Childhood vaccine finance and safety issues.

Health Aff (Millwood)

Institute of Medicine, Board on Health Care Services in Washington, DC, USA.

Published: December 2004

The U.S. national immunization system has been extraordinarily successful. But financing of vaccines is fragmented, and the supply of vaccines has become unreliable. Growing public concern about vaccine safety places additional stress on this system. Because vaccines are given to healthy children, adverse events can be particularly troubling. But excessive public concern can negatively affect vaccine supply and delivery by complicating the job of immunizing children and reducing the incentive to produce vaccines. This paper explores a range of vaccine financing and safety issues-and the linkages between them-and considers recent Institute of Medicine studies and recommendations.

Download full-text PDF

Source
http://dx.doi.org/10.1377/hlthaff.23.5.98DOI Listing

Publication Analysis

Top Keywords

public concern
8
childhood vaccine
4
vaccine finance
4
finance safety
4
safety issues
4
issues national
4
national immunization
4
immunization system
4
system extraordinarily
4
extraordinarily successful
4

Similar Publications

Higher Aircraft Noise Exposure Is Linked to Worse Heart Structure and Function by Cardiovascular MRI.

J Am Coll Cardiol

December 2024

UCL MRC Unit for Lifelong Health and Ageing, University College London, London, United Kingdom; UCL Institute of Cardiovascular Science, University College London, London, United Kingdom; Centre for Inherited Heart Muscle Conditions, Cardiology Department, Royal Free Hospital, London, United Kingdom. Electronic address:

Background: Aircraft noise is a growing concern for communities living near airports.

Objectives: This study aimed to explore the impact of aircraft noise on heart structure and function.

Methods: Nighttime aircraft noise levels (L) and weighted 24-hour day-evening-night aircraft noise levels (L) were provided by the UK Civil Aviation Authority for 2011.

View Article and Find Full Text PDF

Setting up a global SARS-CoV-2 surveillance system requires an understanding of how virus isolation and propagation practices, use of animal or human sera, and different neutralisation assay platforms influence assessment of SARS-CoV-2 antigenicity. In this study, with the contribution of 15 independent laboratories across all WHO regions, we carried out a controlled analysis of neutralisation assay platforms using the first WHO International Standard for antibodies to SARS-CoV-2 variants of concern (source: NIBSC). Live virus isolates (source: WHO BioHub or individual labs) or spike plasmids (individual labs) for pseudovirus production were used to perform neutralisation assays using the same serum panels.

View Article and Find Full Text PDF

Special Issue: "Post-COVID-19 Syndrome".

Viruses

December 2024

Institute of Transplantation Diagnostics and Cell Therapy, Division of Hemostasis, Hemotherapy, and Transfusion Medicine, Blood and Hemophilia Comprehensive Care Center, Heinrich Heine University Medical Center, D-40225 Düsseldorf, Germany.

On 30 January 2020, the World Health Organization declared COVID-19 a Public Health Emergency of International Concern (PHEIC)-the highest WHO warning level [...

View Article and Find Full Text PDF

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been detected in multiple animal species, including white-tailed deer (WTD), raising concerns about zoonotic transmission, particularly in environments with frequent human interactions. To understand how human exposure influences SARS-CoV-2 infection in WTD, we compared infection and exposure prevalence between farmed and free-ranging deer populations in Florida. We also examined the timing and viral variants in WTD relative to those in Florida's human population.

View Article and Find Full Text PDF

In this study, we introduce a novel approach that integrates interpretability techniques from both traditional machine learning (ML) and deep neural networks (DNN) to quantify feature importance using global and local interpretation methods. Our method bridges the gap between interpretable ML models and powerful deep learning (DL) architectures, providing comprehensive insights into the key drivers behind model predictions, especially in detecting outliers within medical data. We applied this method to analyze COVID-19 pandemic data from 2020, yielding intriguing insights.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!