bluuebunny/crossref_metadata_2025_split huggingface dataset:
Simultaneous back‐projection of AIDS incidence data for two or more groups
Authors: Marschner Ian C. , Newstead Stuart V. , Becker Niels G. 
Published: April 2007

AbstractBack‐projection of AIDS incidence data is useful for estimating characteristics of the HIV epidemic curve and forms a basis for projections of the AIDS epidemic curve. Its application to subgroups of the population is limited by its imprecision for groups with a small number of cases. Back‐projection can be made more precise by pooling data from different groups and linking their HIV infection intensities by a model. Here we propose a method based on proportional infection intensities and study its performance with simulations and applications to AIDS in different States of Australia and haemophiliacs in the U.S.A. This method of simultaneous back‐projection is shown to reduce substantially the width of confidence intervals for HIV infection intensities and for total numbers infected.
Estimates of disease incidence in women based on antenatal or neonatal seroprevalence data: HIV in new york city
Authors: Ades A. E. , Medley G. F. 
Published: April 2007

AbstractPiecewise constant incidence models were developed to estimate the force of infection in women from age‐and time‐specific antenatal or neonatal seroprevalence data. Differential inclusion of infected women in sero‐surveys compared to uninfected women was taken into account, with respect to both changes in inclusion rate following infection, and changes in relative inclusion rate over calendar time. These models were applied to anonymous HIV seroprevalence data collected from neonates born to black and Hispanic women in New York City 1988‐1992, with incidence and fertility parameters estimated by maximum likelihood. Estimates of inclusion rate parameters accorded well with what is known about the natural history of HIV. The data could not distinguish between additive and multiplicative combination of the effects of age and time on incidence. Incidence was strongly dependent on age with the highest incidence in women aged 20‐34 years. There was strong evidence that incidence had been falling in Hispanic women since 1982‐1984. The results illustrate the extent to which trends in incidence over time may be confounded by changes in the relative inclusion rate of infected and uninfected women.
Screening tests: Can we get more by doing less?
Authors: Tu Xin M. , Litvak Eugene , Pagano Marcello 
Published: April 2007

AbstractEstimating the prevalence of the human immunodeficiency virus (HIV) in a group is challenging; this is especially so when the prevalence is small. One reason is that the presence of measurement errors resulting from the limited precision of tests makes estimation, using traditional methods, impossible in some screening situations. Measurement error is real, ignoring it leads to severe bias, and inference about the prevalence becomes unsatisfactory. Indeed, in a low prevalence situation the expected number of false positives is very high, often even higher than the number of true positives. The second reason is that in the low prevalence areas the large sample is needed in order to obtain non‐zero estimate. This is usually a very costly, and often unrealistic, solution. This paper considers the advantages and disadvantages of pooled testing as an alternative solution to this problem. We show that by pooling sera samples we not only achieve a cost saving but also, which is counterintuitive, an increase in the estimation accuracy. We also discuss the statistical issues associated with the resulting estimator.
Seasonal and other short‐term influences on United States AIDS incidence
Authors: Bacchetti Peter 
Published: April 2007

AbstractThis paper models monthly AIDS diagnosis counts in terms of smooth secular trend, calendar month effects, and the number of workdays per month. A parameterization of month effects allows separation of true seasonal effects from a linear trend over the calendar year and an arbitrary June effect. There is strong evidence for seasonal patterns, other calendar month effects, and workday effects. Examination of subgroups defined by reporting delay, initial diagnosis, risk group, and region shows evidence for seasonal patterns in some diagnosis groups, for effects due to imputed diagnosis dates, and for effects due to patients' choices of when to seek diagnosis.
Prediction and validation in the public health modelling of HIV/AIDS
Authors: Bailey Norman T. J. 
Published: April 2007

