Force of infection of Helicobacter pylori in Mexico: evidence from a national survey using a hierarchical Bayesian model.

Helicobacter pylori (H. pylori) is present in the stomach of half of the world's population. The force of infection describes the rate at which susceptibles acquire infection. In this article, we estimated the age-specific force of infection of H. pylori in Mexico. Data came from a national H. pylori seroepidemiology survey collected in Mexico in 1987-88. We modelled the number of individuals with H. pylori at a given age as a binomial random variable. We assumed that the cumulative risk of infection by a given age follows a modified exponential catalytic model, allowing some fraction of the population to remain uninfected. The cumulative risk of infection was modelled for each state in Mexico and were shrunk towards the overall national cumulative risk curve using Bayesian hierarchical models. The proportion of the population that can be infected (i.e. susceptible population) is 85.9% (95% credible interval (CR) 84.3%-87.5%). The constant rate of infection per year of age among the susceptible population is 0.092 (95% CR 0.084-0.100). The estimated force of infection was highest at birth 0.079 (95% CR 0.071-0.087) decreasing to zero as age increases. This Bayesian hierarchical model allows stable estimation of state-specific force of infection by pooling information between the states, resulting in more realistic estimates.

Prioritizing Research Informing Antibiotic Prophylaxis Guidelines for Knee Arthroplasty Patients.

INTRODUCTION: Guidelines for routine antibiotic prophylaxis (AP) before dental procedures to prevent periprosthetic joint infection (PJI) have been hampered by the lack of prospective clinical trials. OBJECTIVES: To apply value-of-information (VOI) analysis to quantify the value of conducting further clinical research to reduce decision uncertainty regarding the cost-effectiveness of AP strategies for dental patients undergoing total knee arthroplasty (TKA). METHODS: An updated decision model and probabilistic sensitivity analysis (PSA) evaluated the cost-effectiveness of AP and decision uncertainty for 3 AP strategies: no AP, 2-y AP, and lifetime AP. VOI analyses estimated the value and cost of conducting a randomized controlled trial (RCT) or observational study. We used a linear regression meta-modeling approach to calculate the population expected value of partial perfect information and a Gaussian approximation to calculate population expected value of sample information, and we subtracted the cost for research to obtain the expected net benefit of sampling (ENBS). We determined the optimal trial sample sizes that maximized ENBS. RESULTS: Using a willingness-to-pay threshold of $100,000 per quality-adjusted life-year, the PSA found that a no-AP strategy had the highest expected net benefit, with a 60% probability of being cost-effective, and 2-y AP had a 37% probability. The optimal sample size for an RCT to determine AP efficacy and dental-related PJI risk would require approximately 421 patients per arm with an estimated cost of $14.7 million. The optimal sample size for an observational study to inform quality-of-life parameters would require 2,211 patients with an estimated cost of $1.2 million. The 2 trial designs had an ENBS of approximately $25 to $26 million. CONCLUSION: Given the uncertainties associated with AP guidelines for dental patients after TKA, we conclude there is value in conducting further research to inform the risk of PJI, effectiveness of AP, and quality-of-life values. KNOWLEDGE TRANSFER STATEMENT: The results of this value-of-information analysis demonstrate that there is substantial uncertainty around clinical, health status, and economic parameters that may influence the antibiotic prophylaxis guidance for dental patients with total knee arthroplasty. The analysis supports the contention that conducting additional clinical research to reduce decision uncertainty is worth pursuing and will inform the antibiotic prophylaxis debate for clinicians and dental patients with prosthetic joints.

Cost-effectiveness analysis of a multidisciplinary health-care model for patients with type-2 diabetes implemented in the public sector in Mexico: A quasi-experimental, retrospective evaluation.

OBJECTIVE: In 2007, the Ministry of Health (MoH) in Mexico implemented a multidisciplinary health-care model (MHC) for patients with type-2 diabetes (T2D), which has proven more effective in controlling this condition than the conventional health-care model (CHC). RESEARCH DESIGN AND METHODS: We compared the cost-effectiveness of the MHC vs. the CHC for patients with T2D using a quasi-experimental, retrospective design. Epidemiologic and cost data were obtained from a randomly selected sample of health-care units, using medical records as well as patient- and facility-level data. We modelled the cost-effectiveness of the MHC at one, 10 and 20 years using a simulation model. RESULTS: The average cumulative costs per patient at 20 years were US$4,225 for the MHC and US$4,399 for the CHC. With a willingness to pay one gross domestic product (GDP) per capita per quality-adjusted life year (QALY) (US$8,910), the incremental net benefits per patient were US$1,450 and US$3,737 at 10 and 20 years, respectively. The MHC was cost-effective from the third year onward; however, increasing coverage to 500 patients per year rendered it cost-effective at year one. CONCLUSIONS: The MHC is cost-effective at 10 and 20 years. Cost-effectiveness can be achieved in the short term by increasing MHC coverage.

Revisiting assumptions about age-based mixing representations in mathematical models of sexually transmitted infections.

BACKGROUND: Sexual mixing between heterogeneous population subgroups is an integral component of mathematical models of sexually transmitted infections (STIs). This study compares the fit of different mixing representations to survey data and the impact of different mixing assumptions on the predicted benefits of hypothetical human papillomavirus (HPV) vaccine strategies. METHODS: We compared novel empirical (data-driven) age mixing structures with the more commonly-used assortative-proportionate (A-P) mixing structure. The A-P mixing structure assumes that a proportion of sexual contacts - known as the assortativity constant, typically estimated from survey data or calibrated - occur exclusively within one's own age group and the remainder mixes proportionately among all age groups. The empirical age mixing structure was estimated from the National Survey on Sexual Attitudes and Lifestyles 3 (Natsal-3) using regression methods, and the assortativity constant was estimated from Natsal-3 as well. Using a simplified HPV transmission model under each mixing assumption, we calibrated the model to British HPV16 prevalence data, then estimated the reduction in steady-state prevalence and the number of infections averted due to expanding HPV vaccination from 12- through 26-year-old females alone to 12-year-old males or 27- to 39-year-old females. RESULTS: Empirical mixing provided a better fit to the Natsal-3 data than the best-fitting A-P structure. Using the model with empirical mixing as a reference, the model using the A-P structure often under- or over-estimated the benefits of vaccination, in one case overestimating by 2-fold the number of infections prevented due to extended female catch-up in a high vaccine uptake setting. CONCLUSIONS: An empirical mixing structure more accurately represents sexual mixing survey data, and using the less accurate, yet commonly-used A-P structure has a notable effect on estimates of HPV vaccination benefits. This underscores the need for mixing structures that are less dependent on unverified assumptions and are directly informed by sexual behavior data.