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HIV Molecular Epidemiology for Prevention

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

Deadline for manuscript submissions: closed (31 December 2019) | Viewed by 37755

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Mr. William M. M. Switzer

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Laboratory Branch, Division of HIV/AIDS Prevention, National Center for HIV/AIDS, Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA
Interests: emerging retroviruses; zoonotic retrovirus infections; molecular epidemiology of retrovirus infections; retrovirus evolution; retrovirus diagnostics; phylodynamics; transmission networks; bioinformatics; HIV prevention
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Dr. Dimitrios Paraskevis

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Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, 115 27 Athens, Greece
Interests: virology; AIDS/HIV; STIs; hepatitis; molecular epidemiology
Special Issues, Collections and Topics 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 submissions that pass pre-check are 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 2600 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

Related Special Issues

HIV Molecular Epidemiology for Prevention 2020 in Viruses (16 articles)
HIV Molecular Epidemiology for Prevention 2023 in Viruses

Published Papers (11 papers)

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15 pages, 1049 KiB

Open AccessArticle

Phylodynamics Helps to Evaluate the Impact of an HIV Prevention Intervention

by Tetyana I. Vasylyeva, Alexander Zarebski, Pavlo Smyrnov, Leslie D. Williams, Ania Korobchuk, Mariia Liulchuk, Viktoriia Zadorozhna, Georgios Nikolopoulos, Dimitrios Paraskevis, John Schneider, Britt Skaathun, Angelos Hatzakis, Oliver G. Pybus and Samuel R. Friedman

Viruses 2020, 12(4), 469; https://0-doi-org.brum.beds.ac.uk/10.3390/v12040469 - 20 Apr 2020

Cited by 13 | Viewed by 3132

Abstract

Assessment of the long-term population-level effects of HIV interventions is an ongoing public health challenge. Following the implementation of a Transmission Reduction Intervention Project (TRIP) in Odessa, Ukraine, in 2013–2016, we obtained HIV pol gene sequences and used phylogenetics to identify HIV transmission clusters. We further applied the birth-death skyline model to the sequences from Odessa (n = 275) and Kyiv (n = 92) in order to estimate changes in the epidemic’s effective reproductive number (R_e) and rate of becoming uninfectious (δ). We identified 12 transmission clusters in Odessa; phylogenetic clustering was correlated with younger age and higher average viral load at the time of sampling. Estimated R_e were similar in Odessa and Kyiv before the initiation of TRIP; R_e started to decline in 2013 and is now below R_e = 1 in Odessa (R_e = 0.4, 95%HPD 0.06–0.75), but not in Kyiv (R_e = 2.3, 95%HPD 0.2–5.4). Similarly, estimates of δ increased in Odessa after the initiation of TRIP. Given that both cities shared the same HIV prevention programs in 2013–2019, apart from TRIP, the observed changes in transmission parameters are likely attributable to the TRIP intervention. We propose that molecular epidemiology analysis can be used as a post-intervention effectiveness assessment tool. Full article

(This article belongs to the Special Issue HIV Molecular Epidemiology for Prevention)

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18 pages, 1535 KiB

Open AccessArticle

Molecular Epidemiology of the HIV-1 Subtype B Sub-Epidemic in Bulgaria

by Ivailo Alexiev, Ellsworth M. Campbell, Sergey Knyazev, Yi Pan, Lyubomira Grigorova, Reneta Dimitrova, Aleksandra Partsuneva, Anna Gancheva, Asya Kostadinova, Carole Seguin-Devaux and William M. Switzer

Viruses 2020, 12(4), 441; https://0-doi-org.brum.beds.ac.uk/10.3390/v12040441 - 14 Apr 2020

