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Background: No one knows whether the temporality of nonfatal deliberate self-harm in the United States mirrors the temporality of suicide deaths. Aims: To analyze day- and month-specific variation in population rates for suicide fatalities and, separately, for hospital admissions for nonfatal deliberate self-harm. Methods: For 12 states, we extracted vital statistics data on all suicides (n = 11,429) and hospital discharge data on all nonfatal deliberate self-harm admissions (n = 60,870) occurring in 1997. We used multinomial logistic regression to analyze the significance of day-to-day and month-to-month variations in the occurrence of suicides and nonfatal deliberate self-harm admissions. Results: Both fatal and nonfatal events had a 6%–10% excess occurrence on Monday and Tuesday and were 5%–13% less likely to occur on Saturdays (p < .05). Males were more likely than females to act on Wednesdays and Saturdays. Nonfatal admission rates were 6% above the average in April and May (p < .05). In contrast, suicide rates were 6% above the average in February and March and 8% below it in November (p < .05). Conclusions: Suicides and nonfatal hospital admissions for deliberate self-harm have peaks and troughs on the same days in the United States. In contrast, the monthly patterns for these fatal and nonfatal events are not congruent.

AbstractTotal cost estimates for crime in the USA are both out-of-date and incomplete. We estimated incidence and costs of personal crimes (both violent and non-violent) and property crimes in 2017. Incidence came from national arrest data, multi-state estimates of police-reported crimes per arrest, national victimization and road crash surveys, and police underreporting studies. We updated and expanded upon published unit costs. Estimated crime costs totaled $2.6 trillion ($620 billion in monetary costs plus quality of life losses valued at $1.95 trillion; 95 % uncertainty interval $2.2–$3.0 trillion). Violent crime accounted for 85 % of costs. Principal contributors to the 10.9 million quality-adjusted life years lost were sexual violence, physical assault/robbery, and child maltreatment. Monetary expenditures caused by criminal victimization represent 3 % of Gross Domestic Product – equivalent to the amount spent on national defense. These estimates exclude the additional costs of preventing and avoiding crime such as enhanced lighting and burglar alarms. They also exclude crimes against businesses and most white-collar and corporate offenses.

We estimated how much the Federal government and state/local government pay for different kinds of crashes in the United States. Government costs include reductions in an array of public services (emergency, incident management, vocational rehabilitation, coroner court processing of liability litigation), medical payments, social safety net assistance to the injured and their families, and taxes foregone because victims miss work. Government also pays when its employees crash while working and covers fringe benefits for crash-involved employees and their benefit-eligible dependents in non-work hours. We estimated government shares of crash costs by component. We applied those estimates to existing US Department of Transportation estimates of crash costs to society and employers. Government pays an estimated $35 billion annually because of crashes, an estimated 12.6% of the economic cost of crashes (Federal 7.1%, State/local 5.5%). Government bears a higher percentage of the monetary costs of injury crashes than fatal crashes or crashes involving property damage only. Government is increasingly recovering the medical cost of crashes from auto insurers. Nevertheless, medical costs and income and sales tax losses account for 75% of government's crash costs. For State/local government to break even on a 100%-State funded investment in road safety, the intervention would need to have an unrealistically high benefit-cost ratio of 34. Government invests in medical treatment of illness to save lives and improve quality of life. Curing a child's leukemia, for example, is not less costly than leaving that leukemia untreated. Safety should not be held to a different standard.

This paper aims to estimate lifetime costs resulting from abusive head trauma (AHT) in the USA and the break-even effectiveness for prevention. A mathematical model incorporated data from Vital Statistics, the Healthcare Cost and Utilization Project Kids' Inpatient Database, and previous studies. Unit costs were derived from published sources. From society's perspective, discounted lifetime cost of an AHT averages $5.7 million (95% CI $3.2–9.2 million) for a death. It averages $2.6 million (95% CI $1.0–2.9 million) for a surviving AHT victim including $224,500 for medical care and related direct costs (2010 USD). The estimated 4824 incident AHT cases in 2010 had an estimated lifetime cost of $13.5 billion (95% CI $5.5–16.2 billion) including $257 million for medical care, $552 million for special education, $322 million for child protective services/criminal justice, $2.0 billion for lost work, and $10.3 billion for lost quality of life. Government sources paid an estimated $1.3 billion. Out-of-pocket benefits of existing prevention programming would exceed its costs if it prevents 2% of cases. When a child survives AHT, providers and caregivers can anticipate a lifetime of potentially costly and life-threatening care needs. Better effectiveness estimates are needed for both broad prevention messaging and intensive prevention targeting high-risk caregivers.

