ArticleInfection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases2018
Intelligent Network DisRuption Analysis (INDRA): A targeted strategy for efficient interruption of hepatitis C transmissions.
Article in Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 18 citations in OpenAlex.
- Leveraging injection networks to prevent HIV and other blood borne infections among people who inject drugs in Kenya: design and rationale.BMC infectious diseases · 2025Article
- Genomic surveillance uncovers regional variation in HCV transmission networks in rural United States.Nature communications · 2025Article
- Strategies and Opportunities to Improve Community Health through Advanced Molecular Detection and Genomic Surveillance of Infectious Diseases.Emerging infectious diseases · 2025Article
- Network-based strategies to combat HCV: Examining social and spatial drivers of transmission among PWID in New Delhi.Journal of viral hepatitis · 2024Article
- SOPHIE: Viral outbreak investigation and transmission history reconstruction in a joint phylogenetic and network theory framework.Cell systems · 2022Article
- Primary case inference in viral outbreaks through analysis of intra-host variant population.BMC bioinformatics · 2022Article
- Article
- Hepatitis C Virus Transmission Clusters in Public Health and Correctional Settings, Wisconsin, USA, 2016-2017Emerging infectious diseases · 2021Article
- A review of network simulation models of hepatitis C virus and HIV among people who inject drugs.The International journal on drug policy · 2021Review
- Using machine learning methods to determine a typology of patients with HIV-HCV infection to be treated with antivirals.PloS one · 2020Observational
- A latent class approach to identify multi-risk profiles associated with phylogenetic clustering of recent hepatitis C virus infection in Australia and New Zealand from 2004 to 2015.Journal of the International AIDS Society · 2019Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Hepatitis C virus (HCV) infection is a global public health problem. The implementation of public health interventions (PHI) to control HCV infection could effectively interrupt HCV transmission. PHI targeting high-risk populations, e.g., people who inject drugs (PWID), are most efficient but there is a lack of tools for prioritizing individuals within a high-risk community. Here, we present Intelligent Network DisRuption Analysis (INDRA), a targeted strategy for efficient interruption of hepatitis C transmissions.Using a large HCV transmission network among PWID in Indiana as an example, we compare effectiveness of random and targeted strategies in reducing the rate of HCV transmission in two settings: (1) long-established and (2) rapidly spreading infections (outbreak). Identification of high centrality for the network nodes co-infected with HIV or > 1 HCV subtype indicates that the network structure properly represents the underlying contacts among PWID relevant to the transmission of these infections. Changes in the network's global efficiency (GE) were used as a measure of the PHI effects. In setting 1, simulation experiments showed that a 50% GE reduction can be achieved by removing 11.2 times less nodes using targeted vs random strategies. A greater effect of targeted strategies on GE was consistently observed when networks were simulated: (1) with a varying degree of errors in node sampling and link assignment, and (2) at different levels of transmission reduction at affected nodes. In simulations considering a 10% removal of infected nodes, targeted strategies were ~2.8 times more effective than random in reducing incidence. Peer-education intervention (PEI) was modeled as a probabilistic distribution of actionable knowledge of safe injection practices from the affected node to adjacent nodes in the network. Addition of PEI to the models resulted in a 2-3 times greater reduction in incidence than from direct PHI alone. In setting 2, however, random direct PHI were ~3.2 times more effective in reducing incidence at the simulated conditions. Nevertheless, addition of PEI resulted in a ~1.7-fold greater efficiency of targeted PHI. In conclusion, targeted PHI facilitated by INDRA outperforms random strategies in decreasing circulation of long-established infections. Network-based PEI may amplify effects of PHI on incidence reduction in both settings.
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