The Global Effect of Economic Forces on Human Life Expectancy Omar J. Haque Johns Hopkins University The Woodrow Wilson Research Fellowship Class of 2013

Table of Contents Introduction .................................................................................................................................... 2 Background .................................................................................................................................... 2 Methodology .................................................................................................................................. 4 Empirical Results ........................................................................................................................... 5 Qualitative Results ......................................................................................................................... 7 Supplementary topics Multistep nature of economic development ....................................................................... 9 HIV/AIDS Predicting AIDS .................................................................................................. 15 Combatting AIDS ................................................................................................ 22 Conclusions .................................................................................................................................. 31 References .................................................................................................................................... 33

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Introduction Human life expectancy is defined as the average number of life years remaining given a certain age and is often used as a benchmark of a country’s quality of life, standard of living, and healthcare system (Sullivan and Steven 2012). Much attention has been placed in recent years on the inefficiencies of healthcare systems (such as health insurance, physician compensation, health resource allocation, and prevention strategies) when discussing human health and longevity. It is natural for people to pin the longevity of their own lives on the institutions that are responsible for treating illness. However, this research offers a different point of view. Often ignored in the discussion of life expectancy is the intimate relationship between economic forces, their influence on healthcare systems, and their role in how long we live today. Thus, the goal of paper is to discuss the global effect of socio-economic forces on human longevity, and along the way, propose policy changes that can prolong how long we spend on this earth. We hypothesized that the life expectancy of a country is heavily contingent upon the economic environment of that nation, and correcting health economic forces from a microeconomic level may be the best starting point to increase human longevity worldwide.

Background It is critical to understand that life expectancy is the expected or average number of years a person may live given a certain age (fig.1). Thus, if someone has the life expectancy of ex, it would be interpreted that person is expected to life e years given that he has already aged x years. At the time of this writing, the oldest confirmed age of any human being is 122 years (Jeanne Calment), which is the current maximum life span and upper bound of the human race. Regarding life expectancy, Japan has the highest overall quote (82.72) and Central African 2    

Republic has the lowest (45.91), with the overall world average being 67.88 (United Nations 2010). Often times, a life expectancy quote is misinterpreted or misunderstood. Since life expectancy is an average, high infant mortality and deaths in young-adults can dramatically reduce the average of a country, regardless of how healthy people who reach adulthood may be. Thus, a country with a very low life expectancy (i.e. Nigeria – 50.26) does not mean that the majority of people are drying at 50, but rather most people are drying many years before 50 or over 50. Also, the concept of life expectancy is also distinct from life span. Life expectancy is almost always a number quoted at birth while life span is simply the number of years one person lives.

Fig 1. Life expectancy quotes across the world (Bernard 2003).

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Methodology Country Selection: Countries were selected to conduct qualitative research (via interviews) in areas with very high and low life expectancies and dramatic differences in health economic infrastructure. Greece was chosen as a special case due to country’s economic instability during the time of this study (table 1).

Table 1: Country selection for qualitative research based on large variations in life expectancy and differences in healthcare system structure. Interview Selection: Faculty were interviewed based on the following criteria: graduate level degree (M.D. or Ph.D.) at a major university, full time faculty, specialized knowledge in health economics, and fluent in English. All interviews were recorded and asked if the information 4    

could be distributed for the purpose of this research. In addition, all qualitative conclusions were drawn under the tutelage of Dr. George Bowen and Mrs. Maria Chiola of Oxford University, United Kingdom. Gapminder World Statistical Analysis: Gapminder software was used to asses correlations between life expectancy and various economic factors (such as education, income/ person, health spending as a percentage of GDP, inequality, and unemployment) proposed from general expert consensus. The data Gapminder World draws from is continuously updated and techniques refined to stay in tune with recent trends in statistical analysis.

Empirical Results From our qualitative research, we proposed a group of 6 economic factors (income/person, total health spending, education, medical doctors, inequality, and unemployment) that were recurrent in conversations around the world and we believed to be correlated with life expectancy. Significant correlations were found between life expectancy vs. income/person (A), total health spending (B), education (C), and number of medical doctors (F), but not for inequality (D), or unemployment rate (E).

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Out of these economic factors, education (in terms of primary completion rate) showed the strongest correlation to life expectancy in addition to being a focal point for experts around the world in both developing and developed countries. Next, the Gini coefficient, which is a measure of inequality, showed no correlation with human life expectancy. Finally, from the results of figure F, it seems that after a country has more than 1 doctor per 1,000 people, the addition of more doctors does not cause a dramatic rise in life expectancy. However, the increase from 0 to 1 doctor per 1000 people has a dramatic influence on a country’s life expectancy. This result points to the fact that while medical knowledge is still essential to human health, after a certain 6    

threshold, the addition of more doctors does little to how long people in a country are expected to live.

