Model-Based Predictions of HIV Incidence Among African Women Using HIV Risk Behaviors and Community-Level Data on Male HIV Prevalence and Viral Suppression.
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ABSTRACT: Background
Pre-exposure prophylaxis (PrEP) with tenofovir disoproxil fumarate and emtricitabine has proven highly effective in preventing HIV acquisition and is therefore offered to all participants in the control group as part of the standard of care package in many new HIV prevention studies. We propose a methodology for predicting HIV incidence in a hypothetical "placebo arm" for open-label studies or clinical trials with active control among African women. We apply the method to an open-label PrEP study, HIV Prevention Trials Network 082, which tested strategies to improve PrEP adherence in young African women all of whom were offered PrEP.Methods
Our model predicted HIV infection risk for female study cohorts in sub-Saharan Africa using baseline behavioral risk factors and contemporary HIV prevalence and viral suppression in the local male population. The model was calibrated to HIV incidence in the Vaginal and Oral Interventions to Control the Epidemic study.Results
Our model reproduced the annual HIV incidence of 3.2%-4.8% observed over 1 year of follow-up in the placebo groups of 4 completed clinical studies. We predicted an annual HIV incidence of 3.7% (95% confidence interval: 3.2 to 4.2) among HIV Prevention Trials Network 082 participants in the absence of PrEP and other risk reduction interventions.Conclusions
We demonstrated the potential of the proposed methodology to provide HIV incidence predictions based on assessment of individual risk behaviors and community and time-specific HIV exposure risk using HIV treatment and viral suppression data. These estimates may serve as comparators in HIV prevention trials without a placebo group.
SUBMITTER: Moore JR
PROVIDER: S-EPMC7670079 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundPopulation-level estimates of disease prevalence and control are needed to assess prevention and treatment strategies. However, available data often suffer from differential missingness. For example, population-level HIV viral suppression is the proportion of all HIV-positive persons with suppressed viral replication. Individuals with measured HIV status, and among HIV-positive individuals those with measured viral suppression, likely differ from those without such measurements.MethodsWe discuss three sets of assumptions to identify population-level suppression in the intervention arm of the SEARCH Study (NCT01864603), a community randomized trial in rural Kenya and Uganda (2013-2017). Using data on nearly 100,000 participants, we compare estimates from (1) an unadjusted approach assuming data are missing-completely-at-random (MCAR); (2) stratification on age group, sex, and community; and (3) targeted maximum likelihood estimation to adjust for a larger set of baseline and time-updated variables.ResultsDespite high measurement coverage, estimates of population-level viral suppression varied by identification assumption. Unadjusted estimates were most optimistic: 50% (95% confidence interval [CI] = 46%, 54%) of HIV-positive persons suppressed at baseline, 80% (95% CI = 78%, 82%) at year 1, 85% (95% CI = 83%, 86%) at year 2, and 85% (95% CI = 83%, 87%) at year 3. Stratifying on baseline predictors yielded slightly lower estimates, and full adjustment reduced estimates meaningfully: 42% (95% CI = 37%, 46%) of HIV-positive persons suppressed at baseline, 71% (95% CI = 69%, 73%) at year 1, 76% (95% CI = 74%, 78%) at year 2, and 79% (95% CI = 77%, 81%) at year 3.ConclusionsEstimation of population-level disease burden and control requires appropriate adjustment for missing data. Even in large studies with limited missingness, estimates relying on the MCAR assumption or baseline stratification should be interpreted cautiously.
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Project description:OBJECTIVE:HIV infection in sub-Saharan Africa increasingly occurs among people who inject drugs (PWID). Kenya is one of the first to implement a national needle and syringe program. Our study undertook a baseline assessment as part of evaluating needle and syringe program in a seek, test, treat, and retain approach. METHODS:Participants enrolled between May and December 2012 from 10 sites. Respondent-driven sampling was used to reach 1785 PWID for HIV-1 prevalence and viral load determination and survey data. RESULTS:Estimated HIV prevalence, adjusted for differential network size and recruitment relationships, was 14.5% in Nairobi (95% CI: 10.8 to 18.2) and 20.5% in the Coast region (95% CI: 17.3 to 23.6). Viral load (log10 transformed) in Nairobi ranged from 1.71 to 6.12 (median: 4.41; interquartile range: 3.51-4.94) and in the Coast from 1.71 to 5.88 (median: 4.01; interquartile range: 3.44-4.72). Using log10 viral load 2.6 as a threshold for HIV viral suppression, the percentage of HIV-infected participants with viral suppression was 4.2% in Nairobi and 4.6% in the Coast. Heroin was the most commonly injected drug in both regions, used by 93% of participants in the past month, typically injecting 2-3 times/day. Receptive needle/syringe sharing at last injection was more common in Nairobi (23%) than in the Coast (4%). Estimated incidence among new injectors was 2.5/100 person-years in Nairobi and 1.6/100 person-years in the Coast. CONCLUSIONS:The HIV epidemic is well established among PWID in both Nairobi and Coast regions. Public health scale implementation of combination HIV prevention has the potential to greatly limit the epidemic in this vulnerable and bridging population.