AbstractMathematical models are an integral part of long‐range scientific research and are broadly equivalent to the hypotheses to be tested. Validation consists: (1) in checking whether theoretical expectations are sufficiently close to observed values; and (2) in showing that theoretical constructions that pass the first test can also make verifiable predictions of future events. When modelling is used in operational situations to assist practical decision‐making, as in the public health surveillance, prediction and control of infectious diseases, especially HIV/AIDS, it is easy to use the first criterion, but not so simple to implement the second. The paper discusses various methods of improving the validation of a specific classical compartmental model of HIV/AIDS geared to good serial public health data on AIDS incidence. These methods include model fitting to existing data, cross‐checking findings with independent research results, general circumstantial support, and the possibility in special situations of the quasi‐prediction of present or recent data using models fitted only to sufficiently distant past data.
Dependent HIV incidences in back‐projection of AIDS incidence data
Authors: Becker Niels G. , Chao Xu 
Published: April 2007

AbstractTechniques for reconstructing plausible HIV incidence curves from AIDS incidence data are called methods of back‐projection, or back‐calculation. Approaches to back‐projection tend to make the simplifying assumption that the quarterly HIV incidences are independent, which is not even approximately true. Here we investigate whether smoothed non‐parametric back‐projection based on this simplifying assumption gives sensible back‐projections and appropriate measures of precision for these reconstructed HIV incidence curves. Simple models for HIV transmission are shown to have much greater variation than the corresponding non‐homogeneous Poisson process arising from the independence assumption. Nevertheless, bearing in mind that the objective is to reconstruct the HIV epidemic curve for the current epidemic, it is argued that such back‐projection does give sensible HIV curves. This conclusion is supported by a simulation study, which also finds that confidence intervals for the HIV incidences are wider for transmission data than those determined from independent Poisson data.
Using time of first positive HIV test and other auxiliary data in back‐projection of AIDS incidence
Authors: Marschner Ian C. 
Published: April 2007

AbstractEstimation of HIV incidence by the method of back‐projection typically uses data on the time of diagnosis of AIDS cases, together with known information about the incubation distribution of AIDS. This paper discusses back‐projection using auxiliary data on AIDS cases, particularly the time of first positive HIV test. We discuss the possibility that certain types of auxiliary data, including time of first positive test, can be useful in back‐projection because they provide extra information about the incubation period of AIDS cases. Under a back‐projection model, theoretical efficiency calculations are given comparing back‐projection with and without the time of first positive HIV test of AIDS cases. These calculations suggest that such data have the potential to significantly improve HIV incidence estimates, particularly in the recent past. Smoothed non‐parametric estimates of both HIV incidence and time‐dependent testing rates are described. These can be obtained using the EM algorithm, in conjunction with a smoothing step or a penalized likelihood. The benefit of these methods in practice needs to be assessed as such data become available.
Backcalculation models of age‐specific HIV incidence rates
Authors: Rosenberg Philip S. 
Published: April 2007

AbstractThis paper extends the use of backcalculation to estimate past incidence of HIV infection in different age groups from age‐specific counts of AIDS incidence. The approach is flexible and allows the distribution of age at HIV infection to change over time. In this new approach, the incubation distributions used to backcalculate HIV infection rates depend on the age at HIV infection, because younger age is associated with slower progression. The effect of age on progression is estimated from a joint analysis of natural history data from several cohort studies of gay and bisexual men. As in previous applications, the incubation distributions also change over time to accommodate treatment effects and the 1987 revision of the surveillance definition. The method is applied to AIDS incidence data for the United States population. Estimated infection incidence for the entire population declined from peak levels seen in the mid‐1980s. However, persons under age 25 years have accounted for an increasing proportion of new HIV infections as the epidemic has progressed. Quantitative estimates were sensitive to the assumed incubation distribution, but the trend toward younger age at HIV infection was apparent using several models of the incubation distribution. Although the models are computationally intensive, they provide useful information about seroincidence trends in different age groups.
Incorporating HIV test data into forecasts of the AIDS epidemic in Scotland
Authors: Raab Gillian M. , Fielding Katherine L. , Allardice Gwen 
Published: April 2007

