The Institute for Health Metrics and Evaluation model for predicting the course of the coronavirus disease 2019 pandemic has attracted considerable attention, including from the U.S. government. The appearance of certainty of model estimates is seductive when the world is desperate to know what lies ahead, but caution is warranted regarding the validity and usefulness of the model projections for policymakers.

The Institute for Health Metrics and Evaluation model for predicting the course of the coronavirus disease 2019 pandemic has attracted considerable attention, including from the U.S. government. The appearance of certainty of model estimates is seductive when the world is desperate to know what lies ahead, but caution is warranted regarding the validity and usefulness of the model projections for policymakers.

Introduction

Geographic and transportation barriers are associated with poorer HIV-related health outcomes in sub-Saharan Africa, but data on the impact of these barriers on prevention interventions are limited. We estimated the association between distance to clinic and other transportation-related barriers on pre-exposure prophylaxis (PrEP) uptake and initial clinic visit attendance in a rural community in southwestern Uganda enrolled in the ongoing SEARCH study (NCT01864603).

Methods

Community-wide HIV testing was conducted and offered to adult (≥15 years) participants in Ruhoko. Participants were eligible for PrEP based on an empiric risk score, having an HIV-discordant partner, or self-referral at either the community health campaign or during home-based testing from March to April 2017. We collected data from PrEP-eligible households on GPS-measured distance to clinic, walking time to clinic and road difficulty. A sample of participants was also asked to identify their primary barriers to PrEP use with a semi-quantitative questionnaire. We used multivariable logistic regression to evaluate the association between transportation barriers and (1) PrEP uptake among PrEP-eligible individuals and (2) four-week clinic visit attendance among PrEP initiators.

Results

Of the 701 PrEP-eligible participants, 272 (39%) started PrEP within four weeks; of these, 45 (17%) were retained at four weeks. Participants with a distance to clinic of ≥2 km were less likely to start PrEP (aOR 0.34; 95% CI 0.15 to 0.79, p = 0.012) and less likely to be retained on PrEP once initiated (aOR 0.29; 95% CI 0.10 to 0.84; p = 0.024). Participants who were deemed eligible during home-based testing and did not have the option of same-day PrEP start were also substantially less likely to initiate PrEP (aOR 0.16, 95% CI 0.07 to 0.37, p < 0.001). Of participants asked to name barriers to PrEP use (N = 98), the most frequently cited were "needing to take PrEP every day" (N = 18) and "low/no risk of getting HIV" (N = 18). Transportation-related barriers, including "clinic is too far away" (N = 6) and "travel away from home" (N = 4) were also reported.

Conclusions

Distance to clinic is a significant predictor of PrEP uptake and four-week follow-up visit attendance in a community in rural Uganda. Interventions that address geographic and transportation barriers may improve PrEP uptake and retention in sub-Saharan Africa.

Background

The SEARCH study provided community-based HIV and multidisease testing and antiretroviral therapy (ART) to 32 communities in East Africa and reported no statistically significant difference in 3-year HIV incidence. We used mathematical modeling to estimate the effect of control arm viral suppression and community mixing on SEARCH trial outcomes.

Setting

Uganda and Kenya.

Methods

Using the individual-based HIV modeling software EMOD-HIV, we configured a new model of SEARCH communities. The model was parameterized using demographic, HIV prevalence, male circumcision, and viral suppression data and calibrated to HIV prevalence, ART coverage, and population size. Using assumptions about ART scale-up in the control arm, degree of community mixing, and effect of baseline testing, we estimated comparative HIV incidence under multiple scenarios.

Results

Before the trial results, we predicted that SEARCH would report a 4%-40% reduction between arms, depending on control arm ART linkage rates and community mixing. With universal baseline testing followed by rapidly expanded ART eligibility and uptake, modeled effect sizes were smaller than the study was powered to detect. Using interim viral suppression data, we estimated 3-year cumulative incidence would have been reduced by up to 27% in the control arm and 43% in the intervention arm compared with a counterfactual without universal baseline testing.

Conclusions

Our model suggests that the active control arm substantially reduced expected effect size and power of the SEARCH study. However, compared with a counterfactual "true control" without increased ART linkage because of baseline testing, SEARCH reduced HIV incidence by up to 43%.