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Project description:BackgroundAmong men who have sex with men, there is now clear evidence that the risk of HIV transmission through condomless sex when the HIV-positive partner is virally suppressed is effectively zero. However, an understanding of the accuracy of reporting of viral load among serodiscordant same-sex male couples is missing from the literature.SettingThis analysis uses data from the baseline sample of Stronger Together, a randomized controlled efficacy trial of an innovative dyadic intervention to enhance antiretroviral therapy adherence for HIV serodiscordant male couples in 3 US cities (Atlanta, Boston, and Chicago).MethodsBiomarker-confirmed and self-reported measures of viral load were used to assess the accuracy of self-report of viral suppression. In this descriptive analysis, the percentage of men who inaccurately reported being virally suppressed is compared across demographic, relationship, and HIV care characteristics.ResultsResults confirm those of other recent studies that have shown relatively high levels of inaccuracy in reporting of viral suppression. Although 72.5% of men could accurately report their viral load status, 20% reported that they were virally suppressed when they did not have a biomarker-confirmed measure of viral suppression.ConclusionThese results highlight the need to provide interventions to men who have sex with men living with HIV to support access to care and ensure current knowledge of viral load and to continue to support primary prevention of HIV through condom use and pre-exposure prophylaxis. For couples, particularly serodiscordant male couples, interventions that can teach the couple how to collaborate to achieve and maintain viral suppression for the positive partner are an urgent and pragmatic programmatic priority that can equip couples with the knowledge required to correctly implement U = U strategies.
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Project description:BackgroundViral suppression in patients on antiretroviral treatment (ART) is critical to reducing HIV transmission and HIV-related mortality. Although many studies have evaluated factors associated with viral suppression, few have assessed the extent to which missing viral load data may bias results.MethodsWe included data on all patients starting ART from 2005 to 2019 in eight South African cohorts participating in the International epidemiology Databases to Evaluate AIDS (IeDEA) collaboration. Multivariable logistic regression models were used to determine factors associated with having a viral load measurement within 2 months of a scheduled testing date and having a viral load <400 RNA copies/ml ('viral suppression'). In a sensitivity analysis, missing viral loads were imputed based on patients' clinical and demographic characteristics and outcomes.ResultsViral load tests were scheduled in 603,549 and 77,423 intervals in adults and children, respectively, but test results were recorded in only 40.7% and 41.2%, respectively. The proportion of recorded results suppressed was 85.7% in adults and 72.4% in children. After imputation of missing viral load measurements, viral suppression reduced slightly in adults (85.3%) and increased in children (73.2%). Predictors of virological suppression in adults, which included female sex, older age, higher baseline CD4+ T-cell count and recent testing year, were similar in the main analysis and after imputing missing viral loads.ConclusionsAlthough viral load information was frequently missing in the South African setting, estimates of viral suppression and predictors of viral suppression did not change substantially after adjusting for missing data.
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Project description:Monitoring HIV population viral load (PVL) has been advocated as an important means of inferring HIV transmission potential and predicting the future rate of new HIV infections (HIV incidence) in a particular community. However, the relationship between PVL measures and directly measured HIV incidence has not been quantified in any setting and, most importantly, in a hyperendemic sub-Saharan African setting. We assessed this relationship using one of Africa's largest population-based prospective population cohorts in rural KwaZulu-Natal, South Africa in which we followed 8732 HIV-uninfected participants between 2011 and 2015. Despite clear evidence of spatial clustering of high viral loads in some communities, our results demonstrate that PVL metrics derived from aggregation of viral load data only from the HIV-positive members of a particular community did not predict HIV incidence in this typical hyperendemic, rural African population. Only once we used modified PVL measures, which combined viral load information with the underlying spatial variation in the proportion of the population infected (HIV prevalence), did we find a consistently strong relationship with future risk of HIV acquisition. For example, every 1% increase in the overall proportion of a population having detectable virus (PDV P ) was independently associated with a 6.3% increase in an individual's risk of HIV acquisition (P = 0.001). In hyperendemic African populations, these modified PVL indices could play a key role in targeting and monitoring interventions in the most vulnerable communities where the future rate of new HIV infections is likely to be highest.
