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Fundamentals -- Value -- Optimization -- Waiting lines and waiting times -- Modeling health interventions -- Practicing techniques in context : examples from famine management -- Modeling in R -- Microsimulation -- Modeling large-scale epidemics -- Complexities of epidemic modeling -- Good modeling practices

Facing projected growth in federal deficits, policymakers may increasingly look to Medicare for opportunities to slow spending. Medicare Advantage, which has grown to over one-third of the Medicare population, now costs the federal government over $230 billion a year. Competition in the program is weak in many parts of the country and federal subsidies are distributed unevenly to beneficiaries who are enrolled. This article offers a potential approach toward reforming the Medicare Advantage payment system, which could lower federal costs and enhance equity in the program. It builds a simple framework containing policy options and uses 2015 Centers for Medicare and Medicaid Services data to estimate the stylized impact on federal spending and enrollee benefits.

In a Perspective, Hilary Seligman and Sanjay Basu discuss future scenarios of food assistance programs to improve population health in a changing political environment.

In a Perspective, Hilary Seligman and Sanjay Basu discuss future scenarios of food assistance programs to improve population health in a changing political environment.

Health policy in Europe is at a crossroads. Longstanding challenges, such as persisting social and geographical inequalities, ageing populations, and rising burdens of chronic diseases, are being compounded by new, global threats, such as pandemic influenza and crises in the world's financial markets. Significant improvement in the health of Europe's population has been driven by factors both inside and outside the health sector. Key obstacles to improving population health in Europe result from underlying failures to overcome political and economic issues, including those shaping healthcare financing and delivery systems. How can the public health community respond to these challenges? This paper discusses three examples of how power and politics have shaped the world in which public health works. The focus on individual risk factors diverts attention from underlying determinants, such as the dominance of the market in healthcare, and the political decision to favour a rapid transition from communism in the 1990s. Effective public health policy requires addressing these political forces, seeking to understand the dominant paradigms, how they have been defined and shaped, and how they might be changed. Their effects are often subtle but powerful, shaping the language that is used, the assumptions that are made, and the rules that are implied. We can formulate key policy options to help improve health outcomes by reshaping the critical forces that affect public health risk factors among those populations currently most burdened by significant disease in Europe today.

BACKGROUND: Many low- and middle-income countries are not on track to reach the public health targets set out in the Millennium Development Goals (MDGs). We evaluated whether differential progress towards health MDGs was associated with economic development, public health funding (both overall and as percentage of available domestic funds), or health system infrastructure. We also examined the impact of joint epidemics of HIV/AIDS and noncommunicable diseases (NCDs), which may limit the ability of households to address child mortality and increase risks of infectious diseases. METHODS AND FINDINGS: We calculated each country's distance from its MDG goals for HIV/AIDS, tuberculosis, and infant and child mortality targets for the year 2005 using the United Nations MDG database for 227 countries from 1990 to the present. We studied the association of economic development (gross domestic product [GDP] per capita in purchasing-power-parity), the relative priority placed on health (health spending as a percentage of GDP), real health spending (health system expenditures in purchasing-power-parity), HIV/AIDS burden (prevalence rates among ages 15-49 y), and NCD burden (age-standardised chronic disease mortality rates), with measures of distance from attainment of health MDGs. To avoid spurious correlations that may exist simply because countries with high disease burdens would be expected to have low MDG progress, and to adjust for potential confounding arising from differences in countries' initial disease burdens, we analysed the variations in rates of change in MDG progress versus expected rates for each country. While economic development, health priority, health spending, and health infrastructure did not explain more than one-fifth of the differences in progress to health MDGs among countries, burdens of HIV and NCDs explained more than half of between-country inequalities in child mortality progress (R(2)-infant mortality = 0.57, R(2)-under 5 mortality = 0.54). HIV/AIDS and NCD burdens were also the strongest correlates of unequal progress towards tuberculosis goals (R(2) = 0.57), with NCDs having an effect independent of HIV/AIDS, consistent with micro-level studies of the influence of tobacco and diabetes on tuberculosis risks. Even after correcting for health system variables, initial child mortality, and tuberculosis diseases, we found that lower burdens of HIV/AIDS and NCDs were associated with much greater progress towards attainment of child mortality and tuberculosis MDGs than were gains in GDP. An estimated 1% lower HIV prevalence or 10% lower mortality rate from NCDs would have a similar impact on progress towards the tuberculosis MDG as an 80% or greater rise in GDP, corresponding to at least a decade of economic growth in low-income countries. CONCLUSIONS: Unequal progress in health MDGs in low-income countries appears significantly related to burdens of HIV and NCDs in a population, after correcting for potentially confounding socioeconomic, disease burden, political, and health system variables. The common separation between NCDs, child mortality, and infectious syndromes among development programs may obscure interrelationships of illness affecting those living in poor households--whether economic (e.g., as money spent on tobacco is lost from child health expenditures) or biological (e.g., as diabetes or HIV enhance the risk of tuberculosis).

