An Education Strategy to Respond to Medicine Inequality in Africa

New versatile process efficiently converts biomass to liquid fuel

Institutional Quality and Income Distribution

Background and importance: Rising drug prices are putting pressure on health care budgets. Policymakers are assessing how they can save money through generic drugs. Objective: The aim of this Ph.D. was to explore issues relating to the prices and usage of generic medicines in high- and middle-income countries in five articles. This was done using quantitative and qualitative methods, including price and Herfindahl-Hirschman indexes, difference-in-differences regression analyses, semi-structured stakeholder interviews, and literature reviews. As a Ph.D. “thesis by papers”, each of the five articles should be read as a stand-alone piece. However, the thesis presents an overarching narrative, outlined at the end of Chapter 1. Novelty and empirical contribution: My original contributions to knowledge are: (i) updated analyses of generic drug policies, prices, and usage rates in high-income countries, based on a large, representative sample of generic medicines from 2013 (Chapters 2 and 3); (ii) evidence on the impact of a pharmaceutical tendering system on medicines prices, demand, and competition over a 15-year period (Chapter 4); (iii) quantitative data on the impact of therapeutic tendering on drug spending and prices (Chapter 5); and (iv) qualitative data on how a country can move from a fragmented health-care system to a single-payer one, using tendering as the basis for a comprehensive drug-benefit plan (Chapter 6). Key findings: The prices and market shares of generics varied widely across Europe. For example, prices charged by manufacturers in Switzerland were, on average, more than 2.5 times those in Germany and more than 6 times those in the United Kingdom, based on the results of a commonly used price index. However, the results varied depending on the choice of index, base country, unit of volume, method of currency conversion, and therapeutic category. The results also differed depending on whether one looked at the prices charged by manufacturers or those charged by pharmacists. The proportion of prescriptions filled with generics ranged from 17% in Switzerland to 83% in the United Kingdom. The results of the first two studies indicated that the countries which used tender or tender-like systems to set generic drug prices in retail pharmacies (ie, Denmark, Germany, the Netherlands, and Sweden) had among the lowest prices among the countries included in the studies. Tendering can be an effective policy to procure essential medicines at low prices, based on analysis of data from South Africa and Cyprus. For instance, the average prices of antiretroviral therapies, anti-infective medicines, small-volume parenterals, drops and inhalers, solid-dose medicines, and family-planning agents dropped by roughly 40% or more between 2003 and 2016 in South Africa. Many tender contracts in South Africa remained competitive over time, based on the Herfindahl-Hirschman results, with some notable exceptions. However, the number of different firms winning contracts decreased over time in most tender categories. Also, there were large discrepancies between the drug quantities the health ministry estimated it would need to meet patient demand and the quantities the ministry went on to procure during tender periods. In South Africa, the introduction of therapeutic tendering was associated with an estimated 33% to 44% reduction in the prices of solid-dose drugs in 2014. National governments in countries aiming to introduce national health systems (eg, Cyprus and South Africa) will need to adapt their tendering systems and other pharmaceutical policies during transition periods. Future research directions: More research is needed to better understand the drivers of differences in generic drug prices between countries. It is also important to examine why there are large differences in the prices of drugs in various therapeutic areas, both within and between countries. Also, data from more countries, especially low- and middle-income ones, are needed to determine which features of tendering systems are associated with lower prices. Future studies should re-examine the South African therapeutic tendering system once data from more post-intervention periods are available, possibly using other research designs like interrupted time-series models (ie, segmented regression analysis). Policy implications: Price indexes are useful statistical approaches for comparing drug prices across countries, but policymakers should interpret price indexes with caution given their limitations. This thesis offers useful data for policymakers using, or planning to introduce, tendering systems, especially in countries aiming for universal health coverage, like Cyprus (Chapter 6) and South Africa (Chapters 4 and 5).

ECONOMISTS have vigorously debated whether advertising and other messages supplied by sellers to buyers represent the efficient provision of information or the exploitation of buyers' imperfect access to it. Many economists now agree that each view commands some truth. Advertising should convey information efficiently where the buyer can easily verify it. But it may engender inefficient rent-seeking outlays by producers able to hamper buyers' gaining of information from alternative sources. For example, if buyers sample product information randomly, an incumbent can "jam" the channels through which entrants transmit their messages by loading the sampled population with messages of his own. Or the incumbent's messages can reinforce buyers' habits so as to reduce their prior expectations of the value of trying an alternative brand.2 If sales promotion is effective (by whatever means) in causing buyers to shift among competing products, it becomes a form of rent-seeking outlay by which sellers bid for the available customers.3 The problem for empirical research is to determine the extent to which seller-supplied information pursues a rent-seeking goal and thus incurs social costs. Those costs must be set against the efficiency advantage of sellers (relative to buyers or

