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Health economics, Applied econometrics, Epidemiological and economic simulation modeling, Impact evaluation, AIDS.
Mead Over is a senior fellow at the Center for Global Development researching economics of efficient, effective, and cost-effective health interventions in developing countries. Much of his work since 1987, first at the World Bank and now at the CGD, is on the economics of the AIDS epidemic. After work on the economic impact of the AIDS epidemic and on cost-effective interventions, he co-authored the Bank’s first comprehensive treatment of the economics of AIDS in the book, Confronting AIDS: Public Priorities for a Global Epidemic(1997,1999). His most recent book is Achieving an AIDS Transition: Preventing Infections to Sustain Treatment (2011)in which he offers options, for donors, recipients, activists and other participants in the fight against HIV, to reverse the trend in the epidemic through better prevention. His previous publications include The Economics of Effective AIDS Treatment: Evaluating Policy Options for Thailand (2006). Other papers examine the economics of preventing and of treating malaria. In addition to ongoing work on the determinants of adherence to AIDS treatment in poor countries, he is working on optimal pricing of health care services at the periphery, on the measurement and explanation of the efficiency of health service delivery in poor countries and on optimal interventions to control a global influenza pandemic.
In addition to his numerous research projects at the Center, Over currently serves as a member of PEPFAR’s Scientific Advisory Board and as a member of the Steering Committee of the HIV/AIDS modeling consortium funded by the Bill & Melinda Gates Foundation.
Recruited to the World Bank as a Health Economist in 1986, Mead Over advanced to the position of Lead Health Economist in the Development Research Group, before leaving the World Bank to join the Center for Global Development in 2006. Each spring since 2005, he has taught a module on “Modeling the Cost-Effectiveness of Interventions against Infectious Diseases” as part of the master’s degree program in health economics for developing countries at the Centre d'Etudes et de Recherches sur le Développement International (CERDI) at the University of the Auvergne, Clermont-Ferrand, France.
"Evaluating the Impact of Organizational Reforms in Hospitals," with Naoko Watanabe, Chapter 3 in A. Preker and A.Harding (eds.) Innovations in health service delivery: The corporatization of public hospitals. World Bank, March 2003
You’ve probably already heard about the pharma outrage du jour. In short: start-up Turing Pharmaceuticals, led by combative ex-hedge fund manager Martin Shkreli, recently acquired Daraprim, a 60+ year-old drug to treat a parasitic infection called toxoplasmosis – the only available treatment for this rare infection – which can become deadly for HIV+ individuals and others with weakened immune systems. Turing then promptly raised the price by more than 5000%, from $13.50 to $750 per tablet, such that a single individual’s treatment can now cost up to $634,000. Many, including prominent politicians, are understandably outraged by this “price gouging” of AIDS patients – and the political class seems highly motivated to take action.
In this case, their drive for policy change is backed by a solid economic rationale. This excellent Vox article lays out many of the issues at play in the current drug price flame war – but it doesn’t fully capture the impact of insurance. While there is no legal upper bound to the price of drugs in the US, the same is also true for shoes, cars, and croissants. The profit-maximizing owner of the exclusive distribution rights for any of these products would set its price-cost margin to the inverse of the elasticity of demand. While there is no legal price limit in the US, the profit-maximizing monopolist would be a “moron” (Shkreli’s word) to set the product’s markup price lower or higher than the inverse of its price elasticity.
The VOX article rightly points out that patients are desperate to receive the drug – without it, they will often die – implying that the elasticity of demand is very low. (In plain English, "elasticity" is just the degree to which consumers reduce their purchases in response to a price increase. A good presentation of the math behind Shkreli’s textbook pricing strategy is here.) Insurance coverage decreases the elasticity of demand even more, by lowering the effective price paid by the consumer while passing it on to others in the insurance risk pool. It is these two aspects together that distinguish demand for any drug without substitutes from demand for shoes, cars, or croissants.
But in this case, the product Daraprim is off-patent, so there should be few barriers to a firm wishing to make and sell it. ("Should" may be the operative word here; Turing seems to have taken deliberate steps to hide Daraprim from generic manufacturers in order to artificially limit competition). But to date, the only reason there are no substitutes is that few Americans need the drug. (Although toxoplasmosis used to be one of the most common opportunistic illnesses for AIDS patients, HIV infected people today who promptly begin and rigorously adhere to anti-retroviral therapy will never need this drug.) As soon as Turing decides to sell this drug at this high price, other companies could decide to make it and sell it at a lower price, stealing Turing’s market and quickly driving the price back down.