Qualitative Results

Table 2: Qualitative results based on interviews with health professionals. South Africa: South Africa is currently in a state of economic growth (4%) with a very high degree of true employment and inequality. The overwhelming consensus among experts regarding economic factors that influence life expectancy hinge on education. Improving education not only increases the chances of gaining employment, but it also sheds away the 7    

ignorance, anger, and brutality that currently exists. Also, South Africa is currently experiencing a massive brain drain problem in the medical field – doctors who are trained in South Africa want to practice abroad where conditions are safer and hours are better. A possible way to circumvent this problem is to increase the number of medical schools and other healthcare profession training programs to ease the burden of doctors and give them reasons to practice in South Africa. A very strong hope for South Africa lies in the “20-20” children who have no memory of apartheid and the underpinnings of social inequality. Thus, if they can be motivated to change the face of the country, South Africa’s life expectancy could see a rise in the future. United States: The United States notoriously spends more on healthcare than any other country is the world, yet does not report the highest life expectancy rates. Recently, there has been an increased drive to level the playing field for young children entering the education system in the U.S, which could reduce the inequality still present in the country. However, some experts still believe that the U.S. has a lower life expectancy than other nations because of the diversity of the population and the health challenges that result. For this reason, working on a community level may be the best way to begin to erase these pockets of inequality and raise the overall life expectancy in the United States. France: France’s healthcare system is often regarded as one of the best in the world. The country’s economy was largely shielded from the recession, and because the healthcare system places such a strong emphasis on prevention, French citizens are on average healthier in old age. Also, some experts believe that the French are inherently risk-adverse and as a result, are more likely to partake in prevention programs that pay massive dividends in life years and decrease the burden on the nation’s healthcare system. The main area France could improve its health is with lifestyle – the country has high rates of smoking and lung cancer rates. 8    

United Kingdom: There has been talk that the U.S. should try to mimic the very efficient National Health Service (NHS) healthcare system of the United Kingdom. Doctors are not paid nearly as much in the U.K. compared to the U.S., but they do not face the same bureaucratic barriers and insurance dilemmas of U.S. doctors. The major trade off with the NHS being a single payer health service is that waitlists for procedures can be very long and the health needs of an individual are often times pre-determined by the system. Greece – Greece experienced the biggest debt reconstructing in history in 2011 and has a debt burden of 136.9% of GDP. However, the country serves as a great case study of how lifestyle choices can improve general health and longevity much for efficiently than economic changes. Despite having one of the most unstable economies and political infrastructures in the modern world, the health and life expectancy of Greek citizens did not suffer. In fact, Greece still reports a higher life expectancy than the United States. Thus, the situation in Greece shows that people are as much responsible for the longevity of their lives as any healthcare system or economic policy.

Summplementary Topics Supplementary Topic i) The Multistep Nature of Economic Development A discussion of economic forces and their influence on life expectancy is incomplete without addressing economic development and the inequality that results from growth. Economic inequality is defined as the disparity that allows certain individuals choices that are denied to others (Ray 170). Because inequality is largely an endemic issue, quantifying levels of inequality between nations can be difficult; nevertheless, four basic criteria are used to make these measurements. First, the anonymity principle states that relative levels of inequality are not 9    

dependent on who is earning income. Second, the population principle postulates that the proportions of the population that earn various incomes, and not the size of the population itself, affect relative inequality. Thus, cloning an entire population and their respective incomes should not change measured inequality. Similar to the population principle, the relative income principle states that scaling incomes up or down should not alter inequality. Finally, the Dalton principle asserts that if A and B are income distributions and A can be achieved by a series of regressive transfers, then A must have a higher degree of inequality than B (Ray, 174-178). With these methods in mind, the relationship between economic growth and inequality can be pieced apart. Fundamentally, a given distribution of wealth interacts with an economy to spawn into tomorrow’s distribution of wealth; this process repeats continuously, highlighting the fact that growth and inequality mature and regress in conjunction with one another. Work by Kuznets was one the first attempts to correlate the linkages between inequality and economic variables such as income (1955). The study used the ratio of the richest 20% of the population’s income share to the poorest 60% of the population’s income share (Kuznets ratios) as a measure of relative inequality. Despite data limitations, Kuznets study revealed that economic development is a multistep, sequential, and inherently uneven process. Growth initially advances specific groups of people, leaving the rest play catch up, increasing initial inequality (Ray 198199). The problem in developing countries is one of distribution; the initial influx of wealth caused by growth is slow to diffuse into the remaining population, resulting in social and political unrest. Also, because developing countries often have a labor surplus, wages do not rise due to growth immediately and the laws to protect labor are often missing or difficult to implement (Ray 220). Thus, economic growth without redistributive initiatives is not enough to bridge economic disparities in developing countries. 10    

The tunnel effect is the first step to understanding the initial adverse affects of economic growth in developing countries. Suppose that John is driving in the right lane of a two lane, oneway tunnel where both lanes are jammed. After a while, the left lane begins to move. At first, this will be good news to John because the left lane moving implies that traffic is clearing up ahead. However, if enough times passes with the left lane moving while the right lane remains stagnant, John’s frustration will rapidly increase (Ray 200). Hirschman and Rothschild applied this effect to the tolerance levels for inequality in income distribution due to economic development (1973). History has shown that the advent of economic growth in developing countries has been met with a wide range of tolerance from jubilance to violent protest. The tunnel effect applied to the context of growth insinuates that a citizen that sees improvement around him will assess his prospects for a similar result. Thus, if the citizen believes he will also experience improvement, then his tolerance for growth and development will be high. However, if enough time passes and the citizen’s status has not changed while others around him have experienced good fortune, the initial tolerance will change into frustration and anger. In some cases, increased inequality will not be tolerated at all if the connection between the growth of others and the individual’s welfare is weak up to the point of insignificance. The racial, social, economic, and cultural segregation that is at times apparent in developing countries further increases the likelihood of this intolerance. Therefore, the tunnel effect applied to growth implies that for developing countries, initial economic growth without redistribution will not only be unsuccessful, but can result in catastrophic political and social outcomes (Ray 200-201). While Kuznets ratios revealed the multistep nature of development, the inverted Uhypothesis attempted to take a larger leap to converge upon a general hypothesis of development (1963). The inverted-U hypothesis asserts that development (measured by per capita income) is 11    

