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Enregistrement W2553889324 · doi:10.1097/qad.0000000000001261

Response to diversification of risk-reduction strategies and reduced threat of HIV may explain increases in condomless sex

2016· letter· en· W2553889324 sur OpenAlexaboutno aff
Gabriela Paz‐Bailey, Cyprian Wejnert, Maria C.B. Mendoza, Joseph Prejean

Notice bibliographique

RevueAIDS · 2016
Typeletter
Langueen
DomaineMedicine
ThématiqueHIV/AIDS Research and Interventions
Établissements canadiensnon disponible
Organismes subventionnairesNational Institutes of Health
Mots-clésSerodiscordantSerostatusDemographyMen who have sex with menPsychologyHuman immunodeficiency virus (HIV)Safer sexSocial psychologyMedicineCondomAntiretroviral therapySociologyImmunologyViral load

Résumé

récupéré en direct d'OpenAlex

We appreciate the correspondence by Kippax and Holt [1] regarding explanations for the increases in condomless sex. We agree that there may have been changes in social norms due to the effectiveness of antiretroviral therapy (ART) that are not captured by our survey. Furthermore, the measures we used for seroadaptive behaviors were based on participants’ last sex act and do not reflect the complexities of negotiations for safer sex throughout a partnership. However, we disagree with Kippax and Holt [1] who propose that the predominance of concordant condomless sex in the survey suggests an increase in seroadaptive strategies. The percentage of condomless sex partnerships that was concordant does not increase over time. Further, seroadaptive behaviors are predicated on engaging in different sexual practices according to whether partners are HIV seroconcordant or serodiscordant. The important question is not whether concordant condomless sex is more likely than discordant condomless, as suggested by Kippax and Holt [1], but whether concordant condomless sex is more likely than would be expected by chance alone. If men are consciously choosing partners of the same serostatus, there should be more positive–positive and negative–negative partnerships than would occur by chance according to the marginal probabilities dictated by HIV prevalence and the number of partnerships in our sample. Using a Z test, we compared observed and expected percentages of concordant partnerships. Among MSM reporting condomless sex at last sex using all years combined, 15% were HIV-positive, 76% were HIV-negative, and 9% had unknown HIV status. We used this distribution to compute the expected frequencies of concordant condomless sex partnerships. Among condomless sex partnerships at last sex, 52% were HIV-negative concordant and 9% were HIV-positive concordant. We found evidence suggesting that HIV-negative MSM are not serosorting; they report concordant partners less frequently than what would be expected through random mixing when they engage in condomless anal sex (52% observed vs. 57% expected, P < 0.001), possibly due to insufficient information about their partners’ HIV status. In contrast, our data suggest that HIV-positive MSM may be purposely serosorting when they engage in condomless sex (9% observed vs. 2% expected, P < 0.001). Therefore, although we found evidence to suggest that HIV-positive MSM may be serosorting, the preponderance of concordant partnerships among HIV-negative MSM is not beyond what would be expected through random mixing. As Kippax and Holt [1] note, the diversification and promotion of behavioral and biomedical prevention strategies makes exclusive condom use less likely among MSM. However, having more prevention strategies available for MSM than before does not mean that MSM at highest risk are accessing them. For example, the National HIV Behavioral Surveillance data have shown that only 4% of MSM were using preexposure prophylaxis (PrEP) in 2014 [2]. PrEP use, although low, was higher among white compared with black MSM and among those with greater education and income. Young, black MSM, despite being at higher risk, were less likely to have a PrEP indication compared with young MSM of other races/ethnicities. Kippax and Holt [1] suggest that social norms around condom use have changed due to greater optimism around HIV treatment and prevention, our concern is that the declines in condom use leave a prevention gap that is not bridged at the same pace by PrEP or treatment as prevention. Furthermore, seroadaptive behaviors can only lower risk in the context of disclosure and accurate knowledge of HIV status. As noted by the authors for Australia, similar increases in condomless sex have been reported in other places including Montreal [3], London [4], Glasgow, Edinburg and Scotland [5], Amsterdam [6,7], Denmark [8], and Paris [9]. Mathematical modeling suggests that increases in HIV incidence in the United Kingdom, over a period in which ART coverage and viral suppression are also increasing, is likely due to the countereffect of concomitant increases in condomless sex among MSM [4,10–12]. Modeling work from the Netherlands reached similar conclusions suggesting that the reductions in HIV incidence due to ART and earlier HIV diagnosis have been entirely offset by risk behavior increases among MSM [13]. These findings show that modest increases in condomless sex are enough to negate the preventive benefits of ART, highlighting the vulnerability of any new prevention initiative, such as ART initiation at HIV diagnosis, if it leads to increases in condomless sex [10]. Despite the advances in prevention, key challenges keep many MSM from accessing needed services, including lack of accurate knowledge of HIV status (their own and their partner's), lack of information about HIV risk and prevention, misperceptions regarding personal risk, lack of health insurance, and inadequate health services. As no single strategy provides complete real-world protection, multiple approaches are needed to reduce new HIV infections. Acknowledgements Funding was provided by the Centers for Disease Control and Prevention. Previous presentations of these data: Portions of these data were presented at the Conference on Retroviruses and Opportunistic Infections, Seattle, Georgia, USA, 23–26 February 2015. Conflicts of interest There are no conflicts of interest.

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)0,001
score de la tête « metaresearch » (Gemma)0,001
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 enseignants0,455
Score d'incertitude au seuil0,481

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
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 Opus0,032
Tête enseignante GPT0,328
Écart entre enseignants0,297 · 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

Citations3
Publié2016
Routes d'admission1
Résumé présentoui

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