{"doi":"10.1093/pnasnexus/pgae564","title":"Modeling of randomized hepatitis C vaccine trials: Bridging the gap between controlled human infection models and real-word testing","abstract":"Global elimination of chronic hepatitis C (CHC) remains difficult without an effective vaccine. Since injection drug use is the leading cause of hepatitis C virus (HCV) transmission in Western Europe and North America, people who inject drugs (PWID) are an important population for testing HCV vaccine effectiveness in randomized-clinical trials (RCTs). However, RCTs in PWID are inherently challenging. To accelerate vaccine development, controlled human infection (CHI) models have been suggested as a means to identify effective vaccines. To bridge the gap between CHI models and real-world testing, we developed an agent-based model simulating a two-dose vaccine to prevent CHC in PWID, representing 32,000 PWID in metropolitan Chicago and accounting for networks and HCV infections. We ran 500 trial simulations under 50 and 75% assumed vaccine efficacy (aVE) and sampled HCV infection status of recruited in silico PWID. The mean estimated vaccine efficacy (eVE) for 50 and 75% aVE was 48% (SD ± 12) and 72% (SD ± 11), respectively. For both conditions, the majority of trials (∼71%) resulted in eVEs within 1 SD of the mean, demonstrating a robust trial design. Trials that resulted in eVEs >1 SD from the mean (lowest eVEs of 3 and 35% for 50 and 75% aVE, respectively), were more likely to have imbalances in acute infection rates across trial arms. Modeling indicates robust trial design and high success rates of finding vaccines to be effective in real-life trials in PWID. However, with less effective vaccines (aVEs∼50%) there remains a higher risk of concluding poor vaccine efficacy due to post-randomization imbalances.","journal":"PNAS Nexus","year":2024,"id":470187,"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":3,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9462,"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":774897,"name":"Alexander Gutfraind","orcid":"0000-0002-3324-2220","position":1,"is_corresponding":false},{"id":905062,"name":"Eric Tatara","orcid":"0000-0001-7927-4255","position":2,"is_corresponding":false},{"id":432510,"name":"Nicholson Collier","orcid":"0000-0002-2376-4156","position":3,"is_corresponding":false},{"id":326124,"name":"Scott J. Cotler","orcid":"0000-0003-2564-7786","position":4,"is_corresponding":false},{"id":430163,"name":"Kimberly Page","orcid":"0000-0002-7120-1673","position":5,"is_corresponding":false},{"id":381323,"name":"Jonathan Ozik","orcid":"0000-0002-3495-6735","position":6,"is_corresponding":false},{"id":453675,"name":"Basmattee Boodram","orcid":"0000-0002-3686-8894","position":7,"is_corresponding":false},{"id":669323,"name":"Marian Major","orcid":"0000-0003-0874-359X","position":8,"is_corresponding":false},{"id":280818,"name":"Harel Dahari","orcid":"0000-0002-3357-1817","position":9,"is_corresponding":false},{"id":449944,"name":"Mary Ellen Mackesy‐Amiti","orcid":"0000-0002-7238-5240","position":0,"is_corresponding":true}],"reference_count":36,"raw_metadata":null,"created_at":"2026-07-19T02:05:36.656771Z","pmid":"39777292","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":[]}