Social and economic development is a difficult process in which positive and negative factors interact that causes rises and recessions in development of territories and public communities. Indicators of rating act as indicators of efficiency of management decisions at the central and local levels. However, the level of economic development doesn’t coincide with social development in most of regions of Ukraine.
 The purpose of article is adaptation of a matrix method to rating estimates of social and economic development of regions for identification of regional distinctions, definition of priorities and strategic management of development of regions.
 The economic development of the regions was estimated by GRP per capita, the average salary of employees and the unemployment rate (according to the ILO methodology). Social development is characterized by the number of people enrolled in higher education institutions per 10,000 population; coefficient of incidence of the population; volumes of emissions of pollutants in atmospheric air, thousand tons; crime rates.
 The multidimensional average method with the standardization of indicators based on the variation range was used to calculate the integral indicators of economic and social development. On the basis of integral coefficients, the ranking of regions according to economic and social development was executed. It is established that for the regions of Ukraine there is a characteristic imbalance between economic and social development, which is connected, first of all, with different structure of the economy and territorial differences of regions.
 The combination of results of economic and social development of regions was proposed with the help of building a matrix as a tool for strategic management. In the graphs (vertically), the level of economic development is singled out, in lines (horizontally) the level of social development of the regions is singled out, with the identification of three groups: low, medium and high levels.
 Regions with low economic and low social level get to 1 square; in 2 – with low economic and average social; in 3 – with low economic and high social; in 4 – with average economic and low social; in 5 – with average economic and average social; in 6 – with average economic and high social; in 7 – with high economic and low social; in 8 – with high economic and average social; in 9 – with high economic and high social level.
 Calculations show that in Ukraine no region was detected with simultaneous high levels of economic and social development (the 9th square). The vast majority are regions with average economic and average social development and also regions “below or above an average” level of development, that is one of the directions (economic or social) is “low”, and the second, accordingly, “average”. The position of the region in a matrix specifies what development strategy should be chosen. The economic and social development is higher; the capacity of the region for increase in the standard of living of the population is higher. High economic and social development is followed by the high potential of the region to increase the standard of living of the population.

THE economic and welfare effects of advertising have been extensively studied over the last half-century. However, these efforts have not led to a consensus either as to the effects or the value of advertising. Economists continue to reach polar conclusions that appear to be derived mainly from preconceptions of the social desirability of advertising. On the one hand is research that emphasizes promotion's ability to create "artificial" product differentiation and thereby produce informational confusion.1 This line of research stresses the empirical association of extensive advertising with high concentration and high accounting profits-evidence judged to support increased market power and entry barrier effects.2 A contrary body of research emphasizes the value of advertising in providing information and, hence, in promoting competition.3 The empirical findings most consistent with this view are that prices paid by consumers in (selected) markets are lower with advertising than without it.4

Comparing Risks and Benefits of Colorectal Cancer Screening in Elderly Patients

BackgroundWe assessed the effects of smoking and smoking cessation on life expectancy and active life expectancy among persons aged 55 years or older in Beijing.MethodsThis study included 1593 men and 1664 women who participated in the Beijing Longitudinal Study of Aging, which commenced in 1992 and had 4 survey waves up to year 2000. An abridged life table was used to estimate life expectancy, in which age-specific mortality and age-specific disability rates were adjusted by using a discrete-time hazard model to control confounders.ResultsThe mean ages (SD) for men and women were 70.1 (9.25) and 70.2 (8.72) years, respectively; mortality and disability rates during follow-up were 34.7% and 8.0%, respectively. In both sexes, never smokers had the highest life expectancy and active life expectancy across ages, as compared with current and former smokers. Current heavy smokers had a shorter life expectancy and a shorter active life expectancy than light smokers. Among former smokers, male long-term quitters had a longer life expectancy and longer active life expectancy than short-term quitters, but this was not the case in women.ConclusionsOlder adults remain at higher risk of mortality and morbidity from smoking and can expect to live a longer and healthier life after smoking cessation.

