3

The Economic Cost of Endemic Infectious Diseases

Session I, part A, of the workshop explored the economic cost of endemic infectious diseases, focusing on diseases that disproportionately affect low- and middle-income countries but also affect regional and global financial stability. The diseases presented in this session each highlight different aspects of the economic considerations for endemic infectious diseases: polio is on the brink of eradication; HIV has transitioned from an emerging infection to an endemic disease; and tuberculosis (TB) has a high mortality rate and often affects individuals during their working age. The session was moderated by Thomas Inglesby, director of the Center for Health Security at the Johns Hopkins Bloomberg School of Public Health. Kimberly Thompson, president of Kid Risk, Inc., opened the session with an overview of the economic case for eradicating polio, evaluating the costs and benefits of both eradication and control strategies. Katharina Hauck, senior lecturer in health economics from the Imperial College London, followed with a discussion on the economic impact of HIV/AIDS on labor productivity and quality of life. Finally, Anna Vassall, professor of health economics at the London School of Hygiene & Tropical Medicine, described the costs and value of TB control programs and interventions.

ECONOMIC CASE FOR ERADICATING POLIO

Kimberly Thompson, president of Kid Risk, Inc., began by outlining four questions she hoped to address regarding the economics of polio eradication:

• What are the economic implications of polio control versus eradication? What are the economic costs if polio is not eradicated?
• What have been the economic benefits of the Global Polio Eradication Initiative (GPEI)?
• How can the global community build an economic case to keep the world free of polio after the two remaining regions achieve eradication?
• How can the global community ensure that the necessary investments in activities and functions will be made to sustain a polio-free world?

Pathophysiology of Polio

Thompson described the pathophysiology of polio to illustrate the complexities of modeling the disease. Polio is a positive-stranded RNA virus that exists in three stable forms: serotypes 1, 2, and 3. Live forms of the virus include the oral poliovirus vaccine (OPV), wild poliovirus (WPV), and vaccine-derived poliovirus (VDPV). Thompson noted that OPV—which contains a live attenuated virus—is low cost and easy to administer. It causes an infection in vaccine recipients who can then pass the vaccine-derived infection on to other members of their community. This infection induces an immunologic response that provides protection to both vaccinated individuals and infected community members against future infection and paralysis upon reinfection.

Unlike WPV, the OPV strain of the virus is extremely unlikely to cause central nervous system symptoms. However, OPV can occasionally mutate and begin to act like WPV. In these cases the virus strain is known as VDPV. In approximately 1 out of 2.7 million OPV-induced infections, VDPV can produce a case of vaccine-associated paralytic polio (VAPP) (GPEI, 2015). In populations with low OPV uptake, there may be enough susceptible, unvaccinated individuals nearby to sustain a paralytic polio outbreak if this were to occur. In rare cases, some individuals with B-cell related immunodeficiencies may take a long time to clear the infection and represent a potential source for reintroduction of the virus known as immunodeficiency-related VDPV or iVDPV. Because of this potential for paralytic polio cases in regions that use the oral vaccine, Thompson cautioned that OPV can only aim to achieve polio “control”—that is, a reduction of polio cases as opposed to complete eradication.

An inactivated form of the virus is used in the injectable form of the vaccine, known as inactivated polio vaccine (IPV). IPV is significantly more expensive and more difficult to administer than OPV as it is administered using sterile syringes. In contrast, IPV does not cause an active infection in vaccine recipients, only an immunologic response, and thus there is no risk

for VAPP cases or secondary spread to others—this allows for complete polio “eradication.” According to Thompson, the different patterns associated with WPV transmission, OPV infection, OPV immune response, and IPV immune response make the economic implications of polio infection and intervention complicated to model.

Economic Implications of Polio Control Versus Eradication

Thompson summarized several key findings related to the economics of polio control versus eradication. She reviewed an economic analysis study indicating that “high control” is not an optimal outcome for diseases—like polio—where eradication is possible (Barrett, 2013). According to a cost-benefit analysis, the potential future cost savings of full eradication are high enough that deficit-financed spending is justified in the case of eradication programs as demonstrated by an analysis on polio eradication efforts in the Americas (Musgrove, 1988). Additionally, Thompson highlighted research that quantified the health and economic benefits of U.S. investments in polio control and eradication since 1955 (Thompson and Tebbens, 2006). The retrospective study, using a dynamic poliovirus transmission model, demonstrated that these efforts prevented more than 1 million cases of paralytic polio. Because of treatment cost savings, the investment resulted in net economic benefits exceeding $180 billion, which does not include the intangible costs of suffering, death, and averted fear.