AbstractFor AIDS cases in Scotland the date of HIV antibody positive diagnosis (HIV test date) is recorded on the AIDS case reports. Data are also available on the total numbers of individuals with HIV positive test reports in Scottish laboratories in each year since testing became available. These data are incorporated into a model of the HIV epidemic described in terms of testing rates by calendar year. The HIV infection curve is modelled as a step function, and the testing rates are allowed to differ between steps. Results are presented for intravenous drug users (IDUs) and for homosexual/bisexual men. The estimated rates of testing for the IDUs (estimates from 19 per cent to 44 per cent per year) are considerably higher than those for homosexual/bisexual men (estimates of 10 per cent to 17 per cent per year). Data on the year of testing for AIDS diagnoses gave relatively little improvement in estimates of the HIV infection curve. However, when this information is combined with data on the total number of HIV positive diagnoses per year, there is a dramatic improvement in the estimate of the HIV infection curve. This is particularly marked for infections in the most recent period and for the estimates of cumulative infections up to the present. However, these improvements are gained at the cost of assumptions of similar testing rates applying to all sections of the HIV infected populations, which will be difficult to check in practice. This suggests that these methods should not be used in isolation but in combination with other evidence about the spread of HIV infection in a population.
The effect of covariates on the induction time of AIDS using improved imputation of exact seroconversion times
Authors: Gauvreau Kimberlee , Degruttola Victor , Pagano Marcello , Bellocco Rino 
Published: April 2007

AbstractThis paper explores the effects of covariates such as age, gender, chronological time of seroconversion, and mode of virus transmission on the interval between HIV seroconversion and the development of AIDS. For many cohorts which are available to provide information about such effects, both the time of seroconversion and the time of onset of AIDS may be right‐ or interval‐censored. To analyse these doubly‐censored data, we propose a method in which we first estimate the marginal distribution of the chronological time of seroconversion and use this distribution to impute the seroconversion time for each subject. Subsequently, we estimate the distribution of induction times conditional on the seroconversion distribution. We apply this technique to a cohort of HIV seropositive subjects recruited from various outpatient facilities throughout Italy and show that age at seroconversion has the greatest effect on induction time.
Distribution of the latency period for perinatally acquired AIDS
Authors: Mawhinney Samantha , Pagano Marcello 
Published: April 2007

AbstractIn the United States, over 86 per cent of paediatric cases of acquired immunodeficiency syndrome (AIDS) were infected through maternal or perinatal transmission and current estimates suggest that approximately 6000 children are born to infected women each year. In industrialized countries, less than 25 per cent of infants maternally exposed to the human immunodeficiency virus (HIV) are infected. The exact time of infection is unknown. However an endpoint, birth, exists from which the latency period or the time to diagnosis with clinical AIDS can be measured. In New York City, 7 years of reliable surveillance data were available for children with perinatally acquired AIDS. Using these data, the only estimable aspect of the latency is a conditional distribution, which conditions on diagnosis occurring before age 7. Because newborns carry maternal antibodies, a positive antibody test at birth is only an indication of maternal infection. Screening all newborns for HIV antibodies, while maintaining the anonymity of the mother and child, provides data on the number of children maternally exposed. The above conditioning can be removed by combining the surveillance and newborn screening data to obtain the unconditional latency distribution. We estimate a median diagnosis age of 4.1 years, somewhat longer than previously believed.
Non‐parametric analysis of transfusion‐related HIV and AIDS incidence data
Authors: Motika Milena , Becker Niels G. , Wylie Brenton , Learmont Jennifer , Kaldor John 
Published: April 2007