The CEO chose the price of $750, instead of a much higher price, because it is high enough to make a profit for a few months or years, but low enough to dissuade the biggest global manufacturers from immediately entering the market. The CEO knows that lower-cost generic manufacturers will soon be competing for the same clients, so this is a short-run opportunity, lasting only a few years. People who need the drug but lack insurance will be the biggest losers (AIDS patients who start treatment late are often in this category). But almost all Americans will contribute to Turing’s profits through our higher insurance premiums and taxes (for government-financed care and insurance).
Profit-maximizing ploys like this suggest that in the long-term interest of global health, private corporations require more regulation over their international pricing structure. The public deserves a say in how these firms assigns prices – and how they distinguish pricing across countries with different insurance systems and health needs (so-called "tiered pricing"). Just as utility companies best serve the public interest under government regulation for their local markets, multinational pharmaceutical companies would best serve global health under global regulation that supervises their international pricing as well as their research expenditures. Such regulation should authorize higher prices for drugs in rich countries (where we have higher incomes and health insurance) only on condition that companies give back to society in the form of research on high burden diseases and prices no higher than necessary in poor countries.
One ironic postscript of this entire saga: big pharma itself may end up among the biggest losers. Mr. Shkreli’s transparent greed and “gotcha” attitude have elicited such public outcry that politicians have been forced to take notice – and, anticipating a looming policy crackdown, biotech stock prices have plummeted. This elasticity of public response is why Mr. Shkreli, in addition to suffering the public shaming of media and Reddit attacks, may already be persona non grata among his big pharma peers – and it’s the likely explanation for his recent decision to rescind at least part of the price increase. Perhaps he’ll soon learn that he was the “moron” to dismiss so rudely and transparently the idea that something other than profit-maximization might guide the pricing strategy of a pharma CEO.
Remarkable progress has been made in the global fight against HIV/AIDS. The number of people receiving treatment in low- and middle-income countries increased from 300,000 in 2003 to 13.7 million in 2015, including 7 million supported by the United States. These gains are primarily attributable to a 2003 US government initiative called PEPFAR (the President’s Emergency Plan for AIDS Relief) that provided major new multiyear funding for global HIV/AIDS and created a new entity, the Office of the Global AIDS Coordinator, headed by an ambassador-rank Global AIDS Coordinator who is authorized to allocate PEPFAR’s resources and coordinate all US bilateral and multilateral activities on HIV/AIDS.
However, without dramatic changes to PEPFAR, the next president risks being held responsible for the failure of a program that until now has been one of the United States’ proudest foreign assistance achievements. And because PEPFAR is a major component of US foreign assistance spending, the next president’s choices about PEPFAR will heavily influence any subsequent assessments of his or her humanitarian foreign assistance policies.
In this series of briefs, Center for Global Development experts present concrete, practical policy proposals that will promote growth and reduce poverty abroad. Each can make a difference at virtually no incremental cost to US taxpayers. Together, they can help secure America’s preeminence as a development and security power and partner.
The South African government is currently discussing various alternative approaches to the further expansion of antiretroviral treatment (ART) in public-sector facilities. Alternatives under consideration include the criteria under which a patient would be eligible for free care, the level of coverage with testing and care, how much of the care will be delivered in small facilities located closer to the patients, and how to assure linkage to care and subsequent adherence by ART patients.
Last year, PEPFAR submitted guidelines which encouraged country staff to submit a proposal to conduct an “impact evaluation” (IE) as part of their annual Country Operation Plan (COP). Subsequently, they received only four submissions, of which three were funded. But they also learned that many PEPFAR staff – who are mostly program implementers, or the managers of program implementers – didn’t fully understand what they were being asked to do; what does PEPFAR mean by “impact evaluations”?
In response, PEPFAR has started to conduct impact evaluation workshops in order to support the in-country teams who want to include an impact evaluation proposal in their March 2014 COP submission. I recently had the pleasure of serving on the faculty of the first impact evaluation workshop in Harare, Zimbabwe.
What was it like for a think-tank guy like me to be involved in this exercise? It was interesting, exhilarating and pretty hard work.
