The Impacts of the COVID-19 Pandemic on HIV Testing Utilization Among Men Who Have Sex With Men in China: Cross-sectional Online Survey
Notice bibliographique
Résumé
BACKGROUND: The COVID-19 pandemic has created disruptions in HIV prevention and sexual health services for men who have sex with men (MSM). OBJECTIVE: This study compared HIV testing utilization in 3 different reference periods (period 1: before the COVID-19 outbreak, November 2019-January 2020; period 2: after the outbreak, February-April 2020; and period 3: after the pandemic was under initial control, May-July 2020). Factors associated with HIV testing utilization after the COVID-19 outbreak (combined periods 2 and 3) were also investigated. METHODS: Participants were MSM aged ≥18 years living in Shenzhen, China. Those self-reporting as HIV positive were excluded. A total of 595 participants recruited through multiple sources completed a self-administered online survey during August-September 2020. HIV testing utilization after the COVID-19 outbreak was the dependent variable, and multivariate logistic regression models were fitted. RESULTS: HIV testing utilization was significantly lower in period 2 than in period 1 (n=262 vs 363, 44.0% vs 61.0%, P<.001). However, HIV testing utilization was not significantly higher in period 3 than in period 2 (n=277 vs 262, 46.6% vs 44.0%, P=.21). The prevalence of HIV testing utilization after the COVID-19 outbreak was seen in 331 (55.6%) participants. After adjusting for significant background characteristics, condomless anal intercourse (CAI) with regular male sex partners (RPs; adjusted odds ratio [AOR] 2.15, 95% CI 1.29-3.57) and sexualized drug use (SDU; AOR 2.94, 95% CI 1.41-6.06) both before and after the COVID-19 outbreak, CAI with RPs (AOR 2.07, 95% CI 1.06-4.07) and nonregular male sex partners (NRPs; AOR 3.57, 95%CI: 1.43-8.89) only after the COVID-19 outbreak was positively associated with the dependent variable. Regarding HIV prevention service utilization, HIV testing utilization before the COVID-19 outbreak (AOR 10.75, 95% CI 7.22-16.02) and the use of sexually transmitted infection (STI) testing (AOR 7.02, 95% CI 4.10-12.02), other HIV/STI prevention (AOR 3.15, 95% CI 2.16-4.60), and preexposure prophylaxis (PrEP; AOR 3.58, 95% CI 1.54-8.34) after the COVID-19 outbreak were associated with higher HIV testing utilization. The current perceived risk of HIV infection was higher than that before the COVID-19 outbreak (AOR 1.15, 95% CI 1.01-1.30), and perceived COVID-19 preventive measures taken by HIV testing service providers to be effective (AOR 1.52, 95% CI 1.29-1.78) and perceived higher behavioral control to undergo HIV testing (AOR 1.18, 95% CI 1.00-1.40) were positively associated with HIV testing utilization. Concerns about COVID-19 infection during HIV testing (AOR 0.78, 95% CI 0.68-0.89), avoiding crowded places (AOR 0.68, 95% CI 0.48-0.98), and HIV testing service providers reducing their working hours (AOR 0.59, 95% CI 0.48-0.98) were negatively associated with the dependent variable. CONCLUSIONS: HIV testing utilization among Chinese MSM declined after the COVID-19 outbreak and did not increase after the pandemic was under initial control. Removing structural barriers to accessing HIV testing caused by COVID-19, modifying perceptions related to HIV testing, and making use of HIV self-testing (HIVST) might be useful strategies to improve HIV testing among MSM during the pandemic.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».