Laura Balzer

A hybrid mobile approach for population-wide HIV testing in rural east Africa: an observational study

Background Despite large investments in HIV testing, only 45% of HIV-infected persons in sub-Saharan Africa are estimated to know their status. Optimal methods for maximizing population-level testing remain unknown. We sought to demonstrate the effectiveness at achieving population-wide testing coverage of a hybrid mobile HIV testing approach. Methods From 2013–2014, we enumerated 168,772 adult (≥15 years) residents of 32 communities in Uganda (N=20), and Kenya (N=12) using a door-to-door census. “Stable” residence was defined as living in community for ≥6 months over the past year. In each community we performed 2-week multi-disease community health campaigns (CHC) that included HIV testing, counseling, and referral to care if HIV-infected; CHC non-participants were approached for home-based testing (HBT) over 1–2 months. We determined population HIV testing coverage, and predictors of testing via HBT (vs. CHC) and non-testing. Findings HIV testing was achieved in 89% of stable adult residents (131,307/146,906). HIV prevalence was 9.6% (13,043/136,033 stable and non-stable adults); median CD4+ T-cell count was 514 cells/μL (IQR: 355–703). Among stable adults tested, 43% (56,106/131,307) reported no prior testing. Among HIV-infected adults, 38% (4,932/13,043) were unaware of their status. Among stable CHC attendees, 99.5% (104,635/105,170) accepted HIV testing. Of stable adults tested, 80% (104,635/131,307, range: 60–93%) tested via CHCs. In multivariable analyses of stable adults, predictors of non-testing included male gender (risk ratio [RR]: 1.52, 95% CI: 1.48–1.56), single marital status (RR: 1.70, 95% CI: 1.66–1.75), Kenyan residence (RR: 1.46, 95% CI: 1.41–1.50, vs. Ugandan), and out-of-community migration for ≥1 month in past year (RR: 1.60, 95% CI: 1.53–1.68). Testing was more common among farmers (RR: 0.73, 95% CI: 0.67–0.79) and adults with primary education (RR: 0.84, 95% CI: 0.80–0.89). Interpretation High HIV testing coverage was achieved in rural Ugandan and Kenyan communities using a hybrid, mobile approach of multi-disease CHCs followed by HBT. This approach allowed for flexibility at the community and individual level in reaching testing coverage goals. Men and mobile populations remain challenges for universal testing.

Uptake of Community-Based HIV Testing during a Multi-Disease Health Campaign in Rural Uganda

Background The high burden of undiagnosed HIV in sub-Saharan Africa is a major obstacle for HIV prevention and treatment. Multi-disease, community health campaigns (CHCs) offering HIV testing are a successful approach to rapidly increase HIV testing rates and identify undiagnosed HIV. However, a greater understanding of population-level uptake is needed to maximize effectiveness of this approach. Methods After community sensitization and a census, a five-day campaign was performed in May 2012 in a rural Ugandan community. The census enumerated all residents, capturing demographics, household location, and fingerprint biometrics. The CHC included point-of-care screening for HIV, malaria, TB, hypertension and diabetes. Residents who attended vs. did not attend the CHC were compared to determine predictors of participation. Results Over 12 days, 18 census workers enumerated 6,343 residents. 501 additional residents were identified at the campaign, for a total community population of 6,844. 4,323 (63%) residents and 556 non-residents attended the campaign. HIV tests were performed in 4,795/4,879 (98.3%) participants; 1,836 (38%) reported no prior HIV testing. Of 2674 adults tested, 257 (10%) were HIV-infected; 125/257 (49%) reported newly diagnosed HIV. In unadjusted analyses, adult resident campaign non-participation was associated with male sex (62% male vs. 67% female participation, p = 0.003), younger median age (27 years in non-participants vs. 32 in participants; p<0.001), and marital status (48% single vs. 71% married/widowed/divorced participation; p<0.001). In multivariate analysis, single adults were significantly less likely to attend the campaign than non-single adults (relative risk [RR]: 0.63 [95% CI: 0.53–0.74]; p<0.001), and adults at home vs. not home during census activities were significantly more likely to attend the campaign (RR: 1.20 [95% CI: 1.13–1.28]; p<0.001). Conclusions CHCs provide a rapid approach to testing a majority of residents for HIV in rural African settings. However, complementary strategies are still needed to engage young, single adults and achieve universal testing.