A subsequent study revealed that transitioning from OPV-based control strategies to IPV-based eradication strategies, even in low-income settings, resulted in lower cumulative costs and cases of paralytic disease over a 20-year period (Thompson and Tebbens, 2007). This literature suggests that the benefits of intensively pursuing polio eradication outweigh its challenges, in light of the higher cumulative costs of a wavering commitment to eradication. Thompson cited the case of India, which achieved polio eradication in 2011 following an intensive national campaign and is now refocusing vaccination resources on other targets, such as measles and rubella (Cochi, 2017).

Economic Benefits of the Global Polio Eradication Initiative

Thompson also spoke on the economic benefits of GPEI, a global initiative launched in 1988 and coordinated by the World Health Organization (WHO), Rotary International, the U.S. Centers for Disease Control and Prevention, the United Nations Children’s Fund, and the Bill & Melinda Gates Foundation. She reviewed a retrospective and prospective analysis of the expected costs and cases related to polio with and without the initiative (Tebbens et al., 2010). At the time, the study assumed that eradication

would occur by 2012. Expected net benefits were estimated to be $40–$50 billion between 1988 and 2035, plus an additional $17–19 billion accounting for the benefits of vitamin A supplements, which are commonly coadministered alongside polio vaccination campaigns.

When GPEI succeeds in eradicating the poliovirus, she said significant investments will still need to be made to keep the world polio free. Thompson described a subsequent study analyzing long-term poliovirus risk management policy options assuming eradication by 2016. The study also assumed that following eradication, OPV use would be discontinued and replaced with routine immunization of IPV through the year 2024, thus eliminating the potential for VAPP and WPV reemergence. In this scenario, the transition to IPV would yield an expected $16–17 billion in net benefits between 2013 and 2052, in comparison with the continued use of OPV (Tebbens et al., 2015). These estimates depend on GPEI adopting optimal risk management strategies, including continued high-quality surveillance, access to vaccine stockpiles, and maintaining community immunity prior to OPV cessation. Thompson noted that the magnitude of the benefits supports an economic case for sustained efforts after eradication is achieved. She also noted that the study needs to be updated to take into account that GPEI partners extended the current strategic plan to 2019.

Thompson concluded her remarks by noting the role economists can play in ensuring future investments in polio control and eradication. She described how economists are able to provide policy makers with data and analysis to evaluate potential options, but they are not the decision makers. However, she said, the work of economists can be used to hold policy makers accountable for decisions regarding these investments.

ECONOMIC IMPACT OF HIV/AIDS

Katharina Hauck, senior lecturer in health economics from the Imperial College London, described the links between HIV and gross domestic product (GDP), a principal indicator of a country’s economy (see Figure 3-1). She explained that HIV affects GDP through multiple pathways. For example, health expenditure and lost income from the disease’s morbidity and mortality negatively affect household income, reducing consumption as well as savings and investments in income-generating activities. This in turn lowers investment in capital and lowers labor productivity and GDP. Moreover, Hauck pointed out that HIV-infected individuals may value present benefits more than future benefits based on fear of illness and shorter life expectancy; this might reduce their incentives to invest in education, which further reduces labor productivity and GDP. Another pathway to consider is that children of HIV-infected individuals may become orphans when their parents pass away, which may reduce investments in education. As a

larger proportion of individuals contribute less to the economy from caring for individuals affected by HIV, this may lead to higher dependency ratios. This higher dependency ratio is also influenced by an overall labor force that is reduced by premature mortality and retirement from HIV infection.

Hauck explained that the relationship between HIV and GDP can be modeled with a general equilibrium economic model. General equilibrium approaches in economics attempt to explain the functioning of a system made up of interacting parts using a single mathematical framework. These frameworks, however, are limited by the validity of the assumptions that underlie them. Current research efforts on the economics of HIV focus on improving the data and understanding the interactions that feed into the model. Hauck argued that an improved model will allow for a better prediction of return on investment related to national-level health policies surrounding HIV/AIDS.

