Cost-effectiveness of antiviral stockpiling and near-patient testing for potential influenza pandemic

The FLURESP European commission project: cost-effectiveness assessment of ten public health measures against influenza in Italy: is there an interest in COVID-19 pandemic?

BACKGROUND

The FLURESP project is a public health research funded by the European Commission, with the objective to design a methodological framework to assess the cost-effectiveness of existing public health measures against human influenza pandemics. A dataset has been specifically collected in the frame of the Italian health system. As most of interventions against human influenza are relavant against other respiratory diseases pandemics, potential interests in COVID-19 are discussed.

METHODS

Ten public health measures against human influenza pandemics pandemic were selected to be also relevant to other respiratory virus pandemics such as COVID 19: individual (hand washing, using masks), border control (quarantine, fever screening, border closure), community infection (school closure, class dismissal, social distancing, limitation of public transport), reduction of secondary infections (implementation of antibiotic therapy guidelines), pneumococcal vaccination for at-risk people, development of Intensive Care Unit (ICU) capacity, implementation of life support equipments in ICU, screening interventions, vaccination programs targeting health professional and targeting general population.

RESULTS

Using mortality reduction as effectiveness criteria, the most cost-effective strategies are "reduction of secondary infections" and "implementation of life support equipment in ICU". The least cost-effective option whatever the level of pandemic events are screening interventions and mass vaccination.

CONCLUSIONS

A number of intervention strategies against human influenza pandemics appears relevant against every respiratory virus, including the COVID-19 event. Measures against pandemics should be considered according to their expected effectiveness but also their costs for the society because they impose substantial burden to the population, confirming the interest of considering cost-effectiveness of public health measures to enlighten decision making.

Economic evaluations of interventions against viral pandemics: a scoping review

Objectives

The COVID-19 pandemic has led to suggestions that cost-effectiveness analyses should adopt a broader perspective when estimating costs. This review aims to provide an overview of economic evaluations of interventions against viral pandemics in terms of the perspective taken, types of costs included, comparators, type of economic model, data sources and methods for estimating productivity costs.

Study design

Scoping literature review.

Methods

Publications were eligible if they conducted a cost-effectiveness analysis, cost-utility analysis, cost-benefit analysis or cost-minimisation analysis and evaluated interventions aimed at viral pandemics or for patients infected with viral pandemic disease. We searched PubMed, Embase and Scopus for relevant references and charted data from the selected full-text publications into a predefined spreadsheet based on research sub-questions, summary tables and figures.

Results

From 5410 references, 36 full-text publications fulfilled the inclusion criteria. The economic evaluations were mainly model based and included direct medical costs of hospital treatment. Around half of the studies included productivity costs and the proportion of total costs attributed to productivity costs ranged from 10% to 90%, depending on estimation methods, assumptions about valuation of time, type of intervention, severity of illness and degree of transmission.

Conclusions

Economic evaluations of interventions against viral pandemics differed in terms of estimation methods and reporting of productivity costs, even for similar interventions. Hence, the literature on economic evaluations for pandemic response would benefit from having standards for conducting and reporting economic evaluations, especially for productivity costs.

Economic Analyses of Respiratory Tract Infection Diagnostics: A Systematic Review

BACKGROUND

Diagnostic testing for respiratory tract infections is a tool to manage the current COVID-19 pandemic, as well as the rising incidence of antimicrobial resistance. At the same time, new European regulations for market entry of in vitro diagnostics, in the form of the in vitro diagnostic regulation, may lead to more clinical evidence supporting health-economic analyses.

OBJECTIVE

The objective of this systematic review was to review the methods used in economic evaluations of applied diagnostic techniques, for all patients seeking care for infectious diseases of the respiratory tract (such as pneumonia, pulmonary tuberculosis, influenza, sinusitis, pharyngitis, sore throats and general respiratory tract infections).

METHODS

Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, articles from three large databases of scientific literature were included (Scopus, Web of Science and PubMed) for the period January 2000 to May 2020.

RESULTS

A total of 70 economic analyses are included, most of which use decision tree modelling for diagnostic testing for respiratory tract infections in the community-care setting. Many studies do not incorporate a generally comparable clinical outcome in their cost-effectiveness analysis: fewer than half the studies (33/70) used generalisable outcomes such as quality-adjusted life-years. Other papers consider outcomes related to the accuracy of the test or outcomes related to the prescribed treatment. The time horizons of the studies generally are limited.

CONCLUSIONS

The methods to economically assess diagnostic tests for respiratory tract infections vary and would benefit from clear recommendations from policy makers on the assessed time horizon and outcomes used.

Pandemic risk management: Resources contingency planning and allocation

The repeated history of pandemics, such as SARS, H1N1, Ebola, Zika, and COVID-19, has shown that pandemic risk is inevitable. Extraordinary shortages of medical resources have been observed in many parts of the world. Some attributing factors include the lack of sufficient stockpiles and the lack of coordinated efforts to deploy existing resources to the locations of greatest need. This paper investigates contingency planning and resources allocation from a risk management perspective, as opposed to the prevailing supply chain perspective. The key idea is that the competition for limited critical resources is not only present in different geographical locations but also at different stages of a pandemic. This paper draws on an analogy between risk aggregation and capital allocation in finance and pandemic resources planning and allocation for healthcare systems. The main contribution is to introduce new strategies for optimal stockpiling and allocation balancing spatio-temporal competition for medical supply and demand.

Cost-effectiveness of public health interventions against human influenza pandemics in France: a methodological contribution from the FLURESP European Commission project

BACKGROUND

The FLURESP project is a public health project funded by the European Commission with the objective to design a methodological approach in order to compare the cost-effectiveness of existing public health measures against human influenza pandemics in four target countries: France, Italy, Poland and Romania. This article presents the results relevant to the French health system using a data set specifically collected for this purpose.

METHODS

Eighteen public health interventions against human influenza pandemics were selected. Additionally, two public-health criteria were considered: 'achieving mortality reduction ≥40%' and 'achieving morbidity reduction ≥30%'. Costs and effectiveness data sources include existing reports, publications and expert opinions. Cost distributions were taken into account using a uniform distribution, according to the French health system.

RESULTS

Using reduction of mortality as an effectiveness criterion, the most cost-effective options was 'implementation of new equipment of Extracorporeal membrane oxygenation (ECMO) equipment'. Targeting vaccination to health professionals appeared more cost-effective than vaccination programs targeting at risk populations. Concerning antiviral distribution programs, curative programs appeared more cost-effective than preventive programs. Using reduction of morbidity as effectiveness criterion, the most cost-effective option was 'implementation of new equipment ECMO'. Vaccination programs targeting the general population appeared more cost-effective than both vaccination programs of health professionals or at-risk populations. Curative antiviral programs appeared more cost-effective than preventive distribution programs, whatever the pandemic scenario.

CONCLUSION

Intervention strategies against human influenza pandemics impose a substantial economic burden, suggesting a need to develop public-health cost-effectiveness assessments across countries.

Specimen Pooling to Conserve Additional Testing Resources When Persons' Infection Status Is Correlated: A Simulation Study

In the early stages of a novel pandemic, testing is simultaneously in high demand and low supply, making efficient use of tests of paramount importance. One approach to improve the efficiency of tests is to mix samples from multiple individuals, only testing individuals when the pooled sample returns a positive. To reflect potential clusters of cases that might queue at a testing site and that might increase the efficiency of batch testing, I simulate 10,000 persons being tested in sequence. I use a prevalence ranging from 1% to 45% and batch sizes ranging from 3 to 25 and assume the increased probability of consecutive infections ranges from 0% to 45%. I find that as the likelihood of clustered infections increases, the efficiency of specimen pooling increases. This analysis suggests that when clusters of infected persons exist at testing sites, specimen pooling can remain efficient even as prevalence increases. See video abstract: http://links.lww.com/EDE/B729.

