PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “Demographic modelling”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 397 records · Page 22Linked to original sources

Herbal medicine use during pregnancy in a group of Australian women.

BACKGROUND: There are limited data on the extent of women's use of herbal medicines during pregnancy, despite the fact that knowledge of the potential benefits or harms of many of these products is sparse, particularly with respect to their use in pregnancy. We aimed to measure the prevalence of herbal medicine use in a group of pregnant women attending a public tertiary maternity hospital in Melbourne, Australia. Secondary aims were to explore why women took the herbal medicine, where they received advice, what form the supplements took and if they perceived the supplements to be helpful. METHODS: Consecutive pregnant women were approached in the antenatal clinic and the birth centre at around 36-38 weeks gestation. A questionnaire was developed and self-administered in English, as well as being translated into the four most common languages of women attending the hospital: Cantonese, Vietnamese, Turkish and Arabic. Back translation into English was undertaken by different professional translators to verify accuracy of both words and concepts. Data collected included demographic information, model of pregnancy care and herbal supplement use. Descriptive statistics were used initially, with stratified and regression analysis to compare sub-groups. RESULTS: Of 705 eligible women, 588 (83%) agreed to participate. Of these, 88 (15%) completed the questionnaire in a language other than English. Thirty-six percent of women took at least one herbal supplement during the current pregnancy. The most common supplements taken were raspberry leaf (14%), ginger (12%) and chamomile (11%). Women were more likely to take herbal supplements if they were older, tertiary educated, English speaking, non-smokers and primiparous. CONCLUSION: Use of herbal supplements in pregnancy is likely to be relatively high and it is important to ascertain what supplements (if any) women are taking. Pregnancy care providers should be aware of the common herbal supplements used by women, and of the evidence regarding potential benefits or harm.

Journal Article↗

Estimating and projecting HIV prevalence and AIDS deaths in Tanzania using antenatal surveillance data.

BACKGROUND: The Estimations and Projections Package (EPP 2005) for HIV/AIDS estimates and projects HIV prevalence, number of people living with HIV and new HIV infections and AIDS cases using antenatal clinic (ANC) surveillance data. The prevalence projection produced by EPP can be transferred to SPECTRUM, a demographic projection model, to calculate the number of AIDS deaths. This paper presents estimates and projections of HIV prevalence, new cases of HIV infections and AIDS deaths in Tanzania between 2001 and 2010 using the EPP 2005 and SPECTRUM soft-wares on ANC data. METHODS: For this study we used; the 1985-2004 ANC data set, the 2005 UN population estimates for urban and rural adults, which is based on the 2002 population census, and results of the 2003 Tanzania HIV Indicator Survey. The ANC surveillance sites were categorized into urban and rural areas on the basis of the standard national definitions of urban and rural areas, which led to 40 urban and 35 rural clinic sites. The rural and urban epidemics were run independently by fitting the model to all data and on level fits. RESULTS: The national HIV prevalence increased from 0% in 1981 to a peak of 8.1% in 1995, and gradually decreased to 6.5% in 2004 which stabilized until 2010. The urban HIV epidemic increased from 0% in 1981 peaking at 12.6% in 1992 and leveled to between 10.9% and 11.8% from 2003 to 2010. The rural epidemic peaked in 1995 at 7.0% and gradually declined to 5.2% in 2004, and then stabilized at between 5.1% and 5.3% from 2005 to 2010. New infections are projected to rise steadily, resulting in 250,000 new cases in 2010. Deaths due to AIDS started in 1985 and rose steadily to reach 120,000 deaths in 2010, with more females dying than men. CONCLUSION: The fact that the number of new infections is projected to increase steadily to reach 250,000 per year in 2010 calls for more concerted efforts to combat the spread of HIV infection particularly in the rural areas where the infrastructure needed for prevention programmes such as counseling and testing, condom accessibility and AIDS information is less developed.

Acquired Immunodeficiency Syndrome↗

Why do those using illicit drugs have higher rates of sexually transmitted infection?