Focus on Labor Productivity and Health-Related Quality of Life

With better individual and household data, economists have begun to focus on the key factor identified in the general equilibrium model: labor productivity. Hauck presented a cross-sectional study of more than 17,000 individuals from nine communities with high prevalence of HIV in

Zambia (Thomas et al., in review). The study compared productive days lost attributable to health-seeking behavior and illness over the past 3 months, between HIV positive and HIV negative individuals. The difference in productive days lost per month between the two groups was less than 1 day, which could be a result of the day that HIV positive individuals needed to collect their monthly supply of antiretroviral (ARV) drugs. According to Hauck, these estimates of lost productivity are much lower than those described in previous literature. As it is challenging to compare HIV positive and HIV negative patients using cross-sectional study designs, researchers carry out studies that track patients over time to assess any changes in productivity and income over their productive life. For instance, a study followed 54 HIV positive individuals working in Kenyan tea plantations until the end of their work lives. The researchers found that as many as 3 years before an AIDS-related termination, workers with HIV/AIDS were absent from the job more often and could not continue with their usual output when on the job (Fox et al., 2004).

Furthermore, Hauck noted that other studies indicate a second fall in productivity seen earlier in the lifetime of an HIV-infected individual, right before the initiation of antiretroviral therapy (ART) and lasting approximately 1 year (Larson et al., 2013). She described a scenario of an individual becoming sick and starting treatment, after which their productivity levels recover almost to the levels of an HIV negative individual. This pattern was demonstrated in a study measuring the working days of individuals in two Kenyan tea plantations. Additional dips in productivity can occur over an individual’s lifetime because of treatment failure or resistance to first-line treatment. Hauck pointed out that these declines in health status, especially in the middle of a productive work life, should be prevented given the effect of falling labor productivity on GDP.

Hauck stated that ART has been successful not only in restoring labor productivity but also improving health-related quality of life. She presented a study that evaluated the health-related quality of life of both HIV-infected and uninfected individuals at various stages of life in South Africa and Zambia (Thomas et al., 2017). The study detected no difference in perceived quality of life between HIV-infected individuals on ART for more than 5 years compared with uninfected individuals. The same study revealed that in Zambia, 43 percent of HIV-infected individuals were unaware of their status before participating in the survey, and 12 percent were aware but were not in care (Thomas et al., 2017). Hauck argued that this finding suggests the continued challenge of late linkage to care and delayed treatment initiation.

Implications for Policy Design

Hauck stated that the studies on the effect of HIV on productivity and quality of life have implications for effective policy design. She reiterated that the studies suggest the success of ART not only in restoring labor productivity but also health-related quality of life, removing differences between HIV negative and HIV positive individuals. They also highlight persistent challenges, including late linkage to care and initiation of treatment. People who are unaware of their HIV status may drive the epidemic by infecting their sexual partners. According to Hauck, there is therefore a strong economic rationale for frequent testing and early intervention to reduce the number of new infections.

Another important aspect to consider when designing policy is the need for individual incentives, she added. HIV positive individuals bear the cost of preventing the further spread of HIV to their sexual partners, yet do not reap any individual benefits for this effort (because they are already infected). Policies often assume that HIV-infected people are altruistic, Hauck said, hoping that once they know their status they will take steps to prevent passing on the disease. She continued, however, that the evidence is inconclusive related to changes in risky sexual behavior after a person tests positive for HIV. The idea of altruism contradicts traditional economic theories of rational behavior. According to these economic theories, people only consider their own individual costs and benefits when making decisions.

Economic models, according to Hauck, support a universal “test and treat” strategy. This strategy involves initiating ART for HIV positive individuals as soon as they are diagnosed. She added that early ART is beneficial not only for the patients, who reap health benefits, but also for their sexual partners, who will have a lower risk of contracting the disease. However, as HIV positive individuals do not typically face immediate symptom decline in the early stages of their disease, they may have little motivation to initiate or adhere to treatment because of the low level of potential benefits during this phase (Thomas et al., 2017). Given this challenge, Hauck concluded that health policies should focus on testing and prevention measures targeting both HIV negative and HIV positive individuals, with an additional focus on adherence counseling.

COSTS AND VALUE OF TUBERCULOSIS CONTROL

Anna Vassall, professor of health economics at the London School of Hygiene & Tropical Medicine, described the strong investment case that can be made for TB control programs. TB has a high mortality rate, and it is the leading cause of death among infectious diseases, with 1.7 million

deaths per year (WHO, 2017; The Global Fund, 2018). It often affects people during their working age, which in turn leads to a detrimental effect on the economy in countries with a high burden of TB. Vassall argued that the effect of TB on mortality and productivity makes TB control a worthwhile investment.

