Operational issues and network effects in vaccine markets

One of the most important concerns for managing public health is the prevention of infectious diseases. Although vaccines provide the most effective means for preventing infectious diseases, there are two main reasons why it is often difficult to reach a socially optimal level of vaccine coverage: (i) the emergence of operational issues (such as yield uncertainty) on the supply side, and (ii) the existence of negative network effects on the consumption side. In particular, uncertainties about production yield and vaccine imperfections often make manufacturing some vaccines a risky process and may lead the manufacturer to produce below the socially optimal level. At the same time, negative network effects provide incentives to potential consumers to free ride off the immunity of the vaccinated population. In this research, we consider how a central policy-maker can induce a socially optimal vaccine coverage through the use of incentives to both consumers and the vaccine manufacturer. We consider a monopoly market for an imperfect vaccine; we show that a fixed two-part subsidy is unable to coordinate the market, but derive a two-part menu of subsidies that leads to a socially efficient level of coverage

Literature Review - the vaccine supply chain

Vaccination is one of the most effective ways to prevent the outbreak of an infectious disease. This medical intervention also brings about many logistical quest

Core Allocations for Cooperation Problems in Vaccination

Vaccination is a very effective measure to fight an outbreak of an infectious disease, but it often suffers from delayed deliveries and limited stockpiles. To use these limited doses of vaccine effectively, health agencies can decide to cooperate and share their doses. In this study, we analyze this type of cooperation. Typically cooperation leads to an increased total return, but cooperation is only plausible when this total return can be distributed in a stable way. This makes cooperation a delicate matter. Using cooperative game theory, we derive theoretical sufficient conditions under which cooperation is plausible (i.e., the core is non-empty) and we show that the doses of vaccine can be traded for a market price in those cases. We perform numerical analyses to generalize these findings and we derive analytical expressions for market prices that can be used in general for distributing the total return. Our results demonstrate that cooperation is most likely to be plausible in case of severe shortages and in case of sufficient supply, with possible mismatches between supply and demand. In those cases, trading doses of vaccine for a market price often results in a core allocation of the total return. We confirm these findings with a case study on the redistribution of influenza vaccines

The benefits of combining early aspecific vaccination with later specific vaccination

Timing is of crucial importance for successful vaccination. To avoid a large outbreak, vaccines are administered preferably as quickly as possible. However

PURIFICATION AND RECOVERY OF INFECTIOUS VIRUS PARTICLES USING OSMOLYTE FLOCCULATION

Viral infectious diseases cause millions of deaths and severe illness all around the world affecting public health and economics. Viral vaccines are helping to fight against viral diseases, but current vaccines are expensive and unavailable, especially in poor and developing countries. When measuring the entire manufacturing processing, the downstream processing of vaccines is the major cost of production. Our goal for this research is to develop a low-cost alternative downstream processing platform for new vaccine manufacturing infrastructures. We have developed a novel osmolyte flocculation method for viral particles. To create a platform purification for several types of viral particles, we used two model viruses: porcine parvovirus (PPV) and Sindbis virus (SINV). PPV is a non-enveloped virus, one of smallest known mammalian viruses with a diameter of approximately 20 nm. The enveloped virus, SINV, has a size of 48-52 nm. Using mannitol osmolyte flocculation we demonstrated recovery for both viruses by diafiltration using a micropore membrane. This will allow easy scale-up to production scale and creates a low-cost platform. Our lab’s previous study showed that osmolyte flocculation was specific to viruses as compared to proteins which are present as the contaminants in the process. This preferential flocculation is due to the active hydrophobic surface differences on viruses and protein surfaces. We studied the effect of membrane pore size on the recovery of viruses and were able to achieve 60% recovery of infectious PPV using a 0.1 μm and 500 kDa pore size filters. Recovery of infectious SINV was 79% using 0.1 μm and 96% using 500 kDa pore size membrane filter. Increasing the concentration of virus results in enhanced recovery of infectious particles, but at high concentration, membrane pores can get blocked, causing membrane fouling. We also examined the purity of the recovered virus samples for DNA and protein contaminants. In conclusion, we have developed a novel purification process that was able to purify and recover infectious viral particles using large pore size filters, which can decrease overall processing costs

PURIFICATION AND EFFECTIVENESS OF VACCINES AND ANTIVIRAL COMPOUNDS

Viral infections account for over 13 million deaths per year. Antiviral drugs and vaccines are the most effective method to treat viral diseases. Antiviral compounds have revolutionized the treatment of AIDS, and reduced the mortality rate. However, this disease still causes a large number of deaths in developing countries that lack these types of drugs. Vaccination is the most effective method to treat viral disease; vaccines prevent around 2.5 million deaths per year. Vaccines are not able to offer full coverage due to high operational costs in the manufacturing processes. Although vaccines have saved millions of lives, conventional vaccines often offer reactogenic effects. New technologies have been created to eliminate the undesired side effects. However, new vaccines are less immunogenic and adjuvants such as vaccine delivery vehicles are required. This work focuses on the discovery of new natural antivirals that can reduce the high cost and side effects of synthetic drugs. We discovered that two osmolytes, trimethylamine N-oxide (TMAO) and glycine reduce the infectivity of a model virus, porcine parvovirus (PPV), by 4 LRV (99.99%), likely by disruption of capsid assembly. These osmolytes have the potential to be used as drugs, since they showed antiviral activity after 20 h. We have also focused on improving current vaccine manufacturing processes that will allow fast, effective and economical vaccines to be produced worldwide. We propose virus flocculation in osmolytes followed by microfiltration as an economical alternative for vaccine manufacturing. Osmolytes are able to specifically flocculate hydrophobic virus particles by depleting a hydration layer around the particles and subsequently cause virus aggregation. The osmolyte mannitol was able to flocculate virus particles, and demonstrate a high virus removal, 81% for PPV and 98.1% for Sindbis virus (SVHR). Virus flocculation with mannitol, followed by microfiltration could be used as a platform process for virus purification. Finally, we perform biocompatibility studies on soft-templated mesoporous carbon materials with the aim of using these materials as vaccine delivery vehicles. We discovered that these materials are biocompatible, and the degree of biocompatibility is within the range of other biomaterials currently employed in biomedical applications

