{"doi":"10.21203/rs.3.rs-1220584/v1","title":"Evaluating the sensitivity of jurisdictional-heterogeneity and jurisdictional-mixing in national-level HIV prevention analyses: Context of the U.S. Ending the HIV Epidemic goal.","abstract":"Abstract Background : The U.S. Ending the HIV epidemic (EHE) plan aims to reduce annual HIV incidence by 90% by 2030, by first focusing interventions on 57 jurisdictions (county or state) (EHE-jurisdictions) that contributed to more than 50% of annual HIV diagnoses. Mathematical models that simulate future HIV incidence projections help evaluate the impact of interventions and inform intervention decisions. However, current models are either national-level, which do not consider jurisdictional-heterogeneity, or independent jurisdiction-specific, which do not consider cross jurisdictional interactions. Data suggests that significant proportion of persons have sexual-partnerships with persons outside their own jurisdiction. However, the sensitivity of these jurisdictional interactions on model outcomes and intervention decisions have not been studied. Methods : We developed a compartmental simulation of HIV in the U.S., through composition of 57 EHE and 46 non-EHE jurisdictions, with populations interacting across jurisdictions through sexual partnerships. To evaluate sensitivity of jurisdictional interactions on model outputs, we analyzed 16 scenarios, combinations of proportion of sexual-partnerships mixing outside jurisdiction: no-mixing, low-level-mixing-within-state, high-level-mixing-within-state, or high-level-mixing-within-and-outside-state; jurisdictional-heterogeneity in care and demographics: homogenous or heterogeneous; and intervention assumptions for 2019-2030: baseline or EHE-plan (diagnose, treat, and prevent). Results : Change in incidence in mixing compared to no-mixing scenarios varied by EHE and non-EHE jurisdictions and aggregation-level. When assuming jurisdictional-heterogeneity and baseline-intervention, while the change in aggregated incidence ranged from -2% to 0% for EHE and 5% to 21% for non-EHE, within each jurisdiction it ranged from -31% to 46% for EHE and -18% to 109% for non-EHE. Thus, incidence estimates were sensitive to jurisdictional-mixing more at the jurisdictional-level. As a result, jurisdiction-specific HIV-testing intervals inferred from the model to achieve the EHE-plan were also sensitive, e.g., when no-mixing scenarios suggested testing every 1 year (or 3 years), the three mixing-levels suggested testing every 0.8 to 1.2 years, 0.6 to 1.5 years, and 0.6 to 1.5 years, respectively (or 2.6 to 3.5 years, 2 to 4.8 years, and 2.2 to 4.1 years, respectively). Similar patterns were observed when assuming jurisdictional-homogeneity, however, change in incidence in mixing compared to no-mixing scenarios were high even in aggregated incidence. Conclusions : Accounting for jurisdictional-mixing and jurisdictional-heterogeneity could help improve model-based analyses.","journal":"Research Square","year":2022,"id":305686,"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":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9296,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":718439,"name":"Chaitra Gopalappa","orcid":"0000-0001-8384-6041","position":1,"is_corresponding":false},{"id":974893,"name":"Hanisha Tatapudi","orcid":"0000-0001-6184-9719","position":0,"is_corresponding":true}],"reference_count":19,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T00:32:44.983506Z","pmid":null,"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":[]}