The Cost Effectiveness of Pandemic Influenza Interventions: A Pandemic Severity Based Analysis

Background

The impact of a newly emerged influenza pandemic will depend on its transmissibility and severity. Understanding how these pandemic features impact on the effectiveness and cost effectiveness of alternative intervention strategies is important for pandemic planning.

Methods

A cost effectiveness analysis of a comprehensive range of social distancing and antiviral drug strategies intended to mitigate a future pandemic was conducted using a simulation model of a community of ∼30,000 in Australia. Six pandemic severity categories were defined based on case fatality ratio (CFR), using data from the 2009/2010 pandemic to relate hospitalisation rates to CFR.

Results

Intervention strategies combining school closure with antiviral treatment and prophylaxis are the most cost effective strategies in terms of cost per life year saved (LYS) for all severity categories. The cost component in the cost per LYS ratio varies depending on pandemic severity: for a severe pandemic (CFR of 2.5%) the cost is ∼$9 k per LYS; for a low severity pandemic (CFR of 0.1%) this strategy costs ∼$58 k per LYS; for a pandemic with very low severity similar to the 2009 pandemic (CFR of 0.03%) the cost is ∼$155 per LYS. With high severity pandemics (CFR >0.75%) the most effective attack rate reduction strategies are also the most cost effective. During low severity pandemics costs are dominated by productivity losses due to illness and social distancing interventions, while for high severity pandemics costs are dominated by hospitalisation costs and productivity losses due to death.

Conclusions

The most cost effective strategies for mitigating an influenza pandemic involve combining sustained social distancing with the use of antiviral agents. For low severity pandemics the most cost effective strategies involve antiviral treatment, prophylaxis and short durations of school closure; while these are cost effective they are less effective than other strategies in reducing the infection rate.     

The Possible Impact of Vaccination for Seasonal Influenza on Emergence of Pandemic Influenza via Reassortment

Background

One pathway through which pandemic influenza strains might emerge is reassortment from coinfection of different influenza A viruses. Seasonal influenza vaccines are designed to target the circulating strains, which intuitively decreases the prevalence of coinfection and the chance of pandemic emergence due to reassortment. However, individual-based analyses on 2009 pandemic influenza show that the previous seasonal vaccination may increase the risk of pandemic A(H1N1) pdm09 infection. In view of pandemic influenza preparedness, it is essential to understand the overall effect of seasonal vaccination on pandemic emergence via reassortment.

Methods and Findings

In a previous study we applied a population dynamics approach to investigate the effect of infection-induced cross-immunity on reducing such a pandemic risk. Here the model was extended by incorporating vaccination for seasonal influenza to assess its potential role on the pandemic emergence via reassortment and its effect in protecting humans if a pandemic does emerge. The vaccination is assumed to protect against the target strains but only partially against other strains. We find that a universal seasonal vaccine that provides full-spectrum cross-immunity substantially reduces the opportunity of pandemic emergence. However, our results show that such effectiveness depends on the strength of infection-induced cross-immunity against any novel reassortant strain. If it is weak, the vaccine that induces cross-immunity strongly against non-target resident strains but weakly against novel reassortant strains, can further depress the pandemic emergence; if it is very strong, the same kind of vaccine increases the probability of pandemic emergence.

Conclusions

Two types of vaccines are available: inactivated and live attenuated, only live attenuated vaccines can induce heterosubtypic immunity. Current vaccines are effective in controlling circulating strains; they cannot always help restrain pandemic emergence because of the uncertainty of the oncoming reassortant strains, however. This urges the development of universal vaccines for prevention of pandemic influenza.     

The Impact of the Unstructured Contacts Component in Influenza Pandemic Modeling

Background

Individual based models have become a valuable tool for modeling the spatiotemporal dynamics of epidemics, e.g. influenza pandemic, and for evaluating the effectiveness of intervention strategies. While specific contacts among individuals into diverse environments (family, school/workplace) can be modeled in a standard way by employing available socio-demographic data, all the other (unstructured) contacts can be dealt with by adopting very different approaches. This can be achieved for instance by employing distance-based models or by choosing unstructured contacts in the local communities or by employing commuting data.

