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Biomedical subjects

M Nicas

Publications and source records attributed to M Nicas.

At least 19 recordsLinked to original sources
PubMed2000

Tuberculosis isolation: comparison of written procedures and actual practices in three California hospitals.

OBJECTIVE: To evaluate implementation of healthcare worker exposure control measures for tuberculosis (TB)-patient isolation, as specified by Centers for Disease Control and Prevention (CDC) guidelines and the hospital's TB-control policy. DESIGN: Prospective multihospital study comparing CDC guidelines and hospital policy for TB-patient isolation to once-weekly observations of TB-patient isolation practices over 14 consecutive weeks at each hospital. SETTING: Three urban hospitals (two county, one private community) in counties in California with a high incidence rate of TB. MEASUREMENTS: Work practices for TB-patient isolation were observed and ventilation performance of isolation rooms was assessed while patient rooms were in use for TB isolation. RESULTS: Of 170 TB-patient rooms observed, 119 (70%) involved a patient in a designated TB isolation room, the room was under negative pressure, the door was closed, and a "respiratory precautions" sign was on the door; 32 patient-room units (19%) were not under negative pressure or not designated as negative-pressure rooms. Of 151 patient-room units mechanically capable of negative pressure at a prior point in time, 16 (11%) were not under negative pressure at the time of use. Of 67 patient-room units equipped with continuous monitoring devices, 8 (12%) involved devices that did not accurately reflect the direction of airflow. Of the 62 healthcare workers observed using a respirator for TB, 40 (65%) did not don the respirator properly. CONCLUSIONS: Implementing CDC guidelines for TB-patient isolation was feasible but imperfect in the three hospitals. Day-to-day work practices deviated from hospital policy. Prospectively quantifying the implementation of a hospital TB isolation policy while the room is in use may lead to improved estimates of risk and may help to identify and thereby prevent avoidable healthcare worker exposures to Mycobacterium tuberculosis aerosol. Auditing practices and verifying equipment performance is likely to identify unexpected problems in implementation of the TB control program.

California↗
PubMed2000

Risk-based selection of respirators against infectious aerosols: application to anthrax spores.

This article presents two methods for estimating infection risk among individuals wearing air-purifying respirators against airborne pathogens, with the overall aim of selecting appropriate respiratory protection. Necessary data inputs are the parameters for the ambient pathogen concentration distribution, the respirator penetration distribution, and the infectious dose distribution, along with the breathing rate, duration of a respirator use period, and the number of use periods. The first method assumes that the pathogen does not exhibit a cumulative dose effect, whereas the second accounts for a cumulative dose effect. The methods are illustrated with hypothetical scenarios involving Bacillus anthracis (anthrax) spores. Available data suggest that anthrax spores would exhibit a cumulative dose effect for multiple exposures occurring close in time, as would likely affect personnel responding to a bioterrorist release. The analysis shows that failure to account for a cumulative dose effect when present leads to underestimating infection risk. Three types of air-purifying respirators are compared for their predicted efficacy in reducing the risk of inhalation anthrax. Although uncertainty analyses are not performed, a general conclusion is that a full-facepiece powered air-purifying respirator would be the best air-purifying device for responding to an anthrax spore release. Because such respirators would not prevent all personnel from inhaling an infectious dose, it would be advisable for users not previously vaccinated against anthrax to receive post-exposure prophylactic therapy.

Adult↗
PubMed1999

A multi-zone model evaluation of the efficacy of upper-room air ultraviolet germicidal irradiation.

Engineering controls can be used to reduce the spread of airborne infectious disease, particularly tuberculosis (TB), in high-risk settings. This article evaluates published data on the efficacy of upper-room air ultraviolet germicidal irradiation (UVGI). A three-zone representation of a TB patient room equipped with a germicidal UV lamp is developed. The lamp irradiates the upper-room zone and inactivates airborne mycobacteria; the unirradiated lower-room zone also contains a near-field zone surrounding the TB patient. Infectious particles are generated in the near-field zone and transported throughout the room by air flow between zones. Each zone is independently well-mixed; the whole room, however, is not well-mixed. The three-zone model is applied to a previously published study of UVGI against airborne mycobacteria in a test room. Based on the estimated slopes of the semi-log concentration decay curves for viable mycobacteria, and on the assumption that the test room was essentially well-mixed, the published study reported that UVGI provided 10 to 25 equivalent air changes per hour. However, when the same decay curve slopes are interpreted in the context of the three-zone model, UVGI is seen to be far less effective in reducing exposure intensity near the TB patient. Near-field exposure intensity is relevant because health care workers are usually in close proximity to the TB patients they attend. In general, the interpretation of concentration decay data depends on the specific model of room air mixing that is assumed appropriate. It is recommended that tests of the efficacy of UVGI and other control devices against airborne microorganisms be based on steady-state concentration measurements rather than concentration decay measurements, because the former measurements do not require inferences based on a particular model.