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Project description:Cervicovaginal microbiota not dominated by lactobacilli may facilitate transmission of HIV and other sexually transmitted infections (STIs), as well as miscarriages, preterm births and sepsis in pregnant women. However, little is known about the exact nature of the microbiological changes that cause these adverse outcomes. In this study, cervical samples of 174 Rwandan female sex workers were analyzed cross-sectionally using a phylogenetic microarray. Furthermore, HIV-1 RNA concentrations were measured in cervicovaginal lavages of 58 HIV-positive women among them. We identified six microbiome clusters, representing a gradient from low semi-quantitative abundance and diversity dominated by Lactobacillus crispatus (cluster R-I, with R denoting 'Rwanda') and L. iners (R-II) to intermediate (R-V) and high abundance and diversity (R-III, R-IV and R-VI) dominated by a mixture of anaerobes, including Gardnerella, Atopobium and Prevotella species. Women in cluster R-I were less likely to have HIV (P=0.03), herpes simplex virus type 2 (HSV-2; P<0.01), and high-risk human papillomavirus (HPV; P<0.01) and had no bacterial STIs (P=0.15). Statistically significant trends in prevalence of viral STIs were found from low prevalence in cluster R-I, to higher prevalence in clusters R-II and R-V, and highest prevalence in clusters R-III/R-IV/R-VI. Furthermore, only 10% of HIV-positive women in clusters R-I/R-II, compared with 40% in cluster R-V, and 42% in clusters R-III/R-IV/R-VI had detectable cervicovaginal HIV-1 RNA (Ptrend=0.03). We conclude that L. crispatus-dominated, and to a lesser extent L. iners-dominated, cervicovaginal microbiota are associated with a lower prevalence of HIV/STIs and a lower likelihood of genital HIV-1 RNA shedding.
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Project description:BackgroundThe suppression of viremia among persons with HIV (PWH) using antiretroviral therapy has been hypothesized to reduce HIV incidence at the population level. We investigated the impact of state level viral suppression among PWH in the United States on estimated HIV incidence between 2010 and 2015.MethodsViral suppression data and HIV incidence estimates from the National HIV Surveillance System were available from 29 states and the District of Columbia. We assumed a one year delay for viral suppression to impact incidence. Poisson regression models were used to calculate the estimated annual percent change (EAPC) in incidence rate. We employed a multivariable mixed-effects Poisson regression model to assess the effects of state level race/ethnicity, socioeconomic status, percent men who have sex with men (MSM) and hepatitis C virus prevalence as a proxy for injection drug use on HIV incidence.FindingsFitted HIV incidence for 30 jurisdictions declined from 11.5 in 2010 to 10.0 per 100,000 population by 2015 corresponding with an EAPC of -2.67 (95% confidence interval [95%CI] -2.95, -2.38). Southern states experienced the highest estimated incidence by far throughout this period but upon adjustment for viral suppression and demographics there was a 36% lower incidence rate than Northeast states (adjusted rate ratio [aRR] 0.64; 95%CI 0.42, 0.99). For every 10 percentage point (pp) increase in viral suppression there was an adjusted 4% decline in HIV incidence rate in the subsequent year (aRR 0.96; 95%CI 0.93, 0.99). While controlling for viral suppression, HIV incidence rate increased by 42% (aRR 1.42 95%CI 1.31, 1.54) for every 5 pp increase in percent Black race and by 27% (aRR 1.27 95%CI 1.10, 1.48) for every 1 pp increase in percent MSM in states.InterpretationA decline in estimated HIV incidence from 2010 to 2015 was associated with increasing viral suppression in the United States. Race and sexual orientation were important HIV acquisition risk factors.
