Mathematical Model of Vaccine Noncompliance

Vaccine scares can prevent individuals from complying with a vaccination program. When compliance is high, the critical vaccination proportion is close to being met, and herd immunity occurs, bringing the disease incidence to extremely low levels. Thus, the risk to vaccinate may seem greater than the risk of contracting the disease, inciting vaccine noncompliance. A previous behavior-incidence ordinary differential equation model shows both social learning and feedback contributing to changes in vaccinating behavior, where social learning is the perceived risk of vaccinating and feedback repre- sents new cases of the disease. In our study, we compared several candidate models to more simply illustrate both vaccination coverage and incidence through social learn- ing and feedback. The behavior model uses logistic growth and exponential decay to describe the social learning aspect as well as different functional forms of the disease prevalence to represent feedback. Each candidate model was tested by fitting it to data from the pertussis vaccine scare in England and Wales in the 1970s. Our most parsimonious model shows a superior fit to the vaccine coverage curve during the scare

Physicians Infrequently Adhere to Hepatitis Vaccination Guidelines for Chronic Liver Disease

Background and Goals:Hepatitis A (HAV) and hepatitis B (HBV) vaccination in patients with chronic liver disease is an accepted standard of care. We determined HAV and HBV vaccination rates in a tertiary care referral hepatology clinic and the impact of electronic health record (EHR)-based reminders on adherence to vaccination guidelines.Methods:We reviewed the records of 705 patients with chronic liver disease referred to our liver clinic in 2008 with at least two follow-up visits during the subsequent year. Demographics, referral source, etiology, and hepatitis serology were recorded. We determined whether eligible patients were offered vaccination and whether patients received vaccination. Barriers to vaccination were determined by a follow-up telephone interview.Results:HAV and HBV serologic testing prior to referral and at the liver clinic were performed in 14.5% and 17.7%; and 76.7% and 74% patients, respectively. Hepatologists recommended vaccination for HAV in 63% and for HBV in 59.7% of eligible patients. Patient demographics or disease etiology did not influence recommendation rates. Significant variability was observed in vaccination recommendation amongst individual providers (30-98.6%), which did not correlate with the number of patients seen by each physician. Vaccination recommendation rates were not different for Medicare patients with hepatitis C infection for whom a vaccination reminder was automatically generated by the EHR. Most patients who failed to get vaccination after recommendation offered no specific reason for noncompliance; insurance was a barrier in a minority.Conclusions:Hepatitis vaccination rates were suboptimal even in an academic, sub-speciality setting, with wide-variability in provider adherence to vaccination guidelines. © 2013 Thudi et al

Tracking Chart 2003 Adidas Salomon, Pakistan 01005787B

This document is part of a digital collection provided by the Martin P. Catherwood Library, ILR School, Cornell University, pertaining to the effects of globalization on the workplace worldwide. Special emphasis is placed on labor rights, working conditions, labor market changes, and union organizing.FLA_2003_AdidasSalomon_TC_Pakistan_01005787B.pdf: 27 downloads, before Oct. 1, 2020

Western Baptist Hospital: Problem-Solving With Pneumonia Care Performance Improvement Teams

Describes successful strategies for strengthening pneumonia care, including multidisciplinary performance improvement teams, process improvements built into staff routines, peer collaboratives, standard order sets, and feedback through concurrent review

Tuberculosis in Malta in the 21st century

The World Health Organisation dedicated the 24th of March 1996 as World TB Day in a bid to promote its publicity campaign aimed at increasing awareness of the deteriorating situation as regards the treatment and control of tuberculosis. Today’s world population is about 5,700 million and TB is by far the major cause of death from infectious disease in persons over five years old. WHO estimates that one third of the world’s population, that is, about 1,900 million are already infected and we know that approximately 10% of these will develop the disease. The real concern, however, is that current drugs may become useless. Indeed, it is estimated that more than 50 million people are infected with drug-resistant strains. On a global scale, the main cause of drug resistance is poorly managed TB control programs.peer-reviewe

