Friday, June 2, 2023

Optimal global spending for group A Streptococcus vaccine research and development – npj Vaccines

Optimal spending for Strep A research and development is large, in the tens of billions of USD. More importantly, the benefits are 50 times larger, ranging from USD1.6 trillion to USD37.9 trillion (in 2020 USD). Returns on investment range from 18% to 48.2% per year for 30 years. These returns are large compared with other interventions that have received considerable public support. For example, increased years of education are estimated to return about 9–10% per year in terms of increased income5,6.

Our results call upon national and international policy makers to fund and promote accelerated development of a Strep A vaccine. In this section we discuss a rationale for these policies and some mechanisms at the government’s disposable to provide this funding.

For many reasons, private sector investment in Strep A research and development is unlikely to reach our optimal amounts. First, some research and development, e.g., basic research, is hard to patent and therefore is unlikely to provide an adequate return on investment for private capital. Second, the high required rate of return of pharmaceutical companies due, in part, to their ability to sell products with patent-protected monopolies, will often discourage investment in all but the most promising projects. Third, the probability of success of an individual project is small, resulting in insufficiently high returns to justify the R&D risk. In contrast, a large portfolio of many projects greatly reduces the risk of not developing a viable product.

Public sector policy can move investment toward the optimal amount. A simple way to do this is to directly fund vaccine R&D projects. On a large scale, this mechanism of funding greatly reduces the risk of vaccine R&D by spreading risk across many possible projects. To raise funds for such an investment, governments have several approaches at their disposal: increasing taxes, crowding out other government spending, and debt finance.

Debt finance is particularly appealing as it allows the government to better align the costs and benefits of vaccine development. Any vaccine R&D project is likely to see benefits many years into the future. Debt allows a government to borrow money and pay back the principal in the future after R&D benefits materialize. Moreover, advanced economies can currently borrow at real interest rates substantially lower than our calculated returns on investment.

An alternative to direct funding would be for the government to encourage a large investment fund that would invest in a bond to raise capital for private sector investment into vaccine R&D. Many private investors pooling resources would fund many vaccine R&D projects at the same time7. Profits from successful projects would then provide a return to the bond holders. The government could encourage the development of such a private fund with a guarantee on the principal investment. Such an approach would reduce the risk of vaccine development while providing a role for both the public and private sector in vaccine R&D.

Speeding up the regulatory process, while monitoring safety, would also increase R&D. The annual required return on investment for the pharmaceutical industry is estimated to be at least 8% if not substantially higher8. At this required return, a 2-year regulatory delay would require expected profits be 16% higher to justify a pharmaceutical company making an investment. Reducing time to market would increase the number of projects the private sector finds viable, raising R&D expenditures of the private sector.

Finally, the full benefits of vaccine development cannot be achieved without equitable access to the vaccine. This point is especially notable with regard to Strep A, as most deaths occur in low-income countries due to lack of access to antibiotics. We expect that a Strep A vaccine will be made available in low-income countries in a way similar to pneumococcal and rotavirus vaccines. High-income countries should donate to international organizations like Gavi, the Vaccine Alliance; the World Health Organization; or UNICEF to support vaccine purchases for low-income countries. Such a policy would not be purely altruistic. Overuse of antibiotics is a key cause of increased antimicrobial resistance. Ensuring global access to an effective Strep A vaccine would be a potent defense against the development of such resistance.

Moreover, previous research has shown these donations to be a particularly effective form of foreign aid9. The GAVI model is effective because pharmaceutical manufacturers make substantial profits in high-income countries and then sell at discounts to low-income countries. Moreover, financing from the International Finance Facility for Immunization may be an additional way to support vaccine financing along with nontraditional debt finance that conditions on outcomes10. Potentially, a developing country manufacturer may also sell a Strep A vaccine, at a substantially lower price, as has happened with pneumococcal vaccines.

Our work has limitations. We calculate social surplus but do not analyze pricing. As a result, we cannot predict how the surplus will be split between increased population health and profits to manufacturers.

Additionally, while we view our model as an important step to understand the optimal level of investment, it abstracts from some aspects of the R&D process. We neglect the dynamic aspects of R&D, e.g., the possibility to learn from previous projects to either increase or decrease R&D. To fully understand how our results would differ in this dynamic context we would need to analyze a fully dynamic model. Such a model is beyond the scope of this paper; however, we can speculate, in part, how our results would differ in a dynamic environment.

One point is clear. In a dynamic context, the funder can observe past successes and then condition additional funding on these past successes. One possibility is that the funder will get lucky, with more successes than expected, and need to spend less. However, the funder may get unlucky, see many failures, and need to spend more than expected to get the same result. In this case, we view spending as a random variable, based on the random outcomes of the funded projects, with our model giving the expected spending that is needed on average.