Air Pollution, Indoor↗
PubMed1999

A cost-benefit analysis of genetic screening for susceptibility to occupational toxicants.

Genetic screening can identify individuals with increased susceptibility to certain workplace toxicants. One conceivable benefit is a reduction in occupational disease costs. We examine this rationale by considering the associations among genetic traits, exposure, disease risk, and disease incidence. Given appropriate information, we describe methods for computing the expectation and variance of the future number of disease cases and of the differential screening cost per worker hired (a cost-benefit measure). We present two hypothetical scenarios: (1) benzene-induced cancer with few expected cases, and (2) chronic beryllium disease with many expected cases. We show that variability in disease incidence and cost outcomes must be considered because in specific instances, screening can be cost-beneficial on average but yield an unfavorable outcome with high probability. This circumstance pertains to scenarios involving small differences between the expected number of cases in screened versus unscreened cohorts.

Benzene↗
PubMed1998

A risk/cost analysis of alternative screening intervals for occupational tuberculosis infection.

The Centers for Disease Control and Prevention (CDC) recommends that new health care employees receive a baseline skin test for Mycobacterium tuberculosis (M. tb) infection and that testing be repeated periodically. However, CDC does not explain the quantitative basis for its suggested screening intervals. This article examines the efficacy of alternative screening intervals for workers subject to different annual rates of M. tb infection and estimates the costs. An equation is developed for the cumulative risk of tuberculosis (TB) at 12 years given a specified annual rate of infection (ARI), screening interval, and a combined proportion (p) of successful skin testing and antibiotic prophylaxis. Equations for total cost of screening and cost per disease case prevented are provided. Results assume: (a) costs of $10 per skin test and $10,000 per TB disease case; (b) p = 0.88; and (c) and acceptable cumulative TB risk of 1 per 1000. For ARIs that might be deemed low (0.2% to 0.5%) and medium (1%), CDC screening intervals of 12 months and 6-12 months, respectively, minimize the cost per disease case prevented but permit residual disease risks greater than 1 per 1000. Recommended screening intervals are (i) 6 months for low-risk employee groups and (ii) 3 months for medium- and high-risk (e.g., ARIs of > or = 5%) groups. Interval (i) limits risk to 1 per 1000 and is approximately 50% shorter than the CDC interval for a low-risk group. Interval (ii), which is 67% shorter than the CDC interval for medium-risk groups but equal to that recommended for high-risk groups, permits a risk above 1 per 1000, but is likely the shortest feasible interval.

Antibiotic Prophylaxis↗
PubMed1998

Evaluating the control of tuberculosis among healthcare workers: adherence to CDC guidelines of three urban hospitals in California.