AbstractThe method for making non‐parametric inferences about the probability distribution of the incubation period for AIDS from transfusion‐related AIDS data is extended to include data on individuals who have tested positive for HIV but do not have AIDS at the time of analysis. The method is illustrated with data on individuals infected by transfusion in Australia. The shape of the incubation distribution, as represented by the truncated distribution function, can be estimated, but the additional data contribute very little to the estimation of this shape. With a general non‐parametric form for the incubation distribution the additional data do not overcome the identifiability problem that exists for non‐parametric estimation of this distribution from AIDS data alone. If quarterly rates for HIV testing are specified, the additional data make it possible to estimate the cumulative distribution function for the incubation period. This is also possible when a simple parametric form, with one or two unknown parameters, is used for the testing rates. However, the additional data do not allow effective estimation of the HIV testing rates. The estimated shape of the incubation distribution indicates a higher proportion of short incubation periods than an earlier estimate based on U.S. data. Estimates for the incubation distribution itself do not vary much over a plausible range of HIV testing rates.
Marker values at the time of an AIDS diagnosis
Authors: Taylor Jeremy M. G. , Kim Dong Kee 
Published: April 2007

AbstractIn this paper statistical methods are proposed to estimate the distribution of a CD4 T‐cell number at the time of a clinical AIDS endpoint from serial measurements of CD4 T‐cell values in a cohort study. The statistical formulation of the problem is that of survival analysis with interval censored data, but in which the endpoints are obtained with measurement error. A measurement error likelihood is developed, assuming normality of the CD4 distribution at AIDS. A maximum likelihood estimation procedure and a Gibbs sampling approach are implemented.
A model for AIDS pathogenesis
Authors: Schenzle Dieter 
Published: April 2007

AbstractThe idea is put forward and analysed numerically, that within an infected person HIV evolves to increase its reproductivity within the population of CD4+ cells. A mathematical model predicts initial viremia and CD4+ cell drop after HIV infection and thereafter a slow progressive decline in the number of CD4+ cells, although for an extended period HIV is kept at a relatively low level by an active immune response. The time span T until the number of CD4+ cells falls below 20 per cent of its normal value depends on several model parameters. Assuming Gaussian distributions for these parameters, the model predicts a distribution function for T which resembles the observed distribution function for the incubation period to AIDS.
Non‐parametric estimation and doubly‐censored data: General ideas and applications to AIDS
Authors: Jewell Nicholas P. 
Published: April 2007

AbstractIn many epidemiologic studies of human immunodeficiency virus (HIV) disease, interest focuses on the distribution of the length of the interval of time between two events. In many such cases, statistical estimation of properties of this distribution is complicated by the fact that observation of the times of both events is subject to intervalcensoring so that the length of time between the events is never observed exactly. Following DeGruttola and Lagakos, we call such data doubly‐censored. Jewell, Malani and Vittinghoff showed that, with certain assumptions and for a particular doubly‐censored data structure, non‐parametric maximum likelihood estimation of the interval length distribution is equivalent to non‐parametric estimation of a mixing distribution. Here, we extend these ideas to various other kinds of doubly‐censored data. We consider application of the methods to various studies generated by investigations into the natural history of HIV disease with particular attention given to estimation of the distribution of time between infection of an individual (an index case) and transmission of HIV to their sexual partner.
Modelling the female‐to‐male per‐act HIV transmission probability in an emerging epidemic in Asia
Authors: Satten Glen A. , Mastro Timothy D. , Longini Ira M. 
Published: April 2007

AbstractThe per‐sexual‐act probability of transmission of the human immunodeficiency virus type 1 (HIV) from an infected person to a susceptible sex partner can be determined from a simple model if the number of contacts each study participant has with infected partners is known. The unusual epidemiologic situation in the emerging HIV epidemic in Thailand allowed this quantity to be estimated from a cross‐sectional study of young men conscripted into the Thai military in 1991. Although the simple model does not fit the data, an errors‐in‐variables approach provides a model with adequate fit. Other sources of lack of fit, including heterogeneity of the transmission probability, are discussed. With adjustment for measurement error, the per‐act probability is estimated to be 0.056, an order of magnitude higher than similar estimates in North America. Because data indicate that recently infected persons may be more infectious, and because extensive HIV transmission in Thailand began in 1988, this difference may be due, in part, to a higher proportion of recently infected individuals in the emerging Thai epidemic from 1988 to 1991.
Considerations in choice of a clinical endpoint for AIDS clinical trials
Authors: Neaton James D. , Wentworth Deborah N. , Rhame Frank , Hogan Carlton , Abrams Donald I. , Deyton Lawrence 
Published: April 2007

