Impact of 13-valent pneumococcal conjugate vaccine (PCV13) in a pandemic similar to the 2009 H1N1 in the United States.

BACKGROUND: High rates of bacterial coinfection in autopsy data from the 2009 H1N1 influenza ("flu") pandemic suggest synergies between flu and pneumococcal disease (PD) during pandemic conditions, and highlight the importance of interventions like the 13-valent pneumococcal conjugate vaccine (PCV13) that may mitigate the impact of a pandemic. METHODS: We used a decision-analytic model, estimated from published sources, to assess the impact of pediatric vaccination with PCV13 versus the 7-valent vaccine (PCV7) on PD incidence and mortality in a normal flu season (10% flu incidence) and in a pandemic similar to 2009-2010 H1N1 (20% flu incidence, mild virulence, high impact in children). Both direct and indirect (herd) effects against PD were considered. Effectiveness of PCV13 was extrapolated from observed PCV7 data, using assumptions of serotype prevalence and PCV13 protection against the 6 serotypes not in PCV7. To simulate 2009-2010 H1N1, autopsy data were used to estimate the overall proportion of flu deaths with bacterial coinfections. By assuming that increased risk of death during the pandemic occurred among those with comorbidity (using obesity as proxy) and bacterial coinfections primarily due to S. pneumoniae or S. aureus, we estimated the proportion co-infected among all (fatal and non-fatal) flu cases (7.6% co-infected with any organism; 2.2% with S. pneumoniae). PD incidence, mortality, and total healthcare costs were evaluated over a 1-year horizon. RESULTS: In a normal flu season, compared to PCV7, PCV13 is expected to prevent an additional 13,400 invasive PD (IPD) cases, 399,000 pneumonia cases, and 2,900 deaths, leading to cost savings of $472 M. In a pandemic similar to 2009-2010 H1N1, PCV13 would prevent 22,800 IPD cases, 872,000 pneumonia cases, and 3,700 deaths, resulting in cost savings of $1.0 B compared to PCV7. CONCLUSIONS: In a flu pandemic similar to the 2009-2010 H1N1, protection against the 6 additional serotypes in PCV13 would likely be effective in preventing pandemic-related PD cases, mortality, and associated costs.

Modeling the impact of the 13-valent pneumococcal conjugate vaccine serotype catch-up program using United States claims data.

BACKGROUND: Analysis of US claims data from April 2010 to June 2011 estimated that 39% of the 13-valent pneumococcal conjugate vaccine (PCV13) catch-up eligible cohort would ever receive the catch-up vaccination; a previous analysis assumed 87%. METHODS: This updated figure was applied to a previously published 10-year Markov model while holding all other inputs constant. RESULTS: Our model estimated that the catch-up program as currently implemented is estimated to prevent an additional 1.7 million cases of disease in children aged ≤ 59 months over a 10-year period, compared with routine PCV13 vaccination with no catch-up program. CONCLUSIONS: Because 39% catch-up uptake is less than the level of completion of the 4-dose primary PCV13 series, vaccine-preventable cases of pneumococcal disease and related deaths could be decreased further with additional uptake of catch-up vaccination in the catch-up eligible cohort.

Incorporating calibrated model parameters into sensitivity analyses: deterministic and probabilistic approaches.

OBJECTIVE: The aim of this study was to examine how calibration uncertainty affects the overall uncertainty of a mathematical model and to evaluate potential drivers of calibration uncertainty. METHODS: A lifetime Markov model of the natural history of human papillomavirus (HPV) infection and cervical disease was developed to assess the cost effectiveness of a hypothetical HPV vaccine. Published data on cervical cancer incidence and mortality and prevalence of pre-cursor lesions were used as endpoints to calibrate the age- and HPV-type-specific transition probabilities between health states using the Nelder-Mead simplex method of calibration. A conventional probabilistic sensitivity analysis (PSA) was performed to assess uncertainty in vaccine efficacy, cost and utility estimates. To quantify the uncertainty around calibrated transition probabilities, a second PSA (calibration PSA) was performed using 25 distinct combinations of objective functions and starting simplexes. RESULTS: The initial calibration produced an incremental cost-effectiveness ratio (ICER) of $US 4300 per QALY for vaccination compared with no vaccination, and the conventional PSA gave a 95% credible interval of dominant to $US 9800 around this estimate (2005 values). The 95% credible interval for the ICERs in the calibration PSA ranged from $US 1000 to $US 37,700. CONCLUSIONS: Compared with a conventional PSA, the calibration PSA results reveal a greater level of uncertainty in cost-effectiveness results. Sensitivity analyses around model calibration should be performed to account for uncertainty arising from the calibration process.

