Mitigation of pandemic influenza: review of cost–effectiveness studies

Lugnér, Anna K.; Postma, Maarten J.

doi:10.1586/erp.09.56

Cited by 26 publications

(18 citation statements)

References 38 publications

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“…In addition, despite our effort to provide information on cost effective interventions for developing countries by using the World Bank's thresholds, the transferability of cost outcomes across jurisdictions remains a controversial issue. [56] In comparison to the work of Lugnér and Postma, [57] who reviewed economic evaluations of influenza pandemic interventions from MEDLINE as their sole source, our review is more comprehensive. Lugnér and Postma only provided descriptive results of the review and methodological recommendations for future economic evaluations.…”

Section: Discussionmentioning

confidence: 99%

“…Lugnér and Postma only provided descriptive results of the review and methodological recommendations for future economic evaluations. [57] Whilst our review does not focus on examining methodological approaches but aims to offer policy recommendations, it does not fully succeed due to the limitations of the reviewed studies. These include the paucity of effectiveness and cost effectiveness studies on non-pharmaceutical interventions, and the limited number of studies assessing value for money across interventions.…”

Section: Discussionmentioning

confidence: 99%

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Systematic Review of Economic Evaluations of Preparedness Strategies and Interventions against Influenza Pandemics

et al. 2012

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BackgroundAlthough 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thorough and informed revision of this guidance following the H1N1 2009 pandemic, a systematic review of published and unpublished economic evaluations of preparedness strategies and interventions against influenza pandemics was conducted.MethodsThe search was performed in September 2011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.Results44 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.ConclusionThe 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.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Systematic Review of Economic Evaluations of Preparedness Strategies and Interventions against Influenza Pandemics

et al. 2012

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“…The impact of any particular intervention is difficult to estimate from past epidemics due to variation in the viral strain and its transmission properties, and due to the concurrent effects of many different behavioural responses and government led initiatives. Planning therefore depends increasingly on the predictions of mathematical models of viral spread that permit analyses of the potential impact of various interventions, alone or in combination [13,34,35,36,37,38,39].…”

Section: Introductionmentioning

confidence: 99%

Mitigation Strategies for Pandemic Influenza A: Balancing Conflicting Policy Objectives

et al. 2011

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Mitigation of a severe influenza pandemic can be achieved using a range of interventions to reduce transmission. Interventions can reduce the impact of an outbreak and buy time until vaccines are developed, but they may have high social and economic costs. The non-linear effect on the epidemic dynamics means that suitable strategies crucially depend on the precise aim of the intervention. National pandemic influenza plans rarely contain clear statements of policy objectives or prioritization of potentially conflicting aims, such as minimizing mortality (depending on the severity of a pandemic) or peak prevalence or limiting the socio-economic burden of contact-reducing interventions. We use epidemiological models of influenza A to investigate how contact-reducing interventions and availability of antiviral drugs or pre-pandemic vaccines contribute to achieving particular policy objectives. Our analyses show that the ideal strategy depends on the aim of an intervention and that the achievement of one policy objective may preclude success with others, e.g., constraining peak demand for public health resources may lengthen the duration of the epidemic and hence its economic and social impact. Constraining total case numbers can be achieved by a range of strategies, whereas strategies which additionally constrain peak demand for services require a more sophisticated intervention. If, for example, there are multiple objectives which must be achieved prior to the availability of a pandemic vaccine (i.e., a time-limited intervention), our analysis shows that interventions should be implemented several weeks into the epidemic, not at the very start. This observation is shown to be robust across a range of constraints and for uncertainty in estimates of both R0 and the timing of vaccine availability. These analyses highlight the need for more precise statements of policy objectives and their assumed consequences when planning and implementing strategies to mitigate the impact of an influenza pandemic.

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“…Some examples of the measures are vaccine allocation that immunizes susceptible individuals [3], social distancing that reduces individuals effective contacts accounting for disease transmissions [4], and the prophylactic use of antiviral drugs and the prompt treatment of infections that change the susceptibility and infectivity of uninfected and infected individuals, respectively [5]. In practice, it would be difficult to excise such measures to cover a majority of the host population due to the scarcity of required resources, e.g., the potential shortage of vaccine supply and the inadequate stockpiles of antiviral drugs [6], [7], as well as the consequent social-economic impacts, e.g., school closure and workplace shutdown [8], [9]. As a result, public health authorities will select certain target subpopulations for disease interventions.…”

Section: Introductionmentioning

confidence: 99%

Identifying the Relative Priorities of Subpopulations for Containing Infectious Disease Spread

2013

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In response to the outbreak of an emerging infectious disease, e.g., H1N1 influenza, public health authorities will take timely and effective intervention measures to contain disease spread. However, due to the scarcity of required resources and the consequent social-economic impacts, interventions may be suggested to cover only certain subpopulations, e.g., immunizing vulnerable children and the elderly as well as closing schools or workplaces for social distancing. Here we are interested in addressing the question of how to identify the relative priorities of subpopulations for two measures of disease intervention, namely vaccination and contact reduction, especially when these measures are implemented together at the same time. We consider the measure of vaccination that immunizes susceptible individuals in different age subpopulations and the measure of contact reduction that cuts down individuals’ effective contacts in different social settings, e.g., schools, households, workplaces, and general communities. In addition, we construct individuals’ cross-age contact frequency matrix by inferring basic contact patterns respectively for different social settings from the socio-demographical census data. By doing so, we present a prioritization approach to identifying the target subpopulations that will lead to the greatest reduction in the number of disease transmissions. We calculate the relative priorities of subpopulations by considering the marginal effects of reducing the reproduction number for the cases of vaccine allocation by age and contact reduction by social setting. We examine the proposed approach by revisiting the real-world scenario of the 2009 Hong Kong H1N1 influenza epidemic and determine the relative priorities of subpopulations for age-specific vaccination and setting-specific contact reduction. We simulate the influenza-like disease spread under different settings of intervention. The results have shown that the proposed approach can improve the effectiveness of disease control by containing disease transmissions in a host population.

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Mitigation of pandemic influenza: review of cost–effectiveness studies

Cited by 26 publications

References 38 publications

Systematic Review of Economic Evaluations of Preparedness Strategies and Interventions against Influenza Pandemics

Systematic Review of Economic Evaluations of Preparedness Strategies and Interventions against Influenza Pandemics

Mitigation Strategies for Pandemic Influenza A: Balancing Conflicting Policy Objectives

Identifying the Relative Priorities of Subpopulations for Containing Infectious Disease Spread

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