Maintaining efficient logistics and supply chain management operations during and after coronavirus (COVID-19) pandemic: learning from the past experiences

The outbreak of the novel coronavirus (COVID-19) forced the governing bodies across the world to ban all kinds of travel involving the movement of people. However, the policymakers have been working hard to mobilize the movement of essential goods and services considering its importance in containing the pandemic. It signifies how important the establishment and maintenance of logistics and supply chain management (LSCM) operations are, both during the containment and the successive periods. Motivated with the paramount importance of LSCM operations during the rapid spread of the novel coronavirus (COVID-19) across the globe, this paper critically reviews the existing literature closely related to it. The main aim is to identify and enhance the understanding of the logistical characteristics that play a vital role during pandemics. The selection of the literature was done using Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) methodology. The classification of the selected literature was done using a tripartite framework. Results show that researchers have focused mostly on "Post-event" (48.24%) management of logistical operations followed by the "Pre-event" (31.76%) and least in the "Integrated" (20%.) approaches. Furthermore, the analysis of the results provided useful insights that are discussed in detail. Also, twelve key areas have been identified that need due attention to improve the overall efficiency of the LSCM operations. We believe that the findings from this paper would be useful to the decision-makers and other stakeholders, as far as, maintaining efficient LSCM operations during as well after the pandemics are concerned.

Optimising age coverage of seasonal influenza vaccination in England: A mathematical and health economic evaluation

For infectious disease prevention, policy-makers are typically required to base policy decisions in light of operational and monetary restrictions, prohibiting implementation of all candidate interventions. To inform the evidence-base underpinning policy decision making, mathematical and health economic modelling can be a valuable constituent.

Applied to England, this study aims to identify the optimal target age groups when extending a seasonal influenza vaccination programme of at-risk individuals to those individuals at low risk of developing complications following infection. To perform this analysis, we utilise an age- and strain-structured transmission model that includes immunity propagation mechanisms which link prior season epidemiological outcomes to immunity at the beginning of the following season. Making use of surveillance data from the past decade in conjunction with our dynamic model, we simulate transmission dynamics of seasonal influenza in England from 2012 to 2018. We infer that modified susceptibility due to natural infection in the previous influenza season is the only immunity propagation mechanism to deliver a non-negligible impact on the transmission dynamics. Further, we discerned case ascertainment to be higher for young infants compared to adults under 65 years old, and uncovered a decrease in case ascertainment as age increased from 65 to 85 years of age.

Our health economic appraisal sweeps vaccination age space to determine threshold vaccine dose prices achieving cost-effectiveness under differing paired strategies. In particular, we model offering vaccination to all those low-risk individuals younger than a given age (but no younger than two years old) and all low-risk individuals older than a given age, while maintaining vaccination of at-risk individuals of any age. All posited strategies were deemed cost-effective. In general, the addition of low-risk vaccination programmes whose coverage encompassed children and young adults (aged 20 and below) were highly cost-effective. The inclusion of elder age-groups to the low-risk programme typically lessened the cost-effectiveness. Notably, elderly-centric programmes vaccinating from 65-75 years and above had the least permitted expense per vaccine.

Vaccination is an established method to provide protection against seasonal influenza and its complications. Yet, a need to administer an updated vaccine on an annual basis presents significant operational challenges and sizeable costs. Consequently, policy makers typically have to decide how to deploy a finite amount of resource in a cost-effective manner. A combination of mathematical and health economic modelling can be used to address such a question. Here, we developed an age- and strain-structured mathematical model for seasonal influenza transmission dynamics that incorporates mechanisms for immunity propagation, which we used to reconstruct transmission dynamics of seasonal influenza in England from 2012 to 2018.

We then performed a health economic evaluation assessing the cost-effectiveness of extending a seasonal influenza vaccination programme of at-risk individuals to also include, for targeted age groups, those individuals at low risk of developing complications following infection. The findings suggest the inclusion of low-risk vaccination programmes whose coverage encompassed children and young adults (aged 20 and below) to be highly cost-effective. In contrast, the inclusion of elder age-groups to the low-risk programme typically lessened the cost-effectiveness.

Antiviral treatment for outpatient use during an influenza pandemic: a decision tree model of outcomes averted and cost-effectiveness

Background

Many countries have acquired antiviral stockpiles for pandemic influenza mitigation and a significant part of the stockpile may be focussed towards community-based treatment.

Methods

We developed a spreadsheet-based, decision tree model to assess outcomes averted and cost-effectiveness of antiviral treatment for outpatient use from the perspective of the healthcare payer in the UK. We defined five pandemic scenarios—one based on the 2009 A(H1N1) pandemic and four hypothetical scenarios varying in measures of transmissibility and severity.

Results

Community-based antiviral treatment was estimated to avert 14–23% of hospitalizations in an overall population of 62.28 million. Higher proportions of averted outcomes were seen in patients with high-risk conditions, when compared to non-high-risk patients. We found that antiviral treatment was cost-saving across pandemic scenarios for high-risk population groups, and cost-saving for the overall population in higher severity influenza pandemics. Antiviral effectiveness had the greatest influence on both the number of hospitalizations averted and on cost-effectiveness.

Conclusions

This analysis shows that across pandemic scenarios, antiviral treatment can be cost-saving for population groups at high risk of influenza-related complications.

Distributed Manufacturing of Open Source Medical Hardware for Pandemics

Distributed digital manufacturing offers a solution to medical supply and technology shortages during pandemics. To prepare for the next pandemic, this study reviews the state-of-the-art of open hardware designs needed in a COVID-19-like pandemic. It evaluates the readiness of the top twenty technologies requested by the Government of India. The results show that the majority of the actual medical products have some open source development, however, only 15% of the supporting technologies required to produce them are freely available. The results show there is still considerable research needed to provide open source paths for the development of all the medical hardware needed during pandemics. Five core areas of future research are discussed, which include (i) technical development of a wide-range of open source solutions for all medical supplies and devices, (ii) policies that protect the productivity of laboratories, makerspaces, and fabrication facilities during a pandemic, as well as (iii) streamlining the regulatory process, (iv) developing Good-Samaritan laws to protect makers and designers of open medical hardware, as well as to compel those with knowledge that will save lives to share it, and (v) requiring all citizen-funded research to be released with free and open source licenses.

Estimates for quality of life loss due to Respiratory Syncytial Virus

BACKGROUND

In children aged <5 years in whom severe respiratory syncytial virus (RSV) episodes predominantly occur, there are currently no appropriate standardised instruments to estimate quality of life years (QALY) loss.

OBJECTIVES

We estimated the age-specific QALY loss due to RSV by developing a regression model which predicts the QALY loss without the use of standardised instruments.

METHODS

We conducted a surveillance study which targeted confirmed RSV episodes in children aged <5 years (confirmed cases) and their household members who experienced symptoms of RSV during the same time (suspected cases). All participants were asked to complete questions regarding their health during the infection, with the suspected cases additionally providing health-related quality of life (HR-QoL) loss estimates by completing EQ-5D-3L-Y or EQ-5D-3L instruments. We used the responses from the suspected cases to calibrate a regression model which estimates the HR-QoL and QALY loss due to infection.

FINDINGS

For confirmed RSV cases in children under 5 years of age who sought health care, our model predicted a QALY loss per RSV episode of 3.823 × 10-3 (95% CI 0.492-12.766 × 10-3 ), compared with 3.024 × 10-3 (95% CI 0.329-10.098 × 10-3 ) for under fives who did not seek health care. Quality of life years loss per episode was less for older children and adults, estimated as 1.950 × 10-3 (0.185-9.578 × 10-3 ) and 1.543 × 10-3 (0.136-6.406 × 10-3 ) for those who seek or do not seek health care, respectively.

CONCLUSION

Evaluations of potential RSV vaccination programmes should consider their impact across the whole population, not just young child children.

Investing in antibiotics to alleviate future catastrophic outcomes: What is the value of having an effective antibiotic to mitigate pandemic influenza?

Over 95% of post-mortem samples from the 1918 pandemic, which caused 50 to 100 million deaths, showed bacterial infection complications. The introduction of antibiotics in the 1940s has since reduced the risk of bacterial infections, but growing resistance to antibiotics could increase the toll from future influenza pandemics if secondary bacterial infections are as serious as in 1918, or even if they are less severe. We develop a valuation model of the option to withhold wide use of an antibiotic until significant outbreaks such as pandemic influenza or foodborne diseases are identified. Using real options theory, we derive conditions under which withholding wide use is beneficial, and calculate the option value for influenza pandemic scenarios that lead to secondary infections with a resistant Staphylococcus aureus strain. We find that the value of withholding an effective novel oral antibiotic can be positive and significant unless the pandemic is mild and causes few secondary infections with the resistant strain or if most patients can be treated intravenously. Although the option value is sensitive to parameter uncertainty, our results suggest that further analysis on a case-by-case basis could guide investment in novel agents as well as strategies on how to use them.

