br Mathematical modeling has played an

Mathematical modeling has played an important role in the fight against HIV. Mathematical analysis of a protease inhibitor experiment enabled the development of the first suppressive multi-drug regimens for treating HIV (). Mathematical model use in disease epidemiology dates back almost a century (). Mathematical modeling allows us to rigorously explore the implications of complex hypotheses. Predictive models are particularly useful in epidemiology, where multi-armed experiments in vaccination may be impractical or unethical ().
It is in this tradition that Dimitrov, Kublin, Ramsey and Corey present an analysis of potential vaccination strategies for HIV in () The search for an effective HIV vaccine has been long (), (). Nearly 30years have passed since the first HIV vaccine trials, and we have only recently found the first vaccine candidate with any measurable protection against HIV infection in human subjects (), and the reported efficacy of 31% is too low for regulatory approval. It is likely that incremental advances based on this partial success will soon result in a vaccine with adequate protection, at least for one clade of the virus. As Dimitrov and colleagues point out, however, it is unlikely that a single vaccine will provide the same level of protective immunity to different HIV clades, which vary between geographic regions.
If this is the case, then a decision will need to be made whether to introduce a less effective vaccine, or to wait until a more effective vaccine becomes available. Dimitrov and colleagues present a mathematical model of HIV spread through populations, including ranges of possible purchase MLN4924 behaviors matched to data from HIV surveillance studies in San Francisco and South Africa. They compare three vaccine policies: a vaccination policy where a low efficacy vaccine is introduced immediately and maintained for 10 to 30years, a vaccination policy where the low efficacy vaccine is introduced immediately and switched for a moderate efficacy vaccine when it becomes available 3–8years later, and a policy where no vaccine is introduced until the moderate efficacy vaccine is available.

Ever since the first hematopoietic cell transplantation (HCT) was performed in 1960s, thousands of studies have elucidated the impact of patient and donor factors (sociodemographic, disease and transplant characteristics) on outcomes after the procedure. Fewer studies have looked at the role of center specific factors such as procedure volume, center experience or accreditation status in influencing the outcomes (). Macroeconomic factors such as gross national income per capita or health care expenditure per capita have been shown to impact the diffusion and utilization of HCT, because it is an expensive and resource intensive technology (). However, the impact of these factors on outcomes hasn\’t been well studied especially in the context of individual patient-level and center-specific factors.
In this issue of EBioMedicine, Baldomero et al. present a retrospective population level analysis that examines the interplay of patient-, center- and country level factors on outcomes of allogeneic and autologous HCT using data from the European Society of Blood and Marrow Transplantation (EBMT) database (). The authors use a large patient cohort with a long follow-up of 8years from 404 HCT centers in 25 European countries and incorporate center- and country specific economic data into a detailed multi-level analysis. They describe the association of program accreditation and duration, patient volume, human development index, gross national income/capita, and health care expenditures/capita with clinical outcomes (overall survival (OS), non-relapse mortality (NRM) and relapse) after HCT while adjusting for patient related factors. They report accreditation, higher patient volumes and longer program duration as center properties associated with better overall outcomes. These favorable center characteristics are more common in affluent countries and may explain in part the better survival, decreased NRM and relapse risk after allogeneic HCT in countries with higher economic indices. However, the authors rightly note that this relationship cannot be determined as causal because of the nature of the study and analysis. The relationship between outcomes and center- and country-specific factors is less definitive in the case of autologous HCT.