Cited by 7 | Viewed by 2723

Abstract

HIV-1 subtype B is the predominant strain in Bulgaria, yet little is known about the molecular epidemiology of these infections, including its origin and transmissibility. We used a phylodynamics approach by combining and analyzing 663 HIV-1 polymerase (pol) sequences collected from persons diagnosed with HIV/AIDS between 1988–2018 and associated epidemiologic data to better understand this sub-epidemic in Bulgaria. Using network analyses at a 1.5% genetic distance threshold (d) we found several large phylogenetic clusters composed mostly of men who have sex with men (MSM) and male heterosexuals (HET). However, at d = 0.5%, used to identify more recent transmission, the largest clusters dissociated to become smaller in size. The majority of female HET and persons with other transmission risks were singletons or pairs in the network. Phylogenetic analysis of the Bulgarian pol sequences with publicly available global sequences showed that subtype B was likely introduced into Bulgaria from multiple countries, including Israel and several European countries. Our findings indicate that subtype B was introduced into Bulgaria multiple times since 1988 and then infections rapidly spread among MSM and non-disclosed MSM. These high-risk behaviors continue to spread subtype B infection in Bulgaria as evidenced by the large clusters at d = 0.5%. Relatively low levels of antiretroviral drug resistance were observed in our study. Prevention strategies should continue to include increased testing and linkage to care and treatment, as well as expanded outreach to the MSM communities. Full article

(This article belongs to the Special Issue HIV Molecular Epidemiology for Prevention)

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21 pages, 4009 KiB

Open AccessArticle

Phylogenetic and Demographic Characterization of Directed HIV-1 Transmission Using Deep Sequences from High-Risk and General Population Cohorts/Groups in Uganda

by Nicholas Bbosa, Deogratius Ssemwanga, Alfred Ssekagiri, Xiaoyue Xi, Yunia Mayanja, Ubaldo Bahemuka, Janet Seeley, Deenan Pillay, Lucie Abeler-Dörner, Tanya Golubchik, Christophe Fraser, Pontiano Kaleebu, Oliver Ratmann and on behalf of the MRC/UVRI & LSHTM Uganda Research Unit and The PANGEA Consortium

Viruses 2020, 12(3), 331; https://0-doi-org.brum.beds.ac.uk/10.3390/v12030331 - 18 Mar 2020

Cited by 13 | Viewed by 4608

Abstract

Across sub-Saharan Africa, key populations with elevated HIV-1 incidence and/or prevalence have been identified, but their contribution to disease spread remains unclear. We performed viral deep-sequence phylogenetic analyses to quantify transmission dynamics between the general population (GP), fisherfolk communities (FF), and women at high risk of infection and their clients (WHR) in central and southwestern Uganda. Between August 2014 and August 2017, 6185 HIV-1 positive individuals were enrolled in 3 GP and 10 FF communities, 3 WHR enrollment sites. A total of 2531 antiretroviral therapy (ART) naïve participants with plasma viral load >1000 copies/mL were deep-sequenced. One hundred and twenty-three transmission networks were reconstructed, including 105 phylogenetically highly supported source–recipient pairs. Only one pair involved a WHR and male participant, suggesting that improved population sampling is needed to assess empirically the role of WHR to the transmission dynamics. More transmissions were observed from the GP communities to FF communities than vice versa, with an estimated flow ratio of 1.56 (95% CrI 0.68–3.72), indicating that fishing communities on Lake Victoria are not a net source of transmission flow to neighboring communities further inland. Men contributed disproportionally to HIV-1 transmission flow regardless of age, suggesting that prevention efforts need to better aid men to engage with and stay in care. Full article

(This article belongs to the Special Issue HIV Molecular Epidemiology for Prevention)

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15 pages, 4530 KiB

Open AccessArticle

Molecular Epidemiology of HIV-1 Infected Migrants Followed Up in Portugal: Trends between 2001–2017

by Victor Pimentel, Marta Pingarilho, Daniela Alves, Isabel Diogo, Sandra Fernandes, Mafalda Miranda, Andrea-Clemencia Pineda-Peña, Pieter Libin, M. Rosário O. Martins, Anne-Mieke Vandamme, Ricardo Camacho, Perpétua Gomes and Ana Abecasis

Viruses 2020, 12(3), 268; https://0-doi-org.brum.beds.ac.uk/10.3390/v12030268 - 28 Feb 2020