The study was designed to assess the association between drug use and gonorrhoea in a UK setting and determine whether any differences identified could be explained by variations in sexual behaviour. A case control analysis was undertaken in a population of men and women presenting to an inner city sexually transmitted diseases clinic. The results were analysed using a multivariate model incorporating demographic and behavioural factors potentially associated with acquiring gonorrhoea. Infection with gonorrhoea was found to be associated with illicit drug use (odds ratio 1.8, 1.2-2.8) and the association became non-significant after controlling for sexual behaviour factors. Moderate alcohol use (<5 units/week) was associated with acquiring gonorrhoea but heavier use was not. Patients who used illicit drugs had more casual partners and more foreign partners than those with no history of drug use, but an increased numbers of foreign partners were not associated with a higher prevalence of gonorrhoea. It was concluded that drug use is associated with gonorrhoea in a UK setting. Specific sexual behaviours reported by drug users may increase their risk of gonorrhoea and provide potential targets for behavioural interventions.

Adolescent↗

The social capital:health relationship in two disadvantaged neighbourhoods.

OBJECTIVES: Research into the social determinants of health inequalities is increasingly focusing on macro-level forces affecting individuals and communities. The concept of social capital has been at the centre of this research as a potential explanatory framework for understanding these inequalities. The aim of this study was to identify the components that define social capital and its relationship to self-reported health in two neighbourhoods known to be disadvantaged in south-western Sydney. METHODS: This study uses data from cross-sectional household (door-knock) surveys originally developed as evaluation tools for neighbourhood based interventions. Secondary analyses including factor analysis and multiple regression analysis were used to provide empirical evidence of the components defining social capital and how these, as a concept, were associated with self-reported health. RESULTS: The study revealed six common social capital components in each sample and an additional component in one neighbourhood. These included neighbourhood attachment, support networks, feelings of trust and reciprocity, local engagement, personal attachment to the area, feelings about safety and proactivity in the social context. The social capital model incorporating demographic and socio-economic characteristics explained 23.4% of health variance in one neighbourhood, and 19.3% in the other. Examining the social capital:health relationship revealed that with the exception of feelings of trust and reciprocity, no other social capital component made significant contributions to explaining health variance and that macro-level factors such as housing conditions and employment opportunities emerged as key explanatory factors. CONCLUSION: If interventions are to use social capital as a way of addressing health inequalities, these need to look closely at the role of trust for improving health outcomes of deprived populations as well as ensuring access to resources and infrastructure.

Adolescent↗

Welfare to work: the effect of a health-care program in child-care centers.

OBJECTIVE: Welfare reform has increased pressure on welfare recipients to enter the labor force. When they become employed, former recipients often do not have paid leave that can be used to care for their young children when they are sick. We wished to determine whether an on-site health-care program in child-care centers serving low-income families affected the amount of time parents took off of work to care for mildly ill children. METHODS: We surveyed parents in 6 child-care centers with an on-site health-care program and in 2 comparison centers without such a program. To analyze survey results, a regression model including demographic and other variables was used to determine which, if any, variables were associated with time taken by parents from work to care for sick children. RESULTS: Analyzing the variables of employer leave policy, poverty level, age of child, and enrollment in the health-care program, only the variable of health-care program enrollment was associated with taking less time from work to care for sick children. CONCLUSION: Health-care programs in child-care settings can help parents meet the health needs of their children while reducing absenteeism from work, thereby contributing to job stability.

Child↗

Patient-reported utilization patterns of fentanyl transdermal system and oxycodone hydrochloride controlled-release among patients with chronic nonmalignant pain.