Methods/Results

Here we show how diverse choices can lead to different model outputs and thus to a different evaluation of the effectiveness of the containment/mitigation strategies. Sensitivity analysis has been conducted for different values of the first generation index G₀ , which is the average number of secondary infections generated by the first infectious individual in a completely susceptible population and by varying the seeding municipality. Among the different considered models, attack rate ranges from 19.1% to 25.7% for G₀ = 1.1, from 47.8% to 50.7% for G₀ = 1.4 and from 62.4% to 67.8% for G₀ = 1.7. Differences of about 15 to 20 days in the peak day have been observed. As regards spatial diffusion, a difference of about 100 days to cover 200 km for different values of G₀ has been observed.

Conclusion

To reduce uncertainty in the models it is thus important to employ data, which start being available, on contacts on neglected but important activities (leisure time, sport mall, restaurants, etc.) and time-use data for improving the characterization of the unstructured contacts. Moreover, all the possible effects of different assumptions should be considered for taking public health decisions: not only sensitivity analysis to various model parameters should be performed, but intervention options should be based on the analysis and comparison of different modeling choices.     

Quantifying the Routes of Transmission for Pandemic Influenza

Motivated by the desire to assess nonpharmaceutical interventions for pandemic influenza, we seek in this study to quantify the routes of transmission for this disease. We construct a mathematical model of aerosol (i.e., droplet-nuclei) and contact transmission of influenza within a household containing one infected. An analysis of this model in conjunction with influenza and rhinovirus data suggests that aerosol transmission is far more dominant than contact transmission for influenza. We also consider a separate model of a close expiratory event, and find that a close cough is unlikely (≈1% probability) to generate traditional droplet transmission (i.e., direct deposition on the mucous membranes), although a close, unprotected and horizontally-directed sneeze is potent enough to cause droplet transmission. There are insufficient data on the frequency of close expiratory events to assess the relative importance of aerosol transmission and droplet transmission, and it is prudent to leave open the possibility that droplet transmission is important until proven otherwise. However, the rarity of close, unprotected and horizontally-directed sneezes—coupled with the evidence of significant aerosol and contact transmission for rhinovirus and our comparison of hazard rates for rhinovirus and influenza—leads us to suspect that aerosol transmission is the dominant mode of transmission for influenza.     

Modeling Optimal Age-Specific Vaccination Strategies Against Pandemic Influenza

In the context of pandemic influenza, the prompt and effective implementation of control measures is of great concern for public health officials around the world. In particular, the role of vaccination should be considered as part of any pandemic preparedness plan. The timely production and efficient distribution of pandemic influenza vaccines are important factors to consider in mitigating the morbidity and mortality impact of an influenza pandemic, particularly for those individuals at highest risk of developing severe disease. In this paper, we use a mathematical model that incorporates age-structured transmission dynamics of influenza to evaluate optimal vaccination strategies in the epidemiological context of the Spring 2009 A (H1N1) pandemic in Mexico. We extend previous work on age-specific vaccination strategies to time-dependent optimal vaccination policies by solving an optimal control problem with the aim of minimizing the number of infected individuals over the course of a single pandemic wave. Optimal vaccination policies are computed and analyzed under different vaccination coverages (21%–77%) and different transmissibility levels (R₀\mathcal{R}_{0} in the range of 1.8–3). The results suggest that the optimal vaccination can be achieved by allocating most vaccines to young adults (20–39 yr) followed by school age children (6–12 yr) when the vaccination coverage does not exceed 30%. For higher R₀\mathcal{R}_{0} levels ($\mathcal{R}_{0}>=2.4$\mathcal{R}_{0}>=2.4), or a time delay in the implementation of vaccination (>90 days), a quick and substantial decrease in the pool of susceptibles would require the implementation of an intensive vaccination protocol within a shorter period of time. Our results indicate that optimal age-specific vaccination rates are significantly associated with R₀\mathcal{R}_{0}, the amount of vaccines available and the timing of vaccination.     