Cited by 12 | Viewed by 3911

Abstract

Migration is associated with HIV-1 vulnerability. Objectives: To identify long-term trends in HIV-1 molecular epidemiology and antiretroviral drug resistance (ARV) among migrants followed up in Portugal Methods: 5177 patients were included between 2001 and 2017. Rega, Scuel, Comet, and jPHMM algorithms were used for subtyping. Transmitted drug resistance (TDR) and Acquired drug resistance (ADR) were defined as the presence of surveillance drug resistance mutations (SDRMs) and as mutations of the IAS-USA 2015 algorithm, respectively. Statistical analyses were performed. Results: HIV-1 subtypes infecting migrants were consistent with the ones prevailing in their countries of origin. Over time, overall TDR significantly increased and specifically for Non-nucleoside reverse transcriptase inhibitor (NNRTIs) and Nucleoside reverse transcriptase inhibitor (NRTIs). TDR was higher in patients from Mozambique. Country of origin Mozambique and subtype B were independently associated with TDR. Overall, ADR significantly decreased over time and specifically for NRTIs and Protease Inhibitors (PIs). Age, subtype B, and viral load were independently associated with ADR. Conclusions: HIV-1 molecular epidemiology in migrants suggests high levels of connectivity with their country of origin. The increasing levels of TDR in migrants could indicate an increase also in their countries of origin, where more efficient surveillance should occur. Full article

(This article belongs to the Special Issue HIV Molecular Epidemiology for Prevention)

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13 pages, 3969 KiB

Open AccessArticle

In Search of Covariates of HIV-1 Subtype B Spread in the United States—A Cautionary Tale of Large-Scale Bayesian Phylogeography

by Samuel L. Hong, Simon Dellicour, Bram Vrancken, Marc A. Suchard, Michael T. Pyne, David R. Hillyard, Philippe Lemey and Guy Baele

Viruses 2020, 12(2), 182; https://0-doi-org.brum.beds.ac.uk/10.3390/v12020182 - 05 Feb 2020

Cited by 12 | Viewed by 3614

Abstract

Infections with HIV-1 group M subtype B viruses account for the majority of the HIV epidemic in the Western world. Phylogeographic studies have placed the introduction of subtype B in the United States in New York around 1970, where it grew into a major source of spread. Currently, it is estimated that over one million people are living with HIV in the US and that most are infected with subtype B variants. Here, we aim to identify the drivers of HIV-1 subtype B dispersal in the United States by analyzing a collection of 23,588 pol sequences, collected for drug resistance testing from 45 states during 2004–2011. To this end, we introduce a workflow to reduce this large collection of data to more computationally-manageable sample sizes and apply the BEAST framework to test which covariates associate with the spread of HIV-1 across state borders. Our results show that we are able to consistently identify certain predictors of spread under reasonable run times across datasets of up to 10,000 sequences. However, the general lack of phylogenetic structure and the high uncertainty associated with HIV trees make it difficult to interpret the epidemiological relevance of the drivers of spread we are able to identify. While the workflow we present here could be applied to other virus datasets of a similar scale, the characteristic star-like shape of HIV-1 phylogenies poses a serious obstacle to reconstructing a detailed evolutionary and spatial history for HIV-1 subtype B in the US. Full article

(This article belongs to the Special Issue HIV Molecular Epidemiology for Prevention)

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13 pages, 5835 KiB

Open AccessArticle

Phylodynamic Analysis Complements Partner Services by Identifying Acute and Unreported HIV Transmission

by Ellsworth M. Campbell, Anne Patala, Anupama Shankar, Jin-Fen Li, Jeffrey A. Johnson, Emily Westheimer, Cynthia L. Gay, Stephanie E. Cohen, William M. Switzer and Philip J. Peters

Viruses 2020, 12(2), 145; https://0-doi-org.brum.beds.ac.uk/10.3390/v12020145 - 27 Jan 2020

Cited by 13 | Viewed by 2586

Abstract

Tailoring public health responses to growing HIV transmission clusters depends on accurately mapping the risk network through which it spreads and identifying acute infections that represent the leading edge of cluster growth. HIV transmission links, especially those involving persons with acute HIV infection (AHI), can be difficult to uncover, or confirm during partner services investigations. We integrated molecular, epidemiologic, serologic and behavioral data to infer and evaluate transmission linkages between participants of a prospective study of AHI conducted in North Carolina, New York City and San Francisco from 2011–2013. Among the 547 participants with newly diagnosed HIV with polymerase sequences, 465 sex partners were reported, of whom only 35 (7.5%) had HIV sequences. Among these 35 contacts, 23 (65.7%) links were genetically supported and 12 (34.3%) were not. Only five links were reported between participants with AHI but none were genetically supported. In contrast, phylodynamic inference identified 102 unreported transmission links, including 12 between persons with AHI. Importantly, all putative transmission links between persons with AHI were found among large clusters with more than five members. Taken together, the presence of putative links between acute participants who did not name each other as contacts that are found only among large clusters underscores the potential for unobserved or undiagnosed intermediaries. Phylodynamics identified many more links than partner services alone and, if routinely and rapidly integrated, can illuminate transmission patterns not readily captured by partner services investigations. Full article

