The cost-effectiveness of alternative vaccination strategies for polyvalent meningococcal vaccines in Burkina Faso: A transmission dynamic modeling study.

BACKGROUND: The introduction of a conjugate vaccine for serogroup A Neisseria meningitidis has dramatically reduced disease in the African meningitis belt. In this context, important questions remain about the performance of different vaccine policies that target remaining serogroups. Here, we estimate the health impact and cost associated with several alternative vaccination policies in Burkina Faso. METHODS AND FINDINGS: We developed and calibrated a mathematical model of meningococcal transmission to project the disability-adjusted life years (DALYs) averted and costs associated with the current Base policy (serogroup A conjugate vaccination at 9 months, as part of the Expanded Program on Immunization [EPI], plus district-specific reactive vaccination campaigns using polyvalent meningococcal polysaccharide [PMP] vaccine in response to outbreaks) and three alternative policies: (1) Base Prime: novel polyvalent meningococcal conjugate (PMC) vaccine replaces the serogroup A conjugate in EPI and is also used in reactive campaigns; (2) Prevention 1: PMC used in EPI and in a nationwide catch-up campaign for 1-18-year-olds; and (3) Prevention 2: Prevention 1, except the nationwide campaign includes individuals up to 29 years old. Over a 30-year simulation period, Prevention 2 would avert 78% of the meningococcal cases (95% prediction interval: 63%-90%) expected under the Base policy if serogroup A is not replaced by remaining serogroups after elimination, and would avert 87% (77%-93%) of meningococcal cases if complete strain replacement occurs. Compared to the Base policy and at the PMC vaccine price of US$4 per dose, strategies that use PMC vaccine (i.e., Base Prime and Preventions 1 and 2) are expected to be cost saving if strain replacement occurs, and would cost US$51 (-US$236, US$490), US$188 (-US$97, US$626), and US$246 (-US$53, US$703) per DALY averted, respectively, if strain replacement does not occur. An important potential limitation of our study is the simplifying assumption that all circulating meningococcal serogroups can be aggregated into a single group; while this assumption is critical for model tractability, it would compromise the insights derived from our model if the effectiveness of the vaccine differs markedly between serogroups or if there are complex between-serogroup interactions that influence the frequency and magnitude of future meningitis epidemics. CONCLUSIONS: Our results suggest that a vaccination strategy that includes a catch-up nationwide immunization campaign in young adults with a PMC vaccine and the addition of this new vaccine into EPI is cost-effective and would avert a substantial portion of meningococcal cases expected under the current World Health Organization-recommended strategy of reactive vaccination. This analysis is limited to Burkina Faso and assumes that polyvalent vaccines offer equal protection against all meningococcal serogroups; further studies are needed to evaluate the robustness of this assumption and applicability for other countries in the meningitis belt

Cost-Effectiveness of Alternative Uses of Polyvalent Meningococcal Vaccines in Niger: An Agent-Based Transmission Modeling Study.

Background. Despite the introduction of an effective serogroup A conjugate vaccine (MenAfriVac™), sporadic epidemics of other Neisseria meningitidis serogroups remain a concern in Africa. Polyvalent meningococcal conjugate (PMC) vaccines may offer alternatives to current strategies that rely on routine infant vaccination with MenAfriVac plus, in the event of an epidemic, district-specific reactive campaigns using polyvalent meningococcal polysaccharide (PMP) vaccines. Methods. We developed an agent-based transmission model of N. meningitidis in Niger to compare the health effects and costs of current vaccination practice and 3 alternatives. Each alternative replaces MenAfriVac in the infant vaccination series with PMC and either replaces PMP with PMC for reactive campaigns or implements a one-time catch up campaign with PMC for children and young adults. Results. Over a 28-year period, replacement of MenAfriVac with PMC in the infant immunization series and of PMP in reactive campaigns would avert 63% of expected cases (95% prediction interval 49%-75%) if elimination of serogroup A is not followed by serogroup replacement. At a PMC price of $4/dose, this would cost$1412 ($81-$3510) per disability-adjusted life-year (DALY) averted. If serogroup replacement occurs, the cost-effectiveness of this strategy improves to $662 (cost-saving,$2473) per DALY averted. Sensitivity analyses accounting for incomplete laboratory confirmation suggest that a catch-up PMC campaign would also meet standard cost-effectiveness thresholds. Limitations. The assumption that polyvalent vaccines offer similar protection against all serogroups is simplifying. Conclusions. The use of PMC vaccines to replace MenAfriVac in routine infant immunization and in district-specific reactive campaigns would have important health benefits and is likely to be cost-effective in Niger. An additional PMC catch-up campaign would also be cost-effective if we account for incomplete laboratory reporting.PAT

Dynamic Health Policies for Controlling the Spread of Emerging Infections: Influenza as an Example

The recent appearance and spread of novel infectious pathogens provide motivation for using models as tools to guide public health decision-making. Here we describe a modeling approach for developing dynamic health policies that allow for adaptive decision-making as new data become available during an epidemic. In contrast to static health policies which have generally been selected by comparing the performance of a limited number of pre-determined sequences of interventions within simulation or mathematical models, dynamic health policies produce “real-time” recommendations for the choice of the best current intervention based on the observable state of the epidemic. Using cumulative real-time data for disease spread coupled with current information about resource availability, these policies provide recommendations for interventions that optimally utilize available resources to preserve the overall health of the population. We illustrate the design and implementation of a dynamic health policy for the control of a novel strain of influenza, where we assume that two types of intervention may be available during the epidemic: (1) vaccines and antiviral drugs, and (2) transmission reducing measures, such as social distancing or mask use, that may be turned “on” or “off” repeatedly during the course of epidemic. In this example, the optimal dynamic health policy maximizes the overall population's health during the epidemic by specifying at any point of time, based on observable conditions, (1) the number of individuals to vaccinate if vaccines are available, and (2) whether the transmission-reducing intervention should be either employed or removed

