ArticleMathematical biosciences and engineering : MBE2021
Progression and transmission of HIV (PATH 4.0)-A new agent-based evolving network simulation for modeling HIV transmission clusters.
Article in Mathematical biosciences and engineering : MBE, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 11 citations in OpenAlex.
- Mechanistic modeling of social conditions in disease-prediction simulations via copulas and probabilistic graphical models: HIV case study.Health care management science · 2025Article
- A new mixed agent-based network and compartmental simulation framework for joint modeling of related infectious diseases- application to sexually transmitted infections.Infectious Disease Modelling · 2023Article
- Joint modeling HIV and HPV using a new hybrid agent-based network and compartmental simulation technique.PloS one · 2023Article
- Modeling nonlocal behavior in epidemics via a reaction-diffusion system incorporating population movement along a network.Computer methods in applied mechanics and engineering · 2022Article
- Agent-based evolving network modeling: a new simulation method for modeling low prevalence infectious diseases.Health care management science · 2021Article
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Authors and funding
6 authors at 3 institutions in 1 country.
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Abstract
We present the Progression and Transmission of HIV (PATH 4.0), a simulation tool for analyses of cluster detection and intervention strategies. Molecular clusters are groups of HIV infections that are genetically similar, indicating rapid HIV transmission where HIV prevention resources are needed to improve health outcomes and prevent new infections. PATH 4.0 was constructed using a newly developed agent-based evolving network modeling (ABENM) technique and evolving contact network algorithm (ECNA) for generating scale-free networks. ABENM and ECNA were developed to facilitate simulation of transmission networks for low-prevalence diseases, such as HIV, which creates computational challenges for current network simulation techniques. Simulating transmission networks is essential for studying network dynamics, including clusters. We validated PATH 4.0 by comparing simulated projections of HIV diagnoses with estimates from the National HIV Surveillance System (NHSS) for 2010-2017. We also applied a cluster generation algorithm to PATH 4.0 to estimate cluster features, including the distribution of persons with diagnosed HIV infection by cluster status and size and the size distribution of clusters. Simulated features matched well with NHSS estimates, which used molecular methods to detect clusters among HIV nucleotide sequences of persons with HIV diagnosed during 2015-2017. Cluster detection and response is a component of the U.S. Ending the HIV Epidemic strategy. While surveillance is critical for detecting clusters, a model in conjunction with surveillance can allow us to refine cluster detection methods, understand factors associated with cluster growth, and assess interventions to inform effective response strategies. As surveillance data are only available for cases that are diagnosed and reported, a model is a critical tool to understand the true size of clusters and assess key questions, such as the relative contributions of clusters to onward transmissions. We believe PATH 4.0 is the first modeling tool available to assess cluster detection and response at the national-level and could help inform the national strategic plan.
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