kirk","orcid":"0000-0002-7829-1405","position":18,"is_corresponding":false},{"id":311292,"name":"Julio Montaner","orcid":"0000-0003-0217-6379","position":19,"is_corresponding":false},{"id":312983,"name":"Ankur Pandya","orcid":null,"position":20,"is_corresponding":false},{"id":299058,"name":"Steven Shoptaw","orcid":"0000-0002-3583-0026","position":21,"is_corresponding":false},{"id":311283,"name":"Xiao Zang","orcid":"0000-0002-5722-8255","position":0,"is_corresponding":true}],"reference_count":44,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-18T21:14:22.090509Z","pmid":"33045723","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":[]}