AbstractIn most clinical trials of antiretroviral therapy for patients infected with HIV, the major outcome variable has been the combined clinical endpoint of any new or recurrent AIDS defining event. We review features of combined endpoints and use data from the Terry Beirn Community Programs for Clinical Research on AIDS (CPCRA) to evaluate this outcome measure in terms of relevance, diagnostic certainty and sensitivity. We conclude that this endpoint is not relevant because: (i) the 19 different events constituting the combined endpoint are equally weighted in analyses even though they vary considerably in terms of risk of death; and (ii) events after the first are ignored, thus the event profile of patients is not taken into account in making treatment comparisons. We also conclude that power may be low with use of this endpoint if treatments under study do not have an immediate impact on disease progression, if some events which occur soon after randomization represent a disease process that has already begun to incubate, or if treatment differences for the various events constituting the combined endpoint are differentially effected by treatment. Since the ease and certainty of diagnosis of each of the 19 events also vary, we recommend that survival be the primary endpoint of antiretroviral trials, and that all opportunistic events experienced by patients, not just the first, be collected and summarized. Trial reports should include comparisons of incidence of each event by treatment group so that readers can rank events as they please. A single summary measure which considers severity and the entire event profile, as described here, would also be useful for assessing the impact of treatments on quality of life. Further research on approaches for weighting and combining multiple outcome measures is needed.
The effectiveness of interventions on incubation of AIDS as measured by secular increases within a population
Authors: Hoover Donald R. , Muñtoz Alvaro , He Yanhua , Taylor Jeremy M. G. , Kingsley Lawrence , Chmiel Joan S. , Saah Alfred 
Published: April 2007

AbstractMethods are developed to estimate and test for the impact of intervention use on a population's survival function (time to AIDS). Each participant's history is divided intoJ+ 1 components: Ωooccurring before the intervention is available and Ω1to ΩJoccurring later, as the intervention becomes successively more available. Distribution free truncated Kaplan‐Meier models based on time since exposure fit separately to the risk sets/outcomes in Ωoto ΩJdirectly show the changing patterns of survival. Multivariate proportional hazards models can be used to adjust for covariates. Application of these methods indicates that availability of proven anti‐AIDS interventions may have delayed time to AIDS by 8 months in an educated HIV‐1 infected homosexual cohort with good access to medical care.
Assessing drug compliance using longitudinal marker data, with application to AIDS
Authors: Kim Hyungjin Myra , Lagakos Stephen W. 
Published: April 2007

AbstractThe assessment of non‐compliance to a study medication is an important issue in the evaluation of clinical trials of self‐administered drugs. Traditional methods for evaluating the compliance of subjects include self‐reported questionnaires and pharmacologic assays of drug levels in randomly‐drawn blood samples, but each of these has important limitations. This paper adapts and extends changepoint methods to assess compliance from longitudinal data on laboratory markers that are affected by the drug. The maximum likelihood estimators for two models are developed and examined. The effect of the drug on the marker process, as well as the spacing of the observations of the marker process relative to the time of noncompliance determine which model parameters are estimable. For the situations examined, the method of maximum likelihood is found to perform well in most cases. However, when non‐compliance begins shortly before the last observation of the marker process, these (as well as any other) estimators cannot reliably distinguish non‐compliance from compliance. The methods are illustrated with an example from a recent clinical trial of persons infected with HIV.