Background: An adequate amount of prepaid resources for health is important to ensure access to health services and for the pursuit of universal health coverage. Previous studies on global health financing have described the relationship between economic development and health financing. In this study, we further explore global health financing trends and examine how the sources of funds used, types of services purchased, and development assistance for health disbursed change with economic development. We also identify countries that deviate from the trends. Methods: We estimated national health spending by type of care and by source, including development assistance for health, based on a diverse set of data including programme reports, budget data, national estimates, and 964 National Health Accounts. These data represent health spending for 184 countries from 1995 through 2014. We converted these data into a common inflation-adjusted and purchasing power-adjusted currency, and used non-linear regression methods to model the relationship between health financing, time, and economic development. Findings: Between 1995 and 2014, economic development was positively associated with total health spending and a shift away from a reliance on development assistance and out-of-pocket (OOP) towards government spending. The largest absolute increase in spending was in high-income countries, which increased to purchasing power-adjusted $5221 per capita based on an annual growth rate of 3·0%. The largest health spending growth rates were in upper-middle-income (5·9) and lower-middle-income groups (5·0), which both increased spending at more than 5% per year, and spent $914 and $267 per capita in 2014, respectively. Spending in low-income countries grew nearly as fast, at 4·6%, and health spending increased from $51 to $120 per capita. In 2014, 59·2% of all health spending was financed by the government, although in low-income and lower-middle-income countries, 29·1% and 58·0% of spending was OOP spending and 35·7% and 3·0% of spending was development assistance. Recent growth in development assistance for health has been tepid; between 2010 and 2016, it grew annually at 1·8%, and reached US$37·6 billion in 2016. Nonetheless, there is a great deal of variation revolving around these averages. 29 countries spend at least 50% more than expected per capita, based on their level of economic development alone, whereas 11 countries spend less than 50% their expected amount. Interpretation: Health spending remains disparate, with low-income and lower-middle-income countries increasing spending in absolute terms the least, and relying heavily on OOP spending and development assistance. Moreover, tremendous variation shows that neither time nor economic development guarantee adequate prepaid health resources, which are vital for the pursuit of universal health coverage.

Importance: The increasing burden due to cancer and other noncommunicable diseases poses a threat to human development, which has resulted in global political commitments reflected in the Sustainable Development Goals as well as the World Health Organization (WHO) Global Action Plan on Non-Communicable Diseases. To determine if these commitments have resulted in improved cancer control, quantitative assessments of the cancer burden are required. Objective: To assess the burden for 29 cancer groups over time to provide a framework for policy discussion, resource allocation, and research focus. Evidence Review: Cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life-years (DALYs) were evaluated for 195 countries and territories by age and sex using the Global Burden of Disease study estimation methods. Levels and trends were analyzed over time, as well as by the Sociodemographic Index (SDI). Changes in incident cases were categorized by changes due to epidemiological vs demographic transition. Findings: In 2016, there were 17.2 million cancer cases worldwide and 8.9 million deaths. Cancer cases increased by 28% between 2006 and 2016. The smallest increase was seen in high SDI countries. Globally, population aging contributed 17%; population growth, 12%; and changes in age-specific rates, -1% to this change. The most common incident cancer globally for men was prostate cancer (1.4 million cases). The leading cause of cancer deaths and DALYs was tracheal, bronchus, and lung cancer (1.2 million deaths and 25.4 million DALYs). For women, the most common incident cancer and the leading cause of cancer deaths and DALYs was breast cancer (1.7 million incident cases, 535 000 deaths, and 14.9 million DALYs). In 2016, cancer caused 213.2 million DALYs globally for both sexes combined. Between 2006 and 2016, the average annual age-standardized incidence rates for all cancers combined increased in 130 of 195 countries or territories, and the average annual age-standardized death rates decreased within that timeframe in 143 of 195 countries or territories. Conclusions and Relevance: Large disparities exist between countries in cancer incidence, deaths, and associated disability. Scaling up cancer prevention and ensuring universal access to cancer care are required for health equity and to fulfill the global commitments for noncommunicable disease and cancer control.

Background The amount of resources, particularly prepaid resources, available for health can affect access to health care and health outcomes. Although health spending tends to increase with economic development, tremendous variation exists among health financing systems. Estimates of future spending can be beneficial for policy makers and planners, and can identify financing gaps. In this study, we estimate future gross domestic product (GDP), all-sector government spending, and health spending disaggregated by source, and we compare expected future spending to potential future spending. Methods We extracted GDP, government spending in 184 countries from 1980-2015, and health spend data from 1995-2014. We used a series of ensemble models to estimate future GDP, all-sector government spending, development assistance for health, and government, out-of-pocket, and prepaid private health spending through 2040. We used frontier analyses to identify patterns exhibited by the countries that dedicate the most funding to health, and used these frontiers to estimate potential health spending for each low-income or middle-income country. All estimates are inflation and purchasing power adjusted. Findings We estimated that global spending on health will increase from US$9.21 trillion in 2014 to $24.24 trillion (uncertainty interval [UI] 20.47-29.72) in 2040. We expect per capita health spending to increase fastest in upper-middle-income countries, at 5.3% (UI 4.1-6.8) per year. This growth is driven by continued growth in GDP, government spending, and government health spending. Lower-middle income countries are expected to grow at 4.2% (3.8-4.9). High-income countries are expected to grow at 2.1% (UI 1.8-2.4) and low-income countries are expected to grow at 1.8% (1.0-2.8). Despite this growth, health spending per capita in low-income countries is expected to remain low, at $154 (UI 133-181) per capita in 2030 and $195 (157-258) per capita in 2040. Increases in national health spending to reach the level of the countries who spend the most on health, relative to their level of economic development, would mean $321 (157-258) per capita was available for health in 2040 in low-income countries. Interpretation Health spending is associated with economic development but past trends and relationships suggest that spending will remain variable, and low in some low-resource settings. Policy change could lead to increased health spending, although for the poorest countries external support might remain essential. ; Peer reviewed