BACKGROUND: Although use of long-acting opioid analgesics has increased for chronic nonmalignant pain management, little is known about patient-reported utilization patterns. OBJECTIVE: To assess patient-reported utilization patterns of fentanyl transdermal system and oxycodone hydrochloride (HCl) controlled-release among patients with chronic nonmalignant pain and to compare these patterns to standard dose administration guidelines recommended in the manufacturers. prescribing information (PI). METHODS: Cross-sectional, observational, multicenter study of English-speaking patients who were seeking chronic nonmalignant pain management from 6 outpatient pain clinics. The inclusion criteria for the study were (1) diagnosis of chronic nonmalignant pain, (2) prescription for and current use of either transdermal fentanyl or oxycodone HCl controlled-release, and (3) duration of use for either transdermal fentanyl or oxycodone HCl controlled-release of at least 6 weeks. Patients completed either an oxycodone HCl controlled-release or transdermal fentanyl utilization questionnaire. A conversion table was used to standardize opioid analgesic doses from transdermal fentanyl or oxycodone HCl controlled-release to daily oral morphine equivalents. The principal outcome measures were the average interval between oxycodone HCl controlled-release administrations, the number of days the current transdermal fentanyl patch would be worn, and the percentage of oxycodone HCl controlled-release and transdermal fentanyl patients whose administration frequency exceeded the standard recommendation in the manufacturer.s PI (every 12 hours for oxycodone HCl controlled-release or every 72 hours for transdermal fentanyl). Other outcome measures included the number of oxycodone HCl controlled-release tablets per administration, the daily dose of long-acting opioid, the duration of adequate pain relief, and the difference in daily oral morphine equivalents between transdermal fentanyl and oxycodone HCl controlled-release patients, after adjusting in a multivariate regression model for demographic and clinical characteristics. RESULTS: A total of 690 patients were enrolled in this study; 437 (63.4%) received oxycodone HCl controlled-release and 253 (36.6%) received transdermal fentanyl. Oxycodone HCl controlled-release patients reported taking a median of 1 tablet 3 times per day or a median of 3 tablets per day. A mean of 1.6 tablets per administration and 4.6 tablets per day were taken. The average interval between administrations of oxycodone HCl controlled-release was 7.8 hours, and the median daily dose was 80.0 mg (mean 155.6 mg). Among oxycodone HCl controlled-release patients, 17.5% had an average interval between administrations of 12 or more hours, whereas 1.9% reported the duration of pain relief as 12 or more hours. Transdermal fentanyl patients reported wearing the patch, on average, for 2.5 days (median 2.5),and 41.2% reported wearing the patch for at least 3 days, whereas 14.1% reported the duration of pain relief as at least 3 days. The median daily dosage strength of transdermal fentanyl was 75.0 mcg/hour. In the multivariate regression analysis, oxycodone HCl controlled-release patients had, on average, roughly 22 mg additional oral morphine equivalents per day relative to transdermal fentanyl patients (not statistically significant); the probability that oxycodone HCl controlled-release patients had higher oral morphine equivalents was 82.6%, which suggests a trend toward higher oral morphine equivalents per day in the oxycodone HCl controlled-release group. CONCLUSION: Transdermal fentanyl and oxycodone HCl controlled-release both appear to be used by patients in a manner that is inconsistent with the standard recommendation in the manufacturers' PI;however, the difference between patient-reported utilization and the PI recommendation is more pronounced with oxycodone HCl controlled-release.

Administration, Cutaneous↗

Higher costs and therapeutic factors associated with adherence to NCQA HEDIS antidepressant medication management measures: analysis of administrative claims.