Model-based economic evaluations of diagnostic point of care tests were rarely fit for purpose

OBJECTIVES

Linked evidence models are recommended to predict health benefits and cost-effectiveness of diagnostic tests. We considered how published models accounted for changes in patient pathways that occur with point of care tests (POCTs) and their impact on patient health and costs.

STUDY DESIGN AND SETTING

Model-based evaluations of diagnostic POCTs published from 2004 to 2017 were identified from searching six databases. For each model, we assessed the outcomes considered, and whether reduced time to diagnosis and increased access to testing affected patient health and costs.

RESULTS

Seventy-four model-based evaluations were included: 95% incorporated evidence on test accuracy, but 34% only assessed intermediate outcomes such as rates of correct diagnosis. Of 54 models where POCTs reduced testing time, 39% addressed the economic and 37% addressed the health benefits of faster diagnosis. No model considered differences in access to tests.

CONCLUSION

Many models fail to capture the effects of POCTs in increasing access, advancing speed of diagnosis and treatment, and reducing anxiety and the associated costs. Many only consider the impact of testing from changes in accuracy. Ensuring models incorporate changes in patient pathways from faster and more accessible testing will lead to economic evaluations that better reflect the impact of POCTs.

Using integrated modeling to support the global eradication of vaccine-preventable diseases

The long-term management of global disease eradication initiatives involves numerous inherently dynamic processes, health and economic trade-offs, significant uncertainty and variability, rare events with big consequences, complex and inter-related decisions, and a requirement for cooperation among a large number of stakeholders. Over the course of more than 16 years of collaborative modeling efforts to support the Global Polio Eradication Initiative, we developed increasingly complex integrated system dynamics models that combined numerous analytical approaches, including differential equation-based modeling, risk and decision analysis, discrete-event and individual-based simulation, probabilistic uncertainty and sensitivity analysis, health economics, and optimization. We discuss the central role of systems thinking and system dynamics in the overall effort and the value of integrating different modeling approaches to appropriately address the trade-offs involved in some of the policy questions. We discuss practical challenges of integrating different analytical tools and we provide our perspective on the future of integrated modeling.

From SARS to Avian Influenza Preparedness in Hong Kong

The first human H5N1 case was diagnosed in Hong Kong in 1997. Since then, experience in effective preparedness strategies that target novel influenza viruses has expanded. Here, we report on avian influenza preparedness in public hospitals in Hong Kong to illustrate policies and practices associated with control of emerging infectious diseases. The Hong Kong government's risk-based preparedness plan for influenza pandemics includes 3 response levels for command, control, and coordination frameworks for territory-wide responses. The tiered levels of alert, serious, and emergency response enable early detection based on epidemiological exposure followed by initiation of a care bundle. Information technology, laboratory preparedness, clinical and public health management, and infection control preparedness provide a comprehensive and generalizable preparedness plan for emerging infectious diseases.

Effects of seasonal and pandemic influenza on health-related quality of life, work and school absence in England: Results from the Flu Watch cohort study

BACKGROUND

Estimates of health-related quality of life (HRQoL) and work/school absences for influenza are typically based on medically attended cases or those meeting influenza-like-illness (ILI) case definitions and thus biased towards severe disease. Although community influenza cases are more common, estimates of their effects on HRQoL and absences are limited.

OBJECTIVES

To measure quality-adjusted life days and years (QALDs and QALYs) lost and work/school absences among community cases of acute respiratory infections (ARI), ILI and influenza A and B and to estimate community burden of QALY loss and absences from influenza.

PATIENTS/METHODS

Flu Watch was a community cohort in England from 2006 to 2011. Participants were followed up weekly. During respiratory illness, they prospectively recorded daily symptoms, work/school absences and EQ-5D-3L data and submitted nasal swabs for RT-PCR influenza testing.

RESULTS

Average QALD lost was 0.26, 0.93, 1.61 and 1.84 for ARI, ILI, H1N1pdm09 and influenza B cases, respectively. 40% of influenza A cases and 24% of influenza B cases took time off work/school with an average duration of 3.6 and 2.4 days, respectively. In England, community influenza cases lost 24 300 QALYs in 2010/11 and had an estimated 2.9 million absences per season based on data from 2006/07 to 2009/10.

CONCLUSIONS

Our QALDs and QALYs lost and work and school absence estimates are lower than previous estimates because we focus on community cases, most of which are mild, may not meet ILI definitions and do not result in healthcare consultations. Nevertheless, they contribute a substantial loss of HRQoL on a population level.

Hospital influenza pandemic stockpiling needs: A computer simulation

BACKGROUND

A severe influenza pandemic could overwhelm hospitals but planning guidance that accounts for the dynamic interrelationships between planning elements is lacking. We developed a methodology to calculate pandemic supply needs based on operational considerations in hospitals and then tested the methodology at Mayo Clinic in Rochester, MN.

METHODS

We upgraded a previously designed computer modeling tool and input carefully researched resource data from the hospital to run 10,000 Monte Carlo simulations using various combinations of variables to determine resource needs across a spectrum of scenarios.

RESULTS

Of 10,000 iterations, 1,315 fell within the parameters defined by our simulation design and logical constraints. From these valid iterations, we projected supply requirements by percentile for key supplies, pharmaceuticals, and personal protective equipment requirements needed in a severe pandemic.

DISCUSSION

We projected supplies needs for a range of scenarios that use up to 100% of Mayo Clinic-Rochester's surge capacity of beds and ventilators. The results indicate that there are diminishing patient care benefits for stockpiling on the high side of the range, but that having some stockpile of critical resources, even if it is relatively modest, is most important.

CONCLUSIONS

We were able to display the probabilities of needing various supply levels across a spectrum of scenarios. The tool could be used to model many other hospital preparedness issues, but validation in other settings is needed.

Evidence synthesis and decision modelling to support complex decisions: stockpiling neuraminidase inhibitors for pandemic influenza usage

Objectives: The stockpiling of neuraminidase inhibitor (NAI) antivirals as a defence against pandemic influenza is a significant public health policy decision that must be made despite a lack of conclusive evidence from randomised controlled trials regarding the effectiveness of NAIs on important clinical end points such as mortality. The objective of this study was to determine whether NAIs should be stockpiled for treatment of pandemic influenza on the basis of current evidence. Methods: A decision model for stockpiling was designed. Data on previous pandemic influenza epidemiology was combined with data on the effectiveness of NAIs in reducing mortality obtained from a recent individual participant meta-analysis using observational data. Evidence synthesis techniques and a bias modelling method for observational data were used to incorporate the evidence into the model. The stockpiling decision was modelled for adults (≥16 years old) and the United Kingdom was used as an example. The main outcome was the expected net benefits of stockpiling in monetary terms. Health benefits were estimated from deaths averted through stockpiling. Results: After adjusting for biases in the estimated effectiveness of NAIs, the expected net benefit of stockpiling in the baseline analysis was £444 million, assuming a willingness to pay of £20,000/QALY ($31,000/QALY). The decision would therefore be to stockpile NAIs. There was a greater probability that the stockpile would not be utilised than utilised. However, the rare but catastrophic losses from a severe pandemic justified the decision to stockpile. Conclusions: Taking into account the available epidemiological data and evidence of effectiveness of NAIs in reducing mortality, including potential biases, a decision maker should stockpile anti-influenza medication in keeping with the postulated decision rule.