first accompanied by rising inequality, but then these disparities ultimately wane as the benefits of development radiate to the rest of the economy. Hence, if per capita income is plotted against a measure of inequality, an inverted-U can be drawn. Because growth cannot target every single citizen in a population, fundamentally, economic development is uneven; as a result, growth will result in inequality. However, the path development takes from there is still highly debatable and gaps in the inverted-U hypothesis suggest that the model is an unsuccessful attempt to find a common law in an incredibly complex phenomenon. There are several flaws with Kuznets’ inverted-U hypothesis that indicate redistribution of wealth in developing countries resulting from economic growth does not occur naturally and levels of inequality do not naturally disappear over time. First, because there is such a deep scarcity of data in most third world countries, the inverted-U hypothesis relies on cross-section studies that examine variations in equalities across nations that are at different stages in development (Ray 202). The intrinsic nature of cross-section studies reveals a major problem when applied to development – countries greatly differ in the sociopolitical aspects of their economies, and ignoring such strong forces when analyzing an issue as complex as economic development is careless. Next, the data used to validate the inverted-U already contains large variations; since factors such as government policy are not taken account, the argument for the inevitability of inequality declining further weakens. Most importantly, by pooling various countries and conducting a regression, the statistical implicit assumption is that all countries have the same inequality-income relationship. Thus, the inverted-U postulates that not only do all countries follow the same qualitative pattern for inequality levels, but also the same quantitative pattern as well. The assumption that the income-inequality curve is the same shape for all countries, given the incredible diversity in structural parameters of society, government, and 12    

policies of different nations, is difficult to fathom. The truth may very well be that inequality does fall as economic development progresses, but the inverted-U hypothesis does not provide a clear rationalize for this occurrence. Furthermore, because no time frame is properly understood for this eventual redistribution of wealth by economic activity, the tunnel effect can take over, leading to negative views on development. The last factor that needs to be addressed concerning the relationship between growth and inequality is the possibility that the initial inequality that results from economic growth can actually retard growth before it reaches the remaining population. Empirical evidence does support this notion – regression results from Alesina and Rodrik indicated a substantial negative correlation between initial inequality (measured by Gini coefficients) and subsequent growth (1994). For example, a particularly strong statistic came from the Gini coefficient for initial inequality in land holdings; results showed that an increase in the land Gini coefficient by 1 standard deviation would decrease economic growth by 0.8 percentage points per year. Also, the LandGini coefficients are large and negative: -5.23, -5.24, -5.21 for versions 1, 2, and 3 respectively (Alesina and Rodrick 1994). Gini coefficients are particularly powerful empirical tools because they satisfy all four principles of measuring inequality and also are the ratio of the area between the Lorenz curve and the 45° line to the area of the triangle below the 45° line (Ray 189). The negative correlation between initial inequality and growth that Alesina and Rodrik postulated was further confirmed by a more comprehensive study done by Deininger and Squire (1996b), leaving little doubt about the validity of the correlation. In sum, we have seen that the fundamentals behind economic growth inherently cause initial inequality. This inequality does not necessarily decrease following an inverted-U path as development progresses. Furthermore, the initial inequality has a strong negative correlation to 13    

economic growth. To make matters worse, the tunnel effect implies that there is a limit to individuals’ patience when they see others improving while they themselves remain stagnant. This frustration can lead to social and political uprisings and even the rejection of development altogether. Thus, there is a possibility that the initial inequality caused by economic growth does not fade as there seems to be no innate tendency for inequality to disappear in the long run (Ray 241). South Africa is a prime example of how these very chain of events can lead to social resentment. The economy of South Africa can be classified as a transition economy. Thus, while there is large economic growth in parts of the country such as Sandton, other areas remain very poor. In fact, South Africa is ranked as having one of the highest income inequalities in the world (Human Development Report 2008.) This finding is worsened by the scars from apartheid; the whites in the area feel they are paying for the mistakes of past generations while blacks argue that they entitled to an equal share of the wealth. Due to the lack of distribution of wealth in conjunction with the tunnel effect, the uneven growth in South Africa has burdened the healthcare system. Dr. Flavia Senkubuge, a professor and doctor at University of Pretoria School of Public Health discusses that a major obstacle the South African healthcare system has to face is the Quadruple Burden of Disease. One of these burdens that continue to stress the health system is medical treatment for violence and injuries. Because of the alarming number of homicides and car accidents, beds in some hospitals have become scarce. Dr. Flaiva states that there is more to the problem; the nature of the crimes and attacks South Africans inflict upon one another is especially malicious and continues to shock ER doctors and nurses (2011). Dr. Nara Monkam, an economist at the University of Pretoria, argues that economic income inequality is behind this anger. She states that some South Africans 14    

cannot understand why they are so destitute while others around them have amassed incredible wealth. Even after apartheid ended, the wealth was still not fully redistributed– now, these inequalities are emerging as anger, resentment, and violence, straining the healthcare system (2011). The case of South Africa’s inequalities and the social attitudes that have resulted screams the point that economic growth alone is not the answer to equalize the world. While data is scarce and methods to measure inequality, growth, and incomes will never be fully comprehensive, violence, child homicide, rape, demonstrations, and protests in third world countries should alert people that more needs to be done. Specifically, the understanding that economic growth in low-income countries requires distribution policies to combat the initial rise in inequality is critical to reap the positive benefits of economic development. Only then can the inequality gap begin to be bridged in the developing world.