OBJECTIVE: To determine if the type of antidepressant drug is related to adherence to National Committee for Quality Assurance (NCQA) Antidepressant Medication Management (AMM) quality measures and to assess the 6-month health care costs among newly diagnosed depressed patients. METHODS: The MarketScan Commercial Claims and Encounter database for medical and pharmacy claims from January 2001 to September 2004 was used to assess adherence to the 3 AMM quality-of-care measures. AMM measures include (a) acute phase, the percentage of eligible members who remained on antidepressant medication continuously for 3 months after the initial diagnosis as determined by at least 84 days supply of antidepressant drugs during the first 114 days following receipt of the index antidepressant; (b) continuation phase, the percentage of eligible members who remained on antidepressant medication continuously for the 6 months after the initial diagnosis as determined by at least 180 days supply of antidepressants during the first 214 days following receipt of the index antidepressant; and (c) practitioner contacts, the percentage of members who received at least 3 follow-up office visits or telephone contacts with health care providers, including at least 1 contact with a practitioner licensed to prescribe (may not necessarily be the prescriber of the antidepressant). A fourth measure, overall adherence, was added, if all 3 AMM measures were met. Multivariate regression models determined demographic, clinical (such as receipt of mental health specialty care, the Charlson Comorbidity Index score, and co-occurring bipolar or schizophrenia), and therapy-related factors associated with outcomes of adherence and costs (paid amounts for insurance-reimbursable health care services for inpatient admissions, emergency department services, outpatient services, and outpatient prescription drugs). Health care expenditures (both total and mental-health-specific costs) were measured for each patient for 6 months following the date of service for the index antidepressant. RESULTS: A total of 60,386 adult patients (10.7%) of 562,898 patients with a depression diagnosis met NCQA inclusion criteria in the AMM Technical Specifications (e.g., aged 18 years or older, newly diagnosed with depression and initiating antidepressant therapy, 365 days of continuous enrollment; patients were excluded if there were missing data on dose or quantity of index drug in pharmacy claims or initiated therapy on 2 or more antidepressants as the index medication, exclusion criteria not in the AMM Technical Specifications). Only 19% of patients achieved overall adherence. Rates for the 3 AMM measures were 39% for practitioner contacts, 65% for acute phase, and 44% for continuation phase. Receipt of mental health specialty care was the only factor that was positively associated with greater adherence on all 4 measures (overall measure: odds ratio [OR]=3.895, 95% confidence interval [CI], 3.72-4.07; acute OR=1.38, 95% CI, 1.33-1.43; continuation OR=1.46, 95% CI, 1.41-1.51; contacts OR=5.83, 95% CI, 5.62-6.06). Most patients were initiated on selective serotonin reuptake inhibitors (SSRIs, 69.5%), followed by venlafaxine (21.4%), tricyclic antidepressants (TCAs, 21.4%), bupropion (11.0%), and other antidepressants (e.g., mirtazapine, nefazadone, trazadone; 7.2%). Before adjustment for confounding factors, patients initiated on venlafaxine, TCAs, or other antidepressants had higher rates of adherence on the overall performance measure versus initiators on SSRIs, but the absolute differences were relatively small: 21.4% for venlafaxine and TCAs and 23.1% for other antidepressants versus 18.5% for SSRIs (P <0.001). Patients initiated on venlafaxine, TCAs, or other antidepressants were also more likely to receive care from a mental health specialist, 16.8%, 15.0%, and 54.8%, respectively, compared with SSRIs (13.0%, all P <0.001). Regression analysis showed that only venlafaxine had a higher OR (1.13; 95% CI, 1.05-1.22) compared with SSRIs for adherence on the overall measure. Initiating dose level was in the target range for 70.0% of all patients (24.9% were below target dose and 5.2% above target dose), and adherent patients on all 3 AMM measures were less likely than nonadherent patients (70.4% vs. 68.4%, P <0.001) to be initiated in the target dose range. After multivariate adjustment, the initiating dose (target vs. high) was a significant factor in explaining adherence to the overall measure (OR=1.26; 95% CI, 1.16- 1.37). Adherent patients had 6-month median unadjusted total health care expenses that were nearly 2 times higher compared with nonadherent patients ($5,169 vs. $2,734) and mental health expenditures that were nearly 3 times higher ($1,922 vs. $677). After adjustment, adherent patients compared with nonadherent patients incurred an additional $644 in mental health expenditures and $806 in overall health care expenditures in the 6 months following initiation of antidepressant therapy. CONCLUSIONS: Only 19% of depressed patients initiated on antidepressants met all 3 criteria set forth in the NCQA Health Plan Employer Data and Information Set (HEDIS) AMM quality-of-care performance measures. Receipt of mental health specialty care was the single factor most strongly associated with quality treatment by these measures. Type and dosage level of initial antidepressant was associated with adherence to the NCQA HEDIS AMM measures, but the absolute difference in rates of adherence were relatively small among types of antidepressants. Costs were higher for guideline-adherent individuals in the 6 months following treatment initiation. These analyses were limited to administrative claims that lack indicators of depression disease severity.

