Two resource distribution strategies for dynamic mitigation of influenza pandemics

As recently pointed out by the Institute of Medicine, the existing pandemic containment and mitigation models lack the dynamic decision support capabilities. We present two simulation-based optimization models for developing dynamic predictive resource distribution strategies for cross-regional pandemic outbreaks. In both models, the underlying simulation mimics the disease and population dynamics of the affected regions. The quantity-based optimization model generates a progressive allocation of limited quantities of mitigation resources, including vaccines, antiviral, administration capacities, and social distancing enforcement resources. The budget-based optimization model strives instead allocating a total resource budget. Both models seek to minimize the impact of ongoing outbreaks and the expected impact of potential outbreaks. The models incorporate measures of morbidity, mortality, and social distancing, translated into the societal and economic costs of lost productivity and medical expenses. The models were calibrated using historic pandemic data and implemented on a sample outbreak in Florida, with over four million inhabitants. The quantity-based model was found to be inferior to the budget-based model, which was advantageous in its ability to balance the varying relative cost and effectiveness of individual resources. The models are intended to assist public health policy makers in developing effective distribution policies for mitigation of influenza pandemics

Adaptive Vaccination Strategies to Mitigate Pandemic Influenza: Mexico as a Case Study

Background We explore vaccination strategies against pandemic influenza in Mexico using an age-structured transmission model calibrated against local epidemiological data from the Spring 2009 A(H1N1) pandemic. Methods and Findings In the context of limited vaccine supplies, we evaluate age-targeted allocation strategies that either prioritize youngest children and persons over 65 years of age, as for seasonal influenza, or adaptively prioritize age groups based on the age patterns of hospitalization and death monitored in real-time during the early stages of the pandemic. Overall the adaptive vaccination strategy outperformed the seasonal influenza vaccination allocation strategy for a wide range of disease and vaccine coverage parameters. Conclusions This modeling approach could inform policies for Mexico and other countries with similar demographic features and vaccine resources issues, with regard to the mitigation of the S-OIV pandemic. We also discuss logistical issues associated with the implementation of adaptive vaccination strategies in the context of past and future influenza pandemics

Optimal Pandemic Influenza Vaccine Allocation Strategies for the Canadian Population

BACKGROUND: The world is currently confronting the first influenza pandemic of the 21(st) century. Influenza vaccination is an effective preventive measure, but the unique epidemiological features of swine-origin influenza A (H1N1) (pH1N1) introduce uncertainty as to the best strategy for prioritization of vaccine allocation. We sought to determine optimal prioritization of vaccine distribution among different age and risk groups within the Canadian population, to minimize influenza-attributable morbidity and mortality. METHODOLOGY/PRINCIPAL FINDINGS: We developed a deterministic, age-structured compartmental model of influenza transmission, with key parameter values estimated from data collected during the initial phase of the epidemic in Ontario, Canada. We examined the effect of different vaccination strategies on attack rates, hospitalizations, intensive care unit admissions, and mortality. In all scenarios, prioritization of high-risk individuals (those with underlying chronic conditions and pregnant women), regardless of age, markedly decreased the frequency of severe outcomes. When individuals with underlying medical conditions were not prioritized and an age group-based approach was used, preferential vaccination of age groups at increased risk of severe outcomes following infection generally resulted in decreased mortality compared to targeting vaccine to age groups with higher transmission, at a cost of higher population-level attack rates. All simulations were sensitive to the timing of the epidemic peak in relation to vaccine availability, with vaccination having the greatest impact when it was implemented well in advance of the epidemic peak. CONCLUSIONS/SIGNIFICANCE: Our model simulations suggest that vaccine should be allocated to high-risk groups, regardless of age, followed by age groups at increased risk of severe outcomes. Vaccination may significantly reduce influenza-attributable morbidity and mortality, but the benefits are dependent on epidemic dynamics, time for program roll-out, and vaccine uptake

Diagnosis and Antiviral Intervention Strategies for Mitigating an Influenza Epidemic

