Changing caseloads: macro influences and micro composition - commentary

Welfare ; Public welfare

Why Welfare Caseloads Fluctuate: A Review of Research on AFDC, SSI, and the Food Stamps Program

This report reviews research on trends in the caseloads of three means-tested transfer programs in the United States: Aid to Families with Dependent Children (AFDC), Supplemental Security Income (SSI), and the Food Stamp Program (FSP). Trends in caseloads are the result of 1) program parameters and interactions between programs, 2) economic conditions, 3) norms and values, and 4) demographic characteristics. Most research tries to estimate the relative importance of the first two. The research suggests that all else equal, as welfare programs become more generous and easier to get caseloads increase. Caseload changes are also greatest when two or more of these four factors provide similar incentives for people to alter their behavior. For example, recent declines in AFDC and the FSP caseloads appear to be the result of the combined effect of the strong U.S. economy and policy changes that made work more available and more attractive compared to welfare. Similarly, program interactions are important. When programs provide opposing incentives, they reduce the behavioral response to either incentive, and when programs provide similar incentives, the behavioral response is greater than if only one program provided the incentive. Finally, incentives do not affect everyone in the same way. Program changes that benefit some recipients may hurt others. The research on caseloads has many limitations that reduce confidence in these estimated effects. The research is almost all based on reduced-form models, which tell us little about the causal mechanisms through which exogenous factors affect caseloads. The theory about these causal mechanisms is weak resulting in the possibility of mis-specification and many key variables are poorly measured or omitted.

Undergraduate public health education: a workforce perspective

Objective: To describe the career paths of students who majored in public health at the undergraduate level and to assess the skills and knowledge these g raduates believed were most useful to them in the public health workforce. Method: A telephone survey was conducted of all graduates from Adelaide University\u27s Bachelor of Health Sciences degree from 1992-99 who had majored in public health (124 graduates). Results: The response rate to the graduate survey was 71 %. Using the definition of public health functions from the National Delphi Study on Public Health Functions to delineate the public health workforce, 59% of respondents were employed in public health. Graduates working in public health valued generic skills such as communication and collaboration more highly than more specific public health skills and knowledge areas. However, they also believed their undergraduate course would have been improved by a more practical orientation. Conclusions: A high proportion of graduates from this generalist degree who major in public health find employment in the public health workforce. They greatly value the generic skills associated with their undergraduate public health education and believe their entry into the workforce would have been further facilitated by stronger links between their academic program and the working environment of public health professionals. Implications: Studies of workforce training programs in public health must differentiate between the educational needs of undergraduate and postgraduate students. In particular, strategies need to be developed to provide stronger links between undergraduate students and the public health workforce

The TLR4 D299G and T399I SNPs Are Constitutively Active to Up-Regulate Expression of Trif-Dependent Genes

Peer reviewedPublisher PD

Market-Based Environmental Management: Issues in Implementation

Increasingly, efforts to protect integral features of the natural environment that are essential to human well being face a double challenge. First, the magnitude of some conventional and emerging threats to environmental quality is growing, despite solid progress in controlling some causes. This is particularly the concern on a global scale in terms of atmospheric changes and loss of biological diversity. Second, easily-implemented uniform control methods using feasible technologies or other direct regulatory approaches are already in place for many pollution and resource management problems in the United States. Additional progress with so-called command and control policies can be expensive and disruptive, and thus counter productive to overall economic well being. This type of dilemma is common where environmental deterioration results from diffuse and complex causes inherent in technically-advanced high-consumption industrial societies such as the U.S. Solutions to these types of environmental problems are complicated by the diffuse benefits which obscures the net gains of additional controls that have concentrated and highly visible costs. Given this double bind, many policy analysts and academics have for years advocated more cost-effective and flexible approaches relying on market forces to further some environmental management objectives. Although market-based theory and practical environmental policy are still far apart, the incremental approach to environmental policymaking since the late seventies has resulted in some market-type innovations within traditional regulatory frameworks at all levels of government. The most prominent examples are the Environmental Protection Agency's (EPA) air emissions trading program and the recently enacted sulfur dioxide allowance trading program under the 1990 Clean Air Act Amendments

Performance of a Limiting-Antigen Avidity Enzyme Immunoassay for Cross-Sectional Estimation of HIV Incidence in the United States