OBJECTIVE: To evaluate adherence to components of the Centers for Disease Control and Prevention (CDC) guidelines for preventing the transmission of Mycobacterium tuberculosis in healthcare facilities. DESIGN: Multihospital study using direct observation and a standardized questionnaire. SETTING: Three urban hospitals (two county hospitals and one private community hospital) in counties in California with a high number and incidence rate of tuberculosis (TB) cases. MEASUREMENTS: The ventilation performance of treatment and TB-patient isolation rooms was assessed. Questionnaire data regarding TB control policy and procedures were obtained through interviews with the person(s) responsible for each program component; review of written TB control plans, training, and educational materials; and attendance at hospital TB control meetings and trainings. RESULTS: Twenty-eight percent of isolation rooms tested (7/25) were under positive pressure; 83% of rooms tested (20/24) had six or more nominal air changes per hour (ACH), but supply air did not mix rapidly with room air. Therefore, the nominal ACH likely overestimated the effective ACH and the subsequent protection provided. In virtually all rooms tested (26/27), air potentially containing M tuberculosis aerosol moved toward, rather than away from, likely worker locations. None of the hospitals regularly checked the performance of engineering controls. Only one hospital adhered to the CDC minimum requirements for respiratory protection. Training of healthcare workers generally was underutilized as a TB prevention measure. Hospitals did not provide comprehensive counseling regarding the need for healthcare workers to know their immune status and the risks associated with M tuberculosis infection in an immunocompromised individual. Employee representatives did not have a voice in TB-related decision making. CONCLUSIONS: Important aspects of day-to-day TB control practice did not conform to the written TB control policy. Subsequent to the identification of TB patients, healthcare workers at all three hospitals were potentially exposed to M tuberculosis aerosol due to breaches in negative-pressure isolation, the limitations of dilution ventilation, and the failure to maintain engineering controls and to implement respiratory protection controls fully. These findings lend support to the Occupational Safety and Health Administration's policy presumption that, absent clear evidence to the contrary, newly acquired healthcare-worker M tuberculosis infections are work-related.

California↗
PubMed1998

Assessing the relative importance of the components of an occupational tuberculosis control program.

Hospital-based occupational tuberculosis (TB) control programs have four basic components: rapid detection of TB disease in presenting patients; use of environmental controls, including personal respiratory protection; periodic tuberculin skin testing; and administration of prophylactic antibiotic therapy to newly infected employees. This article assesses which component is the most important in reducing TB disease risk among health care workers. A quantitative framework for estimating disease risk is developed, and two important results are described. First, the rapid identification of TB disease in presenting patients is the most important element in the overall program. Second, once TB disease has been identified, the use of highly efficient environmental controls (which include respiratory protection) becomes the most important element; these controls are especially important for procedures such as bronchoscopy and autopsy, which can aerosolize large numbers of viable Mycobacterium tuberculosis bacilli.

Humans↗
PubMed1997

A simulation model for occupational tuberculosis transmission.

A simulation model of tuberculosis (TB) transmission among hospital employees is described. A hypothetical cohort of 1000 workers was divided into low-, medium-, and high-risk groups. The number of TB patients admitted daily was treated as a Poisson random variable. A patient imparted a daily infection risk that was identical for all workers within a risk group but that varied between risk groups. In some scenarios, infected employees were assigned a daily risk of developing TB disease. If disease developed, the individual remained on the job for 3 calendar weeks and imparted a substantial infection risk to 25 close contacts. Simulations were run over 5-year intervals. Cumulative infection incidence increased over time and with more TB patients admitted. Given a scenario in which there were 600, 300, and 100 susceptibles in the low-, medium-, and high risk groups, respectively, 50 TB patients admitted annually and accounting for disease among infected employees, at 5 years there were approximately 100 primary infections (due to infection by patients), 40 secondary infections (due to infection by diseased coworkers), five primary disease cases, and two secondary disease cases. The input parameter values and simulation outcomes were reasonably consistent with the sparse information reported in the literature.

Humans↗
PubMed1996

Estimating exposure intensity in an imperfectly mixed room.

The well-mixed room model is traditionally used to predict the concentration of contaminants in indoor environments. To account for imperfect air mixing, the room supply/exhaust air rate Q is frequently multiplied by a mixing factor m, where 0 < m < or = 1, and an effective ventilation rate QE = m . Q is used in place of Q in the well-mixed room equations. However, this procedure is inappropriate because a well-mixed room model, albeit with an adjusted ventilation rate, is still used to describe an imperfectly mixed room. To illustrate the errors that may result, a two-zone model is described in which a room is conceptually divided into an upper zone and lower zone, where the latter is the zone of occupancy. Air is supplied to and exhausted from the upper zone at rate Q, and air exchanges between the two zones at rate beta. The lower zone's true ventilation rate is termed its purging flow rate QL, where QL = [beta/(beta + Q)]Q. Expressions for the steady-state contaminant levels in the two zones and for decay from the steady-state levels are presented. In a two-zone room, if one ignores imperfect air mixing and attempts to estimate QE from a decay curve, QE will usually be greater than QL. Given that contaminant is emitted in the lower zone, subsequent use of QE rather than QL to predict steady-state exposure intensity in the room will cause an underestimation error. For a room with an upper- to lower-zone volume ratio of 2:3, the underestimation error can reach 40%. If a room has a single or dominant point source of contaminant, it is recommended that the purging flow rate near the release point be determined, which permits a more accurate prediction of a worker's exposure intensity near the source. Alternative methods for determining the local purging flow rate are described. It is also shown that age-of-air analysis techniques do not provide information directly relevant to estimating exposure intensity.