Small teams of program staff came from South Africa, Tanzania, Uganda and Zambia (Zimbabwe sent a few observers). Each team included representatives from the government, from PEPFAR and from a PEPFAR implementing partner (PEPFAR-speak for a local or international contractor). Unlike the participants at most of the donor-funded workshops I have attended over the last three decades, these were extraordinarily engaged. They had all come with one or more candidate research questions, they all worked to fill out a research template, and they all attended almost every session from morning until night; often working late into the evening.
The 27 participants all had heard of many of these ideas, but few had heard of all of them. And now they needed to choose the most relevant of these for their country context and put them together in order to come up with a study design that would pass muster, first, with their constituencies back in Johannesburg, Dar es Salaam, Kampala and Lusaka, and then next March with OGAC’s Office of Research and Science.
On the way to the airport, I passed by Harare’s famous “balancing rocks.” They remind me of the task facing these PEPFAR teams. Internally valid evidence, balanced on data from a sample, balanced on the choice of an experimental or quasi-experimental method, balanced on the foundation: choice of a policy relevant counterfactual and pair of null and alternative hypotheses. The fact that the in-country teams are designing and overseeing the execution of this learning process assures that, if they carry them they will learn a lot about what makes HIV/AIDS programs work or not work. We should be seeing these studies contracted and launched within a year or so. For the sake of all the HIV infections they might avert and all the patients they might help, let's hope so.
The January 12th earthquake in Haiti is the most lethal natural disaster of the past 20 years. On February 12th, the Associated Press reported that official Haitian government estimates of the dead had been revised upwards, now reaching 230,000 dead. Furthermore, the number could be much higher, since the government admits they have not yet been able to count all the bodies and they have excluded those buried by families or in private cemeteries. As the figure below shows, this new total surpasses the 225,000 dead in the 2004 Indian Ocean tsunami, and dwarfs the death tolls from recent earthquakes in Pakistan-controlled Kashmir and Sichuan, China.
A catastrophe’s death toll can also be measured in relation to the total population. The bars in the next chart show the deaths as percentages of the total populations of each relevant area. For the 2004 Tsunami in the Indian Ocean, the largest death toll was in the Indonesian province of Aceh on the island of Sumatra, where three percent of the population died. The 80,000 deaths in the Pakistan earthquake represented .4 percent of the population Pakistan’s Northwest Frontier Province. The Chinese and Burmese catastrophes killed fewer than one percent of the populations of the surrounding areas. In contrast, the Haitian earthquake killed 11.5 percent of the approximately two million people living in the immediate area of Port-au-Prince, which comes to 2.5% of the entire national population.
So in relative terms also, Haiti’s earthquake surpasses any of these natural disasters which have occurred in other countries.
Finally one can compare the mortality from the earthquake to the mortality from other causes of death which afflict Haiti or have swept the world. The largest cause of mortality in Haiti for the last decade has been the HIV/AIDS epidemic. In 2007, the last year for which UNAIDS has published data, an estimated 7,500 people died of AIDS in Haiti. The earthquake killed 30 times that many Haitians in a few days.
Other notable worldwide epidemics have been the bubonic plague in 1350 and the 1918 influenza epidemic. The first killed somewhere between 30% and 60 % of the population of affected European countries and the second between 3% and 6% of the entire world population. Thus for Haiti as a whole, the earthquake has had a mortality impact comparable to the 1918 flu epidemic and for the most affected region around Port-au-Prince the impact is comparable in magnitude to that of the bubonic plague in a less affected country of Europe.
Students of the bubonic plague of 1350 believe that its longer term repercussions on society were profound, including a general loss of faith in religion, a loss of respect for hereditary authority in general and the state in particular, the empowerment of the middle class and increases in the ratios of capital and land to labor resulting in increased wages for the poorest. While parallels between that continent-spanning catastrophe and the much more focused event in Haiti are risky, it is not hard to believe that Haiti will be a very different place in ten years than it would have been without the earthquake. Let’s hope that it is a better place, not a worse one.
Five million people in poor countries are receiving AIDS treatment, but international AIDS policy is still in crisis. This book shows how to reach an “AIDS transition,” which would keep AIDS deaths down by sustaining treatment while pushing new infections even lower, so that the total number of people living with HIV/AIDS finally begins to decline.