Cost-effectiveness analysis of typhoid conjugate vaccines in an outbreak setting: a modeling study

BackgroundSeveral prolonged typhoid fever epidemics have been reported since 2010 throughout eastern and southern Africa, including Malawi, caused by multidrug-resistant Salmonella Typhi. The World Health Organization recommends the use of typhoid conjugate vaccines (TCVs) in outbreak settings; however, current data are limited on how and when TCVs might be introduced in response to outbreaks.MethodologyWe developed a stochastic model of typhoid transmission fitted to data from Queen Elizabeth Central Hospital in Blantyre, Malawi from January 1996 to February 2015. We used the model to evaluate the cost-effectiveness of vaccination strategies over a 10-year time horizon in three scenarios: (1) when an outbreak is likely to occur; (2) when an outbreak is unlikely to occur within the next ten years; and (3) when an outbreak has already occurred and is unlikely to occur again. We considered three vaccination strategies compared to the status quo of no vaccination: (a) preventative routine vaccination at 9 months of age; (b) preventative routine vaccination plus a catch-up campaign to 15 years of age; and (c) reactive vaccination with a catch-up campaign to age 15 (for Scenario 1). We also explored variations in outbreak definitions, delays in implementation of reactive vaccination, and the timing of preventive vaccination relative to the outbreak.ResultsAssuming an outbreak occurs within 10 years, we estimated that the various vaccination strategies would prevent a median of 15-60% of disability-adjusted life-years (DALYs). Reactive vaccination was the preferred strategy for WTP values of $0-300 per DALY averted. For WTP values >$300, introduction of preventative routine TCV immunization with a catch-up campaign was the preferred strategy. Routine vaccination with a catch-up campaign was cost-effective for WTP values above $890 per DALY averted if no outbreak occurs and >$140 per DALY averted if implemented after the outbreak has already occurred.ConclusionsCountries for which the spread of antimicrobial resistance is likely to lead to outbreaks of typhoid fever should consider TCV introduction. Reactive vaccination can be a cost-effective strategy, but only if delays in vaccine deployment are minimal; otherwise, introduction of preventive routine immunization with a catch-up campaign is the preferred strategy

Generalized Markov models of infectious disease spread: A novel framework for developing dynamic health policies

We propose a class of mathematical models for the transmission of infectious diseases in large populations. This class of models, which generalizes the existing discrete-time Markov chain models of infectious diseases, is compatible with efficient dynamic optimization techniques to assist real-time selection and modification of public health interventions in response to evolving epidemiological situations and changing availability of information and medical resources. While retaining the strength of existing classes of mathematical models in their ability to represent the within-host natural history of disease and between-host transmission dynamics, the proposed models possess two advantages over previous models: (1) these models can be used to generate optimal dynamic health policies for controlling spreads of infectious diseases, and (2) these models are able to approximate the spread of the disease in relatively large populations with a limited state space size and computation time.Infectious disease models Dynamic health policy Discrete-time Markov chain Dynamic programming Epidemiology

A game-theoretic framework for estimating a health purchaser’s willingness-to-pay for health and for expansion

Game theory, Willingness-to-pay, Health care, Moral hazard, Asymmetric information, Resource allocation, Implementation, Colorectal cancer,

A Likelihood Approach for Real-Time Calibration of Stochastic Compartmental Epidemic Models

<div><p>Stochastic transmission dynamic models are especially useful for studying the early emergence of novel pathogens given the importance of chance events when the number of infectious individuals is small. However, methods for parameter estimation and prediction for these types of stochastic models remain limited. In this manuscript, we describe a calibration and prediction framework for stochastic compartmental transmission models of epidemics. The proposed method, Multiple Shooting for Stochastic systems (MSS), applies a linear noise approximation to describe the size of the fluctuations, and uses each new surveillance observation to update the belief about the true epidemic state. Using simulated outbreaks of a novel viral pathogen, we evaluate the accuracy of MSS for real-time parameter estimation and prediction during epidemics. We assume that weekly counts for the number of new diagnosed cases are available and serve as an imperfect proxy of incidence. We show that MSS produces accurate estimates of key epidemic parameters (i.e. mean duration of infectiousness, <i>R</i>₀, and <i>R</i>_eff) and can provide an accurate estimate of the unobserved number of infectious individuals during the course of an epidemic. MSS also allows for accurate prediction of the number and timing of future hospitalizations and the overall attack rate. We compare the performance of MSS to three state-of-the-art benchmark methods: 1) a likelihood approximation with an assumption of independent Poisson observations; 2) a particle filtering method; and 3) an ensemble Kalman filter method. We find that MSS significantly outperforms each of these three benchmark methods in the majority of epidemic scenarios tested. In summary, MSS is a promising method that may improve on current approaches for calibration and prediction using stochastic models of epidemics.</p></div

Identifying the calibration method with statistically dominant performance for predictions at 0.05 significance level.

<p>Red, if MSS is statistically better than all benchmark methods. White, if all methods fail to demonstrate statistically dominant performance. Blue if I.Poi (benchmark A), Green if Particle Filter (benchmark B) and Black if the Ensemble Kalman filter (benchmark C) statistically outperform the MSS method. Multiple colors can occur if more than one method is significantly better than MSS.</p