Supplementary Topic ii) Predicting the impact of HIV/AIDS Acquired immune deficiency syndrome (AIDS) is a disease of the immune system that is caused by the human immunodeficiency virus (HIV) and one of the leading causes of the low life expectancy rates in Africa and around the developing world. In recent years, it has become important to be able to predict the nature of AIDS. There are numerous ways HIV can be transmitted: anal, oral, and vaginal sex, hypodermic needles, childbirth, exchange of fetal and maternal fluid during pregnancy, breastfeeding, or any exchange of bodily fluid that contains the virus. AIDS has been classified as both an epidemic and in recent years, a pandemic; an epidemic is defined as a sudden outbreak of a disease within a country or region while a pandemic is an epidemic of infectious disease that has spread to numerous countries around the 15    

world and plagues a large number of people (Youngerman, 326-328). The global impact of HIV/AIDS is unprecedented; HIV has killed 25 million people and infected 33 million more, many of whom will develop AIDS and die before being treated (UNAIDS 2007). However, the news is not all grim; in the developed world, HIV is no longer a death sentence and treatments, while costly, effectively suppress the infection (Singer, 72-73). Therefore, the HIV/AIDS pandemic is as much an economic distribution problem as it is a medical one, and predicting the impact of AIDS in the years to come for policy decisions has never been more important. There is currently a divide in evaluating the accuracy of epidemiological models in forecasting the impact of HIV/AIDS – one side believes that these models overstate the impact of the AIDS pandemic (Young 2005) while others believe that predictions on the impact of AIDS in the future are too modest (Bell et al. 2003). To piece apart this debate first requires an analysis of the epidemiological models themselves. Next, we evaluate the accuracy of these models with economic theory on the impact of AIDS. Finally, the validity of our interpretations will be tested with empirical evidence from the United States and South Africa. This analysis leads to the conclusion that epidemiological models understate the impact HIV/AIDS will play in the future and highlights the necessity to not underestimate the impact of the HIV/AIDS pandemic. The two most widely accepted HIV/AIDS epidemiological models are the mathematical model and the backcalculation model (Nishiura 2007). The mathematical model explores the population dynamics of HIV/AIDS and is constructed from the bottom up; this approach creates a stronger understanding of the qualitative patterns of disease transmission dynamics. In the model, the initial rate of growth of an epidemic is largely contingent upon the transmission coefficient r, the peak of the epidemic depends on an initial fraction at risk fo , and the likelihood of the epidemic stabilizing depends on the strength of the changes in recruitment to the 16    

population at risk in response to AIDS deaths (determined by φ). The three values, r , fo , and φ, along with the start time of the epidemic, are estimated from local seroprevalence (the level of a pathogen in a population) estimations. However, the time periods between HIV contraction and death, birth rates, and death rates are estimated separately. It is important to note that because this HIV model is meant to be universally applicable and is based on observational outcomes, it does not provide knowledge into intervention strategies (Garnett 2002). The second common HIV/AIDS epidemiological model is the backcalculation model, a more statistical approach to measuring aids prevalence. The model has the ability to reconstruct past rates of HIV, assess current frequency of HIV infection, and estimate future incidence of AIDS. Backcalculation utilizes the statistical distribution of incubation period, defined as the time between infection and diagnosis. As a result, the model depends on assumed incubation distribution, the distribution of infections, and the counts of AIDS diagnoses over time (Bacchetti et al. 1993). The HIV curve is drawn using AIDS incidence and incubation period, allowing for short-term projections. The backcalculation model is often applied to industrialized countries where the history of AIDS incidence can be confidently reported and diagnosed. An advantage of backcalculation is that it allows for the distribution of age at HIV infection to vary over time, since younger age is linked with slower AIDS progression; however, the model has yet to provide reliable, consistent predictions for long-term AIDS incidence (Rosenburg 1994). With a basic understanding of the two basic epidemiological models used to measure future HIV incidence, we now shift our attention to the economic theory behind predicting the future impact of AIDS and how these implications could affect epidemiological models. The stance that the impact of AIDS will be less severe than economic models suggest stems from a particular strain of economic logic. According to this view, AIDS-induced mortality reduces the 17    

strain on population with regards to land and capital, raising the productivity of labor. Even if investment and saving decline as the population spends more on medical care, the negative impact on GDP growth is stifled by the increase in labor productivity. These countervailing forces result in a highly modest prediction of the impact AIDS will play on per-capita GDP (Bell et al. 2003). However, when the theory of human capital and the transmission of AIDS across generations is emphasized, the long-run economic costs of AIDS end up being much higher than models predict. Human capital, defined in this context as the accumulations of investments in people such as knowledge and abilities (Mankiw, 578), plays a major role in long run economic growth. Furthermore, the mechanism that drives this progression is the transmission of ideas, abilities, and knowledge from one generation to the next. A HIV/AIDS pandemic breaks this chain of knowledge, resulting in a substantial stagnation of economic growth and in some developing countries, economic collapse (Ray 119-120). The logical progression of how AIDS impedes economic growth can be made in three steps. First, AIDS selectively destroys existing health capital stock; specifically, young adults are the prime candidates. After becoming infected, young adults lose their productivity and often die in their labor-prime. Thus, the human capital lost from their deaths lies in high-level education, acquiring job-related abilities, and child-rearing. Next, AIDS devastates the mechanism that creates human capital. In a given household, the successful birth and upbringing of a child is largely dependent on the human capital of the patents, both in terms of health and education. Thus, if AIDS takes the lives of one or both of an offspring’s’ parents, the transmission of human capital is weakened across two generations: the offspring and the offspring’s children. Income reductions from the death of a parent can also result in adolescent children leaving school to take 18    