Economics of Tuberculosis Control

The cost of the TB treatment regimen is relatively low. In low- and middle-income countries, a 6-month course of TB treatment can cost as little as $20 per patient, and, when effective, it prevents onward transmission of the disease (Laurence et al., 2015). Vassall explained that this figure rises when accounting for the costs of the health systems needed to deliver the treatment, and may fluctuate based on the high variability of treatment costs across different countries. In many low- and middle-income settings, the costs rise to between $100 and $200, while in high-income settings and countries faced with complex, drug-resistant cases (e.g., Russia), the figure can exceed $10,000 per case (WHO, 2017). Nevertheless, both TB treatment and control continue to be listed as leading health interventions in terms of cost-effectiveness in most low- and middle- income countries (Maher et al., 2007; Horton et al., 2017).

Economic analysis supports TB interventions because of the effect of the disease on poverty, said Vassall. TB infection is indolent, and infected individuals may go 6 months or more before seeking care. During this time, they suffer from adverse health effects and lost income, which can lead to behaviors such as selling assets, taking out loans, and withdrawing children from school (see Figure 3-2). Vassall described a study estimating that up to 40 percent of households in South Africa with a TB infection faced catastrophic expenditures (Foster et al., 2015). She presented additional research that models the positive impact of effective treatment of drug-sensitive and multidrug-resistant TB and expanded access to TB care on catastrophic financial costs faced by families in South Africa and India (Verguet et al., 2017). The study further highlights the need for not only effective service delivery but also social protection strategies for TB patients, in order to have a positive effect on poverty.

This evidence accompanied rising investments in TB control in high-burden countries, predominantly led by increased funding from country-level resources (WHO, 2017). Though the total resources allocated to TB control are increasing, they continue to be insufficient, Vassall said. If new resources are to be designated to TB control, it is not clear where the funding would be most effective. To explain this, she described an economic analysis performed in South Africa that evaluated the costs versus the health benefits in disability-adjusted life years from prevention, expanded access

to care, and improved treatment quality for TB (Menzies et al., 2016) (see Figure 3-3). The results suggested that there are no obvious low-cost, high-return options for TB control. Policy makers can invest small amounts and achieve a low level of impact, or make a larger investment for a higher return. The analysis concluded by highlighting the need for a comprehensive “combination” package of interventions to control the disease, though this would require the country to increase baseline TB funding by a factor of two to three. While this strategy would strain the public-sector budget, it would also be associated with substantial reductions in health and economic costs borne by patients, she said.

New Technology Development and Uptake for Tuberculosis Control

Vassall discussed the challenge of new technology development and uptake for TB care, noting that even when these technologies become available, they might not prove to be cost-effective. The rapid TB diagnosis tool Xpert, for example, was predicted to be highly cost-effective though expensive particularly in low- and middle-income settings (Vassall et al., 2011). In reality, when the technology was employed in South Africa, it proved to have no effect on mortality while requiring additional services for implementation (Vassall et al., 2017). Vassall noted that this experience

highlighted the need for broader health system investments and a further analysis of the supply-and-demand interactions that dictate how patients proceed through the health care pathway (see Figure 3-4).

Vassall argued that the demand for and supply of quality interventions such as new technologies are affected by a variety of proximal and distal constraints. Some constraints may become apparent through scale up or may indirectly affect the care pathway (Vassall et al., 2016). For example, on the demand side, there may be proximal constraints such as those that directly block knowledge, access, uptake, or adherence to treatment options. These proximal constraints are in turn influenced by distal constraints such as underlying values and preferences, cultural norms, and household resources. On the supply side, the knowledge and behavior of health care providers as well as the availability of staff and supplies may be potential proximal constraints; distal factors such as human resource availability, health financing, and the functioning of health systems may influence those proximal constraints. Vassall concluded that investment packages need to not only focus on the technologies but also address the various proximal and distal constraints to ensure that patients get the care they need.

DISCUSSION

Inglesby summarized the following points he captured from the presentations:

• Control strategies and interventions for polio, HIV, and TB are complex and distinct for each disease.
• Global goals and campaigns play an important role in driving such efforts.
• To reflect real-world situations, economic models depend on effective implementation and human behavioral responses.
• Testing and case detection for these diseases are critical but are associated with significant costs.
• Different technologies, drugs, and vaccines affect calculations in economic analyses.
• Future investment on these strategies should be a concern as a decrease in funding may jeopardize the progress already made.