This paper uses contract theory to suggest simple contract designs that could be used by the Global Fund. Using a basic model of procurement, we lay out five alternative options and consider when each is likely to be most appropriate. We ultimately provide a synthesis to guide policy makers as to when and how 'results-based' incentive contracts can be used in practice.
On September 17, the World Bank issued a preliminary report on the economic impact of Ebola Viral Disease (hereafter Ebola). (Landing page is here and report is here.) I was one of a team of fourteen people contributing to this initial effort and the only member of the group not from the Bank.
Most of the team members are “country economists” whose job is usually to monitor the macroeconomic situation in their assigned countries and to routinely feed these assessments to the rest of the Bank for designing or evaluating projects and programs. Although I thought I knew the Bank pretty well from my 20 years in its Development Economics Research Group (1986-2006), I gained a new appreciation of the skills of the country economists as I watched them gather and assemble tidbits of relevant data about how Ebola is affecting the economies of Liberia, Sierra Leone, and Guinea.
For example, the country economist for Liberia was able to gather data on cement sales (see Figure 1), which tell the story of an exhilarating construction boom in 2013, very good news for a desperately poor economy recovering from years of civil war. Then around March of 2014 cement sales dove to mid-2013 levels. Causality is murky, but it’s fair to ask whether this drop was a response to the discovery of the first West African Ebola case in neighboring Guinea. The recovery of sales the following month to a level near the previous peak suggests that investors and construction contractors had shrugged off their worry, thinking that the outbreak had been contained. But then in August, 2014, as evidence accumulated that Ebola was out of control in Monrovia, cement sales plummeted to pre-boom levels. Since WHO’s latest update shows Liberia’s epidemic continuing to grow, it seems likely that the last quarter of 2014 will see further collapses in cement sales, to levels below those of 2010.
Similarly, a World Bank country economist contacted the Sierra Leone immigration department to request data on travel to that country. Here too the story is one of economic retraction, if not collapse, as travel declined by 75 percent between April and August of 2014. Note that business travel (the green segment of the bars in Figure 2) declined by even more (in both relative and absolute terms) than other types of visitors, which suggests that these declines in visitor numbers will depress future as well as current economic performance.
In my first blog on the economic impact of Ebola, I argued that most of the economic impact of the outbreak of a mortal disease like Ebola is from aversion behavior, rather than from either the “direct” or the “indirect” channels that health economists doing so-called “cost-of-illness” studies typically consider. (For cogent expositions of COI definitions and methods, see the Cost of Illness Handbook published by the US Environmental Protection Agency or the PPT slides posted on the CDC website.) These bits of data on cement sales and visitors show impacts of the Ebola outbreak which lie well outside the cost of treating the few thousand cases of illness or of replacing the labor of the sick and dying. The cement and travel market effects are instead manifestations of aversion behavior and its crushing impact on economic activity.
On the basis of these building blocks, and others cited in the World Bank report, the country economists used their intuition and the national account identity to build out estimates of the 2014 impact of Ebola on Liberia, Sierra Leone, and Guinea. They then went further, estimating optimistic and pessimistic 2015 scenarios for each of the three countries. Their results are assembled in Figure 3 below.
Some features of these results stand out. First, the country economists judge that even in their optimistic 2015 projection, Liberia will sustain as large an impact as in 2014. Under their optimistic assumptions, Guinea is expected to regain part of its losses and Sierra Leone to suffer much less than in 2014. But the difference between the economists’ optimistic scenarios (in green) and their pessimistic ones (in red) is quite large, reflecting enormous uncertainty. Over all three countries, the estimated 2015 impact in the optimistic scenario is only about 12 percent of the impact in the pessimistic one. Adding the blue 2014 estimate for all three countries to the red 2015 estimate gives a pessimistic estimate of US$1.2 billion total loss of domestic product over the two years. For a population of only 22 million people in the three countries, this comes to about US$50 per capita, which is more than a tenth of the per capita GDP of Liberia, for example.
The report concludes with four recommendations, which are summarized in the report’s landing page as:
“Support the humanitarian efforts to finance medical equipment, emergency treatment units and personnel salaries”
“Help countries bridge the $290 million fiscal gap for 2014 and continue as the gap grows in 2015”
“Provide infrastructure and financing to countries’ international transportation links”
“Strengthen the surveillance, detection and treatment capacity of African health systems” Source: World Bank, September, 2014.