Association of Implementation of a Universal Testing and Treatment Intervention With HIV Diagnosis, Receipt of Antiretroviral Therapy, and Viral Suppression in East Africa

Importance Antiretroviral treatment (ART) is now recommended for all HIV-positive persons. UNAIDS has set global targets to diagnose 90% of HIV-positive individuals, treat 90% of diagnosed individuals with ART, and suppress viral replication among 90% of treated individuals, for a population-level target of 73% of all HIV-positive persons with HIV viral suppression. Objective To describe changes in the proportions of HIV-positive individuals with HIV viral suppression, HIV-positive individuals who had received a diagnosis, diagnosed individuals treated with ART, and treated individuals with HIV viral suppression, following implementation of a community-based testing and treatment program in rural East Africa. Design, Setting, and Participants Observational analysis based on interim data from 16 rural Kenyan (n = 6) and Ugandan (n = 10) intervention communities in the SEARCH Study, an ongoing cluster randomized trial. Community residents who were 15 years or older (N = 77 774) were followed up for 2 years (2013-2014 to 2015-2016). HIV serostatus and plasma HIV RNA level were measured annually at multidisease health campaigns followed by home-based testing for nonattendees. All HIV-positive individuals were offered ART using a streamlined delivery model designed to reduce structural barriers, improve patient-clinician relationships, and enhance patient knowledge and attitudes about HIV. Main Outcomes and Measures Primary outcome was viral suppression (plasma HIV RNA<500 copies/mL) among all HIV-positive individuals, assessed at baseline and after 1 and 2 years. Secondary outcomes included HIV diagnosis, ART among previously diagnosed individuals, and viral suppression among those who had initiated ART. Results Among 77 774 residents (male, 45.3%; age 15-24 years, 35.1%), baseline HIV prevalence was 10.3% (7108 of 69 283 residents). The proportion of HIV-positive individuals with HIV viral suppression at baseline was 44.7% (95% CI, 43.5%-45.9%; 3464 of 7745 residents) and after 2 years of intervention was 80.2% (95% CI, 79.1%-81.2%; 5666 of 7068 residents), an increase of 35.5 percentage points (95% CI, 34.4-36.6). After 2 years, 95.9% of HIV-positive individuals had been previously diagnosed (95% CI, 95.3%-96.5%; 6780 of 7068 residents); 93.4% of those previously diagnosed had received ART (95% CI, 92.8%-94.0%; 6334 of 6780 residents); and 89.5% of those treated had achieved HIV viral suppression (95% CI, 88.6%-90.3%; 5666 of 6334 residents). Conclusions and Relevance Among individuals with HIV in rural Kenya and Uganda, implementation of community-based testing and treatment was associated with an increased proportion of HIV-positive adults who achieved viral suppression, along with increased HIV diagnosis and initiation of antiretroviral therapy. In these communities, the UNAIDS population-level viral suppression target was exceeded within 2 years after program implementation. Trial Registration clinicaltrials.gov Identifier: NCT01864683

Evaluating linkage to care for hypertension after community-based screening in rural Uganda

To determine the frequency and predictors of hypertension linkage to care after implementation of a linkage intervention in rural Uganda.

