PEPFAR, national governments, and other stakeholders are investing unprecedented resources to provide HIV treatment in developing countries. This study reports empirical data on costs and cost trends in a large sample of HIV treatment sites. In 2006–2007, we conducted cost analyses at 43 PEPFAR-supported outpatient clinics providing free comprehensive HIV treatment in Botswana, Ethiopia, Nigeria, Uganda, and Vietnam. We collected data on HIV treatment costs over consecutive 6-month periods from scale-up of dedicated HIV treatment services at each site. The study included all patients receiving HIV treatment and care at study sites (62,512 ART and 44,394 pre-ART patients). Outcomes were costs per-patient and total program costs, subdivided by major cost categories. Median annual economic costs were $202 (2009 USD) for pre-ART patients and $880 for ART patients. Excluding ARVs, per-patient ART costs were $298. Care for newly initiated ART patients cost 15–20% more than for established patients. Per-patient costs dropped rapidly as sites matured, with per-patient ART costs dropping 46.8% between first and second 6-month periods after the beginning of scale-up, and an additional 29.5% the following year. PEPFAR provided 79.4% of funding for service delivery, and national governments provided 15.2%. Treatment costs vary widely between sites, and high early costs drop rapidly as sites mature. Treatment costs vary between countries and respond to changes in ARV regimen costs and the package of services. While cost reductions may allow near-term program growth, programs need to weigh the trade-off between improving services for current patients and expanding coverage to new patients.

BackgroundGovernments and international donors have partnered to provide free HIV treatment to over 6 million individuals in low and middle-income countries. Understanding the determinants of HIV treatment costs will help improve efficiency and provide greater certainty about future resource needs.Methods and FindingsWe collected data on HIV treatment costs from 54 clinical sites in Botswana, Ethiopia, Mozambique, Nigeria, Uganda, and Vietnam. Sites provided free HIV treatment funded by the U.S. President’s Emergency Plan for AIDS Relief (PEPFAR), national governments, and other partners. Service delivery costs were categorized into successive six-month periods from the date when each site began HIV treatment scale-up. A generalized linear mixed model was used to investigate relationships between site characteristics and per-patient costs, excluding ARV expenses. With predictors at their mean values, average annual per-patient costs were $177 (95% CI: 127–235) for pre-ART patients, $353 (255–468) for adult patients in the first 6 months of ART, and $222 (161–296) for adult patients on ART for >6 months (excludes ARV costs). Patient volume (no. patients receiving treatment) and site maturity (months since clinic began providing treatment services) were both strong independent predictors of per-patient costs. Controlling for other factors, costs declined by 43% (18–63) as patient volume increased from 500 to 5,000 patients, and by 28% (6–47) from 5,000 to 10,000 patients. For site maturity, costs dropped 41% (28–52) between months 0–12 and 25% (15–35) between months 12–24. Price levels (proxied by per-capita GDP) were also influential, with costs increasing by 22% (4–41) for each doubling in per-capita GDP. Additionally, the frequency of clinical follow-up, frequency of laboratory monitoring, and clinician-patient ratio were significant independent predictors of per-patient costs.ConclusionsSubstantial reductions in per-patient service delivery costs occur as sites mature and patient cohorts increase in size. Other predictors suggest possible strategies to reduce per-patient costs.

Population-level effects of control strategies on the dynamics of Chlamydia trachomatis transmission are difficult to quantify. In this study, we calibrated a novel sex- and age-stratified pair-formation transmission model of chlamydial infection to epidemiologic data in the United States for 2000–2015. We used sex- and age-specific prevalence estimates from the National Health and Nutrition Examination Surveys, case report data from national chlamydia surveillance, and survey data from the Youth Risk Behavior Survey on the proportion of the sexually active population aged 15–18 years. We were able to reconcile national prevalence estimates and case report data by allowing for changes over time in screening coverage and reporting completeness. In retrospective analysis, chlamydia prevalence was estimated to be almost twice the current levels in the absence of screening and partner notification. Although chlamydia screening and partner notification were both found to reduce chlamydia burden, the relative magnitude of their estimated impacts varied in our sensitivity analyses. The variation in the model predictions highlights the need for further data collection and research to improve our understanding of the natural history of chlamydia and the pathways through which prevention strategies affect transmission dynamics.

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Previous studies have consistently found an inverse relationship between household-level poverty and health status. However, what is not well understood is whether and how the average economic status at the community level plays a role in the poverty-health relationship. The purpose of this study is to investigate the concentration of poverty at the community level in Tanzania and its association with the availability and quality of primary health care services, the utilization of services, and health outcomes among household categories defined by wealth scores. A principal component method has been applied to rank households separately by urban/rural location using reported levels of asset ownership and living conditions. The household wealth scores were also used to classify communities into three cluster-types based on the proportion of households belonging to the poorest wealth tercile. On average, all the wealth terciles living in low poverty concentration areas were found to have better health outcomes and service utilization rates than their counterparts living in high poverty concentration clusters. Consistent with the finding is that high poverty concentration areas were further away from facilities offering primary health care than low poverty concentration areas. Moreover, the facilities closest to the high poverty concentration areas had fewer doctors, medical equipment and drugs. Among the high poverty concentration clusters, the 10 communities with the best women's body mass index (BMI) measures were found to have access to facilities with a greater availability of equipment and drugs than the 10 communities with the worst BMI measures. Although this study does not directly measure quality, the characteristics that differentiate high poverty concentration clusters from low poverty concentration clusters point to quality as more important than physical access among the study population.