Assessing the effectiveness of HIV/STI risk communication displays among Melbourne Sexual Health Centre attendees: a cross-sectional, observational and vignette-based study.

INTRODUCTION: Increasing rates of sexually transmitted infections (STIs) over the past decade underscore the need for early testing and treatment. Communicating HIV/STI risk effectively can promote individuals' intention to test, which is critical for the prevention and control of HIV/STIs. We aimed to determine which visual displays of risk would be the most likely to increase testing or use of prevention strategies. METHODS: A vignette-based cross-sectional survey was conducted with 662 clients (a median age of 30 years (IQR: 25-36), 418 male, 203 female, 41 other genders) at a sexual health clinic in Melbourne, Australia, between February and June 2023. Participants viewed five distinct hypothetical formats, presented in a randomised order, designed to display the same level of high risk for HIV/STIs: icon array, colour-coded risk metre, colour-coded risk bar, detailed text report and guideline recommendation. They reported their perceived risk, concern and intent to test for each risk display. Associations between the format of the risk display and the intention to test for HIV/STI were analysed using logistic regression. RESULTS: About 378 (57%) of participants expressed that the risk metre was the easiest to understand. The risk metre (adjusted OR (AOR)=2.44, 95% CI=1.49 to 4.01) and risk bar (AOR=2.08, CI=1.33 to 3.27) showed the greatest likelihood of testing compared with the detailed text format. The icon array was less impactful (AOR=0.73, CI=0.57 to 0.94). The risk metre also elicited the most concern but was the most preferred and understood. High-risk perception and concern levels were strongly associated with their intention to have an HIV/STI test. CONCLUSIONS: Displaying risk differently affects an individual's perceived risk of an HIV/STI and influences their intention to test.

Using AI to Differentiate Mpox From Common Skin Lesions in a Sexual Health Clinic: Algorithm Development and Validation Study.

BACKGROUND: The 2022 global outbreak of mpox has significantly impacted health facilities, and necessitated additional infection prevention and control measures and alterations to clinic processes. Early identification of suspected mpox cases will assist in mitigating these impacts. OBJECTIVE: We aimed to develop and evaluate an artificial intelligence (AI)-based tool to differentiate mpox lesion images from other skin lesions seen in a sexual health clinic. METHODS: We used a data set with 2200 images, that included mpox and non-mpox lesions images, collected from Melbourne Sexual Health Centre and web resources. We adopted deep learning approaches which involved 6 different deep learning architectures to train our AI models. We subsequently evaluated the performance of each model using a hold-out data set and an external validation data set to determine the optimal model for differentiating between mpox and non-mpox lesions. RESULTS: The DenseNet-121 model outperformed other models with an overall area under the receiver operating characteristic curve (AUC) of 0.928, an accuracy of 0.848, a precision of 0.942, a recall of 0.742, and an F1-score of 0.834. Implementation of a region of interest approach significantly improved the performance of all models, with the AUC for the DenseNet-121 model increasing to 0.982. This approach resulted in an increase in the correct classification of mpox images from 79% (55/70) to 94% (66/70). The effectiveness of this approach was further validated by a visual analysis with gradient-weighted class activation mapping, demonstrating a reduction in false detection within the background of lesion images. On the external validation data set, ResNet-18 and DenseNet-121 achieved the highest performance. ResNet-18 achieved an AUC of 0.990 and an accuracy of 0.947, and DenseNet-121 achieved an AUC of 0.982 and an accuracy of 0.926. CONCLUSIONS: Our study demonstrated it was possible to use an AI-based image recognition algorithm to accurately differentiate between mpox and common skin lesions. Our findings provide a foundation for future investigations aimed at refining the algorithm and establishing the place of such technology in a sexual health clinic.

Modelling the Epidemiological Impact and Cost-Effectiveness of PrEP for HIV Transmission in MSM in China.

Risk of HIV infection is high in Chinese MSM, with an annual HIV incidence ranging from 3.41 to 13.7/100 person-years. Tenofovir-based PrEP is effective in preventing HIV transmission in MSM. This study evaluates the epidemiological impact and cost-effectiveness of implementing PrEP in Chinese MSM over the next two decades. A compartmental model for HIV was used to forecast the impact of PrEP on number of infections, deaths, and disability-adjusted life years (DALY) averted. We also provide an estimate of the incremental cost-effectiveness ratio (ICER) and the cost per DALY averted of the intervention. Without PrEP, there will be 1.1-3.0 million new infections and 0.7-2.3 million HIV-related deaths in the next two decades. Moderate PrEP coverage (50%) would prevent 0.17-0.32 million new HIV infections. At Truvada's current price in China, daily oral PrEP costs $46,813-52,008 per DALY averted and is not cost-effective; on-demand Truvada reduces ICER to $25,057-27,838 per DALY averted, marginally cost-effective; daily generic tenofovir-based regimens further reduce ICER to $3675-8963, wholly cost-effective. The cost of daily oral Truvada PrEP regimen would need to be reduced by half to achieve cost-effectiveness and realize the public health good of preventing hundreds of thousands of HIV infections among MSM in China.

Prevalence of human papillomavirus by geographical regions, sexual orientation and HIV status in China: a systematic review and meta-analysis.