Spatial Transmission of 2009 Pandemic Influenza in the US

The 2009 H1N1 influenza pandemic provides a unique opportunity for detailed examination of the spatial dynamics of an emerging pathogen. In the US, the pandemic was characterized by substantial geographical heterogeneity: the 2009 spring wave was limited mainly to northeastern cities while the larger fall wave affected the whole country. Here we use finely resolved spatial and temporal influenza disease data based on electronic medical claims to explore the spread of the fall pandemic wave across 271 US cities and associated suburban areas. We document a clear spatial pattern in the timing of onset of the fall wave, starting in southeastern cities and spreading outwards over a period of three months. We use mechanistic models to tease apart the external factors associated with the timing of the fall wave arrival: differential seeding events linked to demographic factors, school opening dates, absolute humidity, prior immunity from the spring wave, spatial diffusion, and their interactions. Although the onset of the fall wave was correlated with school openings as previously reported, models including spatial spread alone resulted in better fit. The best model had a combination of the two. Absolute humidity or prior exposure during the spring wave did not improve the fit and population size only played a weak role. In conclusion, the protracted spread of pandemic influenza in fall 2009 in the US was dominated by short-distance spatial spread partially catalysed by school openings rather than long-distance transmission events. This is in contrast to the rapid hierarchical transmission patterns previously described for seasonal influenza. The findings underline the critical role that school-age children play in facilitating the geographic spread of pandemic influenza and highlight the need for further information on the movement and mixing patterns of this age group.     

Economic Analysis of Pandemic Influenza Vaccination Strategies in Singapore

Background

All influenza pandemic plans advocate pandemic vaccination. However, few studies have evaluated the cost-effectiveness of different vaccination strategies. This paper compares the economic outcomes of vaccination compared with treatment with antiviral agents alone, in Singapore.

Methodology

We analyzed the economic outcomes of pandemic vaccination (immediate vaccination and vaccine stockpiling) compared with treatment-only in Singapore using a decision-based model to perform cost-benefit and cost-effectiveness analyses. We also explored the annual insurance premium (willingness to pay) depending on the perceived risk of the next pandemic occurring.

Principal Findings

The treatment-only strategy resulted in 690 deaths, 13,950 hospitalization days, and economic cost of USD$497 million. For immediate vaccination, at vaccine effectiveness of >55%, vaccination was cost-beneficial over treatment-only. Vaccine stockpiling is not cost-effective in most scenarios even with 100% vaccine effectiveness. The annual insurance premium was highest with immediate vaccination, and was lower with increased duration to the next pandemic. The premium was also higher with higher vaccine effectiveness, attack rates, and case-fatality rates. Stockpiling with case-fatality rates of 0.4–0.6% would be cost-beneficial if vaccine effectiveness was >80%; while at case-fatality of >5% stockpiling would be cost-beneficial even if vaccine effectiveness was 20%. High-risk sub-groups warrant higher premiums than low-risk sub-groups.

Conclusions

The actual pandemic vaccine effectiveness and lead time is unknown. Vaccine strategy should be based on perception of severity. Immediate vaccination is most cost-effective, but requires vaccines to be available when required. Vaccine stockpiling as insurance against worst-case scenarios is also cost-effective. Research and development is therefore critical to develop and stockpile cheap, readily available effective vaccines.     