Evidence synthesis and decision modelling to support complex decisions: stockpiling neuraminidase inhibitors for pandemic influenza usage

Objectives: The stockpiling of neuraminidase inhibitor (NAI) antivirals as a defence against pandemic influenza is a significant public health policy decision that must be made despite a lack of conclusive evidence from randomised controlled trials regarding the effectiveness of NAIs on important clinical end points such as mortality. The objective of this study was to determine whether NAIs should be stockpiled for treatment of pandemic influenza on the basis of current evidence. Methods: A decision model for stockpiling was designed. Data on previous pandemic influenza epidemiology was combined with data on the effectiveness of NAIs in reducing mortality obtained from a recent individual participant meta-analysis using observational data. Evidence synthesis techniques and a bias modelling method for observational data were used to incorporate the evidence into the model. The stockpiling decision was modelled for adults (≥16 years old) and the United Kingdom was used as an example. The main outcome was the expected net benefits of stockpiling in monetary terms. Health benefits were estimated from deaths averted through stockpiling. Results: After adjusting for biases in the estimated effectiveness of NAIs, the expected net benefit of stockpiling in the baseline analysis was £444 million, assuming a willingness to pay of £20,000/QALY ($31,000/QALY). The decision would therefore be to stockpile NAIs. There was a greater probability that the stockpile would not be utilised than utilised. However, the rare but catastrophic losses from a severe pandemic justified the decision to stockpile. Conclusions: Taking into account the available epidemiological data and evidence of effectiveness of NAIs in reducing mortality, including potential biases, a decision maker should stockpile anti-influenza medication in keeping with the postulated decision rule.

Pandemic Risk Assessment Model (PRAM): a mathematical modeling approach to pandemic influenza planning

The Pandemic Risk Assessment Model (PRAM) is a mathematical model developed to analyse two pandemic influenza control measures available to public health: antiviral treatment and immunization. PRAM is parameterized using surveillance data from Alberta, Canada during pandemic H1N1. Age structure and risk level are incorporated in the compartmental, deterministic model through a contact matrix. The model characterizes pandemic influenza scenarios by transmissibility and severity properties. Simulating a worst-case scenario similar to the 1918 pandemic with immediate stockpile release, antiviral demand is 20·3% of the population. With concurrent, effective and timely immunization strategies, antiviral demand would be significantly less. PRAM will be useful in informing policy decisions such as the size of the Alberta antiviral stockpile and can contribute to other pandemic influenza planning activities and scenario analyses.

Sources and Characteristics of Utility Weights for Economic Evaluation of Pediatric Vaccines: A Systematic Review

BACKGROUND

Cost-effectiveness analysis of pediatric vaccines for infectious diseases often requires quality-of-life (utility) weights.

OBJECTIVE

To investigate how utility weights have been elicited and used in this context.

METHODS

A systematic review was conducted of studies published between January 1990 and July 2013 that elicited or used utility weights in cost-effectiveness analyses of vaccines for pediatric populations. The review focused on vaccines for 17 infectious diseases and is presented following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology.

RESULTS

A total of 6410 titles and abstracts and 225 full-text articles were reviewed. Of those selected for inclusion (n = 101), 15 articles described the elicitation of utility weights and 86 described economic modeling studies using utilities. Various methods were used to generate utilities, including time trade-off, contingent valuation, and willingness to pay, as well as a preference-based measure with associated value sets, such as the EuroQol five-dimensional questionnaire or the Health Utilities Index. In modeling studies, the source of utilities used was often unclear, poorly reported, or based on weak underlying evidence. We found no articles that reported on the elicitation or use of utilities in diphtheria, polio, or tetanus.

CONCLUSIONS

The scarcity of appropriate utility weights for vaccine-preventable infectious diseases in children and a lack of standardization in their use in economic assessments limit the ability to accurately assess the benefits associated with interventions to prevent infectious diseases. This is an issue that should be of concern to those making decisions regarding the prevention and treatment of infectious childhood illnesses.

Extending the elderly- and risk-group programme of vaccination against seasonal influenza in England and Wales: a cost-effectiveness study

BACKGROUND

The present study aims to evaluate the cost-effectiveness of extending the pre-2013 influenza immunisation programme for high-risk and elderly individuals to those at low risk of developing complications following infection with seasonal influenza.

METHODS

We performed an economic evaluation comparing different extensions of the pre-2013 influenza programme to seven possible age groups of low-risk individuals (aged 2-4 years, 50-64 years, 5-16 years, 2-4 and 50-64 years, 2-16 years, 2-16 and 50-64 years, and 2-64 years). These extensions are evaluated incrementally on four base scenarios (no vaccination, risk group only with coverage as observed between 1995 and 2009, risk group and 65+, and risk group with 75% coverage and 65+). Impact of vaccination is assessed using a transmission model built and parameterised from a previously published study. The study population is all individuals of all ages in England and Wales representing an average total of 52.6 million people over 14 influenza seasons (1995-2009).

RESULTS

The influenza programme (risk group and elderly) prior to 2013 is likely to be cost effective (incremental cost effectiveness ratio: 7,475 £/QALY, net benefit: 253 M£ [15-829]). Extension to any one of the low-risk target groups defined earlier is likely to be cost-effective. However, strategies that do not include vaccination of school-aged children are less likely to be cost-effective. The most efficient strategy is extension to the 5-16 year age group while universal vaccination (extension to all low-risk individuals over 2 years) will achieve the highest net benefit. While extension to the 2-16 year age group is likely to be very cost effective, the cost-effectiveness of extensions beyond 2-16 years is very uncertain. Extension to the 5-16 year age group would likely remain cost-effective even without herd immunity effects to other age groups. As our study includes a strong historical component, our results depend on the efficacy of the influenza vaccine remaining at levels similar to the ones achieved in the past over a long-period of time (assumed to vary between 28% and 70% depending of the circulating strains and age groups).

CONCLUSIONS

Making use of surveillance data from over a decade in conjunction with a dynamic model, we find that vaccination of children in the United Kingdom is likely to be highly cost-effective, not only for their own benefit but also to reduce the disease burden in the rest of the community.

Targeted vaccination in healthy school children - Can primary school vaccination alone control influenza?

BACKGROUND

The UK commenced an extension to the seasonal influenza vaccination policy in autumn 2014 that will eventually see all healthy children between the ages of 2-16 years offered annual influenza vaccination. Models suggest that the new policy will be both highly effective at reducing the burden of influenza as well as cost-effective. We explore whether targeting vaccination at either primary or secondary schools would be more effective and/or cost-effective than the current strategy.

METHODS

An age-structured deterministic transmission dynamic SEIR-type mathematical model was used to simulate a national influenza outbreak in England. Costs including GP consultations, hospitalisations due to influenza and vaccinations were compared to potential gains in quality-adjusted life years achieved through vaccinating healthy children. Costs and benefits of the new JCVI vaccination policy were estimated over a single season, and compared to the hypothesised new policies of targeted and heterogeneous vaccination.

FINDINGS AND CONCLUSION

All potential vaccination policies were highly cost-effective. Influenza transmission can be eliminated for a particular season by vaccinating both primary and secondary school children, but not by vaccinating only one group. The most cost-effective policy overall is heterogeneous vaccination coverage with 48% uptake in primary schools and 34% in secondary schools. The Joint Committee on Vaccination and Immunisation can consider a modification to their policy of offering seasonal influenza vaccinations to all healthy children of ages 2-16 years.

Cost-effectiveness of influenza vaccination in prior pneumonia patients in Israel

Pneumonia is a common complication of influenza infection, and accounts for the majority of influenza mortality. Both the WHO and the Ministry of Health in Israel prioritize seasonal influenza vaccination primarily on the basis of age and specific co-morbidities. Here we consider whether the targeting of individuals previously infected with pneumonia for influenza vaccination would be a cost-effective addition to the current policy. We performed a retrospective cohort data analysis of 163,990 cases of pneumonia hospitalizations and 1,305,223 cases of outpatient pneumonia from 2004 to 2012, capturing more than 54% of the Israeli population. Our findings demonstrate that patients infected with pneumonia in the year prior had a substantially higher risk of becoming infected with pneumonia in subsequent years (relative risk >2.34, p<0.01). Results indicated that the benefit of targeting for influenza vaccination patients hospitalized with pneumonia in prior year would be cost-saving regardless of age. Complementing the current policy with the targeting of prior pneumonia patients would require vaccination of only a further 2.3% of the Israeli population to save additional 204-407 quality-adjusted life years (QALYs) annually at a mean price of 58-1056 USD/QALY saved. Global uncertainty analysis demonstrates that the cost-effectiveness of adding this policy is robust over a vast range of conditions. As prior pneumonia patients are currently not prioritized for influenza vaccination in Israel, nor elsewhere, this study suggests a novel supplement of current policies to improve cost-effectiveness of influenza vaccination. Future studies should use case-control study to further evaluate the effectiveness of vaccination in prior pneumonia patients.