jobs. Finally, the chance children will contact the disease once they reach adulthood makes investment in human capital (i.e. education) less appealing, even if both parents are HIV negative. It becomes clear from this analysis that the manner in which AIDS weakens the transmission of human capital is insidious; the effects are only felt over the long run since poor education today results in low productivity of adults a generation later. Lastly, AIDS weakens economic growth because the children of AIDS victims are not only less likely to invest in their own self capital, but also in the education of their offspring (Bell et al. 2003). With the inclusion of this third step, a vicious cycle emerges: AIDS destroys the productivity and human capital of young adults. These young adults who die from AIDS leave behind children with limited income and access to education. When these children of AIDS victims grow up, they are less inclined to invest in the human capital for their own offspring, perpetuating the cycle of human capital loss and decreased productivity. The presented argument implies that in order to assess the long-term effects of AIDS, the relationship between human capital and economic growth must be thoroughly analyzed. The decision on how much to invest in education is influenced by premature adult mortality; the family’s lifetime income becomes contingent upon the adults’ health status and the expected return on the investment depends on the level of premature mortality among the children once they reach adulthood (Bell et al. 2003). AIDS clearly leads to an increase in premature mortality and if the levels of HIV/AIDS reach high levels, the step-wise reduction cycle of human capital and productivity can derail an economy. Because current epidemiological models do not place enough emphasis on these economic factors, their underestimation of the impact AIDS will play in the future can lead to bad health policy for future generations; empirical evidence supports this claim. 19    

In the case of the United States, models of HIV/AIDS under-predicted the levels of AIDS incidence (Nishura 2007). The data from figure 1 shows a model that assumed a normally distributed epidemic curve (black line) using data up until the dashed line to make the prediction (Bregman and Langmuir 1990).

Fig. 1. Observed and Predicted AIDS incidence in the United States from 1981 – 2003 (CDC 2004).

The problem that occurs with HIV/AIDS models is that they attempt to apply a purely epidemiological approach to a highly complex economic, social, and political problem; AIDS is not solely a medical concern; in fact, scientific research has made tremendous advances in preventative drugs and novel treatments for HIV. The issue again lies in the distribution and costs of these treatments. For example, in rich nations such as the U.S., the cost for HIV drugs is about $10,000 per year. This price range however is far out of reach for most people in subSaharan Africa, where the incidence of HIV/AIDS is much higher. Some African countries have attempted to implement compulsory licensing of HIV/AIDS drugs to lower costs for citizens; even these efforts at locally manufacturing drugs have not dropped the price low enough for many Africans, many whose annual spending on healthcare is less than $10 (Singer, 71-73). South Africa is another prime target to test the predictive capability of epidemiological models for HIV/AIDS. The country has the most developed economy and health care sector in sub-Saharan Africa. Yet, the AIDS pandemic has grown there at an alarming pace with 20    

prevalence among 15-49 year-olds spiking from 1% in 1990 to 20% by 2000 (UNAIDS 2002). In the absence of the AIDS epidemic, South Africa would have experienced substantial growth per capita income. Instead, the country could now be moving towards a quiet, yet progressive economic recession (Bell et al 2003). The issues concerning AIDS in South Africa highlight the political and social aspects of the disease that epidemiological models are unable to capture. Many critics have accused President Thabo Mbeki and his administration for through denial and backward policies concerning AIDS. For example, in 2000, President Mbeki consulted with many scientists who denied that HIV causes AIDS. To further complicate matters, the President went on to appoint several people who shared this stance to his presidential AIDS advisory panel. These types of stories highlight the doubt, poor education, and poverty that has surrounded AIDS in Africa and help explain why the pandemic has hit Africa particularly hard (Youngerman, 71-74). Also, it becomes clear that prevention measures must take into account local culture and behavior patterns; factors that are incredibly difficult to incorporate into generic epidemiological models. Our examination of the epidemiological models of HIV/AIDS, coupled with economic theory emphasizing human capital, leads to the conclusion that these models under-predict the impact of AIDS in the years to come. Comparing this deduction with empirical evidence from the U.S. and South Africa revealed key flaws in epidemiological models. With regards to the U.S., data is abundant and accurately recorded, but models still underestimate the future effect of AIDS, revealing that even with precise data, key assumptions and underlying factors are missed. When analyzing the case of AIDS in South Africa, the fact that the pandemic is not just a medical concern is emphasized. There are several political and social factors that generic models simply cannot account for that play a large role in the long-run impact of AIDS. 21    

Finally, numerous policy implications result from these conclusions. The first aspect, which is fiscal by nature, states that because AIDS kills many young adults, the pandemic weakens the tax base. As a result, the resources available to meet the demands for public expenditures such as education and health services decrease. Second, AIDS worsens inequality; the weakening of the generational transmission mechanism will result in inequality of the next generation of adults and the families they create. Lastly, AIDS results in an increase in premature mortality that can result in the collapse of an economy; thus, policy should aim to avoid this occurrence. The tools to combat such an event are spending on measures to contain disease and treat the infected, helping orphans have access to education, and taxes to finance benefit programs (Bell et al. 2003). By not underestimating the impact of AIDS and realizing the disease is more than a medical concern, future generations will be better equipped to fight this pandemic and being to contain its multifaceted adverse affects that still plague many areas of the world.