Precision medicine research designed to reduce health disparities often involves studying multi-level datasets to understand how diseases manifest disproportionately in one group over another, and how scarce health care resources can be directed precisely to those most at risk for disease. In this article, we provide a structured tutorial for medical and public health research­ers on the application of machine learning methods to conduct precision medicine research designed to reduce health dispari­ties. We review key terms and concepts for understanding machine learning papers, including supervised and unsupervised learning, regularization, cross-validation, bagging, and boosting. Metrics are reviewed for evaluating machine learners and major families of learning approaches, including tree-based learning, deep learning, and ensemble learning. We highlight the advan­tages and disadvantages of different learning approaches, describe strategies for interpret­ing "black box" models, and demonstrate the application of common methods in an example dataset with open-source statistical code in R.Ethn Dis. 2020;30(Suppl 1):217-228; doi:10.18865/ed.30.S1.217

BACKGROUND: Regional trade agreements are major international policy instruments that shape macro-economic and political systems. There is widespread debate as to whether and how these agreements pose risks to public health. Here we perform a comprehensive systematic review of quantitative studies of the health impact of trade and investment agreements. We identified studies from searches in PubMed, Web of Science, EMBASE, and Global Health Online. Research articles were eligible for inclusion if they were quantitative studies of the health impacts of trade and investment agreements or policy. We systematically reviewed study findings, evaluated quality using the Quality Assessment Tool from the Effective Public Health Practice Project, and performed network citation analysis to study disciplinary siloes. RESULTS: Seventeen quantitative studies met our inclusion criteria. There was consistent evidence that implementing trade agreements was associated with increased consumption of processed foods and sugar-sweetened beverages. Granting import licenses for patented drugs was associated with increased access to pharmaceuticals. Implementing trade agreements and associated policies was also correlated with higher cardiovascular disease incidence and higher Body Mass Index (BMI), whilst correlations with tobacco consumption, under-five mortality, maternal mortality, and life expectancy were inconclusive. Overall, the quality of studies is weak or moderately weak, and co-citation analysis revealed a relative isolation of public health from economics. CONCLUSION: We identified limitations in existing studies which preclude definitive conclusions of the health impacts of regional trade and investment agreements. Few address unobserved confounding, and many possible consequences and mechanisms linking trade and investment agreements to health remain poorly understood. Results from our co-citation analysis suggest scope for greater interdisciplinary collaboration. Notwithstanding these limitations, our results find evidence that trade agreements pose some significant health risks. Health protections in trade and investment treaties may mitigate these impacts.

Why have patterns of healthcare spending varied during the Great Recession? Using cross-national, harmonised data for 27 EU countries from 1995 to 2011, we evaluated political, economic, and health system determinants of recent changes to healthcare expenditure. Data from EuroStat, the IMF, and World Bank (2013 editions) were evaluated using multivariate random- and fixed-effects models, correcting for pre-existing time-trends. Reductions in government health expenditure were not significantly associated with magnitude of economic recessions (annual change in GDP, p=0.31, or cumulative decline, p=0.40 or debt crises (measured by public debt as a percentage of GDP, p=0.38 or per capita, p=0.83)). Nor did ideology of governing parties have an effect. In contrast, each $100 reduction in tax revenue was associated with a $2.72 drop in health spending (95% CI: $1.03-4.41). IMF borrowers were significantly more likely to reduce healthcare budgets than non-IMF borrowers (OR=3.88, 95% CI: 1.95 -7.74), even after correcting for potential confounding by indication. Exposure to lending from international financial institutions, tax revenue falls, and decisions to implement cuts correlate more closely than underlying economic conditions or orientation of political parties with healthcare expenditure change in EU member states.