Changes in Population HIV RNA Levels in Mbarara, Uganda, During Scale-up of HIV Antiretroviral Therapy Access:

Objective:In a rural Ugandan community scaling up antiretroviral therapy (ART), we sought to determine if population-based HIV RNA levels [population viral load (VL)] decreased from 2011 to 2012. Design:Serial cross-sectional analyses (May 2011 and May 2012) of a defined study community of 6300 persons in a district with HIV prevalence of 8%. Methods:We measured HIV-1 RNA (VL) levels on all individuals testing positive for HIV during a 5-day high-throughput multidisease community health campaign in May 2012 that recruited two-thirds of the population. We aggregated individual-level VL results into population VL metrics including the proportion of individuals with an undetectable VL and compared these VL metrics to those we previously reported for this geographic region in 2011. Results:In 2012, 223 of 2179 adults were HIV-seropositive adults (10%). Overall, among 208 of 223 HIV-seropositive adults in whom VL was tested, 53% had an undetectable VL [95% confidence interval (CI): 46 to 60], up from 37% (95% CI: 30 to 45; P = 0.02) in 2011. Seven (3%) individuals had a VL of >100,000 copies/mL in 2012, down from 21 (13%) in 2011 (P = 0.0007). Mean log (VL) (geometric mean) was 3.18 log (95% CI: 3.06 to 3.29 log) in 2012, down from 3.62 log (95% CI: 3.46 to 3.78 log) in 2011 (P < 0.0001). Similar reductions in population VL were seen among men and women. Conclusions:Reductions in population VL metrics and a substantial increase in the proportion of persons with an undetectable VL were observed in a rural Ugandan community from 2011 to 2012. These findings from a resource-limited setting experiencing rapid ART scale-up may reflect a population-level effectiveness of expanding ART access.

Adaptive pair‐matching in randomized trials with unbiased and efficient effect estimation

In randomized trials, pair-matching is an intuitive design strategy to protect study validity and to potentially increase study power. In a common design, candidate units are identified, and their baseline characteristics used to create the best n/2 matched pairs. Within the resulting pairs, the intervention is randomized, and the outcomes measured at the end of follow-up. We consider this design to be adaptive, because the construction of the matched pairs depends on the baseline covariates of all candidate units. As a consequence, the observed data cannot be considered as n/2 independent, identically distributed pairs of units, as common practice assumes. Instead, the observed data consist of n dependent units. This paper explores the consequences of adaptive pair-matching in randomized trials for estimation of the average treatment effect, conditional the baseline covariates of the n study units. By avoiding estimation of the covariate distribution, estimators of this conditional effect will often be more precise than estimators of the marginal effect. We contrast the unadjusted estimator with targeted minimum loss based estimation and show substantial efficiency gains from matching and further gains with adjustment. This work is motivated by the Sustainable East Africa Research in Community Health study, an ongoing community randomized trial to evaluate the impact of immediate and streamlined antiretroviral therapy on HIV incidence in rural East Africa.

The roles of outlet density and norms in alcohol use disorder

BACKGROUND Alcohol outlet density and norms shape alcohol consumption. However, due to analytic challenges we do not know: (a) if alcohol outlet density and norms also shape alcohol use disorder, and (b) whether they act in combination to shape disorder. METHODS We applied a new targeted minimum loss-based estimator for rare outcomes (rTMLE) to a general population sample from New York City (N = 4000) to examine the separate and combined relations of neighborhood alcohol outlet density and norms around drunkenness with alcohol use disorder. Alcohol use disorder was assessed using the World Mental Health Comprehensive International Diagnostic Interview (WMH-CIDI) alcohol module. Confounders included demographic and socioeconomic characteristics, as well as history of drinking prior to residence in the current neighborhood. RESULTS Alcohol use disorder prevalence was 1.78%. We found a marginal risk difference for alcohol outlet density of 0.88% (95% CI 0.00-1.77%), and for norms of 2.05% (95% CI 0.89-3.21%), adjusted for confounders. While each exposure had a substantial relation with alcohol use disorder, there was no evidence of additive interaction between the exposures. CONCLUSIONS Results indicate that the neighborhood environment shapes alcohol use disorder. Despite the lack of additive interaction, each exposure had a substantial relation with alcohol use disorder and our findings suggest that alteration of outlet density and norms together would likely be more effective than either one alone. Important next steps include development and testing of multi-component intervention approaches aiming to modify alcohol outlet density and norms toward reducing alcohol use disorder.