MicroRNA Expression and Virulence in Pandemic Influenza Virus-Infected Mice

The worst known H1N1 influenza pandemic in history resulted in more than 20 million deaths in 1918 and 1919. Although the underlying mechanism causing the extreme virulence of the 1918 influenza virus is still obscure, our previous functional genomics analyses revealed a correlation between the lethality of the reconstructed 1918 influenza virus (r1918) in mice and a unique gene expression pattern associated with severe immune responses in the lungs. Lately, microRNAs have emerged as a class of crucial regulators for gene expression. To determine whether differential expression of cellular microRNAs plays a role in the host response to r1918 infection, we compared the lung cellular “microRNAome” of mice infected by r1918 virus with that of mice infected by a nonlethal seasonal influenza virus, A/Texas/36/91. We found that a group of microRNAs, including miR-200a and miR-223, were differentially expressed in response to influenza virus infection and that r1918 and A/Texas/36/91 infection induced distinct microRNA expression profiles. Moreover, we observed significant enrichment in the number of predicted cellular target mRNAs whose expression was inversely correlated with the expression of these microRNAs. Intriguingly, gene ontology analysis revealed that many of these mRNAs play roles in immune response and cell death pathways, which are known to be associated with the extreme virulence of r1918. This is the first demonstration that cellular gene expression patterns in influenza virus-infected mice may be attributed in part to microRNA regulation and that such regulation may be a contributing factor to the extreme virulence of the r1918.H1N1 influenza A viruses continue to pose serious threats to public health, as exemplified by the ongoing 2009 H1N1 influenza pandemic. The 1918-1919 H1N1 influenza pandemic was even deadlier in comparison, causing more than 20 million deaths worldwide. The keys to unlocking the mystery of the extreme virulence of the 1918 virus were provided with the reconstruction of the virus (reconstructed 1918 influenza virus [r1918]) by reverse genetics (37). The lethality of r1918 has since been examined in both mouse and macaque models (17, 18). Unlike the nonlethal infections of some other H1N1 influenza virus strains, such as A/Texas/36/91 (Tx/91) or A/Kawasaki/173/01 (K173), the r1918 causes severe and lethal pulmonary disease. We subsequently conducted functional genomics analyses that revealed that the extreme virulence of r1918 was correlated with atypical expression of immune response-related genes, including massive induction of cellular genes related to inflammatory response and cell death pathways (17, 18). In spite of these findings, the mechanistic basis for these atypical gene expression patterns remains unknown.Cellular gene expression is a complicated process and is subject to regulation by many cellular factors. As a group of newly identified cellular regulators, microRNAs are known to regulate the expression of a large number of targets, mainly cellular genes. Through mRNA degradation or translational repression of their targets, microRNAs regulate a wide range of crucial physiologic and pathological processes. For example, miR-34a acts as a tumor suppressor by inhibiting the expression of sirt1 (40), whereas miR-21 contributes to myocardial disease by inhibiting the expression of spry1 (36). By targeting zeb1/2, the miR-200 family members play roles in maintaining the epithelial phenotype of cancer cells (27). Furthermore, Let-7s regulates the expression of hbl-1, which drives the developmental progression of epidermal stem cells (5). Cellular microRNAs also play critical roles in virus-host interactions. The cellular microRNA miR-122 is an indispensable factor in supporting hepatitis C virus (HCV) replication (16), whereas miR-196 and miR-296 substantially attenuate viral replication through type I interferon (IFN)-associated pathways in liver cells (28). Furthermore, miR-125b and miR-223 directly target human immunodeficiency virus type 1 (HIV-1) mRNA, thereby attenuating viral gene expression in resting CD4⁺ T cells (14), and miR-198 modulates HIV-1 replication indirectly by repressing the expression of ccnt1 (34), a cellular factor necessary for HIV-1 replication. More importantly, viruses may promote their life cycles by modulating the intracellular environment through actively regulating the expression of multiple cellular microRNAs. For example, human T-cell lymphotropic virus type 1 (HTLV-1) modulates the expression of a number of cellular microRNAs in order to control T-cell differentiation (3). Similarly, human cytomegalovirus (HCMV) selectively manipulates the expression of miR-100 and miR-101 to facilitate its own replication (38). In contrast, the involvement of microRNAs during influenza A virus infection or pathogenesis is largely unknown.To determine whether cellular microRNAs play a role in the host response to influenza virus infection, we performed a systematic profiling of cellular microRNAs in lung tissues from mice infected with r1918 or a nonlethal seasonal influenza virus, Tx/91 (17). We identified a group of microRNAs whose expression patterns differentiated the host response to r1918 and Tx/91 infection. We assessed the potential functions of differentially expressed microRNAs by analyzing the predicted target genes whose expression was inversely correlated with the expression of these microRNAs. Our report provides a new perspective on the contribution of microRNAs to the pathogenesis of lethal 1918 influenza virus infection.     