Cost-effectiveness of pneumococcal vaccines for adults in the United States

Introduction

In 2012, the Advisory Committee on Immunization Practices (ACIP) revised recommendations for adult pneumococcal vaccination to include a sequential regimen of 13-valent pneumococcal conjugate vaccine (PCV13) followed by 23-valent pneumococcal polysaccharide vaccine (PPSV23) for certain high-risk adults with immunocompromising conditions. This study, from a payer perspective, examined: (1) the cost-effectiveness of the new 2012 ACIP vaccine policy recommendation relative to the 1997 ACIP recommendation; (2) the cost-effectiveness of potential future pneumococcal vaccination policies; and (3) key assumptions that influence study results.

Methods

A static cohort model that incorporated costs, health outcomes, and quality-adjusted life-year (QALY) losses associated with invasive pneumococcal disease and non-bacteremic pneumococcal pneumonia (NBPP) was developed to evaluate seven pneumococcal vaccination strategies for a 50-year-old adult cohort over a 50-year period using incremental cost-effectiveness ratios (ICERs).

Results

For objective 1, the 2012 ACIP recommendation is the more economically efficient strategy (ICER was $25,841 per QALY gained vs. no vaccination). For objective 2, the most efficient vaccination policy would be to maintain the 2012 recommendation for PPSV23 for healthy and immunocompetent adults with comorbidities, and to modify the recommendation for adults with immunocompromising conditions by replacing PPSV23 with a sequential regimen of PCV13 and PPSV23 at age 65 (ICER was $23,416 per QALY gained vs. no vaccination). For objective 3, cost-effectiveness ratios for alternative pneumococcal vaccine policies were highly influenced by assumptions used for vaccine effectiveness against NBPP and accounting for the herd protection effects of pediatric PCV13 vaccination on adult pneumococcal disease.

Conclusion

Modifying the 2012 recommendation to include an additional dose of PCV13 at age 65, followed by PPSV23, for adults with immunocompromising conditions appears to be a cost-effective vaccine policy. Given the uncertainty in the available data and the absence of key influential data, comprehensive sensitivity analyses should be conducted by policy-makers when evaluating new adult pneumococcal vaccine strategies.

Electronic supplementary material

The online version of this article (doi:10.1007/s12325-014-0115-y) contains supplementary material, which is available to authorized users.

Buy now, saved later? The critical impact of time-to-pandemic uncertainty on pandemic cost-effectiveness analyses

Background Investment in pandemic preparedness is a long-term gamble, with the return on investment coming at an unknown point in the future. Many countries have chosen to stockpile key resources, and the number of pandemic economic evaluations has risen sharply since 2009. We assess the importance of uncertainty in time-to-pandemic (and associated discounting) in pandemic economic evaluation, a factor frequently neglected in the literature to-date.

Methods We use a probability tree model and Monte Carlo parameter sampling to consider the cost effectiveness of antiviral stockpiling in Cambodia under parameter uncertainty. Mean elasticity and mutual information (MI) are used to assess the importance of time-to-pandemic compared with other parameters. We also consider the sensitivity to choice of sampling distribution used to model time-to-pandemic uncertainty.

Results Time-to-pandemic and discount rate are the primary drivers of sensitivity and uncertainty in pandemic cost effectiveness models. Base case cost effectiveness of antiviral stockpiling ranged between is US$112 and US$3599 per DALY averted using historical pandemic intervals for time-to-pandemic. The mean elasticities for time-to-pandemic and discount rate were greater than all other parameters. Similarly, the MI scores for time to pandemic and discount rate were greater than other parameters. Time-to-pandemic and discount rate were key drivers of uncertainty in cost-effectiveness results regardless of time-to-pandemic sampling distribution choice.

Conclusions Time-to-pandemic assumptions can “substantially” affect cost-effectiveness results and, in our model, is a greater contributor to uncertainty in cost-effectiveness results than any other parameter. We strongly recommend that cost-effectiveness models include probabilistic analysis of time-to-pandemic uncertainty.

Economic Evidence and Point-of-Care Testing

Health economics has been an established feature of the research, policymaking, practice and management in the delivery of healthcare. However its role is increasing as the cost of healthcare begins to drive changes in most healthcare systems. Thus the output from cost effectiveness studies is now being taken into account when making reimbursement decisions, e.g. in Australia and the United Kingdom. Against this background it is also recognised that the health economic tools employed in healthcare, and particularly the output from the use of these tools however, are not always employed in the routine delivery of services. One of the notable consequences of this situation is the poor record of innovation in healthcare with respect to the adoption of new technologies, and the realisation of their benefits. The evidence base for the effectiveness of diagnostic services is well known to be limited, and one consequence of this has been a very limited literature on cost effectiveness. One reason for this situation is undoubtedly the reimbursement strategies employed in laboratory medicine for many years, simplistically based on the complexity of the test procedure, and the delivery as a cost-per-test service. This has proved a disincentive to generate the required evidence, and little effort to generate an integrated investment and disinvestment business case, associated with care pathway changes. Point-of-care testing creates a particularly challenging scenario because, on the one hand, the unit cost-per-test is larger through the loss of the economy of scale offered by automation, whilst it offers the potential of substantial savings through enabling rapid delivery of results, and reduction of facility costs. This is important when many health systems are planning for complete system redesign. We review the literature on economic assessment of point-of-care testing in the context of these developments.

Using a Dynamic Model to Consider Optimal Antiviral Stockpile Size in the Face of Pandemic Influenza Uncertainty

BACKGROUND

The Canadian National Antiviral Stockpile (NAS) contains treatment for 17.5% of Canadians. This assumes no concurrent intervention strategies and no wastage due to non-influenza respiratory infections. A dynamic model can provide a mechanism to consider complex scenarios to support decisions regarding the optimal NAS size under uncertainty.

METHODS

We developed a dynamic model for pandemic influenza in Canada that is structured by age and risk to calculate the demand for antivirals to treat persons with pandemic influenza under a wide-range of scenarios that incorporated transmission dynamics, disease severity, and intervention strategies. The anticipated per capita number of acute respiratory infections due to viruses other than influenza was estimated for the full pandemic period from surveys based on criteria to identify potential respiratory infections.

RESULTS

Our results demonstrate that up to two thirds of the population could develop respiratory symptoms as a result of infection with a pandemic strain. In the case of perfect antiviral allocation, up to 39.8% of the population could request antiviral treatment. As transmission dynamics, severity and timing of the emergence of a novel influenza strain are unknown, the sensitivity analysis produced considerable variation in potential demand (median: 11%, IQR: 2-21%). If the next pandemic strain emerges in late spring or summer and a vaccine is available before the anticipated fall wave, the median prediction was reduced to 6% and IQR to 0.7-14%. Under the strategy of offering empirical treatment to all patients with influenza like symptoms who present for care, demand could increase to between 65 and 144%.

CONCLUSIONS

The demand for antivirals during a pandemic is uncertain. Unless an accurate, timely and cost-effective test is available to identify influenza cases, demand for antivirals from persons infected with other respiratory viruses will be substantial and have a significant impact on the NAS.

Analysis of 2009 pandemic influenza A/H1N1 outcomes in 19 European countries: association with completeness of national strategic plans

OBJECTIVE

To describe changes in reported influenza activity associated with the 2009 H1N1 pandemic in European countries and determine whether there is a correlation between these changes and completeness of national strategic pandemic preparedness.

DESIGN

A retrospective correlational study.

SETTING

Countries were included if their national strategic plans had previously been analysed and if weekly influenza-like illness (ILI) data from sentinel networks between week 21, 2006 and week 20, 2010 were more than 50% complete.

OUTCOME MEASURES

For each country we calculated three outcomes: the percentage change in ILI peak height during the pandemic relative to the prepandemic mean; the timing of the ILI peak and the percentage change in total cases relative to the prepandemic mean. Correlations between these outcomes and completeness of a country's national strategic pandemic preparedness plan were assessed using the Pearson product-moment correlation coefficient.

