Special Issue "HIV Molecular Epidemiology for Prevention"

A special issue of Viruses (ISSN 1999-4915). This special issue belongs to the section "Animal Viruses".

Deadline for manuscript submissions: 31 December 2019.

Special Issue Editors

Mr. William M. Switzer
E-Mail Website
Guest Editor
Laboratory Branch, Division of HIV/AIDS Prevention, National Center for HIV/AIDS, Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, USA
Tel. 404-639-0219; Fax: +1 404 639 0092
Interests: emerging retroviruses; zoonotic retrovirus infections; molecular epidemiology of retrovirus infections; retrovirus evolution; retrovirus diagnostics; phylodynamics; transmission networks; bioinformatics; HIV prevention
Dr. Dimitrios Paraskevis
E-Mail Website
Guest Editor
Department of Hygiene Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Greece
Interests: molecular epidemiology of viral infections; molecular epidemiology of HIV-1 and applications to public health; viral resistance; molecular diagnostics
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

The molecular epidemiology of infectious diseases is being transformed by the increasing availability of pathogen nucleotide sequence data from advances in sequencing technologies and their global availability. Molecular sequences combined with epidemiologic data are critical for understanding pathogen emergence, transmission histories, identifying reservoirs and new infections, preventing onward transmission, monitoring disease progression, and linking infected persons to treatment and care. In 2017, WHO estimates about 36.9 million people were living with HIV globally. Of those, almost 940,000 died from AIDS-related illnesses and approximately 75% were unaware of their HIV status. For HIV, drug resistance monitoring is the standard of care for new diagnoses, and testing is routinely available at commercial laboratories or frequently done for research studies. More recently, these HIV polymerase sequences are being used to identify persons with genetically similar strains, characterize transmission clusters and dynamics, and recognize clusters with rapid and active transmission, all of which permit focused public health interventions of limited resources to those persons and places with the highest risk of new infections. In the US, rapidly detecting and responding to clusters and outbreaks is a key pillar of the President’s 2019 intitiative “Ending the HIV Epidemic” in the next decade. This goal is consistent with the WHO target of ending the HIV/AIDS epidemic by 2030. Transmission clusters can be identified using network and phylogenetic analyses of molecular sequences, or combinations of both, and bioinformatics methods are used or being developed to determine timing of infection, time–space clusters, the prediction of cluster growth and spread, and the modeling of transmission dynamics and targeted prevention strategies.

This Special Issue aims to provide new insights and advances in the molecular epidemiology of HIV infection, including how molecular epidemiology is being used for surveillance, understanding transmission dynamics (patterns, order, and probability), the spread of HIV locally and globally, phylodynamics, outbreak and cluster detection, transmission networks, the use of partial and whole genomes, ultradeep sequencing for molecular epidemiology, transmitted drug resistance, and the modeling of transmission clusters and targeted prevention strategies. We cordially invite you to contribute original papers and review articles on these and related topics to highlight recent advances in molecular epidemiologic methods used to study HIV transmission and prevention.

Dr. William M. Switzer
Dr. Dimitrios Paraskevis
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Viruses is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • human immunodeficiency virus (HIV)
  • molecular epidemiology
  • transmission dynamics
  • transmission networks and clusters
  • cluster detection
  • phylogenetic analysis
  • phylodynamics
  • drug resistance testing
  • sequence analysis
  • subtypes
  • quasispecies
  • public health response
  • risk factors
  • persons who inject drugs
  • interventions
  • pre- and post-exposure prophylaxis
  • modeling
  • prevention and care
  • partner services
  • contact tracing
  • disease surveillance
  • co-infections
  • data integration and visualization
  • bioinformatics

Published Papers (1 paper)

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Research

Open AccessArticle
Combining Viral Genetics and Statistical Modeling to Improve HIV-1 Time-of-Infection Estimation towards Enhanced Vaccine Efficacy Assessment
Viruses 2019, 11(7), 607; https://doi.org/10.3390/v11070607 - 03 Jul 2019
Abstract
Knowledge of the time of HIV-1 infection and the multiplicity of viruses that establish HIV-1 infection is crucial for the in-depth analysis of clinical prevention efficacy trial outcomes. Better estimation methods would improve the ability to characterize immunological and genetic sequence correlates of [...] Read more.
Knowledge of the time of HIV-1 infection and the multiplicity of viruses that establish HIV-1 infection is crucial for the in-depth analysis of clinical prevention efficacy trial outcomes. Better estimation methods would improve the ability to characterize immunological and genetic sequence correlates of efficacy within preventive efficacy trials of HIV-1 vaccines and monoclonal antibodies. We developed new methods for infection timing and multiplicity estimation using maximum likelihood estimators that shift and scale (calibrate) estimates by fitting true infection times and founder virus multiplicities to a linear regression model with independent variables defined by data on HIV-1 sequences, viral load, diagnostics, and sequence alignment statistics. Using Poisson models of measured mutation counts and phylogenetic trees, we analyzed longitudinal HIV-1 sequence data together with diagnostic and viral load data from the RV217 and CAPRISA 002 acute HIV-1 infection cohort studies. We used leave-one-out cross validation to evaluate the prediction error of these calibrated estimators versus that of existing estimators and found that both infection time and founder multiplicity can be estimated with improved accuracy and precision by calibration. Calibration considerably improved all estimators of time since HIV-1 infection, in terms of reducing bias to near zero and reducing root mean squared error (RMSE) to 5–10 days for sequences collected 1–2 months after infection. The calibration of multiplicity assessments yielded strong improvements with accurate predictions (ROC-AUC above 0.85) in all cases. These results have not yet been validated on external data, and the best-fitting models are likely to be less robust than simpler models to variation in sequencing conditions. For all evaluated models, these results demonstrate the value of calibration for improved estimation of founder multiplicity and of time since HIV-1 infection. Full article
(This article belongs to the Special Issue HIV Molecular Epidemiology for Prevention)
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