By financing medical care, the first of these recommendations reduces the direct and indirect costs of the Ebola epidemic. The other three recommendations address and attempt to mitigate the devastating economic impact of the aversion behavior. Bridging the fiscal gap sustains government functions and thereby reassures observers that the governments will not collapse under the stress of the epidemic. Financing the international transportation links can improve their security against Ebola transmission, thus reducing the aversion behavior of international trading partners. And strengthening surveillance and detection systems provides an early warning system that reassures domestic and international economic agents that, once under control, the Ebola epidemic will NOT soon return. If the World Bank and other donors vigorously implemment these policies, one can hope that these fragile young economies will soon resume the robust growth they recently experienced.
The Center for Global Development presents a seminar and discussion on
Prices, Diagnostic Tests and the Demand for Malaria Treatment: Evidence from a Randomized Trial
Harvard School of Public Health & Brookings Institution
With discussantRachel Nugent
Center for Global Development
Moderated by Mead Over
Center for Global Development Tuesday, June 29, 201012:00pm--1:30pmA light lunch will be served
atCenter for Global Development Lobby-level Conference Center1800 Massachusetts Avenue, NW, Washington, DC
Summary: CGD recently issued a major report on global drug resistance. CGD’s working group pointed to inappropriate use of medicines as a major driver of drug resistance across all major developing country diseases. This seminar will present results of new research on how to reduce the overuse and misuse of anti-malarials through better diagnosis of malaria. Due to widespread parasite resistance and high costs of Artemisinin Combination Therapies (ACTs), fewer than 15% of children with malaria are treated with effective medicines. The Affordable Medicines Facility for malaria (AMFm) is an initiative to subsidize the bulk of the cost of ACTs to suppliers, in part by dramatically reducing the final price of ACTs to consumers in the retail sector, or drug shops (where malaria treatment is most commonly sought). However, because the majority of people seeking malaria treatment in drug shops have received no formal diagnosis, substantial increases in access to ACTs may lead to inappropriate utilization of the drug. A high rate of overtreatment with ACTs is problematic, wasting subsidy funds and potentially stimulating the evolution of resistance. This paper reports on a field experiment from Western Kenya in which subsidized ACTs, along with subsidized Rapid Diagnostic Tests (RDTs), were made available in drug shops. We explore whether the targeting of the ACT subsidy to people with confirmed malaria could be improved by creating financial incentives for individuals to be tested before purchasing ACTs.
This blog is the first in a series of three on the quality of PEPFAR’s HIV treatment programs.
Counting the number of patients on treatment is no longer enough. For years even the friendliest critics of the global struggle against AIDS have pointed out that this metric unfairly neglects the people who are not put on treatment and then die, largely because their deaths are uncounted except in so far as they increase the treatment “coverage rate.” This diverts attention from the challenge of assuring that patients are retained on treatment and remain alive and healthy, rather than failing treatment and dying, sometimes after only a few months.
By adopting the “HIV treatment cascade” as its theme for the October 2 meeting of its Scientific Advisory Board meeting, PEFPAR has signaled its willingness to be judged by a much more comprehensive metric of its on-the-ground success. A vivid metaphor, the “AIDS treatment cascade” provides a snapshot assessment of the quality of AIDS treatment across the stages of care, and shows that there is room for improvement in Africa. (Also see WHO’s discussion of the “cascade” in Chapter 3 of their Global update on HIV treatment 2013.)
The following figure compares the AIDS treatment cascade in the United States (as it was presented and explained in this blog from the Centers for Disease Control) to estimates of the cascade in Africa that were synthesized for the SAB by Elvin Geng and Thomas Odeny.
Figure 1. Cumulative loss of patients in the AIDS treatment cascade in the United States and in Africa. In Africa, the proportion of patients with viral suppression is unknown.
Source:US data is from CDC’s June 2013 “Today’s HIV/AIDS epidemic”. Africa estimates are derived by the authors from Elvin Geng’s PEPFAR SAB presentation (October, 2012) which credits Rosen S, Fox MP (2011) Retention in HIV Care between Testing and Treatment in Sub-Saharan Africa: A Systematic Review. PLoS Med 8(7): e1001056. , Fox MP, Rosen S (2010) Patient retention in antiretroviral therapy programs up to three years on treatment in sub-Saharan Africa, 2007-2009: systematic review. Trop Med Int Health 2010-Jun:15 Suppl 1:1-15.
