Modeling the Effectiveness of Respiratory Protective Devices in Reducing Influenza Outbreak

Outbreaks of influenza represent an important health concern worldwide. In many cases, vaccines are only partially successful in reducing the infection rate, and respiratory protective devices (RPDs) are used as a complementary countermeasure. In devising a protection strategy against influenza for a given population, estimates of the level of protection afforded by different RPDs is valuable. In this article, a risk assessment model previously developed in general form was used to estimate the effectiveness of different types of protective equipment in reducing the rate of infection in an influenza outbreak. It was found that a 50% compliance in donning the device resulted in a significant (at least 50% prevalence and 20% cumulative incidence) reduction in risk for fitted and unfitted N95 respirators, high‐filtration surgical masks, and both low‐filtration and high‐filtration pediatric masks. An 80% compliance rate essentially eliminated the influenza outbreak. The results of the present study, as well as the application of the model to related influenza scenarios, are potentially useful to public health officials in decisions involving resource allocation or education strategies.     

Do poor people have a stronger relationship between income and mortality than the rich? Implications of panel data for health-health analysis

Articles developing health-health analysis have used the observation that richer people tend to face reduced mortality risk to estimate the break-even cost per life saved of health regulations. If government requires that the private sector spend more than this break-even cutoff, the risk of dying due to reduced health investment is increased by more than it will be reduced by the direct action of the health regulation. We use panel data to suggest that the relationship between income and the probability of death is greater for poor people than for the rich. As a consequence, break-even cutoffs are roughly twice as large for the richest 20% of the population than they are for the poorest 20%. The nonlinearity in the income-to-mortality linkage also implies that income transfers between income groups which are ignored in traditional cost-benefit analysis will affect the conclusions of health-health analysis significantly.     

A comparison of confidence regions and designs in estimation of a ratio

A computer simulation is performed to compare confidence regions arising from Fie1ler's theorem and approximate large sample intervals in estimating the point of extremum in quadratic regression. In addition, two designs, one of which is motivated by optimal design theory, are compared. These comparisons are made by examining the confidence level and accuracy of the regions, as well as the concentration of the standard point estimator, in a variety of settings. The results have implications for the more general problem of estimating a ratio of linear combinations in the general linear model.     

Controlling for causality in the link from income to mortality

While previous research shows that wealthier people tend to live longer, it is not clear whether this occurs because wealthy people make greater investments in health and safety or because inherently healthy people tend to make more money. This article uses measures of initial health to focus on the flow from wealth to good health. While the estimated link between income and mortality is less than in other articles, we find that a significant link still remains. In particular, we estimate that health and safety regulations, which cost more than $12.2 million per life saved, are likely to kill more people through increased poverty than they save directly. Estimates of costs per life saved provided by the Office of Management and Budget suggest that many health and safety programs implemented in the last 20 years would be eliminated using this criterion.