Mental disorders are associated with elevated mortality rates and reduced life expectancy. However, it is unclear whether these associations differ by socioeconomic position (SEP). The aim of this study was to explore comprehensively the role of individual-level SEP in the associations between specific types of mental disorders and mortality (due to all causes, and to natural or external causes), presenting both relative and absolute measures. This was a cohort study including all residents in Denmark on January 1, 2000, following them up until December 31, 2020. Information on mental disorders, SEP (income percentile, categorized into low, <20%; medium, 20-79%; and high, ≥80%), and mortality was obtained from nationwide registers. We computed the average reduction in life expectancy for those with mental disorders, relative and absolute differences in mortality rates, and proportional attributable fractions. Subgroup analyses by sex and age groups were performed. Overall, 5,316,626 individuals (2,689,749 females and 2,626,877 males) were followed up for 95.2 million person-years. People with mental disorders had a shorter average life expectancy than the general population regardless of SEP (70.9-77.0 vs. 77.2-85.1 years, depending on income percentile). Among individuals with a mental disorder, the subgroup in the top 3% of the income distribution had the longest average life expectancy (77.0 years), and this estimate was lower than the shortest life expectancy in the general Danish population (77.2 years for individuals in the bottom 6% income distribution). The mortality rate differences were larger in the low-income than the high-income group (19.6 vs. 13.3 per 1,000 person-years). For natural causes of death, a socioeconomic gradient for differences in life expectancy and mortality rates was observed across most diagnoses, both sexes, and all age groups. For external causes, no such gradient was observed. In the low-SEP group, 10.1% of all deaths and 23.7% of those related to external causes were attributable to mental disorders, compared with 3.5% and 8.7% in the high-SEP group. Thus, our data indicate that people with mental disorders have a shorter life expectancy even than people with the lowest SEP in the general population. The socioeconomic gradients in mortality rates due to natural causes highlight a greater need for coordinated care of physical diseases in people with mental disorders and low SEP.

The results reported by Leung and colleagues corroborate previous studies and illustrate that the inaccuracy of life expectancy (LE) prediction is transversal among physicians, regardless of their specialty or years of experience.1–4 Although their conclusion stated that respondents tend to underestimate LE, interestingly, their results also showed that for patients with short LE (<10 years), respondents were more likely to overestimate LE rather than underestimate. For example, for the single patient with LE <5 years, virtually all respondents overestimated his LE. Similarly, for patients with short LE, inaccuracies of LE’s estimation ranged from 10 to 15 years apart from the actual LE, and were frequently overestimated. Finally, the report shows that when LE estimation was simplified to a dichotomous dilemma, the actual 10-year LE represented the most difficult cut-off to estimate, reflecting an uncertain grey zone between the most sick and healthy patients, and where probably most prostate cancer patients would fit in. However, does accuracy of LE really matter? Yes. Clinicians need the most accurate estimates of LE in situations in which there is uncertainty regarding the need for screening and/or aggressive local therapy. These situations may include patients diagnosed with low-risk or moderate-risk prostate cancer in which LE of candidates for attempted curative therapy should not be less than 10 years. Obviously, addressing the issue of LE only tackles part of the problem; even some patients with excellent LE do not need aggressive therapy for low-risk disease. Life tables, well known in the life insurance industry, are the oldest and possibly the most widely accessible scheme for prediction of individual LE. They represent an average prediction of the remaining life years based on sex and age characteristics of a group of individuals. Moreover, life tables reflect population-specific characteristics. However, their ability to predict individual patients’ LE, except for a few studies, is largely unknown.5 Reports have shown that LE in men of the same age differs significantly according to their overall health status. For example, 70-year-old men could have up to 11.3 years of LE disparity based solely on their comorbidities.6 Currently, apart from empiric LE predictions based on life experience and personal belief, various tools can assist physicians in the process of LE estimation in prostate cancer patients. These consist of life tables from Statistics Canada, comorbidity indices (i.e., Charlson Comorbidity Index) and multivariate prognostic models (i.e., nomograms).7–9 Accuracy of these models ranges from 68% to 84%, but unfortunately most of these tools lack of external validation and are frequently unknown in regular clinical settings. Physicians may unfortunately tend to rely solely on their clinical experience and, according to Leung and colleagues,1 they will largely miss the target one out of three times. What are the consequences of LE estimation inaccuracy? LE estimation is critical in low-risk prostate cancer management since it justifies screening strategies and delivery of definitive therapy. Although prevalent, death from prostate cancer is relatively rare in patients with low-risk disease within a 10-year period after diagnosis. Any treatments for patients who would die from other-cause or competing-risks before reaching the 10-year cut-off may be considered overtreatment and a “failure to deliver treatment benefits.” If the potential benefit of any curative-intent therapy does not bring about longer LE there is no true effectiveness of the therapy in term of overall survival. This point is even more striking when morbidity, mortality, quality of life issues and costs for the health care system are taken into account. Finally, LE estimation in men with prostate cancer remains a complex task. Assistance with models and statistical tools can improve its accuracy. In an era of computerized data and digitalized charts, clinicians should be able to easily access local databases for long-term monitoring of LE estimations and ultimately improve patient selection. In the future, health-quality metrics for treatment effectiveness may need to include LE estimations accuracy at diagnosis, especially for patients with low-risk disease prostate cancer.