Air Movements↗
PubMed1996

Refining a risk model for occupational tuberculosis transmission.

The traditional Poisson probability model for airborne Mycobacterium tuberculosis (M.tb) infection, also termed the Wells-Riley equation, can be modified to account for a health care worker's use of respiratory protection. It was previously shown that the beta distribution on the interval [0,1] is a good descriptor of respirator penetration values experienced by an individual worker from wearing to wearing, and of average respirator penetration values experienced by different workers. Based on the premise that the gamma distribution can reasonably describe the time-varying M.tb aerosol exposure levels experienced by health care workers, analytical solutions are presented for an individual worker's cumulative risk of infection, and for the worker population mean cumulative risk of infection, with and without use of respiratory protection. The gamma distribution is shown to be similar to the lognormal in describing right-skewed distributions of aerosol exposure concentrations on the interval [0, infinity).

Humans↗
PubMed1996

An analytical framework for relating dose, risk, and incidence: an application to occupational tuberculosis infection.

An adverse health impact is often treated as a binary variable (response vs. no response), in which case the risk of response is defined as a monotonically increasing function R of the dose received D. For a population of size N, specifying the forms of R(D) and of the probability density function (pdf) for D allows determination of the pdf for risk, and computation of the mean and variance of the distribution of incidence, where the latter parameters are denoted E[SN] and Var[SN], respectively. The distribution of SN describes uncertainty in the future incidence value. Given variability in dose (and risk) among population members, the distribution of incidence is Poisson-binomial. However, depending on the value of E[SN], the distribution of incidence is adequately approximated by a Poisson distribution with parameter mu = E[SN], or by a normal distribution with mean and variance equal to E[SN] and Var[SN]. The general analytical framework is applied to occupational infection by Mycobacterium tuberculosis (M. tb). Tuberculosis is transmitted by inhalation of 1-5 microns particles carrying viable M. tb bacilli. Infection risk has traditionally been modeled by the expression: R(D) = 1 - exp(-D), where D is the expected number of bacilli that deposit in the pulmonary region. This model assumes that the infectious dose is one bacillus. The beta pdf and the gamma pdf are shown to be reasonable and especially convenient forms for modeling the distribution of the expected cumulative dose across a large healthcare worker cohort. Use of the the analytical framework is illustrated by estimating the efficacy of different respiratory protective devices in reducing healthcare worker infection risk.

Cohort Studies↗
PubMed1995

Respiratory protection and the risk of Mycobacterium tuberculosis infection.

Tuberculosis (TB) can be transmitted to susceptible healthcare workers via inhalation of droplet nuclei carrying viable Mycobacterium tuberculosis bacilli. Several types of respiratory protective devices are compared with respect to efficacy against droplet nuclei penetration: surgical masks, disposable dust/mist particulate respirators (PRs), elastomeric halfmask respirators with high-efficiency (HEPA) filters, and powered air-purifying respirators (PAPRs) with elastomeric halfmask facepieces and HEPA filters. It is estimated that these devices permit, respectively, 42%, 5.7%, 2%, and 0.39% penetration of droplet nuclei into the facepiece. More limited data for the disposable HEPA filtering-facepiece respirator suggest that it would allow droplet nuclei penetration of 3% or less, similar to the value estimated for the elastomeric halfmask HEPA filter respirator. Because a respirator wearer's cumulative infection risk depends on the extent of droplet nuclei penetration, the cumulative risk will differ, given use of these different respirators. Hypothetical but realistic "low-exposure" and "high-exposure" scenarios are posed that involve, respectively, a 1.6% and a 6.4% annual risk of infection for healthcare workers. For the low-exposure scenario, the 10-year cumulative risks given no respirators versus surgical masks versus disposable dust/mist PRs versus elastomeric halfmask HEPA filter respirators versus HEPA filter PAPRs are, respectively, 15%, 6.7%, 0.94%, 0.33%, and .064%. For the high-exposure scenario, the 10-year cumulative risks for no respirator use versus use of the same four types of respirators are, respectively, 48%, 24%, 3.7%, 1.3%, and 0.26%. The use of disposable HEPA filtering-facepiece respirator should permit cumulative risks close to those estimated for the elastomeric halfmask HEPA filter respirator. It is concluded that when an infectious TB patient undergoes a procedure that generates respiratory aerosols, and when droplet nuclei source control is inadequate, healthcare workers attending the patient may need to wear highly protective respirators, such as HEPA filter PAPRs.