(This article belongs to the Special Issue HIV Molecular Epidemiology for Prevention)

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12 pages, 336 KiB

Open AccessArticle

Characterization of Molecular Cluster Detection and Evaluation of Cluster Investigation Criteria Using Machine Learning Methods and Statewide Surveillance Data in Washington State

by Steven J. Erly, Joshua T. Herbeck, Roxanne P. Kerani and Jennifer R. Reuer

Viruses 2020, 12(2), 142; https://0-doi-org.brum.beds.ac.uk/10.3390/v12020142 - 26 Jan 2020

Cited by 8 | Viewed by 2293

Abstract

Molecular cluster detection can be used to interrupt HIV transmission but is dependent on identifying clusters where transmission is likely. We characterized molecular cluster detection in Washington State, evaluated the current cluster investigation criteria, and developed a criterion using machine learning. The population living with HIV (PLWH) in Washington State, those with an analyzable genotype sequences, and those in clusters were described across demographic characteristics from 2015 to2018. The relationship between 3- and 12-month cluster growth and demographic, clinical, and temporal predictors were described, and a random forest model was fit using data from 2016 to 2017. The ability of this model to identify clusters with future transmission was compared to Centers for Disease Control and Prevention (CDC) and the Washington state criteria in 2018. The population with a genotype was similar to all PLWH, but people in a cluster were disproportionately white, male, and men who have sex with men. The clusters selected for investigation by the random forest model grew on average 2.3 cases (95% CI 1.1–1.4) in 3 months, which was not significantly larger than the CDC criteria (2.0 cases, 95% CI 0.5–3.4). Disparities in the cases analyzed suggest that molecular cluster detection may not benefit all populations. Jurisdictions should use auxiliary data sources for prediction or continue using established investigation criteria. Full article

(This article belongs to the Special Issue HIV Molecular Epidemiology for Prevention)

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22 pages, 2715 KiB

Open AccessArticle

HIV-1 Unique Recombinant Forms Identified in Slovenia and Their Characterization by Near Full-Length Genome Sequencing

by Maja M. Lunar, Jana Mlakar, Tomaž Mark Zorec and Mario Poljak

Viruses 2020, 12(1), 63; https://0-doi-org.brum.beds.ac.uk/10.3390/v12010063 - 03 Jan 2020

Cited by 7 | Viewed by 2927

Abstract

Surveillance of HIV circulating recombinant forms (CRFs) is important because HIV diversity can affect various aspects of HIV infection from prevention to diagnosis and patient management. A comprehensive collection of pol sequences obtained from individuals diagnosed with HIV-1 from 2000 to 2016 in Slovenia was subtyped to identify possible unique recombinant forms (URFs). Selected samples were subjected to near full-length genome (NFLG) sequencing and detailed recombination analyses. Discordant subtyping results were observed for 68/387 (17.6%) sequences and 20 sequences were identified as the most probable URFs and selected for NFLG characterization. Further, 11 NFLGs and two sequences of >7000 base pairs were obtained. Seven sequences were identified as “pure” subtypes or already characterized CRFs: subtype B (n = 5), sub-subtype A6 (n = 1), and CRF01_AE (n = 1). The remaining six sequences were determined to be URFs; four displayed a single recombination event and two exhibited a complex recombination pattern involving several subtypes or CRFs. Finally, three HIV strains were recognized as having epidemic potential and could be further characterized as new CRFs. Our study shows that the identification of new CRFs is possible, even in countries where HIV diversity is considered limited, emphasizing the importance of the surveillance of HIV recombinant forms. Full article

(This article belongs to the Special Issue HIV Molecular Epidemiology for Prevention)