The discussion began with the topic of using economics to understand the social and behavioral aspects of endemic diseases. Jennifer Gardy, associate professor at the University of British Columbia’s School of Population and Public Health, raised the issue of the ethical principles of reciprocity and altruism related to TB and HIV. She explained that patients take on a burden when they seek and subsequently receive treatment, and are therefore owed support by the public health system. She asked how individual economic incentives and social support are being used to address this challenge. Vassall responded that economic incentives are in fact being used, and cited a recent study that suggested that conditional cash transfers and social support had a positive effect on TB treatment (Wingfield et al., 2017). She said that advocates for TB control are bringing attention to economic incentives by focusing on the catastrophic costs related to the disease. Hauck said that there are a few studies on the efficacy and cost-effectiveness of conditional cash transfers to keep adolescent girls in schools, because of the link between school attendance and early infection with HIV (Baird et al., 2012; Pettifor et al., 2016). The evidence, however, is inconclusive and dependent on the subgroups analyzed, the people who receive the cash, and the method by which they receive it.

Ramanan Laxminarayan, director of the Center for Disease Dynamics, Economics & Policy, commented on the “fear factor” of infectious diseases—that is, how they affect behavior change in individuals who are not infected. In addition, when the incidence of a certain disease declines, countries stop paying attention, often leading to a resurgence of the disease, which has been the case in Sri Lanka with malaria and in Venezuela with polio. He also noted that the problem that ministers of finance face is the sheer magnitude of health care costs. These costs can be as much as billions of dollars, leading to what he described as “billion-itis,” making it difficult for any meaningful economic analysis to prove useful for resource allocation. Laxminarayan concluded by asking whether there is a need

to expand focus beyond direct health care costs to include the behavioral choices of those not infected, including individuals in the agricultural and industrial sectors. To clarify this point, he explained that in Paraguay the major economic effect of malaria fell on those not infected, as they had to change crop choices to anticipate the increase of malaria cases during harvest seasons.

Thompson responded by highlighting the need to calculate the economic value of cases prevented, not just the number of actual cases. This presents a challenge, she said, as it is far more difficult to count cases prevented, which further demonstrates the need for modeling. She added that past modeling efforts focused only on case numbers and failed to note the potential for disease resurgence. Thompson emphasized the importance of clearly emphasizing the risk of disease resurgence to policy makers, particularly when the strategies needed to address these threats are no longer in place such as in the case of Venezuela. She argued that models should assign value to cases prevented to ensure sustained efforts even when case numbers are low.

Hauck responded to Laxminarayan’s question by sharing her insights on HIV. She suggested that with the arrival of an effective treatment for HIV, individuals might perceive the costs of infection to be lower. She noted that HIV has evolved from a life-threatening illness to a chronic condition—a fact that changes the underlying incentive structure. This demonstrates the need to educate the public further on the side effects of treatment and the continued danger of infection, she said. She argued that policies should account for how individuals make decisions based on time and risk preferences in the context of competing infectious disease threats like malaria. Vassall emphasized the need for a greater understanding of the impact of borrowing not only on families facing financial catastrophes because of TB infection, but also in the communities to which they belong. The current studies only look at the economic effect at the individual/household level, but it is clear that the economic decisions at this level ripple into the community as it affects the lenders’ household savings and investment horizons, she said.

Patrick Hickey, chair of the Department of Pediatrics at the Uniformed Services University of the Health Sciences, noted that as some countries approach adequate control for a specific disease, allocating resources efficiently to identify and treat the last few cases becomes a primary challenge. He asked how useful economic models can be in regard to “last mile” concerns. Thompson responded by explaining that countries and their partners need to determine where the last mile is, and to understand the associated barriers to care (e.g., undervaccination and undertreatment). Related to economic models, she added that sometimes strategies are overly optimistic and do not reflect the uncertainty of what happens in the field. She noted

that models must account for increasing costs over time as progress is made toward goals. She described a study characterizing the cost function of vaccination campaigns as coverage increases (Ozawa et al., 2018). Thompson argued that when eradication is the goal, associated costs will be higher, but the long-term benefits will be substantial enough to outweigh them.