Aerosols↗
PubMed1994

Modeling respirator penetration values with the beta distribution: an application to occupational tuberculosis transmission.

The lognormal distribution typically is used to model variability in respiratory penetration values. The lognormal model is a good descriptor where the average penetration value is low, but may be a poor descriptor where the average penetration value is high because a significant fraction of penetration values could be predicted to exceed unity. In this regard, the beta distribution offers greater flexibility than the lognormal in modeling penetration values over the physically plausible interval [0,1]. The beta distribution also is shown to be mathematically convenient for describing the risk of airborne transmission of tuberculosis among a respirator-wearing population. Infection can occur following inhalation of respirable particles, termed droplet nuclei, carrying viable Mycobacterium tuberculosis bacilli. Based on the expected number of infectious doses inhaled, the Poisson probability model traditionally is used to predict an individual's risk of infection. This article synthesizes the beta distribution, as applied to average penetration values among a respirator-wearing population, and the Poisson distribution, as applied to an individual's infection risk, to describe the population risk of M. tuberculosis infection.

Humans↗
PubMed1993

A task-based statistical model of a worker's exposure distribution: Part I--Description of the model.

The authors present a task-based model to describe a single worker's exposures to a single airborne chemical toxicant. The model accounts for variability in short-term time-weighted average (TWA) exposure values within a task, and for variability in arithmetic mean exposure levels between tasks. For a given workday, the 8-hour TWA value is equated with the sample mean of an appropriate number of short-term TWAs arising from stratified random sampling of short-term TWAs with proportional allocation by task. The model accounts for autocorrelation in the stochastic process that generates successive short-term TWA values. Due to the underlying random process, a given type of workday with regard to the set of task times has an associated distribution of 8-hour TWA values; the variance of this distribution increases with increasing autocorrelation in the time series of short-term TWAs. A worker's total distribution of 8-hour TWAs is a mixture of these day-specific distributions weighted by the relative frequency of each type of workday; the variance of the total distribution increases with greater day-to-day variability in the array of task times.

Air Pollutants, Occupational↗
PubMed1993

A task-based statistical model of a worker's exposure distribution: Part II--Application to sampling strategy.

A task-based statistical model of a worker's exposure distribution for an airborne chemical toxicant is applied to estimating the long-term average exposure level, mu. The precision in estimation is represented by the variance of the sample estimator, denoted by Var[mu]. A traditional sampling strategy consists of integratively measuring the 8-hr time-weighted average exposure level on randomly selected workdays, and computing the sample mean; this strategy is termed "simple one-stage cluster sampling," where each 8-hr workday is a cluster of thirty-two 15-min periods. Three alternative strategies involving measurements of 15-min TWAs are examined: simple random sampling of 15-min periods, and stratified random sampling of 15-min periods with proportional allocation by task, and with optimum allocation by task. All four survey designs provide unbiased estimates of mu. However, for a fixed cost, the stratified sampling designs may provide a lower Var[mu] than simple one-stage cluster sampling for less work time monitored.

Air Pollutants, Occupational↗
PubMed1992

A probability model for assessing exposure among respirator wearers: Part I--Description of the model.

The basic respirator equation states that the contaminant level inside a respirator (CI) is the product of the contaminant level outside the respirator (CO) and the decimal fraction penetration (P). On the basis of this relation, the authors present a probability model for the lognormal total distribution of CI levels among a respirator-wearing population; the model accounts for between-wearer and within-wearer variability in both CO levels and P values. The assumptions underlying the model are shown to be consistent with current knowledge about the variability in CO levels and P values. The model provides the basis for assessing the probability of overexposure to acute toxicants and to chronic toxicants among a respirator-wearing population.

Air Pollutants, Occupational↗