Optimal Vaccine Allocation for the Early Mitigation of Pandemic Influenza

With new cases of avian influenza H5N1 (H5N1AV) arising frequently, the threat of a new influenza pandemic remains a challenge for public health. Several vaccines have been developed specifically targeting H5N1AV, but their production is limited and only a few million doses are readily available. Because there is an important time lag between the emergence of new pandemic strain and the development and distribution of a vaccine, shortage of vaccine is very likely at the beginning of a pandemic. We coupled a mathematical model with a genetic algorithm to optimally and dynamically distribute vaccine in a network of cities, connected by the airline transportation network. By minimizing the illness attack rate (i.e., the percentage of people in the population who become infected and ill), we focus on optimizing vaccine allocation in a network of 16 cities in Southeast Asia when only a few million doses are available. In our base case, we assume the vaccine is well-matched and vaccination occurs 5 to 10 days after the beginning of the epidemic. The effectiveness of all the vaccination strategies drops off as the timing is delayed or the vaccine is less well-matched. Under the best assumptions, optimal vaccination strategies substantially reduced the illness attack rate, with a maximal reduction in the attack rate of 85%. Furthermore, our results suggest that cooperative strategies where the resources are optimally distributed among the cities perform much better than the strategies where the vaccine is equally distributed among the network, yielding an illness attack rate 17% lower. We show that it is possible to significantly mitigate a more global epidemic with limited quantities of vaccine, provided that the vaccination campaign is extremely fast and it occurs within the first weeks of transmission.     

Capacity and Adaptations of General Practice during an Influenza Pandemic

Background

GPs play a major role in influenza epidemics, and most patients with influenza-like-illness (ILI) are treated in general practice or by primary care doctors on duty in out-of-hours services (OOH). Little is known about the surge capacity in primary care services during an influenza pandemic, and how the relationship between them changes.

Aim

To investigate how general practice and OOH services were used by patients during the 2009 pandemic in Norway and the impact of the pandemic on primary care services in comparison to a normal influenza season.

Materials

Data from electronic remuneration claims from all OOH doctors and regular GPs for 2009.

Methods

We conducted a registry-based study of all ILI consultations in the 2009 pandemic with the 2008/09 influenza season (normal season) as baseline for comparison.

Results

The majority (82.2%) of ILI consultations during the 2009 pandemic took place in general practice. The corresponding number in the 2008/09 season was 89.3%. Compared with general practice, the adjusted odds ratio for ILI with all other diagnoses as reference in OOH services was 1.23 (95% CI, 1.18, 1.27) for the 2008/2009 season and 1.87 (95% CI, 1.84, 1.91) for the pandemic influenza season. In total there was a 3.3-fold increase in ILI consultations during the pandemic compared to the 2008/09 season. A 5.5-fold increase of ILI consultations were observed in OOH services in comparison to the 2008/09 season. Children and young adults with ILI were the most frequent users of OOH services during influenza periods.

Conclusions

The autumn pandemic wave resulted in a significantly increased demand on primary care services. However, GPs in primary care services in Norway showed the ability to increase capacity in a situation with increased patient demand.     