Adult↗

The law of attrition.

In an ongoing effort of this Journal to develop and further the theories, models, and best practices around eHealth research, this paper argues for the need for a "science of attrition", that is, a need to develop models for discontinuation of eHealth applications and the related phenomenon of participants dropping out of eHealth trials. What I call "law of attrition" here is the observation that in any eHealth trial a substantial proportion of users drop out before completion or stop using the application. This feature of eHealth trials is a distinct characteristic compared to, for example, drug trials. The traditional clinical trial and evidence-based medicine paradigm stipulates that high dropout rates make trials less believable. Consequently eHealth researchers tend to gloss over high dropout rates, or not to publish their study results at all, as they see their studies as failures. However, for many eHealth trials, in particular those conducted on the Internet and in particular with self-help applications, high dropout rates may be a natural and typical feature. Usage metrics and determinants of attrition should be highlighted, measured, analyzed, and discussed. This also includes analyzing and reporting the characteristics of the subpopulation for which the application eventually "works", ie, those who stay in the trial and use it. For the question of what works and what does not, such attrition measures are as important to report as pure efficacy measures from intention-to-treat (ITT) analyses. In cases of high dropout rates efficacy measures underestimate the impact of an application on a population which continues to use it. Methods of analyzing attrition curves can be drawn from survival analysis methods, eg, the Kaplan-Meier analysis and proportional hazards regression analysis (Cox model). Measures to be reported include the relative risk of dropping out or of stopping the use of an application, as well as a "usage half-life", and prediction models reporting demographic usage discontinuation in a population. Differential dropout or usage rates between two interventions could be a standard metric for the "usability efficacy" of a system. A "run-in and withdrawal" trial design is suggested as a methodological innovation for Internet-based trials with a high number of initial dropouts/nonusers and a stable group of hardcore users.

Delivery of Health Care↗

Spatio-temporal variations in population growth in India since 1901.

"On the basis of census data we analyse population growth since 1901 first for India as a whole, secondly on State level. The spatio-temporal patterns suggest a process of innovation and diffusion with regard to the spatial change of natural increase. The southern States cover more stages of the model of demographic transition than the northern States. Explanations about these spatial differentials come for example [from] sociocultural differences between north and south determining two demographic regions according to Satpura Range." (SUMMARY IN GER AND RUS)

Asia↗

Domestic production vs international immigration: Options for the US physician workforce.

OBJECTIVE: To determine alternate combinations for reductions in US medical school graduates (USMGs), international medical graduate (IMG) immigration, and graduate medical education (GME) residencies, based on future physician supply targets. DESIGN: A demographic projection model of the physician supply was constructed and calibrated to fit observed American Medical Association Physician Masterfile data and current supply forecasts. Total annual input to GME was backcast from given future supply targets, adjusting for the portion of IMGs in GME who do not enter the US workforce. MAIN OUTCOME MEASURES: The annual number of new physicians added to supply from domestic or international sources needed to reach future physician-to-population ratio targets. RESULTS: Because of the low rate of attrition from the physician supply, it takes up to 50 years for workforce policy to effectively stabilize the physician-to-population ratio at a target level. All target ratios considered here would require immediate reductions in the total number of GME positions. These reductions must be followed by gradual annual increases to account for population growth. The size of USMG and IMG reductions are interrelated and depend critically on the percentage of IMG trainees who remain to practice in the United States. CONCLUSIONS: Reductions in future physician supply can come from either the IMG or USMG component of physician production, or both. The model developed here allows the estimation of multiple combinations of both GME components.