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13 pages, 965 KiB

Open AccessArticle

Exploring HIV-1 Transmission Dynamics by Combining Phylogenetic Analysis and Infection Timing

by Chris Verhofstede, Virginie Mortier, Kenny Dauwe, Steven Callens, Jessika Deblonde, Géraldine Dessilly, Marie-Luce Delforge, Katrien Fransen, André Sasse, Karolien Stoffels, Dominique Van Beckhoven, Fien Vanroye, Dolores Vaira, Ellen Vancutsem and Kristel Van Laethem

Viruses 2019, 11(12), 1096; https://0-doi-org.brum.beds.ac.uk/10.3390/v11121096 - 26 Nov 2019

Cited by 7 | Viewed by 3075

Abstract

HIV-1 pol sequences obtained through baseline drug resistance testing of patients newly diagnosed between 2013 and 2017 were analyzed for genetic similarity. For 927 patients the information on genetic similarity was combined with demographic data and with information on the recency of infection. Overall, 48.3% of the patients were genetically linked with 11.4% belonging to a pair and 36.9% involved in a cluster of ≥3 members. The percentage of early diagnosed (≤4 months after infection) was 28.6%. Patients of Belgian origin were more frequently involved in transmission clusters (49.7% compared to 15.3%) and diagnosed earlier (37.4% compared to 12.2%) than patients of Sub-Saharan African origin. Of the infections reported to be locally acquired, 69.5% were linked (14.1% paired and 55.4% in a cluster). Equal parts of early and late diagnosed individuals (59.9% and 52.4%, respectively) were involved in clusters. The identification of a genetically linked individual for the majority of locally infected patients suggests a high rate of diagnosis in this population. Diagnosis however is often delayed for >4 months after infection increasing the opportunities for onward transmission. Prevention of local infection should focus on earlier diagnosis and protection of the still uninfected members of sexual networks with human immunodeficiency virus (HIV)-infected members. Full article

(This article belongs to the Special Issue HIV Molecular Epidemiology for Prevention)

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23 pages, 844 KiB

Open AccessArticle

Combining Viral Genetics and Statistical Modeling to Improve HIV-1 Time-of-Infection Estimation towards Enhanced Vaccine Efficacy Assessment

by Raabya Rossenkhan, Morgane Rolland, Jan P.L. Labuschagne, Roux-Cil Ferreira, Craig A. Magaret, Lindsay N. Carpp, Frederick A. Matsen IV, Yunda Huang, Erika E. Rudnicki, Yuanyuan Zhang, Nonkululeko Ndabambi, Murray Logan, Ted Holzman, Melissa-Rose Abrahams, Colin Anthony, Sodsai Tovanabutra, Christopher Warth, Gordon Botha, David Matten, Sorachai Nitayaphan, Hannah Kibuuka, Fred K. Sawe, Denis Chopera, Leigh Anne Eller, Simon Travers, Merlin L. Robb, Carolyn Williamson, Peter B. Gilbert and Paul T. Edlefsen Show full author list Hide full author list

Viruses 2019, 11(7), 607; https://0-doi-org.brum.beds.ac.uk/10.3390/v11070607 - 03 Jul 2019

Cited by 10 | Viewed by 4624

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 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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10 pages, 214 KiB

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The Impact of Human Mobility on Regional and Global Efforts to Control HIV Transmission

by Emily A. Eshraghian, Sepideh N. Ferdos and Sanjay R. Mehta

Viruses 2020, 12(1), 67; https://0-doi-org.brum.beds.ac.uk/10.3390/v12010067 - 06 Jan 2020

Cited by 12 | Viewed by 3168

Abstract

HIV prevention and control methods are implemented on different scales to reduce the spread of the virus amongst populations. However, despite such efforts, HIV continues to persist in populations with a global incidence rate of 1.8 million in 2017 alone. The introduction of new infections into susceptible regional populations promotes the spread of HIV, indicating a crucial need to study the impact of migration and mobility on regional and global efforts to prevent HIV transmission. Here we reviewed studies that assess the impact of human mobility on HIV transmission and spread. We found an important role for both travel and migration in driving the spread of HIV across regional and national borders. Combined, our results indicate that even in the presence of control and preventive efforts, if migration and travel are occurring, public health efforts will need to remain persistent to ensure that new infections do not grow into outbreaks. Full article

(This article belongs to the Special Issue HIV Molecular Epidemiology for Prevention)

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