Targeted estimation and inference for the sample average treatment effect in trials with and without pair-matching

In cluster randomized trials, the study units usually are not a simple random sample from some clearly defined target population. Instead, the target population tends to be hypothetical or ill-defined, and the selection of study units tends to be systematic, driven by logistical and practical considerations. As a result, the population average treatment effect (PATE) may be neither well defined nor easily interpretable. In contrast, the sample average treatment effect (SATE) is the mean difference in the counterfactual outcomes for the study units. The sample parameter is easily interpretable and arguably the most relevant when the study units are not sampled from some specific super-population of interest. Furthermore, in most settings, the sample parameter will be estimated more efficiently than the population parameter. To the best of our knowledge, this is the first paper to propose using targeted maximum likelihood estimation (TMLE) for estimation and inference of the sample effect in trials with and without pair-matching. We study the asymptotic and finite sample properties of the TMLE for the sample effect and provide a conservative variance estimator. Finite sample simulations illustrate the potential gains in precision and power from selecting the sample effect as the target of inference. This work is motivated by the Sustainable East Africa Research in Community Health (SEARCH) study, a pair-matched, community randomized trial to estimate the effect of population-based HIV testing and streamlined ART on the 5-year cumulative HIV incidence (NCT01864603). The proposed methodology will be used in the primary analysis for the SEARCH trial. Copyright

Estimating Effects with Rare Outcomes and High Dimensional Covariates: Knowledge is Power

Abstract Many of the secondary outcomes in observational studies and randomized trials are rare. Methods for estimating causal effects and associations with rare outcomes, however, are limited, and this represents a missed opportunity for investigation. In this article, we construct a new targeted minimum loss-based estimator (TMLE) for the effect or association of an exposure on a rare outcome. We focus on the causal risk difference and statistical models incorporating bounds on the conditional mean of the outcome, given the exposure and measured confounders. By construction, the proposed estimator constrains the predicted outcomes to respect this model knowledge. Theoretically, this bounding provides stability and power to estimate the exposure effect. In finite sample simulations, the proposed estimator performed as well, if not better, than alternative estimators, including a propensity score matching estimator, inverse probability of treatment weighted (IPTW) estimator, augmented-IPTW and the standard TMLE algorithm. The new estimator yielded consistent estimates if either the conditional mean outcome or the propensity score was consistently estimated. As a substitution estimator, TMLE guaranteed the point estimates were within the parameter range. We applied the estimator to investigate the association between permissive neighborhood drunkenness norms and alcohol use disorder. Our results highlight the potential for double robust, semiparametric efficient estimation with rare events and high dimensional covariates.

Population-Based Assessment of Hypertension Epidemiology and Risk Factors among HIV-Positive and General Populations in Rural Uganda.

Background Antiretroviral therapy scale-up in Sub-Saharan Africa has created a growing, aging HIV-positive population at risk for non-communicable diseases such as hypertension. However, the prevalence and risk factors for hypertension in this population remain incompletely understood. Methods We measured blood pressure and collected demographic data on over 65,000 adults attending multi-disease community health campaigns in 20 rural Ugandan communities (SEARCH Study: NCT01864603). Our objectives were to determine (i) whether HIV is an independent risk factor for hypertension, and (ii) awareness and control of hypertension in HIV-positive adults and the overall population. Results Hypertension prevalence was 14% overall, and 11% among HIV-positive individuals. 79% of patients were previously undiagnosed, 85% were not taking medication, and 50% of patients on medication had uncontrolled blood pressure. Multivariate predictors of hypertension included older age, male gender, higher BMI, lack of education, alcohol use, and residence in Eastern Uganda. HIV-negative status was independently associated with higher odds of hypertension (OR 1.2, 95% CI: 1.1–1.4). Viral suppression of HIV did not significantly predict hypertension among HIV-positives. Significance The burden of hypertension is substantial and inadequately controlled, both in HIV-positive persons and overall. Universal HIV screening programs could provide counseling, testing, and treatment for hypertension in Sub-Saharan Africa.