Supplementary Topic iii) Combatting Aids from an International Prescriptive Due to the global effect of human immunodeficiency virus (HIV) and the resulting acquired immunodeficiency syndrome (AIDS), the world’s first line of defense against this pandemic lies in the interlocking and cooperation of multinational institutions. Specifically, agencies created by the United Nations (UN), non-governmental organizations (NGOs), and drug companies have played major roles in the fight against HIV/AIDS. Although these institutions did significantly contribute to AIDS prevention and treatment, major flaws in the global response to HIV/AIDS within these organizations resulted in the deaths of millions of people inflicted with AIDS. An analysis of the efforts the UN, NGOs, and pharmaceutical companies enacted in the fight against HIV/AIDS is critical not only to improve the world’s containment of the 22    

disease, but also to avoid the same mistakes in the case of future pandemics. First, the manner in which multinational organizations combatted AIDS will be investigated, highlighting both positive and negative attributes. After understanding the strengths and weaknesses of the multinational institutional response to HIV/AIDS, deductions concerning what should have been done can be isolated. Finally, these deductions help form a standard for how the UN, NGOs, and pharmaceutical companies should cooperate in the future to fight pandemics. From the following analysis, it becomes clear that while UN agencies and NGOs have made strides in AIDS treatment and prevention, they are limited by funding and human labor. Pharmaceutical companies on the other hand have incredible power to transform the face of HIV/AIDS but are incentivized to maximize profits over seeing global health improve. If HIV/AIDS is to be eradicated and a basis for tackling future pandemics established, the economic incentives of multinational institutions as a whole must be rearranged to prioritize human health. In 1946, the UN founded the World Health Organization (WHO) during a period of international cooperation following World War II. The mission of the WHO, which was headquartered in Geneva, was “the attainment by all peoples of the highest possible level of health” (Youngerman, 22). By the 1960s, the WHO had evolved into one of the world’s public health authorities. However, upon realizing that the traditional approach of relying on international sanitary regulations to limit the spread of epidemics was ineffective, the WHO moved to a new model that was adopted in 2005 and implemented in 2007. These changes placed greater emphasis on preventive measures within countries and required reporting a wider range of diseases. With the advent of the AIDS epidemic in the 1980s, the UN created UNAIDS in 1995 to address the issue. Separate from the WHO, UNAIDS was a joint UN program that coordinated the work of ten other UN agencies (Youngerman, 22-23). 23    

The synchronization between different UN agencies was strong, leading to positive steps in combatting HIV/AIDS. For example, the WHO helped coordinate disease outbreak information via an online collection called WHONET that monitors evidence of resistance to antibiotics and other medicines. Another strong change UN agencies took in the new model against global health epidemics was a movement towards decentralized, entrepreneurial work at the local level. This shift, linked by complex international funding and information networks such as WHONET, encouraged healthy competition and creativity, widening the support base for HIV/AIDS volunteers and contributors (Youngerman, 23-24). Next, the disease control priorities project (DCPP), launched in 2001 by the WHO in conjunction with the National Institutes of Health and the World Bank, was aimed to generate knowledge to assist decision makers in developing countries. Specifically, the project was targeted at health policy in the public sector to find affordable, effective interventions to rapidly improve welfare in destitute populations. The work was incredibly successful in identifying policy changes and intervention strategies for the health problems of low-income and middle-income countries for HIV/AIDS. The DCPP used disability adjusted life years (DALYs) as the primary measure of disease burden (Laxminarayan et al., 2006). DALYs are used in health economics to compare the burden of different ailments across countries; they take into account not only the lives lost through disease but also the number of years of disability caused (Kremer 2002). The DCPP found that for low-income countries, high-income countries, and world wide, the DALYs for HIV/AIDS were 5.1, 0.4, and 4.7 (Laxminarayan et al., 2006). The 4.7 DALY difference between HIV/AIDS for high and lowincome countries pointed towards a problem in distribution over medical knowledge. However, the DCPP proposed that cost-effective interventions do exist. For prevention, results from the DCPP called for peer-based education for high-risk groups ($1-74 per DALY averted), voluntary 24    