BACKGROUND: Many countries have amassed antiviral stockpiles for pandemic preparedness. Despite extensive trial data and modelling studies, it remains unclear how to make optimal use of antiviral stockpiles within the constraints of healthcare infrastructure. Modelling studies informed recommendations for liberal antiviral distribution in the pandemic phase, primarily to prevent infection, but failed to account for logistical constraints clearly evident during the 2009 H1N1 outbreaks. Here we identify optimal delivery strategies for antiviral interventions accounting for logistical constraints, and so determine how to improve a strategy's impact. METHODS AND FINDINGS: We extend an existing SEIR model to incorporate finite diagnostic and antiviral distribution capacities. We evaluate the impact of using different diagnostic strategies to decide to whom antivirals are delivered. We then determine what additional capacity is required to achieve optimal impact. We identify the importance of sensitive and specific case ascertainment in the early phase of a pandemic response, when the proportion of false-positive presentations may be high. Once a substantial percentage of ILI presentations are caused by the pandemic strain, identification of cases for treatment on syndromic grounds alone results in a greater potential impact than a laboratory-dependent strategy. Our findings reinforce the need for a decentralised system capable of providing timely prophylaxis. CONCLUSIONS: We address specific real-world issues that must be considered in order to improve pandemic preparedness policy in a practical and methodologically sound way. Provision of antivirals on the scale proposed for an effective response is infeasible using traditional public health outbreak management and contact tracing approaches. The results indicate to change the transmission dynamics of an influenza epidemic with an antiviral intervention, a decentralised system is required for contact identification and prophylaxis delivery, utilising a range of existing services and infrastructure in a "whole of society" response

Literature Review - the vaccine supply chain

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

Trends in parameterization, economics and host behaviour in influenza pandemic modelling: a review and reporting protocol.

BACKGROUND: The volume of influenza pandemic modelling studies has increased dramatically in the last decade. Many models incorporate now sophisticated parameterization and validation techniques, economic analyses and the behaviour of individuals. METHODS: We reviewed trends in these aspects in models for influenza pandemic preparedness that aimed to generate policy insights for epidemic management and were published from 2000 to September 2011, i.e. before and after the 2009 pandemic. RESULTS: We find that many influenza pandemics models rely on parameters from previous modelling studies, models are rarely validated using observed data and are seldom applied to low-income countries. Mechanisms for international data sharing would be necessary to facilitate a wider adoption of model validation. The variety of modelling decisions makes it difficult to compare and evaluate models systematically. CONCLUSIONS: We propose a model Characteristics, Construction, Parameterization and Validation aspects protocol (CCPV protocol) to contribute to the systematisation of the reporting of models with an emphasis on the incorporation of economic aspects and host behaviour. Model reporting, as already exists in many other fields of modelling, would increase confidence in model results, and transparency in their assessment and comparison

International Externalities in Pandemic Influenza Mitigation

A serious influenza pandemic could be devastating for the world. Ideally, such a pandemic could be contained, but this may be infeasible. One promising method for pandemic mitigation is to treat infectious individuals with antiviral pharmaceuticals. While most of the benefits from treatment accrue to the country in which treatment occurs, there are some positive spillovers: when one country treats more of its population this both reduces the attack rate in the other country and increases the marginal benefit from additional treatment in the other country. These externalities and complementarities may mean that self-interested rich countries should optimally pay for some AV treatment in poor countries. This dissertation demonstrates the presence of antiviral treatment externalities in simple epidemiological SIR models, and then in a descriptively realistic Global Epidemiological Model (GEM). This GEM simulates pandemic spread between cities through the international airline network, and between cities and rural areas through ground transport. Under the base case assumptions of moderate transmissibility of the flu, the distribution of antiviral stockpiles from rich countries to poor and lower middle income countries may indeed pay for itself: providing a stockpile equal to 1% of the population of poor countries will reduce cases in rich countries after 1 year by about 6.13 million cases at a cost of 4.62 doses per rich-country case avoided. Concentrating doses on the outbreak country is, however, even more cost-effective: in the base case it reduces the number of influenza cases by 4.76 million cases, at the cost of roughly 1.92 doses per case avoided. These results depend on the transmissibility of the flu strain, the efficacy of antivirals in reducing infection and on the proportion of infectious who can realistically be identified and treated

Operations research in disaster preparedness and response: The public health perspective

Operations research is the scientific study of operations for the purpose of better decision making and management. Disasters are defined as events whose consequences exceed the capability of civil protection and public health systems to provide necessary responses in a timely manner. Public health science is applied to the design of operations of public health services and therefore operations research principles and techniques can be applied in public health. Disaster response quantitative methods such as operations research addressing public health are important tools for planning effective responses to disasters. Models address a variety of decision makers (e.g. first responders, public health officials), geographic settings, strategies modelled (e.g. dispensing, supply chain network design, prevention or mitigation of disaster effects, treatment) and outcomes evaluated (costs, morbidity, mortality, logistical outcomes) and use a range of modelling methodologies. Regarding natural disasters the modelling approaches have been rather limited. Response logistics related to public health impact of disasters have been modelled more intensively since decisions about procurement, transport, stockpiling, and maintenance of needed supplies but also mass vaccination, prophylaxis, and treatment are essential in the emergency management. Major issues at all levels of disaster response decision making, including long-range strategic planning, tactical response planning, and real-time operational support are still unresolved and operations research can provide useful techniques for decision management.-JRC.G.2-Global security and crisis managemen