Background: A limiting antigen avidity enzyme immunoassay (HIV-1 LAg-Avidity assay) was recently developed for cross-sectional HIV incidence estimation. We evaluated the performance of the LAg-Avidity assay alone and in multi-assay algorithms (MAAs) that included other biomarkers. Methods and Findings: Performance of testing algorithms was evaluated using 2,282 samples from individuals in the United States collected 1 month to >8 years after HIV seroconversion. The capacity of selected testing algorithms to accurately estimate incidence was evaluated in three longitudinal cohorts. When used in a single-assay format, the LAg-Avidity assay classified some individuals infected >5 years as assay positive and failed to provide reliable incidence estimates in cohorts that included individuals with long-term infections. We evaluated >500,000 testing algorithms, that included the LAg-Avidity assay alone and MAAs with other biomarkers (BED capture immunoassay [BED-CEIA], BioRad-Avidity assay, HIV viral load, CD4 cell count), varying the assays and assay cutoffs. We identified an optimized 2-assay MAA that included the LAg-Avidity and BioRad-Avidity assays, and an optimized 4-assay MAA that included those assays, as well as HIV viral load and CD4 cell count. The two optimized MAAs classified all 845 samples from individuals infected >5 years as MAA negative and estimated incidence within a year of sample collection. These two MAAs produced incidence estimates that were consistent with those from longitudinal follow-up of cohorts. A comparison of the laboratory assay costs of the MAAs was also performed, and we found that the costs associated with the optimal two assay MAA were substantially less than with the four assay MAA. Conclusions: The LAg-Avidity assay did not perform well in a single-assay format, regardless of the assay cutoff. MAAs that include the LAg-Avidity and BioRad-Avidity assays, with or without viral load and CD4 cell count, provide accurate incidence estimates

a global network of chronic kidney disease cohorts

Background Chronic kidney disease (CKD) is a global health burden, yet it is still underrepresented within public health agendas in many countries. Studies focusing on the natural history of CKD are challenging to design and conduct, because of the long time-course of disease progression, a wide variation in etiologies, and a large amount of clinical variability among individuals with CKD. With the difference in health-related behaviors, healthcare delivery, genetics, and environmental exposures, this variability is greater across countries than within one locale and may not be captured effectively in a single study. Methods Studies were invited to join the network. Prerequisites for membership included: 1) observational designs with a priori hypotheses and defined study objectives, patient-level information, prospective data acquisition and collection of bio-samples, all focused on predialysis CKD patients; 2) target sample sizes of 1,000 patients for adult cohorts and 300 for pediatric cohorts; and 3) minimum follow-up of three years. Participating studies were surveyed regarding design, data, and biosample resources. Results Twelve prospective cohort studies and two registries covering 21 countries were included. Participants age ranges from >2 to >70 years at inclusion, CKD severity ranges from stage 2 to stage 5. Patient data and biosamples (not available in the registry studies) are measured yearly or biennially. Many studies included multiple ethnicities; cohort size ranges from 400 to more than 13,000 participants. Studies’ areas of emphasis all include but are not limited to renal outcomes, such as progression to ESRD and death. Conclusions iNET-CKD (International Network of CKD cohort studies) was established, to promote collaborative research, foster exchange of expertise, and create opportunities for research training. Participating studies have many commonalities that will facilitate comparative research; however, we also observed substantial differences. The diversity we observed across studies within this network will be able to be leveraged to identify genetic, behavioral, and health services factors associated with the course of CKD. With an emerging infrastructure to facilitate interactions among the investigators of iNET-CKD and a broadly defined research agenda, we are confident that there will be great opportunity for productive collaborative investigations involving cohorts of individuals with CKD

A Comparison of Two Measures of HIV Diversity in Multi-Assay Algorithms for HIV Incidence Estimation

Background: Multi-assay algorithms (MAAs) can be used to estimate HIV incidence in cross-sectional surveys. We compared the performance of two MAAs that use HIV diversity as one of four biomarkers for analysis of HIV incidence. Methods: Both MAAs included two serologic assays (LAg-Avidity assay and BioRad-Avidity assay), HIV viral load, and an HIV diversity assay. HIV diversity was quantified using either a high resolution melting (HRM) diversity assay that does not require HIV sequencing (HRM score for a 239 base pair env region) or sequence ambiguity (the percentage of ambiguous bases in a 1,302 base pair pol region). Samples were classified as MAA positive (likely from individuals with recent HIV infection) if they met the criteria for all of the assays in the MAA. The following performance characteristics were assessed: (1) the proportion of samples classified as MAA positive as a function of duration of infection, (2) the mean window period, (3) the shadow (the time period before sample collection that is being assessed by the MAA), and (4) the accuracy of cross-sectional incidence estimates for three cohort studies. Results: The proportion of samples classified as MAA positive as a function of duration of infection was nearly identical for the two MAAs. The mean window period was 141 days for the HRM-based MAA and 131 days for the sequence ambiguity-based MAA. The shadows for both MAAs were <1 year. Both MAAs provided cross-sectional HIV incidence estimates that were very similar to longitudinal incidence estimates based on HIV seroconversion. Conclusions: MAAs that include the LAg-Avidity assay, the BioRad-Avidity assay, HIV viral load, and HIV diversity can provide accurate HIV incidence estimates. Sequence ambiguity measures obtained using a commercially-available HIV genotyping system can be used as an alternative to HRM scores in MAAs for cross-sectional HIV incidence estimation