testing and counseling ($14-261 per DALY averted), social marketing distribution of condoms and promotion ($19-205 per DALY averted), and improving the safety of blood and needles ($451 per DALY averted). Antiretroviral treatment on the other hand was more expensive ($10-500 per DALY averted); however, the cost effectiveness of treatments was affected by drug prices, which will be addressed further on (Laxminarayan et al., 2006). UN agencies, despite strides in prevention and treatment policies, had their flaws. Some economists have argued that the creation of UNAIDS as a distinct organization led to inefficiency and distorted incentives. They argue that when the UN decided to form UNAIDS, they overestimated the incidence of AIDS in East and West Africa. However, economic models for predicting the future incidence of diseases, especially the HIV/AIDS pandemic, have not always been accurate. Also, the WHO experienced problems with bureaucracy, inadequate enforcement of power, lack of funding, and politics. The new model that UN agencies utilized, focusing more on change at a local level, had shortcomings as well. Because work was decentralized, entrepreneurial, and community driven, it suffered from the duplication of efforts in the same area, economic inefficiency, entrepreneurial amateurism, and a lack of influence due to numerous independent groups having their own entrenched beliefs. Time has yet to show if the benefits of the WHO and UNAIDS outweigh the costs (Youngerman 24-29). Along with UN agencies, NGOs also played a large role in combatting HIV/AIDS. NGOs are part of the non-profit sector, an area that has grown increasingly important in fighting societal problems and injustices. As the name implies, NGOs are private organizations that work outside of the government to address causes or interests. They are held together by common beliefs and shared values instead of political imperatives (government) and consumer incentives (commercial sector). The expansion of NGOs, labeled the “barefoot revolution,” can be 25    

attributed to the end of the Cold War, technological developments, and growing resources. With the demise of the Cold War came an end to ideological orthodoxy; as a result, the UN became a forum for interactions between governments and NGOs. Second, technology increased the flow of information between groups, driving the formation of multinational organizations that had certain global missions. Finally, the growing resources of NGOs, from individual donors, governments, and the UN, have facilitated the growth of these organizations by increasing capability, cost-effectiveness, and reputation (Sethna 2003). The nature of NGOs gave them several advantages over governments when tackling the problem of HIV/AIDS. Because of the local manner in which HIV was transmitted, the strong experience of NGOs in working at the community level paid dividends. Also, NGOs were autonomous and as a result, were not shackled by governmental regulations and party incentives; therefore, they responded to the needs of locals much more quickly. Third, NGOs acted as a bridge between the community and the national level. They often were able to employ innovative methods that were both cost-effective and area-specific (Sehgal 1991). For these reasons, the role of NGOs in the treatment and prevention HIV/AIDS cannot be overlooked. Specifically, NGOs set trends that became institutionalized in the field of AIDS prevention. These trends were advocacy for HIV/AIDS patients, distribution of education materials to specific groups, peer education, and improved access to drug trials and treatments. Also, with the emergence of NGOs as significant forces in the fight against AIDS, the WHO and UN developed links with NGOs, creating a more unified front against the disease. NGOs also faced less bureaucracy and conducted their services more openly regarding sensitive issues such as sexual orientation and condom use compared to governmental agencies. Next, NGOs were often staffed by members of the community, creating credibility and understanding among the people whom the NGOs were 26    

serving. As a result, more members of a community were likely to attend preventive care clinics, change their attitudes, and alter their behavior (Sethna 2003). Despite the unique attributes NGOs possessed regarding HIV/AIDS, they had numerous limitations. Smaller NGOs simply could not meet the demand and large-scale budgeting of an issue as global and widespread as AIDS. This circumstance reduced the likelihood that a certain NGO would receive funding from a donor. Next, due to their limited in-house technical capacity, NGOs were limited to simpler projects. Also, because the staff of an NGO was usually underpaid, along with the possibility that the entire organization was underfunded, NGOs ran the risk of burning out. For this reason, they attempted to find the capricious balance between paid and volunteer staff; this feat was often very difficult in the physically and emotionally taxing field of ground-level AIDS research. Lastly, some highly effective NGO initiatives went unnoticed or were not reproducible on a larger patient scale (Sethna 2003). Finally, the role of pharmaceutical companies in combatting AIDS became a perennial issue ever since HIV/AIDS drugs were developed. In general, pharmaceutical companies are multinational firms that develop, produce, and market licensed drugs in both generic and/or branded forms. The first drug on the market to treat HIV/AIDS was AZT (zidovudine); it was sold under the brand name Retrovir and manufactured by the pharmaceutical company Burroughs Wellcome, later taken over by the British firm, GlaxoSmithKline (Angell, 24-27). While there was no doubt that these organizations brought significant health benefits to developing countries, pharmaceutical research and development (R&D) for health problems specific to poorer countries was deficient. This aspect becomes even more unfortunate in today’s world where modern medical technologies allow for tremendous improvements in HIV/AIDS health in low-income countries (Kremer 2002). 27    

The issues in response with drug companies and AIDS treatments were two fold. First, pharmaceutical companies, unlike governments, UN agencies, and NGOs, were profitmaximizing firms. Second, due to the poverty in developing countries, the pharmaceutical industry of developing countries was fundamentally different. First, developing countries had a smaller market for pharmaceuticals compared to the developed world. They also resided in a different disease environment, where infectious and parasitic diseases were more prevalent than noncommunicable conditions. Next, pharmaceuticals in developing countries were also misused due to the fact that medical personnel were scarce. For example, in Sub-Saharan Africa, there was 1 physician per 10,000 people (World Bank, 2001b). Due to this scarcity of qualified medical professionals, self-prescription became very common. Based on these issues, there was a call for developed nations to provide pharmaceuticals to the developing world. The issue and frustration now is caused by the lack of accessibility of these pharmaceuticals to the developing nations of the world (Kremer 2002). Taken together, profit-maximizing drug companies in the distorted pharmaceutical market of the developing world led to severe economic distribution problems, leaving millions of AIDS patients dead without having ever had access to treatment. In the end, drug companies were reluctant to invest in developing countries because their potential revenue was far smaller than the sum of what customers had the ability to pay. For example, in 2003, South Africa’s Competition Commission ruled that GlaxoSmithKline, a major manufacturer of HIV/AIDS medication, had violated the country’s Competition Act. The accusation was centered on GlaxoSmithKline charging excessively high prices and refusing to license their patents to generic manufacturers in return for royalty payments. After the ruling, GlaxoSmithKline allowed four South African drug companies to make three of its AID drugs and sell them to all of sub-Saharan 28    