Demography↗

[Modeling labor resources using demoeconomic models of the BACHUE (DEMB) type in Poland].

The author analyzes demographic and economic models developed by Poland's Institute of Statistics and Demography. "The economic submodel describes the Polish national economy as divided into 11 sectors and branches of the production sphere and 7 sectors of the non-production sphere. The demographic submodel covers 5 blocks of equations." The author notes an interdependence among the variables studied and relates this to socioeconomic and demographic development factors. (SUMMARY IN ENG AND RUS)

Demography↗

Patch aging and the S-Allee effect: breeding system effects on the demographic response of plants to habitat fragmentation.

We used empirical and modeling approaches to examine effects of plant breeding systems on demographic responses to habitat fragmentation. Empirically, we investigated effects of local flowering plant density on pollination and of population size on mate availability in a common, self-incompatible purple coneflower, Echinacea angustifolia, growing in fragmented prairie habitat. Pollination and recruitment increased with weighted local density around individual flowering plants. This positive density dependence is an Allee effect. In addition, mean mate compatibility between pairs of plants increased with population size. Based on this empirical study, we developed an individual-based, spatially explicit demographic model that incorporates autosomal loci and an S locus. We simulated habitat fragmentation in populations identical except for their breeding system, self-incompatible (SI) or self-compatible (SC). Both populations suffered reduced reproduction in small patches because of scarcity of plants within pollination distance (potential mates) and inbreeding depression. But SI species experienced an additional, genetic contribution to the Allee effect (S-Allee effect) caused by allele loss at the S locus, which reduces mate availability, thereby decreasing reproduction. The strength of the S-Allee effect increases through time (i.e., patches age) because random genetic drift reduces S-allele richness. We investigate how patch aging influences extinction and discuss how the S-Allee effect influences communities in fragmented habitat.

Breeding↗

Forecasting the need for physicians in the United States: the Health Resources and Services Administration's physician requirements model.

OBJECTIVE: The Health Resources and Services Administration's Bureau of Health Professions developed a demographic utilization-based model of physician specialty requirements to explore the consequences of a broad range of scenarios pertaining to the nation's health care delivery system on need for physicians. DATA SOURCE/STUDY SETTING: The model uses selected data primarily from the National Center for Health Statistics, the American Medical Association, and the U.S. Bureau of Census. Forecasts are national estimates. STUDY DESIGN: Current (1989) utilization rates for ambulatory and inpatient medical specialty services were obtained for the population according to age, gender, race/ethnicity, and insurance status. These rates are used to estimate specialty-specific total service utilization expressed in patient care minutes for future populations and converted to physician requirements by applying per-physician productivity estimates. DATA COLLECTION/EXTRACTION METHODS: Secondary data were analyzed and put into matrixes for use in the mainframe computer-based model. Several missing data points, e.g., for HMO-enrolled populations, were extrapolated from available data by the project's contractor. PRINCIPAL FINDINGS: The authors contend that the Bureau's demographic utilization model represents improvements over other data-driven methodologies that rely on staffing ratios and similar supply-determined bases for estimating requirements. The model's distinct utility rests in offering national-level physician specialty requirements forecasts.

Adolescent↗

Differences in cervical cancer mortality among black and white women.