A deeper look at the figure shows that most of the difference between the US and Africa occurs at the first stage in the cascade, that of diagnosis. The US health system is estimated to detect and diagnose 80% of its HIV infected population of approximately 1.1 million, while Elvin Geng estimates that in the recent past the 40-some African countries have managed to detect only about 40% of the continent’s much larger mass of 26 million HIV positive people. (In view of PEPFAR’s recent dramatic scale-up of HIV testing, this first stage of the cascade may see a rapid improvement in coming years.)
Given the difficulty of testing the entire African population for HIV, a useful alternative perspective to the cumulative approach depicted in Figure 1 is to independently judge each stage shift, by calculating the proportion of patients from each stage who don’t make it to the next one (See Figure 2).
Figure 2. Incremental loss of patients between one stage and the next in the AIDS treatment cascade in the United States and in Africa. Sources: Same as Figure 1.
Source: US data is from CDC’s June 2013 “Today’s HIV/AIDS epidemic”. Africa estimates are derived by the authors from Elvin Geng’s PEPFAR SAB presentation (October, 2012) which credits Rosen S, Fox MP (2011) Retention in HIV Care between Testing and Treatment in Sub-Saharan Africa: A Systematic Review. PLoS Med 8(7): e1001056. , Fox MP, Rosen S (2010) Patient retention in antiretroviral therapy programs up to three years on treatment in sub-Saharan Africa, 2007-2009: systematic review. Trop Med Int Health 2010-Jun:15 Suppl 1:1-15.
Still, Figure 2 makes clear that Africa’s treatment cascade faces severe challenges at two other important stages, that from diagnosis to care, where Africa loses 41% compared to the US’s 23%, and that from initiation to retention, where Africa loses 30% compared to the US’s 9%.
As we absorb the implication that HIV/AIDS treatment is losing vast numbers of patients, one immediate question elicited from this data is if the data is accurate enough to warrant alarm.
For example, another presentation at the SAB shows that patient retention in Africa may actually be better than estimated, because some of the patients who have not returned to an individual facility may have continued their care at a different facility. The researchers sent out health personnel on motorcycles to look for the patients who were unaccounted for. This effort confirmed that facility’s retention rates are indeed biased downward by the inability of patient records systems to track transferring patients. In facilities whose own records showed a retention rate of 60% after three years, the corrected estimate was about 80% retention or about one-third better [ (80%-60%)/60% = 1/3 ]. (See Table 1 below.)
Source: Geng EH, Glidden DV, Bwana MB, Musinguzi N, Emenyonu N, et al. (2011) Retention in Care and Connection to Care among HIV-Infected Patients on Antiretroviral Therapy in Africa: Estimation via a Sampling-Based Approach. PLoS ONE 6(7): e21797.
Still, there is great variation in treatment retention across facilities. Figure 3 shows the two year retention in each of five specific facilities spread over three study countries. Here, the retention one year after antiretroviral therapy (ART) initiation is best at Site 2 (slight over 90%) and worst at Site 5 (roughly 70%). At two years after ART initiation, Site 4 (slightly over 90%) retains its proportion over the course of a year, while Site 5’s proportion declines to lower than 65%.
Source: Presentation by Odeny at PEPFAR SAB (October 2-3, 2013) on behalf of Elvin Geng , Odeny and other investigators in the East Africa IeDEA consortium.
On the other hand, Vivek Jain of UCSF showed that in some instances the retention rate at six and twelve months could be in the high-nineties. So a patient’s chance of successful treatment appears to vary dramatically and unacceptably according to the facility that patient attends.
We must bear in mind how extraordinarily well Africa is doing now compared to ten years ago when the US launched the PEPFAR program. At that time virtually 100% of HIV infected Africans went undiagnosed, un-linked, un-initiated and un-retained. So the international campaign to expand treatment in Africa has achieved a virtual miracle in providing the opportunity for treatment to so many.
And it is a welcome sign of the maturity of the United States PEPFAR program that its management has chosen to shine a spotlight on the broken links in the continuum of AIDS care in Africa.
Clearly, a 11% cumulative success rate is unacceptable if it means that 89% of HIV infected people fail to benefit from proffered treatment.
Even if a proper measure of retention in treatment yields a less pessimistic estimate of the attrition in the treatment cascade, the enormous loss of patients throughout the treatment cascade remains a glaring reminders of the need to better understand the causes of patient loss at every stage in the cascade and how these losses can be stemmed.