RESULTS

Nineteen countries were included. The ILI peak occurred earlier than the mean seasonal peak in 17 countries. In 14 countries the pandemic peak was higher than the seasonal peak, though the difference was large only in Norway, the UK and Greece. Nine countries experienced more total ILI cases during the pandemic compared with the mean for prepandemic years. Five countries experienced two distinct pandemic peaks. There was no clear pattern of correlation between overall completeness of national strategic plans and pandemic influenza outcome measures and no evidence of association between these outcomes and components of pandemic plans that might plausibly affect influenza outcomes (public health interventions, vaccination, antiviral use, public communication). Amongst the 17 countries with a clear pandemic peak, only the correlation between planning for essential services and change in total ILI cases significantly differed from zero: correlation coefficient (95% CI) 0.50 (0.02, 0.79).

CONCLUSIONS

The diversity of pandemic influenza outcomes across Europe is not explained by the marked variation in the completeness of pandemic plans.

Recommendations for the prevention and treatment of influenza using antiviral drugs based on cost-effectiveness

Influenza is an acute respiratory disease that causes epidemics and pandemics in the human population of temperate regions. Influenza epidemics occur every year during the winter months, affecting approximately 10% of the population. The primary strategy for reducing the effect of influenza in the community is to vaccinate persons who are at risk or caring for high-risk individuals each year before seasonal increases in influenza virus circulation occur. Antiviral drugs can be used for the treatment of influenza and the prevention of seasonal and post-exposure influenza. Four antiviral drugs are available for the prevention and treatment of influenza infections: oseltamivir, zanamivir, rimantadine and amantadine. Antiviral drugs can be used for the treatment of influenza and for post-exposure and seasonal influenza prevention. The cost-effectiveness of antiviral therapies ranged from cost savings to more than US$130,000 per quality-adjusted life-year (QALY) for influenza treatment, from GB pound9000 to more than pound1 million per QALY for seasonal prevention and from cost savings to pound100,000 per QALY for post-exposure prevention. Based on the cost-effectiveness threshold of pound30,000 or $40,000 per QALY, antiviral therapies can be recommended for influenza treatment and post-exposure prevention in healthy and high-risk individuals and for seasonal prevention in high-risk individuals. Zanamivir, oseltamivir and amantadine have favorable cost-effectiveness ratios for these interventions, but amantadine should only be used in countries with a low prevalence of resistant virus. The stockpile of antiviral drugs should be maintained in developed countries because they are cost effective for the prevention and treatment of a possible influenza pandemic.

Systematic review of economic evaluations of preparedness strategies and interventions against influenza pandemics

BACKGROUND

Although public health guidelines have implications for resource allocation, these issues were not explicitly considered in previous WHO pandemic preparedness and response guidance. In order to ensure a thorough and informed revision of this guidance following the H1N1 2009 pandemic, a systematic review of published and unpublished economic evaluations of preparedness strategies and interventions against influenza pandemics was conducted.

METHODS

The search was performed in September 2011 using 10 electronic databases, 2 internet search engines, reference list screening, cited reference searching, and direct communication with relevant authors. Full and partial economic evaluations considering both costs and outcomes were included. Conversely, reviews, editorials, and studies on economic impact or complications were excluded. Studies were selected by 2 independent reviewers.

RESULTS

44 studies were included. Although most complied with the cost effectiveness guidelines, the quality of evidence was limited. However, the data sources used were of higher quality in economic evaluations conducted after the 2009 H1N1 pandemic. Vaccination and drug regimens were varied. Pharmaceutical plus non-pharmaceutical interventions are relatively cost effective in comparison to vaccines and/or antivirals alone. Pharmaceutical interventions vary from cost saving to high cost effectiveness ratios. According to ceiling thresholds (Gross National Income per capita), the reduction of non-essential contacts and the use of pharmaceutical prophylaxis plus the closure of schools are amongst the cost effective strategies for all countries. However, quarantine for household contacts is not cost effective even for low and middle income countries.

CONCLUSION

The available evidence is generally inconclusive regarding the cost effectiveness of preparedness strategies and interventions against influenza pandemics. Studies on their effectiveness and cost effectiveness should be readily implemented in forthcoming events that also involve the developing world. Guidelines for assessing the impact of disease and interventions should be drawn up to facilitate these studies.

The impact of pandemic influenza H1N1 on health-related quality of life: a prospective population-based study

Background

While the H1N1v influenza pandemic in 2009 was clinically mild, with a low case-fatality rate, the overall disease burden measured in quality-adjusted life years (QALY) lost has not been estimated. Such a measure would allow comparison with other diseases and assessment of the cost-effectiveness of pandemic control measures.

Methods and Findings

Cases of H1N1v confirmed by polymerase chain reaction (PCR) and PCR negative cases with similar influenza-like illness (ILI controls) in 7 regions of England were sent two questionnaires, one within a week of symptom onset and one two weeks later, requesting information on duration of illness, work loss and antiviral use together with EQ-5D questionnaires. Results were compared with those for seasonal influenza from a systematic literature review. A total QALY loss for the 2009 pandemic in England was calculated based on the estimated total clinical cases and reported deaths. A total of 655 questionnaires were sent and 296 (45%) returned. Symptoms and average illness duration were similar between confirmed cases and ILI controls (8.8 days and 8.7 days respectively). Days off work were greater for cases than ILI controls (7.3 and 4.9 days respectively, p = 0.003). The quality-adjusted life days lost was 2.92 for confirmed cases and 2.74 for ILI controls, with a reduction in QALY loss after prompt use of antivirals in confirmed cases. The overall QALY loss in the pandemic was estimated at 28,126 QALYs (22,267 discounted) of which 40% was due to deaths (24% with discounting).

Conclusion

Given the global public health significance of influenza, it is remarkable that no previous prospective study of the QALY loss of influenza using standardised and well validated methods has been performed. Although the QALY loss was minor for individual patients, the estimated total burden of influenza over the pandemic was substantial when compared to other infectious diseases.

Strategies for antiviral stockpiling for future influenza pandemics: a global epidemic-economic perspective

Influenza pandemics present a global threat owing to their potential mortality and substantial economic impacts. Stockpiling antiviral drugs to manage a pandemic is an effective strategy to offset their negative impacts; however, little is known about the long-term optimal size of the stockpile under uncertainty and the characteristics of different countries. Using an epidemic-economic model we studied the effect on total mortality and costs of antiviral stockpile sizes for Brazil, China, Guatemala, India, Indonesia, New Zealand, Singapore, the UK, the USA and Zimbabwe. In the model, antivirals stockpiling considerably reduced mortality. There was greater potential avoidance of expected costs in the higher resourced countries (e.g. from $55 billion to $27 billion over a 30 year time horizon for the USA) and large avoidance of fatalities in those less resourced (e.g. from 11.4 to 2.3 million in Indonesia). Under perfect allocation, higher resourced countries should aim to store antiviral stockpiles able to cover at least 15 per cent of their population, rising to 25 per cent with 30 per cent misallocation, to minimize fatalities and economic costs. Stockpiling is estimated not to be cost-effective for two-thirds of the world's population under current antivirals pricing. Lower prices and international cooperation are necessary to make the life-saving potential of antivirals cost-effective in resource-limited countries.

Cost-effectiveness of stockpiling 23-valent pneumococcal polysaccharide vaccine to prevent secondary pneumococcal infections among a high-risk population in the United States during an influenza pandemic

BACKGROUND

Secondary bacterial infections (especially pneumococcal infections) were a major cause of death during prior influenza pandemics. One strategy to prevent pneumococcal infections in adults during a future pandemic is to stockpile 23-valent pneumococcal polysaccharide vaccine (PPSV23). Stockpiling a pneumococcal vaccine can ensure that it is available when needed most-that is, at the onset of a pandemic.

OBJECTIVE

The purpose of this article was to project the health and economic impact of stockpiling PPSV23 to prevent secondary pneumococcal infections among high-risk adults aged 18 to 64 years during an influenza pandemic within the United States.