A dynamic model also raises the possibility that the funder can learn about the probability of success from outcomes and then alter funding plans based on this new information. While giving more funding to approaches that have produced successes in the past may seem intuitive, the funder may also wish to reduce funding after successes because less harm from Strep A would be expected to remain. Learning should have a large effect in a model with many different approaches to develop a vaccine, all with highly uncertain probabilities. In this case, funding a few projects to learn about how likely the approaches are to succeed and then concentrating investment in the most promising approaches would be a useful strategy. We take comfort in the fact that Strep A vaccine development, according to our calibration, is a problem with few approaches, each with an estimated high success probability, and therefore we expect learning will not largely change the conclusions of our model.

Finally, as funding is spread out over multiple years in a dynamic model, this difference would delay the time required to develop a vaccine. The funder would need to wait for the various results to make additional funding decisions. These delays would also reduce rates of return as the time between making the investment and realizing the benefits would be extended. We have accommodated for this effect in our calculations by assuming a 10-year delay between investment and vaccine benefits and then assuming total benefits are spread out over a 30-year period. But the exact timeline of investment, discovery, and realization of benefits is uncertain.

An astute reader will notice that we omit the cost of manufacturing and delivery that would be necessary to realize the full health benefits. To understand the quantitative importance of this omission we obtain vaccine delivery costs from11. These costs are estimated to be USD3.70 per person vaccinated with a two-dose vaccine. Moreover, based on the UNICEF price for PCV-13 applicable to GAVI countries, USD3.30 per dose, we estimate an upper bound on manufacturing costs of USD6.60 per person vaccinated.12. We assume manufacturers do not sell below production cost and view this as a reasonable assumption given evidence that the manufacturing costs of Gardasil (an HPV vaccine) are possibly below the GAVI price13. Combining these costs, we estimate a manufacturing and delivery cost of USD10.30 per person vaccinated. We then calculate the present discounted value of these costs and compare them with the estimated health benefits. We find the present discounted value of these costs to be USD42 billion, which is 2.6% of our total estimated benefits. Consequently, we view our main conclusions as robust to the inclusion of manufacturing and delivery costs.

In calibrating the fraction by which the vaccine reduces harm we have not accounted for potential adverse effects of the vaccine. To explore the potential magnitude of these adverse effects we obtain data from the U.S. National Vaccine Injury Compensation Program14. The program has paid USD4.9 billion in total for 9304 claims. Therefore, it has paid out USD527,000 per claim. The program estimates it pays out about one claim per million vaccinations. Consequently, it has paid out USD0.53 per vaccination. We use this as a measure of the expected cost of adverse events per vaccine, and we calculate the present discounted value of these expected costs. This value is USD2.2 billion, which represents 0.14% of our total estimated benefits.

While additional vaccine costs and adverse events would lower our estimated benefits slightly, there are also important reasons to believe we have underestimated the benefits. For example, a Strep A vaccine may reduce the use of antibiotics, which is an important factor in the development of antimicrobial resistance. Additionally, it may prevent future health problems of an initial Strep A infection (e.g., future heart failure) that are not directly caused by Strep A and therefore not included in our benefits. Finally, the broad benefits of vaccines, e.g., increased labor force participation and productivity and increased education are omitted from our estimates15.

Potentially, adverse effects may be a larger concern with a Strep A vaccine than with other vaccines. This possibility is due to the U.S. Food and Drug Administration’s ban on Strep A vaccine human trials. However, this ban was based on one vaccine trial, from 1969, and the concerns raised by that trial have subsequently been questioned. In fact, in lifting the ban the U.S. Food and Drug Administration referred to its previous viewpoint as “obsolete,” and recent vaccine research has resumed with no similar adverse events16. We expect modern trials to perform extensive safety testing, and therefore in the calibration of our model we use a high cost to develop an approved vaccine of USD1 billion.

Our model takes harm from Strep A as given, and a vaccine as the correct mechanism to alleviate this harm. Scale-up of antibiotic use may provide an alternative approach to reduce the burden of Strep A. However, in our view, antibiotic scale-up has important limitations. Typically, antibiotic access is limited in low-income countries. This limited access stems from the inability to afford a visit to a doctor to obtain a diagnosis, the inability to afford a complete course of the antibiotic, and the lack of rapid tests to confirm Strep A infection17. Moreover, these costs are incurred for every Strep A infection. In contrast, a vaccine requires fewer contacts with the health care system (one to three depending on the number of required doses), and patients are not usually required to pay for vaccines in low-income countries18. Moreover, we base our estimates of Strep A harm on the Australian experience, in part, because it is a country where antibiotics are widely available but Strep A still has a substantial burden. We view it, therefore, as a rough estimate of Strep A harm even after a substantial scale-up of antibiotics. Finally, any global scale-up of antibiotic use comes with the potential cost of illegitimate use of antibiotics leading to increased potential for antimicrobial resistance.

The COVID-19 pandemic made clear that a large public investment in a vaccine can unlock enormous benefits. This recognition raises the question: for what other pathogens can the feat be repeated? Strep A is a most promising answer.

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