Though home-based human immunodeficiency virus (HIV) counseling and testing (HBHCT) is implemented in many sub-Saharan African countries as part of their HIV programs, linkage to HIV care remains a challenge. The purpose of this study is to test an intervention to enhance linkage to HIV care and improve HIV viral suppression among individuals testing HIV positive during HBHCT in rural Uganda.

To determine an association between unemployment rates and human immunodeficiency virus (HIV) mortality in the Organisation for Economic Co-operation and Development (OECD).

Tracking the spread of antimicrobial-resistant Neisseria gonorrhoeae is a major priority for national surveillance programmes.

Development assistance for health (DAH), the value of which peaked in 2013 and fell in 2015, is unlikely to rise substantially in the near future, increasing reliance on domestic and innovative financing sources to sustain health programmes in low-income and middle-income countries. We examined innovative financing instruments (IFIs)-financing schemes that generate and mobilise funds-to estimate the quantum of financing mobilised from 2002 to 2015. We identified ten IFIs, which mobilised US$8·9 billion (2·3% of overall DAH) in 2002-15. The funds generated by IFIs were channelled mostly through GAVI and the Global Fund, and used for programmes for new and underused vaccines, HIV/AIDS, malaria, tuberculosis, and maternal and child health. Vaccination programmes received the largest amount of funding ($2·6 billion), followed by HIV/AIDS ($1080·7 million) and malaria ($1028·9 million), with no discernible funding targeted to non-communicable diseases.

Mathematical simulation models are commonly used to inform health policy decisions. These health policy models represent the social and biological mechanisms that determine health and economic outcomes, combine multiple sources of evidence about how policy alternatives will impact those outcomes, and synthesize outcomes into summary measures salient for the policy decision. Calibrating these health policy models to fit empirical data can provide face validity and improve the quality of model predictions. Bayesian methods provide powerful tools for model calibration. These methods summarize information relevant to a particular policy decision into (1) prior distributions for model parameters, (2) structural assumptions of the model, and (3) a likelihood function created from the calibration data, combining these different sources of evidence via Bayes’ theorem. This article provides a tutorial on Bayesian approaches for model calibration, describing the theoretical basis for Bayesian calibration approaches as well as pragmatic considerations that arise in the tasks of creating calibration targets, estimating the posterior distribution, and obtaining results to inform the policy decision. These considerations, as well as the specific steps for implementing the calibration, are described in the context of an extended worked example about the policy choice to provide (or not provide) treatment for a hypothetical infectious disease. Given the many simplifications and subjective decisions required to create prior distributions, model structure, and likelihood, calibration should be considered an exercise in creating a reasonable model that produces valid evidence for policy, rather than as a technique for identifying a unique theoretically optimal summary of the evidence.

On 11 March 2011, the Great East Japan Earthquake, followed by a tsunami and nuclear-reactor meltdowns, produced one of the most severe disasters in the history of Japan. The adverse impact of this ‘triple disaster’ on the health of local populations and the health system was substantial. In this study we examine population-level health indicator changes that accompanied the disaster, and discuss options for re-designing Fukushima’s health system, and by extension that of Japan, to enhance its responsiveness and resilience to current and future shocks.

Differences in methods and data used in past studies have limited comparisons of the cost of illness of diabetes across countries. We estimate the full global economic burden of diabetes in adults aged 20-79 years in 2015, using a unified framework across all countries. Our objective was to highlight patterns of diabetes-associated costs as well as to identify the need for further research in low-income regions.