OBJECTIVE: Human papillomavirus (HPV) infection causes multiple cancers in both women and men. In China, both HPV vaccination and cervical cancer screening coverages are low. We aim to investigate the temporal and geographical trends of HPV DNA prevalence in heterosexual men, women, men who have sex with men (MSM) and people living with HIV (PLHIV) in China. METHODS: We conducted a systematic review, collecting publications in PubMed, Web of Science, China National Knowledge Infrastructure (CNKI) and Wanfang Data from January 2000 to May 2017. A total of 247 studies were selected for this meta-analysis to estimate pooled HPV prevalence, incidence of cervical cancer and risk of infection for subgroups. Meta-regression was applied to identify contributing factors to prevalence heterogeneities. RESULTS: The national HPV prevalence was 15.6% (95% CI (14.4% to 16.9%)) in women with normal cervical cytology, and Central China had the highest prevalence (20.5% (15.2% to 25.8%)). HPV prevalence in heterosexual men (14.5% (11.3% to 17.7%)) was comparable with that of women (OR=1.09 (0.98 to 1.17)), but HPV prevalence in MSM (59.9% (52.2% to 67.6%)) was significantly higher than that in heterosexual men (OR=8.81 (8.01 to 9.69)). HIV-positive women (45.0% (38.4% to 51.6%)) and HIV-positive MSM (87.5% (82.3% to 90.9%)) had 4.67 (3.61 to 6.03) and 6.46 (5.20 to 8.02) times higher risk of HPV infection than their HIV negative counterparts. CONCLUSION: HPV infection is prevalent in China, particularly in Central China, in comparison with the global level and neighbouring countries. Targeted HPV vaccination for women, MSM and PLHIV and scale-up of cervical screening for women are priorities in curbing the HPV epidemic in China.

Clinical features-based machine learning models to separate sexually transmitted infections from other skin diagnoses.

INTRODUCTION: Many sexual health services are overwhelmed and cannot cater for all the individuals who present with sexually transmitted infections (STIs). Digital health software that separates STIs from non-STIs could improve the efficiency of clinical services. We developed and evaluated a machine learning model that predicts whether patients have an STI based on their clinical features. METHODS: We manually extracted 25 demographic features and clinical features from 1315 clinical records in the electronic health record system at Melbourne Sexual Health Center. We examined 16 machine learning models to predict a binary outcome of an STI or a non-STI diagnosis. We evaluated the models' performance with the area under the ROC curve (AUC), accuracy and F1-scores. RESULTS: Our study included 1315 consultations, of which 36.8% (484/1315) were diagnosed with STIs and 63.2% (831/1315) had non-STI conditions. The study population predominantly consisted of heterosexual men (49.5%, 651/1315), followed by gay, bisexual and other men who have sex with men (GBMSM) (25.7%), women (21.6%) and unknown gender (3.2%). The median age was 31 years (intra-quartile range (IQR) 26-39). The top 5 performing models were CatBoost (AUC 0.912), Random Forest (AUC 0.917), LightGBM (AUC 0.907), Gradient Boosting (AUC 0.905) and XGBoost (AUC 0.900). The best model, CatBoost, achieved an accuracy of 0.837, sensitivity of 0.776, specificity of 0.831, precision of 0.782 and F1-score of 0.778. The key important features were lesion duration, type of skin lesions, age, gender, history of skin disorders, number of lesions, dysuria duration, anorectal pain and itchiness. CONCLUSIONS: Our best model demonstrates a reasonable performance in distinguishing STIs from non-STIs. However, to be clinically useful, more detailed information such as clinical images, may be required to reach sufficient accuracy.

Should human papillomavirus vaccination target women over age 26, heterosexual men and men who have sex with men? A targeted literature review of cost-effectiveness.

BACKGROUND: Human papillomavirus (HPV) vaccination for young women up to age 26 is highly cost-effective and has been implemented in 65 countries globally. We investigate the cost-effectiveness for HPV vaccination program in older women (age > 26 years), heterosexual men and men who have sex with men (MSM). METHOD: A targeted literature review was conducted on PubMed for publications between January 2000 and January 2017 according to the PRISMA guidelines. We included English-language articles that reported the incremental cost-effectiveness ratio (ICER) of HPV vaccination programs for women over age 26, heterosexual men, and MSM and identified the underlying factors for its cost-effectiveness. RESULTS: We included 36 relevant articles (six, 26 and four in older women, heterosexual men and MSM, respectively) from 17 countries (12 high-income (HICs) and five low- and middle-income (LMICs) countries). Most (4/6) studies in women over age 26 did not show cost-effectiveness ($65,000-192,000/QALY gained). Two showed cost-effectiveness, but only when the vaccine cost was largely subsidised and protection to non-naïve women was also considered. Sixteen of 26 studies in heterosexual men were cost-effective (ICER = $19,600-52,800/QALY gained in HICs; $49-5,860/QALY gained in LMICs). Nonavalent vaccines, a low vaccine price, fewer required doses, and a long vaccine protection period were key drivers for cost-effectiveness. In contrast, all four studies on MSM consistently reported cost-effectiveness (ICER = $15,000-$43,000/QALY gained), particularly in MSM age < 40 years and those who were HIV-positive. Countries' vaccination coverage did not significantly correlate with its per-capita Gross National Income. CONCLUSION: Targeted HPV vaccination for MSM should be next priority in HPV prevention after having established a solid girls vaccination programme. Vaccination for heterosexual men should be considered when 2-dose 4vHPV/9vHPV vaccines become available with a reduced price, whereas targeted vaccination for women over age 26 is unlikely to be cost-effective.