So how can retention be improved throughout the cascade? Stay tuned. In my next blog I will report on other sessions from the October 2-3 SAB meeting that addressed this question.
A new research study by Hoare et al in PLoS (ungated) projects that, within ten years after countries attain universal access to antiretroviral treatment for AIDS, one fifth of all patients starting treatment will never have a chance to benefit from the least-expensive and least-toxic treatments, because their initial infection will be a drug resistant strain of HIV.
We all know that drugs can get “worn out” from overuse. In rich countries, some of us remember when penicillin used to reliably treat many diseases, but now many disease agents are resistant to it. How, why and when do drugs stop working? CGD’s new report, The Race Against Drug Resistance, drives home the limited lifespan of all drugs and urges global action to contain this growing threat. A graphic in the report’s Annex depicts the lifespan of many different drugs in several important classes arrayed on a historical timeline. Among antibiotics, penicillin started failing after about ten years of use.
Antiretrovirals, at the bottom right of this figure, are not immune to drug resistance. In fact, because the AIDS retrovirus, HIV, replicates literally billions of times each day inside the body of a single patient, the chances of a resistant strain of HIV appearing are higher than they would be for a microbe that replicates more slowly. Note in the figure that several antiretrovirals have had extremely short lifespans.
Increased access to any given drug also means an increase in the risk that the drug will be worn out –because the more exposure a pathogen has to a drug, the more chances that pathogen has of “discovering” how to evade it. This tradeoff between how long a drug lasts and how many people it reaches each year can be displayed as a tradeoff frontier like the left-most panel here:
Of course, as the CGD working group’s report explains in fascinating detail, this tradeoff is not immune to policy. The report details a range of policy options available to individual countries, pharmaceutical manufacturers, and the broader public health community. Collective, global action can shift the tradeoff frontier to the northeast – so that we can have more years of drug efficacy for any given level of access.
The PLoS article provides useful insights into some of the parameters affecting the speed with which antiretrovirals will become worn out and scarily suggests that much ART resistance may remain hidden for some time, meaning that measured resistance may be underestimated. But, because the article assumes universal access to ARVs, it sheds no light on the tradeoff between access and the duration of drug efficacy. Because universal free access to ART is unlikely in the most severely affected countries, the question then arises whether some of the policies recommended in the new working group report can help minimize the development and spread of drug-resistant HIV variants in situations where free public access is less than universal.
As laid out in logical sequence on pages 24 – 30, the unfettered operation of existing market-driven supply and consumption of drugs like ARVs actually hastens drug obsolescence. Unfortunately, if left to their own devices, physicians and patients may insufficiently encourage adherence to ARV regimes, a practice that speeds the development of drug resistance within an individual patient and can lead to the spread of that resistant strain to others. In a 2004 study of the benefits and costs of ART in India, my coauthors and I recognized this issue by defining “structured” ART as having the following seven features:
Standardized, competency-based training of physicians in antiretroviral therapy management.
Prescription of a standard triple-drug regimen.
Support from a multidisciplinary team that includes a counselor and a nutritionist.
Regular clinical and lab-based monitoring of the patient’s treatment status.
Counseling to prevent transmission.
Prophylaxis for opportunistic illnesses when indicated.
Diagnosis and treatment of opportunistic illnesses.
At that time in India, when free public provision of ART had just begun, most AIDS patients in the country sought ART in the private sector and the limited evidence available suggested that most of it – and indeed most ART available at that time in the public sector – was “unstructured.”
One solution to this problem is regulation of the private sector in an attempt to assure that private sector ART is “structured.” Another approach, adopted by the AMFm initiative (see Box 4.6 on page 44 of the report) is to subsidize the price of a drug-efficacy extending technology in order to crowd out the free market’s drug-corroding influence. My coauthors and I incorporated assumptions of the magnitude of this crowding-out effect in order to arrive at advantageous estimates of the cost-effectiveness of the AMFm initiative for malaria and of ART in India.
Through a subsidy—either of a more durable drug (as in the case of the AMFm) or of an adherence maximizing form of treatment (“structured” ART as we recommended in India )—the tradeoff between access and drug durability will become less acute, as in the second panel of the figure above, thus benefiting both current and future patients and reducing the potential future fiscal burden of more expensive newer medications.