Calibrating longitudinal models to cross-sectional data: the effect of temporal changes in health practices.

OBJECTIVES: To assess the impact of simulating temporal changes in health-care practice patterns when calibrating longitudinal models to cross-sectional data. METHODS: A Markov model of cervical cancer was calibrated to recent age-specific US data on the prevalence of cervical abnormalities, cervical cancer incidence, and related mortality. The impact of failing to account for temporal changes in screening practices was assessed by comparing results from 1) a conventional calibration that incorrectly assumed that all women had been exposed to current screening practices in the past and 2) an historically accurate calibration that reflected the fact that US women 65 years of age and older had not received currently available screening practices at younger ages. RESULTS: The parameter set derived from conventional calibration produced a cervical cancer incidence rate of 13.4 per 100,000 among women aged 65 years and older, which is equal to the target end point. However, when this parameter set was used in the model to simulate the effects of historically correct screening, cervical incidence and related mortality in the 65 years and older age group were overestimated by 18% and 47%, respectively. Finally, when the parameter set was correctly calibrated by assuming historical changes in screening in the calibration process, excellent calibration to both incidence and mortality was obtained. CONCLUSIONS: Calibrating longitudinal models to cross-sectional data without accounting for temporal changes in clinical practice may result in a parameter set that is not as optimized as it appears and may lead to bias in evaluating the effectiveness of interventions.

Methods of model calibration: observations from a mathematical model of cervical cancer.

BACKGROUND: Mathematical models are commonly used to predict future benefits of new therapies or interventions in the healthcare setting. The reliability of model results is greatly dependent on accuracy of model inputs but on occasion, data sources may not provide all the required inputs. Therefore, calibration of model inputs to epidemiological endpoints informed by existing data can be a useful tool to ensure credibility of the results. OBJECTIVE: To compare different computational methods of calibrating a Markov model to US data. METHODS: We developed a Markov model that simulates the natural history of human papillomavirus (HPV) infection and subsequent cervical disease in the US. Because the model consists of numerous transition probabilities that cannot be directly estimated from data, calibration to multiple disease endpoints was required to ensure its predictive validity. Goodness of fit was measured as the mean percentage deviation of model-predicted endpoints from target estimates. During the calibration process we used the manual, random and Nelder-Mead calibration methods. RESULTS: The Nelder-Mead and manual calibration methods achieved the best fit, with mean deviations of 7% and 10%, respectively. Nelder-Mead accomplished this result with substantially less analyst time than the manual method, but required more intensive computing capability. The random search method achieved a mean deviation of 39%, which we considered unacceptable despite the ease of implementation of that method. CONCLUSIONS: The Nelder-Mead and manual techniques may be preferable calibration methods based on both performance and efficiency, provided that sufficient resources are available.

Public health and economic impact of the 13-valent pneumococcal conjugate vaccine (PCV13) in the United States.

The 7-valent pneumococcal conjugate vaccine (PCV7) has dramatically decreased pneumococcal disease incidence, and the 13-valent vaccine (PCV13) protects against 6 additional Streptococcus pneumoniae serotypes. A decision-analytic model was constructed to evaluate the impact of infant vaccination with PCV13 versus PCV7 on pneumococcal disease incidence and mortality as well as the incremental benefit of a serotype catch-up program. PCV13 effectiveness was extrapolated from observed PCV7 data, using assumptions regarding serotype prevalence and PCV13 protection against additional serotypes. The model predicts that PCV13 is more effective and cost saving compared with PCV7, preventing 106,000 invasive pneumococcal disease (IPD) cases and 2.9 million pneumonia cases, and saving $11.6 billion over a 10-year period. The serotype catch-up program would prevent an additional 12,600 IPD cases and 404,000 pneumonia cases, and save an additional $737 million compared with no catch-up program.

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.