In response to Hickey’s question, Hauck added that there is a trade-off between equity and efficiency related to this question about the costs of reaching the last mile. Costs for the last case of a disease can be high, but if society wants to deliver benefits to remote or marginalized communities, they must weigh the challenge of efficiency against the goal of equity, she said. She also noted that there are significant benefits to the elimination of the last cases of a disease. This eradication dividend is gained not only by the country itself, but also by other countries in the region and the global community. As an example, she said that all countries were able to eliminate smallpox surveillance and vaccination following the eradication of the disease. She added that studies are currently under way to assess if the success with smallpox case can be translated to other diseases.

In contrast, Vassall said that TB is not at the last mile stage yet, particularly because of challenges with latent TB, but there is nevertheless a need to expand focus beyond health services. Currently, she said health systems rely on infected individuals to present themselves to facilities, but in the future health workers will need to actively search for cases, which will have higher cost implications. She noted there are little data on the cost of finding new cases, and that treatment costs are only estimates and often do not reflect actual costs in peripheral facilities.

The discussion shifted to the topic of using economics in the policy world. Jeffrey Duchin, health officer and chief of the Communicable Disease Epidemiology and Immunization Section for Public Health—Seattle and King County, Washington, asked about the effect of economic modeling on policy makers, and how to use models for infectious diseases as powerful tools to create change in policy. Thompson responded by referencing her experience with GPEI. She explained that close collaboration, open communication, clarifying questions, and shared understanding with policy makers throughout the process have been critically important.

Thompson also noted that policy-making partners have been helpful in highlighting trends and future challenges. She remarked that while models must capture the complexity of the disease’s biology and epidemiology, they must also be accessible to ministers of health and finance. Hauck added that researchers must devise methods to provide answers more quickly than the 6-year waiting period associated with randomized control trials. She said economic modeling and other economic research tools (e.g., quasi-experimental methods including difference in differences and regression discontinuity analysis) are cheaper, faster, and are increasingly being used

in the context of public health. Vassall noted that the underlying policy environment of a country is important as it in turn affects the utilization of economic modeling. She argued that even when economic analysis does not drive action, it can still move policy debate forward by disproving fallacious arguments (e.g., “TB care is not cost-effective”). She emphasized the need for researchers to spend time in the countries under study to understand the local context and build local ownership. This type of long-term engagement, she said, facilitates the institutionalization of economic advice and strengthens the countries’ capacities.

Continuing the discussion on policy, Jesse Goodman, professor of medicine at Georgetown University, noted that benefits and costs related to microbial control efforts change over time, and communicating this to policy makers with short-term decision horizons is a challenge. He further argued that there are externalities associated with policy decisions, as present-day decision makers may not own the downstream costs and benefits of their actions. Goodman asked panelists to share their experiences accounting for these concerns in political or practical situations.

Thompson explained that everything is dynamic, and that economic analyses must tackle these dynamics according to the uncertainty and variability in different country contexts regarding their interventions, policies, and preferences. She added that technical work must be done to get the modeling right first, and then results can be translated and put into context for policy makers and their staff. With regard to externalities, she noted that the polio program has been conservative about characterizing the costs and benefits over time, as it is important to make sure they are not double counted. According to Thompson, polio eradication efforts’ largest benefit to other diseases stems from having established a large surveillance network of laboratories and field activities to control and eradicate the disease. These resources proved critical during the 2002–2004 severe acute respiratory syndrome outbreak and more recently for the Ebola response in Nigeria.

Hauck responded to Goodman’s question of changing costs and benefits related to control efforts by stating that for HIV these changes are mainly relevant to the cost of the drug treatment. These uncertainties include unknown future prices of ART, particularly with respect to second-line drugs, and the speed at which drug resistance will develop. In addition, she noted that several health system costs (such as service delivery platforms) are shared across multiple interventions taking advantage of economies of scope, but calculating these costs is challenging.

Vassall agreed with Goodman’s comments and observed that TB research has historically used cohort models that estimate the number of deaths prevented. She noted that there is now an opportunity to use new methods to capture cases averted and account for potential long-term gains

and savings to health systems, even though assessing longer-term effects introduces more uncertainties. On the topic of policy makers, Vassall shared the example of top-level stakeholders making decisions to increase funding or launching new control initiatives, but with no follow-up action and disbursements of funds. She stated that there is a need to focus on how policy makers operate and the mechanism necessary for them to implement relevant policies.