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Project description:In order to prevent and/or control infections it is necessary to understand their early-time dynamics. However this is precisely the phase of HIV about which the least is known. To investigate the initial stages of HIV infection within a host we have developed a multi-type, continuous-time branching process model. This model is a stochastic extension of the standard viral dynamics model, under the assumption that the number of cell targets for viral infection is constant, biologically reasonable since, during the earliest stages of HIV infection, very few cells are infected relative to their total population size. We use our model to investigate three important clinical characteristics of early HIV infection following intravenous challenge: risk of infection, time to infection clearance (assuming failed infection), and time to infection detection. Our focus is on the impact of errors in viral replication that result in non-infectious virus production on these characteristics. Only a small fraction of circulating virus in any chronically infected individual is capable of infecting susceptible cells: estimates range from 1/104 - 1/103. Characterization and quantification of the processes by which virus becomes defective remains incomplete. We consider two mechanisms that result in defective virus: (1) Copying errors, i.e., lethal errors in reverse transcription, which introduce mutations into the HIV-1 proviral genome, some of which may cripple the viral genome produced, and (2) Packaging errors, i.e., errors during viral packaging, at the end of the viral replication cycle, which cause defective virus by packaging new virions without, for example, viral RNA or key proteins required for infectivity. We show that assumptions on mechanisms of defective virus production can significantly impact early HIV infection model predictions. For example, the risk of infection is orders of magnitude higher if all defective virus is associated with packaging errors, but infection is predicted to be detectable sooner following HIV exposure if all defective virus is associated with copying errors. Thus, in order to make reliable predictions of risk, clearance time, and detection time, better characterization of viral replication is required.
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Project description:HIV treatment programs face challenges in identifying patients at risk for loss-to-follow-up and uncontrolled viremia. We applied predictive machine learning algorithms to anonymised, patient-level HIV programmatic data from two districts in South Africa, 2016-2018. We developed patient risk scores for two outcomes: (1) visit attendance ≤ 28 days of the next scheduled clinic visit and (2) suppression of the next HIV viral load (VL). Demographic, clinical, behavioral and laboratory data were investigated in multiple models as predictor variables of attending the next scheduled visit and VL results at the next test. Three classification algorithms (logistical regression, random forest and AdaBoost) were evaluated for building predictive models. Data were randomly sampled on a 70/30 split into a training and test set. The training set included a balanced set of positive and negative examples from which the classification algorithm could learn. The predictor variable data from the unseen test set were given to the model, and each predicted outcome was scored against known outcomes. Finally, we estimated performance metrics for each model in terms of sensitivity, specificity, positive and negative predictive value and area under the curve (AUC). In total, 445,636 patients were included in the retention model and 363,977 in the VL model. The predictive metric (AUC) ranged from 0.69 for attendance at the next scheduled visit to 0.76 for VL suppression, suggesting that the model correctly classified whether a scheduled visit would be attended in 2 of 3 patients and whether the VL result at the next test would be suppressed in approximately 3 of 4 patients. Variables that were important predictors of both outcomes included prior late visits, number of prior VL tests, time since their last visit, number of visits on their current regimen, age, and treatment duration. For retention, the number of visits at the current facility and the details of the next appointment date were also predictors, while for VL suppression, other predictors included the range of the previous VL value. Machine learning can identify HIV patients at risk for disengagement and unsuppressed VL. Predictive modeling can improve the targeting of interventions through differentiated models of care before patients disengage from treatment programmes, increasing cost-effectiveness and improving patient outcomes.
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Project description:ObjectivesTo determine clinic-level and individual-level correlates of viral suppression among HIV-positive adolescents and young adult (AYA) aged 10-24 years receiving antiretroviral treatment (ART).DesignMultilevel cross-sectional analysis using viral load data and facility surveys from HIV treatment programs throughout Kenya.MethodsWe abstracted medical records of AYA in HIV care, analyzed the subset on ART for more than 6 months between January 2016 and December 2017, and collected information on services at each clinic. Multilevel logistic regression models were used to determine correlates of viral suppression at most recent assessment.ResultsIn 99 HIV clinics, among 10 096 AYA on ART more than 6 months, 2683 (27%) had unsuppressed viral load at last test. Among 16% of clinics, more than 80% of AYA were virally suppressed. Clinic-level correlates of individual viral suppression included designated adolescent spaces [aOR: 1.32, 95% CI (1.07-1.63)] and faster viral load turnaround time [aOR: 1.06 (95% CI 1.03-1.09)]. Adjusting for clinic-level factors, AYA aged 10-14 and 15-19 years had lower odds of viral suppression compared with AYA aged 20-24 years [aOR: 0.61 (0.54-0.69) and 0.59 (0.52-0.67], respectively. Compared with female patients, male patients had lower odds of viral suppression [aOR: 0.69 (0.62-0.77)]. Compared with ART duration of 6-12 months, ART for 2-5, above 5-10 or more than 10 years was associated with poor viral suppression (P < 0.001).ConclusionDedicated adolescent space, rapid viral load turnaround time, and tailored approaches for male individuals and perinatally infected AYA may improve viral suppression. Routine summarization of viral load suppression in clinics could provide benchmarking to motivate innovations in clinic-AYA and individual-AYA care strategies.
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