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Enregistrement W1910255447 · doi:10.1016/j.ebiom.2015.08.039

HIV Phylogeographic Analyses and Their Application in Prevention and Early Detection Programmes: The Case of the Tijuana–San Diego Border Region

2015· letter· en· W1910255447 sur OpenAlexaboutno aff
Santiago Ávila‐Ríos, Gustavo Reyes‐Terán

Notice bibliographique

RevueEBioMedicine · 2015
Typeletter
Langueen
DomaineImmunology and Microbiology
ThématiqueHIV Research and Treatment
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésLatin AmericansMedicineHuman immunodeficiency virus (HIV)GeographyGerontologyEnvironmental healthFamily medicinePolitical science

Résumé

récupéré en direct d'OpenAlex

As the deadline for the UNAIDS 90–90–90 target approaches, huge challenges in HIV diagnosis, access to treatment and follow up have become evident. This initiative aims to have 90% of people living with HIV diagnosed, 90% of diagnosed people receiving antiretroviral therapy (ART) and 90% of people receiving ART under viral suppression by 2020 (http://www.unaids.org/sites/default/files/media_asset/90-90-90_UNAIDS. 90–90–90: An ambitious treatment target to help end the AIDS epidemic. http://www.unaids.org/sites/default/files/media_asset/90-90-90_en_0.pdf. Accessed August, 2015.Google Scholar). In this regard, huge improvements have been made on ART programmes around the world, especially in resource-limited settings. Nevertheless, identifying new and undiagnosed HIV infections is an important issue in large areas of the world where stigmatization and ignorance towards HIV infection and its transmission routes still prevail. This is the case of most Latin American countries, which generally present concentrated epidemics with a wide variety of epidemiological scenarios, most of which are characterized by late presentation of individuals living with HIV to clinical care (Crabtree-Ramirez et al., 2011Crabtree-Ramirez B. Caro-Vega Y. Shepherd B.E. et al.Cross-sectional analysis of late HAART initiation in Latin America and the Caribbean: late testers and late presenters.PLoS One. 2011; 6e20272Crossref PubMed Scopus (61) Google Scholar). In Mexico, a middle-income country with a strong ART programme, it is estimated that more than half of HIV-infected individuals are unaware of their serologic status (http://www.censida.salud.gob.mx/descargas/2009/VIHSIDAenMexico2CENSIDA. El VIH/SIDA en México 2009. http://www.censida.salud.gob.mx/descargas/2009/VIHSIDAenMexico2009.pdf. Accessed August, 2015.Google Scholar). Cases like this render ART programmes alone unable to control the epidemics and constitute a major challenge for the ambitious 90–90–90 target to become a reality. Knowledge on HIV transmission dynamics is needed in order to focus and strengthen prevention and early detection programmes, urgently needed in Latin America. In recent years, HIV phylogenetic and phylogeographic analyses have been ever more recognized as a fundamental tool for studying HIV transmission dynamics, which can result in the generation of public health policies improving HIV prevention programmes (Grabowski and Redd, Mar 2014Grabowski M.K. Redd A.D. Molecular tools for studying HIV transmission in sexual networks.Curr. Opin. HIV AIDS. Mar 2014; 9: 126-133Crossref PubMed Scopus (66) Google Scholar). Phylogenetic and clustering analyses can provide useful information on clinical and demographic factors shaping HIV transmission in specific geographic areas, and when geographic data is available, can identify the specific location and spread of HIV transmission hotspots. Large multinational efforts such as PANGEA-HIV (Pillay et al., Mar 2015Pillay D. Herbeck J. Cohen M.S. et al.PANGEA-HIV: phylogenetics for generalised epidemics in Africa.Lancet Infect. Dis. Mar 2015; 15: 259-261Summary Full Text Full Text PDF PubMed Scopus (40) Google Scholar) have been created to use viral sequence data to assess transmission of HIV in the context of generalized epidemics. Moreover, recent studies have demonstrated the possibility of identifying HIV transmission hotspots in near real time by the secondary phylogenetic analysis of HIV sequences obtained for routine drug resistance testing in concentrated epidemics with a high sampling density (Poon et al., 2015Poon A.F. Joy J.B. Woods C.K. et al.The impact of clinical, demographic and risk factors on rates of HIV transmission: a population-based phylogenetic analysis in British Columbia, Canada.J. Infect. Dis. 2015; 211 (Mar 15): 926-935Crossref PubMed Scopus (79) Google Scholar). In this issue of E-Biomedicine, Mehta et al. (Mehta et al., 2015Mehta S.R. Wertheim J.O. Brouwer K.C. et al.HIV transmission networks in the San Diego-Tijuana border region.EBioMedicine. 