OBJECTIVE: To determine whether stage of disease and treatment patterns account for mortality differences between black and white women with cervical cancer. METHODS: Using data obtained from the Surveillance, Epidemiology, and End Results (SEER) Program for 1988-1994, we determined the associations between race and stage, and race and treatment. Racial differences in survival for up to 7 years of follow-up were adjusted for age, marital status, SEER location, International Federation of Gynecology and Obstetrics (FIGO) stage of disease, lymph node status, grade, histology, and treatment. RESULTS: Cumulative mortality was 36% (366 deaths in 1029 women) for black women and 24% (1215 deaths in 5021 women) for white women; unadjusted hazard ratio was 1.60 (95% confidence interval [CI] 1.43, 1.80). Black women were more likely to present with advanced disease than white women (43.8% compared with 34.8%). In a model adjusting for demographics and FIGO stage, the hazard ratio for black women compared with white women decreased to 1.35 (95% CI 1.19, 1.54). Treatment varied by race, with black women receiving surgery less often (33.5% compared with 48.2%, respectively) and radiation therapy more often (35.3% and 25.2%, respectively) than white women. In a comprehensive model including demographic factors, FIGO stage, other tumor characteristics, and treatment, the adjusted hazard ratio for mortality remained high for black women at 1.30 (95% CI 1.14, 1.48). CONCLUSION: Race remains an independent predictor of cervical cancer survival after accounting for age, stage of disease, treatment patterns, and other factors. Future studies should assess racial differences in clinical severity of disease, comorbidity, and socioeconomic status.

Adult↗

A mathematical model of growth of population of fish in the larval stage: density-dependence effects.

A mathematical model for the growth of a population of fish in the larval stage is proposed. The emphasis is put on the first part of the larval stage, when the larvae are still passive. It is assumed that during this stage, the larvae move with the phytoplankton on which they feed and share their food equally, leading to ratio-dependence. The other stages of the life cycle are modeled using simple demographic mechanisms. A distinguishing feature of the model is that the exit from the early larval stage as well as from the active one is determined in terms of a threshold to be reached by the larvae. Simplifying the model further on, the whole dynamics is reduced to a two dimensional system of state-dependent delay equations. The model is put in perspective with some of the main hypotheses proposed in the literature as an explanation to the massive destruction which occurs between the egg stage and the adult stage.

Animals↗

A model of the spread of HIV infection and the demographic impact of AIDS.

The objective of the computer simulation model described here is to project, for periods up to one or more decades, the annual incidence and prevalence of HIV infection and AIDS in a population with given epidemiological, behavioural and demorgraphic characteristics. In addition, the epidemic's impact on a range of demographic variables is calculated. The epidemiological components of the model use a compartmental approach and they are described with sets of linear differential equations. The demographic framework in which the epidemiological components are integrated, is based on a standard cohort component method of population projection. The simulated population is stratified by age, gender, sexual behaviour, marital status and infection/disease status. The concluding section provides an illustrative application of the model to a Central African population. In this hypothetical simulation covering the period from 1975 to 2000, HIV prevalence in the adult population rises from 0 to 21 per cent. By the end of the projection period mortality is about double the level that would have prevailed in the absence of the epidemic, but, owing to the very high birth rates that prevail in most of Africa, the growth rate of the population remains substantially positive.

Acquired Immunodeficiency Syndrome↗

Modeling population pharmacokinetics of lidocaine: should cardiac output be included as a patient factor?

BACKGROUND: Inclusion of cardiac output and other physiologic parameters, in addition to or instead of, demographic variables might improve the population pharmacokinetic modeling of lidocaine. METHODS: Thirty-one patients were included in a population pharmacokinetic study of lidocaine. After bolus injection of lidocaine (1 mg/kg), 22 or 10 blood samples per patient were taken from a radial artery. During the experiment, cardiac output was measured using a thoracic electrical bioimpedance method. The following four population pharmacokinetic models were constructed and their performances investigated: a model with no covariates, a model with cardiac output as covariate, a model with demographic covariates, and a model with both cardiac output and demographic characteristics as covariates. Model discrimination was performed with the likelihood ratio test. RESULTS: Inclusion of cardiac output resulted in a significant improvement of the pharmacokinetic model, but inclusion of demographic covariates was even better. However, the best model was obtained by inclusion of both demographic covariates and cardiac output in the pharmacokinetic model. CONCLUSIONS: When population pharmacokinetic models are used for individualization of dosing schedules, physiologic covariates, e.g., cardiac output, can improve their ability to predict the individual kinetics.

Adult↗