Bilevel linear programs: generalized models for the lower-level reaction set and related problems

Bilevel programming forms a class of optimization problems that model hierarchical relation between two independent decision-makers, namely, the leader and the follower, in a collaborative or conflicting setting. Decisions in this hierarchical structure are made sequentially where the leader decides first and then the follower responds by solving an optimization problem, which is parameterized by the leader's decisions. The follower's reaction, in return, affects the leader's decision, usually through shaping the leader's objective function. Thus, the leader should take into account the follower's response in the decision-making process. A key assumption in bilevel optimization is that both participants, the leader and the follower, solve their problems optimally. However, this assumption does not hold in many important application areas because: (i) there is no known efficient method to solve the lower-level formulation to optimality; (ii) the follower either is not sufficiently sophisticated or does not have the required computational resources to find an optimal solution to the lower-level problem in a timely manner; or (iii) the follower might be willing to give up a portion of his/her optimal objective function value in order to inflict more damage to the leader. This dissertation mainly focuses on developing approaches to model such situations in which the follower does not necessarily return an optimal solution of the lower-level problem as a response to the leader's action. That is, we assume that the follower's reaction set may include both exact and inexact solutions of the lower-level problem. Therefore, we study a generalized class of the follower's reaction sets. This is arguably the case in many application areas in practice, thus our approach contributes to closing the gap between the theory and practice in the bilevel optimization area. In addition, we develop a method to solve bilevel problems through single-level reformulations under the assumption that the lower-level problem is a linear program. The most common technique for such transformations is to replace the lower-level linear optimization problem by its KKT optimality conditions. We propose an alternative technique for a broad class of bilevel linear integer problems, based on the strong duality property of linear programs and compare its performance against the current methods. Finally, we explore bilevel models in an application setting of the pediatric vaccine pricing problem

“Feeling Better Than Ever”:Are there any internally consistent responses to the challenge of ‘better than perfect’ human health enhancement technology in a health technology appraisal context?

Most modern publicly funded national healthcare systems (NHSes) make decisions about which technologies to fund and which to reject through the principles of health economics, and specifically the principles of ‘Health Technology Appraisal’ (HTA). Current HTA methods implicitly assume that health is anchored between zero (worst possible health) and one (best possible health), but the mathematics underlying HTA does not require this – mathematically the concept of ‘better than perfect’ health is entirely meaningful. However, to date there are no examples of technologies which actually create ‘better than perfect’ health and so the problem has never really been considered by health economists. This PhD thesis proposes that human enhancements – technologies which can “modify basic parameters of the human condition, which were previously thought immutable” (Bostrom & Roache, 2008) – might be able to create ‘better than perfect’ health states, and traces some of the implications of this for NHSes under current HTA rules. The key observation is that there is no obvious practical limit to how much better than ‘perfect’ health could get, and therefore a risk that following HTA rules blindly could lead to an NHS becoming ‘Subverted’ – NHSes becoming vehicles for prescribing this wonderful enhancement rather than making sick people healthier. It is therefore critical that the NHS regulators – and most specifically HTA agencies – adopt a systematic approach to ‘better than perfect’ healthcare to prevent this outcome if they believe it to be unjust. To begin to develop such a systematic approach, this thesis creates an economic theory of human enhancement and tests whether there is any approach which is consistent with all implications of this theory. The study draws heavily on interdisciplinary readings of the relatively developed bioethics literature on ‘better than perfect’ health and the health economic methods of health technology appraisal. It is hoped that the results from this approach will inform the response of HTA agencies and other regulators to the emerging issue of ‘better than perfect’ healthcare technologies in a health technology appraisal context, as well as providing meaningful avenues of further research on the same topic

Operational issues and network effects in vaccine markets.

One of the most important concerns for managing public health is the prevention of infectious diseases. Although vaccines provide the most effective means for preventing infectious diseases, there are two main reasons why it is often difficult to reach a socially optimal level of vaccine coverage: (i) the emergence of operational issues (such as yield uncertainty) on the supply side, and (ii) the existence of negative network effects on the consumption side. In particular, uncertainties about production yield and vaccine imperfections often make manufacturing some vaccines a risky process and may lead the manufacturer to produce below the socially optimal level. At the same time, negative network effects provide incentives to potential consumers to free ride off the immunity of the vaccinated population. In this research, we consider how a central policy-maker can induce a socially optimal vaccine coverage through the use of incentives to both consumers and the vaccine manufacturer. We consider a monopoly market for an imperfect vaccine; we show that a fixed two-part subsidy is unable to coordinate the market, but derive a two-part menu of subsidies that leads to a socially efficient level of coverage