2015; 2: 1456-1463Summary Full Text Full Text PDF PubMed Scopus (41) Google Scholar) present a phylogeographic study to assess the characteristics of HIV transmission in the Tijuana–San Diego crossing of the Mexico–U.S. border region. This work is a good example of how phylogenetic and phylogeographic analyses on already existing HIV sequence data can provide useful information on HIV transmission dynamics in an especially complex HIV transmission hotspot. The Tijuana–San Diego border is probably the busiest land border crossing in the world, characterized by a large transnational commercial sex network, a large population of people who inject drugs (PWID), and a large population of men who have sex with men (MSM) (Strathdee et al., 2012Strathdee S.A. Magis-Rodriguez C. Mays V.M. Jimenez R. Patterson T.L. The emerging HIV epidemic on the Mexico-U.S. border: an international case study characterizing the role of epidemiology in surveillance and response.Ann. Epidemiol. 2012; 22 (Jun): 426-438Crossref PubMed Scopus (90) Google Scholar). The prostitution district in Tijuana is frequented by thousands of U.S. and foreign tourists each year and this region geographically overlaps with a neighbourhood known for its high density of PWID. Risk behaviour for HIV acquisition is high in the border region and is strongly associated with economic disparities, with a high frequency of male clients negotiating condom-less sex with female sex workers (FSW), who accept higher rates for unprotected sex out of economic necessity and are also often PWID (Strathdee et al., 2012Strathdee S.A. Magis-Rodriguez C. Mays V.M. Jimenez R. Patterson T.L. The emerging HIV epidemic on the Mexico-U.S. border: an international case study characterizing the role of epidemiology in surveillance and response.Ann. Epidemiol. 2012; 22 (Jun): 426-438Crossref PubMed Scopus (90) Google Scholar, Martinez-Donate et al., 2015Martinez-Donate A.P. Hovell M.F. Rangel M.G. et al.Migrants in transit: the importance of monitoring HIV risk among migrant flows at the Mexico-US border.Am. J. Public Health. 2015; 105 (Mar): 497-509Crossref PubMed Scopus (34) Google Scholar, Robertson et al., 2014Robertson A.M. Syvertsen J.L. Ulibarri M.D. Rangel M.G. Martinez G. Strathdee S.A. Prevalence and correlates of HIV and sexually transmitted infections among female sex workers and their non-commercial male partners in two Mexico-USA border cities.J. Urban Health. 2014; 91 (Aug): 752-767Crossref PubMed Scopus (22) Google Scholar). In their study, Mehta et al. describe the epidemics in Tijuana and San Diego as highly separated, the last one dominated by MSM clusters. Nevertheless, the authors identified bidirectional mixed international clusters including FSW, PWID and MSM, describing this border region as a “melting pot” of risk groups. International clusters had higher proportion of females, heterosexuals and PWID, highlighting the importance of commercial sex in HIV transmission across the border and pointing areas of opportunity for prevention interventions. Moreover, albeit with considerable overlap in both directions, a shift in viral migration from Tijuana to San Diego was observed comparing 2014 to the 1990s, when the opposite was true. It is important to mention that even with a relatively low sampling density, clusters providing useful epidemiological information were found yielding useful conclusions to inform public health policies. Also, the lack of male individuals in clusters including FSW is also informative as it underscores the need to focus detection efforts in their customers and partners. Following WHO recommendations to implement HIV drug resistance (DR) surveillance in the region, many Latin American countries are making efforts to implement HIVDR surveys nationally, with the support of WHO-accredited national and regional laboratories. Thus, even with an important limitation in sequencing capacity, generation of HIV sequence data linked to basic socio-demo-geographic data is expected to grow significantly in the next few years. These data could also be used in phylogenetic and transmission network analysis to inform HIV transmission dynamics in the region, always with a cautious interpretation due to sampling limitations. Eventually, these data could improve targeting of prevention and early detection efforts to place this region of the world closer to the 90–90–90 target in 2020. The authors declare no conflicts of interest. HIV Transmission Networks in the San Diego–Tijuana Border RegionThis study sampled ~7% of HIV infected individuals in the border region, and although the sampled networks on each side of the border were largely separate, there was evidence of persistent bidirectional cross-border transmissions that linked risk groups, thus highlighting the importance of the border region as a “melting pot” of risk groups. Full-Text PDF Open Access

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,709
Score d'incertitude au seuil0,371

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,025
Tête enseignante GPT0,316
Écart entre enseignants0,291 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2015
Routes d'admission1
Résumé présentoui

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