Africa. While the price of AIDS treatment in Africa dropped to $300 a year, few believed that drug companies took a huge loss considering that they made $10,000 a year per AIDS patient in the United States (Angell, 206-208). While there has been a tremendous global initiative from multinational organizations to fight HIV/AIDS, much more should have been done by these organizations. To fully understand where multinational institutions fell short, the history behind HIV/AIDS must be assessed. AIDs was first documented in 1981 by investigators in New York and California. Initially, most US AIDS cases were homosexual men or intravenous drug users. By 1983, researchers had isolated HIV and recognized the virus as the agent behind AIDS. HIV/AIDS spread to epidemic proportions during the 1980s, especially in sub-Saharan Africa where the disease may have originated. By 2002, AIDS had claimed over 25 million lives around the world (Sethna 2003). Clearly, any pandemic that takes 25 million lives over the course of 22 years was not met with the proper international resistance. When AIDS first came on the medical scene, emphasis was on finding a cure instead of preventative measures. Only recently did the WHO and UNAIDS move towards more preventative aspects. In the future, combatting epidemics cannot hinge on finding a cure; as HIV/AIDS has shown, even if effective treatments are in existence, they will not resolve the problem without a global infrastructure in place to distribute these treatments. Next, the AIDS epidemic was originally met in some developing countries with doubt (i.e. South Africa). HIV/AIDS has opened up minds around the world to the destruction disease can cause; nevertheless, ignorance should also be combatted immediately in the form of educating high-risk populations. Third, as the pharmaceutical industry has shown, pandemics are rarely purely a medical concern. Social, political, and economic factors will always play a role in combatting global disease; for this reason, it is imperative that multinational institutions, the first 29    

line of defense against epidemics, work in unison with the proper economic incentives. A major issue that was touched on earlier was the profit-maximizing nature of pharmaceutical companies and how this behavior was not in the best interest of global health. Therefore, it was no coincidence that NGOs, the WHO, and UNAIDS cooperated well with each other while drug companies were always under social and political fire for their profit-incentivized actions. It is important to recognize that drug companies were acting like any other profit-maximizing firm would in a market; the issue was that the market was health - an area riddled with strong emotions, a sense of entitlement among humanity for basic health, and nonprofit organizations. Therefore, pharmaceutical companies require regulation to align their priorities with those of the rest of the multinational institutions in regards to fighting HIV/AIDS. In conclusion, by analyzing the roles of the WHO, UNAIDS, NGOs, and pharmaceutical companies played in response to the AIDS pandemic, it becomes clear that there was a lack of coordination and cooperation in the global effort to combat HIV/AIDS. While the WHO, UNAIDS, and NGOs took positive steps by localizing their efforts, the lack of funding and human resources inhibited their global impact. What these organizations did do incredibly well was evaluate the burden of HIV/AIDS across nations and purpose cost-effective methods of prevention and treatment. Pharmaceutical firms on the other hand made large profits and had tremendous power in treating and preventing the HIV/AIDS pandemic; however, due to their profit-maximizing behavior, drug companies failed to prioritize the health of people in the developing world where they were unlikely to make a large profit. Even when social and political pressure forced drug companies to settle and lower prices, the changes were not large enough to directly influence the citizens of low-income countries. From this picture, it becomes apparent that the tools to fight AIDS in terms of policy, treatment, and prevention exist. Now, the 30    

battle against HIV/AIDS requires drug companies to turn their incentives away from profitmaximization and towards health regarding HIV/AIDS drugs. There needs to be a global movement among governments and other multinational institutions that fight AIDS to change the infrastructure of the pharmaceutical industry specifically for AIDS treatment and prevention. Not only will this change create cohesion between drug companies and other multinational organizations, but also will equip humanity with a basic formula for policy changes in the event of another epidemic.

Conclusions From both empirical and qualitative results, it is very clear that many economic forces play a factor in human life expectancy, and these forces are as important to understand as the health systems they regulate. Education, whether it is in the first world or third world, seems to be a common theme in improving human longevity and breaking away from the prejudices and violence in the world. Also, lifestyle choices are as pivotal to human health as the strength of an economy or the quality of medical care. Life expectancy showed a positive correlation with income/person, total health spending, education (primary school completion rate), and number of medical doctors per 1000 people. These four factors are strong starting points to begin to rectify the health economic problems of nations in an effort to increase life expectancy. Next, health economic interventions should utilize micro-economic community level approaches since every nation, city, and community has its own health nuances that are very difficult to account for abroad and predict using a top-down approach. Bottom-up approaches can utilize aid with the help of community leaders, and trust can be built between the giver and receiver or clinical treatment. Finally, and perhaps most important, we as individuals are as responsible for our 31    

health and life expectancy as the healthcare systems that treat us when we fall sick. Thus, the final onus of responsibility rests with the individual, and that is precisely where health economists and doctors need to begin address the global life expectancy problem.

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