Tracking Chart 2007 Russell Brands, Pakistan 260257628F

This document is part of a digital collection provided by the Martin P. Catherwood Library, ILR School, Cornell University, pertaining to the effects of globalization on the workplace worldwide. Special emphasis is placed on labor rights, working conditions, labor market changes, and union organizing.FLA_2007_Russell_Brands_TC_Pakistan_260257628F.pdf: 6 downloads, before Oct. 1, 2020

Nonparametric Bounds and Sensitivity Analysis of Treatment Effects

This paper considers conducting inference about the effect of a treatment (or exposure) on an outcome of interest. In the ideal setting where treatment is assigned randomly, under certain assumptions the treatment effect is identifiable from the observable data and inference is straightforward. However, in other settings such as observational studies or randomized trials with noncompliance, the treatment effect is no longer identifiable without relying on untestable assumptions. Nonetheless, the observable data often do provide some information about the effect of treatment, that is, the parameter of interest is partially identifiable. Two approaches are often employed in this setting: (i) bounds are derived for the treatment effect under minimal assumptions, or (ii) additional untestable assumptions are invoked that render the treatment effect identifiable and then sensitivity analysis is conducted to assess how inference about the treatment effect changes as the untestable assumptions are varied. Approaches (i) and (ii) are considered in various settings, including assessing principal strata effects, direct and indirect effects and effects of time-varying exposures. Methods for drawing formal inference about partially identified parameters are also discussed.Comment: Published in at http://dx.doi.org/10.1214/14-STS499 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Estimating cluster-level local average treatment effects in cluster randomised trials with non-adherence

Non-adherence to assigned treatment is a common issue in cluster randomised trials (CRTs). In these settings, the efficacy estimand may be also of interest. Many methodological contributions in recent years have advocated using instrumental variables to identify and estimate the local average treatment effect (LATE). However, the clustered nature of randomisation in CRTs adds to the complexity of such analyses. In this paper, we show that under certain assumptions, the LATE can be estimated via two-stage least squares (TSLS) using cluster-level summaries of outcomes and treatment received. Implementation needs to account for this, as well as the possible heteroscedasticity, to obtain valid inferences. We use simulations to assess the performance of TSLS of cluster-level summaries under cluster-level or individual-level non-adherence, with and without weighting and robust standard errors. We also explore the impact of adjusting for cluster-level covariates and of appropriate degrees of freedom correction for inference. We find that TSLS estimation using cluster-level summaries provides estimates with small to negligible bias and coverage close to nominal level, provided small sample degrees of freedom correction is used for inference, with appropriate use of robust standard errors. We illustrate the methods by re-analysing a CRT in UK primary health settings.Comment: 21 pages, 6 Figure

Immunogenicity and tolerability of an MF59-adjuvanted, egg-derived, A/H1N1 pandemic influenza vaccine in children 6-35 months of age

Background: Vaccines against pandemic A/H1N1 influenza should provide protective immunity in children, because they are at greater risk of disease than adults. This study was conducted to identify the optimal dose of an MF59 (R)-adjuvanted, egg-derived, A/H1N1 influenza vaccine for young children. Methods: Children 6-11 months (N = 144) and 12-35 months (N = 186) of age received vaccine formulations containing either 3.75 mu g antigen with half the standard dose of MF59 or 7.5 mu g antigen with a standard dose of MF59, or a nonadjuvanted formulation containing 15 mu g antigen (children 12-35 months only). Participants were given 2 primary vaccine doses 3 weeks apart, followed by 1 booster dose of MF59-adjuvanted seasonal influenza vaccine 1 year later. Immunogenicity was assessed by hemagglutination inhibition and microneutralization assays. Results: All vaccine formulations were highly immunogenic and met all 3 European licensure criteria after 2 doses. MF59-adjuvanted vaccines met all licensure criteria after 1 dose in both age cohorts, while nonadjuvanted vaccine did not meet all criteria after 1 dose in children 12-35 months. A single booster dose was highly immunogenic, and stable antibody persistence was observed in response to all vaccines. All vaccines were well tolerated. Conclusions: In this study, a single dose of 3.75 mu g antigen with half the standard dose of MF59 was shown to be optimal, providing adequate levels of immediate and long-term antibodies in pediatric subjects 6-35 months of age. These data demonstrated that MF59 adjuvant allowed for reduced antigen content and promoted significant long-term antibody persistence in children, with a satisfactory safety profile