Quantitative Aspects of the Economic Growth of Nations: VIII. Distribution of Income by Size

Study ObjectivesMillions of Americans obtain insufficient sleep daily, yet it is unknown the relationship between sleep and life expectancy by county across the United States.MethodsUsing the 2019–2025 Centers for Disease Control and Prevention Behavioral Risk Factor Surveillance System surveys, we tested the associations between insufficient sleep and life expectancy at the county level while controlling for common adverse health behaviors (i.e. smoking, diet, and inactivity) across multiple years (2019–2025).ResultsInsufficient sleep was significantly negatively correlated with life expectancy in most states from 2019 to 2025, such that lower sleep insufficiency was associated with longer life expectancy. Moreover, sleep insufficiency was significantly associated with lower life expectancy when controlling for traditional predictors of mortality, with only smoking displaying a stronger association.ConclusionsThese findings demonstrate the importance of adequate sleep in all communities regardless of income level, access to health care services, or geographical classification.Statement of SignificanceInsufficient sleep is a common daily occurrence, yet the impact of insufficient sleep on life expectancy at the county level of the United States is unknown. Understanding this relationship at the county level can illuminate possible inequities between neighboring areas and allow for local leaders to make informed decisions for public health initiatives, while highlighting the impact of poor health outcomes consistent across the United States. We find that across the United States, while taking into consideration common behavior factors associated with mortality, insufficient sleep is significantly associated with shorter life expectancy, thereby highlighting the importance of sleep regardless of income level, access to health care services, or geographical classification.

Several studies reported that patients with acute myeloid leukemia (AML) who remain in long-term remission after allogeneic or autologous transplant have a shorter life expectancy, compared to the general population. However, little is known about the life expectancy of adult long-term survivors of AML who were treated with chemotherapy alone without a transplant and there have been no comparisons with survival among the general population. The current study indicates that the life expectancy of AML patients who achieved and maintained CR for at least 3 years is shorter than expected for age in the US population. This was observed also in patients who did not undergo a transplant including those who have not relapsed during the entire long follow-up period. Thus, late relapse does not explain why patients without transplants have a shortened life expectancy. Taken together, these data strongly suggest that prior chemotherapy for the underlying AML is at least a major contributing factor for the known shortened life expectancy post-transplant.

The hypothesis that certain demographic social and economic development factors independent of family planning program efforts can influence fertility decline was examined using survey data from 83 less developed countries. Independent variables included economic development (GNP per capita and energy consumption per capita) social development (adult literacy and life expectancy) urbanization and family planning program effort. The crude birthrate (CBR) was used to measure fertility. The 1970 level of social and economic development was correlated with change in fertility between 1960 and 1980. The 1974 measure of national family planning programs was also used in the analysis. A much stronger relationship was found between the CBR and social development and family planning effort than was found for economic development. The association of urbanization with fertility was stronger than that for economic development but weaker than the social or family planning program development indicators. Identical mean CBRs were found in the Asian (34.2) and Latin American (34.3) countries in the study. However in Asia family planning effort was higher and in Latin America levels of social and economic development were higher. Literacy and especially life expectancy showed consistently stronger zero-order correlations with family planning effort than either of the economic development indicators or urbanization. Family planning effort and literacy were always significant predictors of the 1960-80 change in CBR. These results suggest that policies to reduce fertility should concentrate simultaneously on increasing literacy improving health conditions and strengthening family planning program efforts. Moreover the finding that fertility is sensitive to certain measures of development and not to others indicates that separate measures of social and economic development can be isolated.

Spiritual care for patients' quality of life (QOL) and hope should be included in home medical care for patients with limited life expectancy. This study aimed to analyze the associations between estimated life expectancy, QOL, and hope among patients receiving home medical care in Japan. This multicenter cross-sectional study involved 29 home medical care facilities in Japan. Patients were categorized by estimated life expectancy, as assessed by home medical care physicians. The outcomes were QOL measured via the Quality-of-Life Scale for Elderly Patients Receiving Professional Home Care (QOL-HC: higher score indicates better QOL), the domain scores of health-related hope ("health," "role and connectedness," and "something to live for"; higher scores indicate higher levels of hope), and life functioning measured using the WHO Disability Assessment Schedule 2.0 (WHODAS 2.0; higher score indicates worse functioning and disability). QOL-HC scores were significantly higher in patients with shorter life expectancy (< 6 m vs. ≥ 1 y, adjusted mean differences: 0.7 points [95%CI 0.1 to 1.3]). Regarding health-related hope, "something to live for" scores were associated with shorter life expectancy (< 6 m vs. ≥ 1 y, -17.7 points [-34.2 to -1.2]), whereas "role and connectedness" scores did not change remarkably with shorter life expectancy (< 6 m vs. ≥ 1 y, -3.3 points [-16.4 to 9.8]). Furthermore, shorter life expectancy was associated with higher WHODAS 2.0 scores (< 6 m vs. ≥ 1 y, 19.6 points [4.3 to 34.8]). Home medical care physicians who engage in spiritual care should facilitate thoughtful dialogue with their patients by recognizing declines in life functions and hope for fulfilment, which are associated with short life expectancy.