Effective use of a Limited Antiviral Stockpile for Pandemic Influenza

Just allocation of resources for control of infectious diseases can be profoundly influenced by the dynamics of those diseases. In this paper we discuss the use of antiviral drugs for treatment of pandemic influenza. While the primary effect of such drugs is to alleviate and shorten the duration of symptoms for treated individuals, they can have a secondary effect of reducing transmission in the community. However, existing stockpiles may be insufficient for all clinical cases. Here we use simple mathematical models to present scenarios where the optimum policies to minimise morbidity and mortality, with a limited drug stockpile, are not always the most intuitively obvious and may conflict with theories of justice. We discuss ethical implications of these findings.     

北京市某区医院感染控制及流感大流行应对准备现状调查

目的 了解医院应对流感大流行的能力。方法 通过现场调查方法调查6家二级及以上医院和5家一级医院。结果 (1)二级及以上医院呼吸相关科室医生218人（14.15 %）,护士314人（19.26%）,病床数469张（19.68%）,呼吸机27台(36.99%);一级医院呼吸相关科室医生29人（14.79%）,护士24人（35.29 %）,病床数53张(22.27%); 呼吸相关科室医护人员比例除1家外,其余均低于1：2; 2家医院ICU病床数占整个医院总床数比例低于2%。(2)5家二级及以上医院设置了呼吸相关科室,5家一级医院设置了传染病接诊室。所有医院均能提供口罩和手套,棉纱口罩和N95口罩各有4家医院（36.36%）能够提供,部分医院能够提供洗手设备和洗手用品;2家医院为职工（18.18%）医院接种流感疫苗。(3)10家（91.91%）医院只储备部分个人防护用品,3家（27.27%）储备抗病毒药物。结论 目前医院应对流感大流行的能力有限。     

A Delay Differential Model for Pandemic Influenza with Antiviral Treatment

The use of antiviral drugs has been recognized as the primary public health strategy for mitigating the severity of a new influenza pandemic strain. However, the success of this strategy requires the prompt onset of therapy within 48 hours of the appearance of clinical symptoms. This requirement may be captured by a compartmental model that monitors the density of infected individuals in terms of the time elapsed since the onset of symptoms. We show that such a model can be expressed by a system of delay differential equations with both discrete and distributed delays. The model is analyzed to derive the criterion for disease control based on two critical factors: (i) the profile of treatment rate; and (ii) the level of treatment as a function of time lag in commencing therapy. Numerical results are also obtained to illustrate the feasible region of disease control. Our findings show that due to uncertainty in the attack rate of a pandemic strain, initiating therapy immediately upon diagnosis can significantly increase the likelihood of disease control and substantially reduce the required community-level of treatment. This suggests that reliable diagnostic methods for influenza cases should be rapidly implemented within an antiviral treatment strategy.     

Moral Principles for Allocating Scarce Medical Resources in an Influenza Pandemic

One of the societal problems in a new influenza pandemic will be how to use the scarce medical resources that are available for prevention and treatment, and what medical, epidemiological and ethical justifications can be given for the choices that have to be made. Many things may become scarce: personal protective equipment, antiviral drugs, hospital beds, mechanical ventilation, vaccination, etc. In this paper I discuss two general ethical principles for priority setting (utility and equity) and explain how these principles will often point in diverging directions. Moreover, each of these principles can be understood in different, again often competing, ways. Notwithstanding these controversies and conflicts, in the context of pandemic response there are at least some points of convergence: several policies can be justified by appeal to different ethical principles and theories. Convergence may be found with respect to a focus on saving the most lives (instead of other aggregative accounts); giving priority antiviral prophylaxis and therapy for life-saving pandemic responders; and, partly depending on epidemiology of the pandemic, to prioritise vaccination of children. Although decision-making about access to intensive care will involve choices with immediate tragic implications, the ethical complexity of these choices is relatively modest (although decisions will not be easy): there are persuasive moral reasons for giving priority to patients who are expected to benefit most within the shortest time. Finally, in the last section I tentatively argue that constraints on people’s freedom, as necessary for an effective public health approach, may support giving somewhat more weight to saving the most lives, than to concerns of equity.