METHODS

A cost-effectiveness model was developed to evaluate the health and economic effects of stockpiling PPSV23 versus not stockpiling this vaccine for preventing secondary pneumococcal infections among 20 million high-risk US adults aged 18 to 64 years during an influenza pandemic. The model was used to project the number of pneumococcal cases, hospitalizations, deaths, and days of work loss averted. Three health outcomes (deaths, hospitalizations, and outpatient care) were estimated from secondary pneumococcal infections. To assess the overall effectiveness of the different strategies, the quality-adjusted life-year (QALY) was used as a measure of these 3 health outcomes. The results are presented for 3 scenarios based on the pandemic severity and anticipated prepandemic influenza vaccine availability: base case, more-severe case, and less-severe case.

RESULTS

In the base-case scenario, vaccinating 20 million high-risk adults with PPSV23 avoided 2858 deaths, 878 hospitalizations, 41,881 pneumococcal pneumonia cases, and 232,891 days of work loss during a pandemic. Under the more-severe case scenario, vaccination avoided 21,921 deaths, 10,280 hospitalizations, 70,345 pneumococcal cases, and approximately 1.12 million days of work loss. Under the less-severe case scenario, pneumococcal vaccination avoided 715 deaths, 219 hospitalizations, 10,470 pneumococcal cases, and 58,235 days of work loss. The incremental cost-effectiveness ratio for stockpiling PPSV23 versus no stockpiling for the base-case and less-severe case scenarios was $39,946 and $198,653 per QALY, respectively. For the more-severe case scenario, stockpiling PPSV23 was cost saving. Probabilistic sensitivity analyses found that the range of incremental cost-effectiveness ratio values was broad due to the large uncertainty regarding the timing and impact of the next pandemic. In addition, the shelf life of PPSV23 and stockpile management substantially influenced the cost-effectiveness ratio.

CONCLUSIONS

For severe pandemics or pandemics in which prepandemic influenza vaccine is unavailable, stockpiling of PPSV23 can be a cost-effective strategy for reducing the health and economic burden associated with secondary pneumococcal infections in a high-risk US population. However, for a mildly severe pandemic in which prepandemic influenza vaccine is available, stockpiling of PPSV23 may not be cost-effective.

The possible macroeconomic impact on the UK of an influenza pandemic

Little is known about the possible impact of an influenza pandemic on a nation's economy. We applied the UK macroeconomic model 'COMPACT' to epidemiological data on previous UK influenza pandemics, and extrapolated a sensitivity analysis to cover more extreme disease scenarios. Analysis suggests that the economic impact of a repeat of the 1957 or 1968 pandemics, allowing for school closures, would be short-lived, constituting a loss of 3.35 and 0.58% of GDP in the first pandemic quarter and year, respectively. A more severe scenario (with more than 1% of the population dying) could yield impacts of 21 and 4.5%, respectively. The economic shockwave would be gravest when absenteeism (through school closures) increases beyond a few weeks, creating policy repercussions for influenza pandemic planning as the most severe economic impact is due to policies to contain the pandemic rather than the pandemic itself.Accounting for changes in consumption patterns made in an attempt to avoid infection worsens the potential impact. Our mild disease scenario then shows first quarter/first year reductions in GDP of 9.5/2.5%, compared with our severe scenario reductions of 29.5/6%. These results clearly indicate the significance of behavioural change over disease parameters.

Investment in antiviral drugs: a real options approach

Real options analysis is a promising approach to model investment under uncertainty. We employ this approach to value stockpiling of antiviral drugs as a precautionary measure against a possible influenza pandemic. Modifications of the real options approach to include risk attitude and deviations from expected utility are presented. We show that risk aversion counteracts the tendency to delay investment for this case of precautionary investment, which is in contrast to earlier applications of risk aversion to real options analysis. Moreover, we provide a numerical example using real world data and discuss the implications of real options analysis for health policy. Suggestions for further extensions of the model and a comparison with the expected value of information analysis are put forward.

Cost-effectiveness of pharmaceutical-based pandemic influenza mitigation strategies

We used a hybrid transmission and economic model to evaluate the relative merits of stockpiling antiviral drugs and vaccine for pandemic influenza mitigation. In the absence of any intervention, our base-case assumptions generated a population clinical attack rate of 31.1%. For at least some parameter values, population prepandemic vaccination strategies were effective at containing an outbreak of pandemic influenza until the arrival of a matched vaccine. Because of the uncertain nature of many parameters, we used a probabilistic approach to determine the most cost-effective strategies. At a willingness to pay of >A$24,000 per life-year saved, more than half the simulations showed that a prepandemic vaccination program combined with antiviral treatment was cost-effective in Australia.

Optimal vaccine stockpile design for an eradicated disease: application to polio

Eradication of a disease promises significant health and financial benefits. Preserving those benefits, hopefully in perpetuity, requires preparing for the possibility that the causal agent could re-emerge (unintentionally or intentionally). In the case of a vaccine-preventable disease, creation and planning for the use of a vaccine stockpile becomes a primary concern. Doing so requires consideration of the dynamics at different levels, including the stockpile supply chain and transmission of the causal agent. This paper develops a mathematical framework for determining the optimal management of a vaccine stockpile over time. We apply the framework to the polio vaccine stockpile for the post-eradication era and present examples of solutions to one possible framing of the optimization problem. We use the framework to discuss issues relevant to the development and use of the polio vaccine stockpile, including capacity constraints, production and filling delays, risks associated with the stockpile, dynamics and uncertainty of vaccine needs, issues of funding, location, and serotype dependent behavior, and the implications of likely changes over time that might occur. This framework serves as a helpful context for discussions and analyses related to the process of designing and maintaining a stockpile for an eradicated disease.

Mitigation of pandemic influenza: review of cost-effectiveness studies

We conducted a review of economic evaluations of pandemic influenza control measures. In the studies found, we detected various interventions being investigated: antiviral stockpiling and treatment, prophylaxis, vaccination, school closure and restricting international travel. Cost-effectiveness varied but often showed potentials for the favorable economic profiles of these measures. Both static and dynamic models were used. We conclude that the choice of an appropriate model - in particular, a dynamic model - is crucial to arrive at valid cost-effectiveness ratios. Yet, of the economic evaluations considered here, only a few were based on dynamic modeling. We recommend that further research is directed toward linking dynamic epidemiological models for pandemic spread with economic outcomes by considering the full impacts on national economies, including direct, indirect, medical and nonmedical costs.

Public health and economic impact of vaccination with 7-valent pneumococcal vaccine (PCV7) in the context of the annual influenza epidemic and a severe influenza pandemic

BACKGROUND

Influenza pandemic outbreaks occurred in the US in 1918, 1957, and 1968. Historical evidence suggests that the majority of influenza-related deaths during the 1918 US pandemic were attributable to bacterial pneumococcal infections. The 2009 novel influenza A (H1N1) outbreak highlights the importance of interventions that may mitigate the impact of a pandemic.

METHODS

A decision-analytic model was constructed to evaluate the impact of 7-valent pneumococcal conjugate vaccine (PCV7) on pneumococcal disease incidence and mortality during a typical influenza season (13/100) and a severe influenza pandemic (30/100). Outcomes were compared for current PCV7 vaccination practices vs. no vaccination. The model was estimated using published sources and includes indirect (herd) protection of non-vaccinated persons.

RESULTS

The model predicts that PCV7 vaccination in the US is cost saving for a normal influenza season, reducing pneumococcal-related costs by $1.6 billion. In a severe influenza pandemic, vaccination would save $7.3 billion in costs and prevent 512,000 cases of IPD, 719,000 cases of pneumonia, 62,000 IPD deaths, and 47,000 pneumonia deaths; 84% of deaths are prevented due to indirect (herd) protection in the unvaccinated.

CONCLUSIONS

PCV7 vaccination is highly effective and cost saving in both normal and severe pandemic influenza seasons. Current infant vaccination practices may prevent >1 million pneumococcal-related deaths in a severe influenza pandemic, primarily due to herd protection.

