Combining epidemiological and genetic networks signifies the importance of early treatment in HIV-1 transmission.

Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE

Original Publication: San Francisco, CA : Public Library of Science

Gene Regulatory Networks* ; Genes, Viral* ; Sexual Behavior* ; Social Support*; Anti-Retroviral Agents/*therapeutic use ; HIV Infections/*drug therapy ; HIV-1/*genetics; Adult ; Antiretroviral Therapy, Highly Active ; Cohort Studies ; Female ; HIV Infections/epidemiology ; HIV Infections/transmission ; HIV Infections/virology ; Heterosexuality ; Homosexuality ; Humans ; Italy/epidemiology ; Male ; Middle Aged ; Time Factors ; Viral Load

Inferring disease transmission networks is important in epidemiology in order to understand and prevent the spread of infectious diseases. Reconstruction of the infection transmission networks requires insight into viral genome data as well as social interactions. For the HIV-1 epidemic, current research either uses genetic information of patients' virus to infer the past infection events or uses statistics of sexual interactions to model the network structure of viral spreading. Methods for a reliable reconstruction of HIV-1 transmission dynamics, taking into account both molecular and societal data are still lacking. The aim of this study is to combine information from both genetic and epidemiological scales to characterize and analyse a transmission network of the HIV-1 epidemic in central Italy.We introduce a novel filter-reduction method to build a network of HIV infected patients based on their social and treatment information. The network is then combined with a genetic network, to infer a hypothetical infection transmission network. We apply this method to a cohort study of HIV-1 infected patients in central Italy and find that patients who are highly connected in the network have longer untreated infection periods. We also find that the network structures for homosexual males and heterosexual populations are heterogeneous, consisting of a majority of 'peripheral nodes' that have only a few sexual interactions and a minority of 'hub nodes' that have many sexual interactions. Inferring HIV-1 transmission networks using this novel combined approach reveals remarkable correlations between high out-degree individuals and longer untreated infection periods. These findings signify the importance of early treatment and support the potential benefit of wide population screening, management of early diagnoses and anticipated antiretroviral treatment to prevent viral transmission and spread. The approach presented here for reconstructing HIV-1 transmission networks can have important repercussions in the design of intervention strategies for disease control.

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0 (Anti-Retroviral Agents)

Date Created: 20121003 Date Completed: 20130221 Latest Revision: 20211021

20240628

PMC3460924

10.1371/journal.pone.0046156

23029421