Vaccination against pandemic influenza A/H1N1v in England: a real-time economic evaluation

Decisions on how to mitigate an evolving pandemic are technically challenging. We present a real-time assessment of the effectiveness and cost-effectiveness of alternative influenza A/H1N1v vaccination strategies. A transmission dynamic model was fitted to the estimated number of cases in real-time, and used to generate plausible autumn scenarios under different vaccination options. The proportion of these cases by age and risk group leading to primary care consultations, National Pandemic Flu Service consultations, emergency attendances, hospitalisations, intensive care and death was then estimated using existing data from the pandemic. The real-time model suggests that the epidemic will peak in early November, with the peak height being similar in magnitude to the summer wave. Vaccination of the high-risk groups is estimated to prevent about 45 deaths (80% credibility interval 26-67), and save around 2900 QALYs (80% credibility interval 1600-4500). Such a programme is very likely to be cost-effective if the cost of vaccine purchase itself is treated as a sunk cost. Extending vaccination to low-risk individuals is expected to result in more modest gains in deaths and QALYs averted. Extending vaccination to school-age children would be the most cost-effective extension. The early availability of vaccines is crucial in determining the impact of such extensions. There have been a considerable number of cases of H1N1v in England, and so the benefits of vaccination to mitigate the ongoing autumn wave are limited. However, certain groups appear to be at significantly higher risk of complications and deaths, and so it appears both effective and cost-effective to vaccinate them. The United Kingdom was the first country to have a major epidemic in Europe. In countries where the epidemic is not so far advanced vaccination of children may be cost-effective. Similar, detailed, real-time modelling and economic studies could help to clarify the situation.

Antiviral medications for pregnant women for pandemic and seasonal influenza: an economic computer model

OBJECTIVE

To estimate the economic value of administering antiviral medications to pregnant women who have come in contact with an infectious individual with influenza.

METHODS

A computer-simulation model was developed to predict the potential economic effect of antiviral use for postexposure prophylaxis among pregnant women in both seasonal influenza and pandemic influenza scenarios. The model allowed us to examine the effects of varying influenza exposure risk, antiviral efficacy, antiviral cost, and the probability of different influenza outcomes such as hospitalization, preterm delivery, and mortality.

RESULTS

For a variety of pandemic influenza scenarios (attack rate 20% or more, probability of preterm birth for women with influenza 12% or more, mortality for a preterm neonate 2% or more, and probability of influenza-attributable hospitalization 4.8% or more), the postexposure prophylactic use of antiviral medications was strongly cost-effective, with incremental cost-effectiveness ratio values below $50,000 per quality-adjusted life-year. Antiviral prophylaxis became an economically dominant strategy (that is, less costly and more effective) when the influenza attack rate is 20% or more and preterm birth rate is 36% or more, and when attack rate is 30% or more and preterm birth rate is 24% or more. Antiviral prophylaxis was not cost-effective under seasonal influenza conditions.

CONCLUSION

These findings support the use of antiviral medications for postexposure prophylaxis among pregnant women in a pandemic influenza scenario but not in a seasonal influenza setting.

Influenza outbreak during Sydney World Youth Day 2008: the utility of laboratory testing and case definitions on mass gathering outbreak containment

BACKGROUND

Influenza causes annual epidemics and often results in extensive outbreaks in closed communities. To minimize transmission, a range of interventions have been suggested. For these to be effective, an accurate and timely diagnosis of influenza is required. This is confirmed by a positive laboratory test result in an individual whose symptoms are consistent with a predefined clinical case definition. However, the utility of these clinical case definitions and laboratory testing in mass gathering outbreaks remains unknown.

METHODS AND RESULTS

An influenza outbreak was identified during World Youth Day 2008 in Sydney. From the data collected on pilgrims presenting to a single clinic, a Markov model was developed and validated against the actual epidemic curve. Simulations were performed to examine the utility of different clinical case definitions and laboratory testing strategies for containment of influenza outbreaks. Clinical case definitions were found to have the greatest impact on averting further cases with no added benefit when combined with any laboratory test. Although nucleic acid testing (NAT) demonstrated higher utility than indirect immunofluorescence antigen or on-site point-of-care testing, this effect was lost when laboratory NAT turnaround times was included. The main benefit of laboratory confirmation was limited to identification of true influenza cases amenable to interventions such as antiviral therapy.

CONCLUSIONS

Continuous re-evaluation of case definitions and laboratory testing strategies are essential for effective management of influenza outbreaks during mass gatherings.

Investment decisions in influenza pandemic contingency planning: cost-effectiveness of stockpiling antiviral drugs

BACKGROUND

The threat of an influenza pandemic has led to stockpiling of antiviral drugs in order to mitigate a plausible outbreak. If the stockpile would be used in relation to the recent pandemic alert, an investment decision about renewing the stock for a possible subsequent pandemic is essential. The decision should include cost-effectiveness considerations.

METHODS

We constructed a cost-effectiveness analysis in the Dutch context, explicitly including risk of an outbreak. Outcomes from a dynamic transmission model, comparing an intervention with a non-intervention scenario, were input in our health economic calculations.

RESULTS

Stockpiling was cost-effective from the health-care perspective if the actual risk is 37% for 30 years. If less than 60% of the population would take the antiviral drugs or the attack rate is about 50%, the investment would not be cost-effective from this perspective.

CONCLUSION

Risk perception, realistic coverage among population and size of a pandemic are crucial parameters and highly decisive for the investment decision.

Recommendations for modeling disaster responses in public health and medicine: a position paper of the society for medical decision making

PURPOSE

Mathematical and simulation models are increasingly used to plan for and evaluate health sector responses to disasters, yet no clear consensus exists regarding best practices for the design, conduct, and reporting of such models. The authors examined a large selection of published health sector disaster response models to generate a set of best practice guidelines for such models.

METHODS

. The authors reviewed a spectrum of published disaster response models addressing public health or health care delivery, focusing in particular on the type of disaster and response decisions considered, decision makers targeted, choice of outcomes evaluated, modeling methodology, and reporting format. They developed initial recommendations for best practices for creating and reporting such models and refined these guidelines after soliciting feedback from response modeling experts and from members of the Society for Medical Decision Making.

RESULTS

. The authors propose 6 recommendations for model construction and reporting, inspired by the most exemplary models: health sector disaster response models should address real-world problems, be designed for maximum usability by response planners, strike the appropriate balance between simplicity and complexity, include appropriate outcomes that extend beyond those considered in traditional cost-effectiveness analyses, and be designed to evaluate the many uncertainties inherent in disaster response. Finally, good model reporting is particularly critical for disaster response models.

CONCLUSIONS

. Quantitative models are critical tools for planning effective health sector responses to disasters. The proposed recommendations can increase the applicability and interpretability of future models, thereby improving strategic, tactical, and operational aspects of preparedness planning and response.

Quarantine for pandemic influenza control at the borders of small island nations

BACKGROUND

Although border quarantine is included in many influenza pandemic plans, detailed guidelines have yet to be formulated, including considerations for the optimal quarantine length. Motivated by the situation of small island nations, which will probably experience the introduction of pandemic influenza via just one airport, we examined the potential effectiveness of quarantine as a border control measure.

METHODS

Analysing the detailed epidemiologic characteristics of influenza, the effectiveness of quarantine at the borders of islands was modelled as the relative reduction of the risk of releasing infectious individuals into the community, explicitly accounting for the presence of asymptomatic infected individuals. The potential benefit of adding the use of rapid diagnostic testing to the quarantine process was also considered.

RESULTS

We predict that 95% and 99% effectiveness in preventing the release of infectious individuals into the community could be achieved with quarantine periods of longer than 4.7 and 8.6 days, respectively. If rapid diagnostic testing is combined with quarantine, the lengths of quarantine to achieve 95% and 99% effectiveness could be shortened to 2.6 and 5.7 days, respectively. Sensitivity analysis revealed that quarantine alone for 8.7 days or quarantine for 5.7 days combined with using rapid diagnostic testing could prevent secondary transmissions caused by the released infectious individuals for a plausible range of prevalence at the source country (up to 10%) and for a modest number of incoming travellers (up to 8000 individuals).

CONCLUSION

Quarantine at the borders of island nations could contribute substantially to preventing the arrival of pandemic influenza (or at least delaying the arrival date). For small island nations we recommend consideration of quarantine alone for 9 days or quarantine for 6 days combined with using rapid diagnostic testing (if available).