AIDS Incidence Data Research Articles

Mean generation function model in AIDS epidemic estimation

BackgroundSince the first case of HIV infection was reported in China in 1985, the incidence and mortality of AIDS have been increasing rapidly, which has caused serious damage to the life and health of people in China and all over the world. Therefore, it is of great significance to study the technique for predicting AIDS morbidity and mortality. The purpose of this research is to explore the applicability of the mean generation function model (MGFM) in the early warning of AIDS morbidity and mortality, to predict its prevalence trend, to enrich the prediction techniques and methods of AIDS research and to provide suggestions for AIDS transmission control.MethodsIn this research, the MGFM was applied to predict the incidence and mortality of AIDS in China. AIDS incidence and mortality data in China from 2008 to 2019 were used to construct the prediction model.ResultsThe MGFM can predict the annual incidence and mortality of AIDS. The model constructed in this research predicted that the incidence and mortality of AIDS in China will continue to increase from 2020 to 2023.ConclusionThe mean birth function model was an effective method to monitor and predict the changing trend of AIDS incidence and mortality in China.

Analysing the impact of migration on HIV/AIDS cases using epidemiological modelling to guide policy makers.

In this paper, we present the impact of migration on the spread of HIV and AIDS cases. A simple model for HIV and AIDS that incorporates migration and addresses its contributions to the spread of HIV and AIDS cases was constructed. The model was calibrated to HIV and AIDS incidence data from Malaysia. We explore the use of Markov chain Monte Carlo (MCMC) simulation method to estimate uncertainty in all the unknown parameters incorporated in our proposed model. Among the migrant population, 1.5572e-01 were susceptible to HIV transmission, which constituted 67,801 migrants. A proportion of migrants, 6.3773e-04, were estimated to be HIV infected, constituting 278 migrants. There were 72 (per 10,000) migrants estimated to have had AIDS, representing a proportion of 1.6611e-08. The result suggests that the disease-free steady state was unstable since the estimated basic reproduction number was 2.0906 and 2.3322 for the models without and with migration, respectively. This is not a good indicator from the public health point of view, as the aim is to stabilize the epidemic at the disease-free equilibrium. The advantage of introduction of migration to the simple model validated the true and the transmission rate associated with HIV and AIDS epidemic disease in Malaysia. It also indicates an approximately 12 percentage points increase in the rate of HIV infection with migration.

The impact of implementing HIV prevention policies therapy and control strategy among HIV and AIDS incidence cases in Malaysia.

Malaysia is faced with a high HIV/AIDS burden that poses a public health threat. We constructed and applied a compartmental model to understand the spread and control of HIV/AIDS in Malaysia. A simple model for HIV and AIDS disease that incorporates condom and uncontaminated needle-syringes interventions and addresses the relative impact of given treatment therapy for infected HIV newborns on reducing HIV and AIDS incidence is presented. We demonstrated how treatment therapy for new-born babies and the use of condoms or uncontaminated needle-syringes impact the dynamics of HIV in Malaysia. The model was calibrated to HIV and AIDS incidence data from Malaysia from 1986 to 2011. The epidemiological parameters are estimated using Bayesian inference via Markov chain Monte Carlo simulation method. The reproduction number optimal for control of the HIV/AIDS disease obtained suggests that the disease-free equilibrium was unstable during the 25 years. However, the results indicated that the use of condoms and uncontaminated needle-syringes are pivotal intervention control strategies; a comprehensive adoption of the intervention may help stop the spread of HIV disease. Treatment therapy for newborn babies is also of high value; it reduces the epidemic peak. The combined effect of condom use or uncontaminated needle-syringe is more pronounced in controlling the spread of HIV/AIDS.

Global dynamics and cost-effectiveness analysis of HIV pre-exposure prophylaxis and structured treatment interruptions based on a multi-scale model

• A novel multi-scale model for HIV infection with drug resistance is proposed and global dynamics are analyzed. • Cost-effectiveness of pre-exposure prophylaxis (PrEP) and structured treatment interruptions (STI) are analyzed. • PrEP effectiveness needed to eliminate the disease for different fraction of acquired drug resistance are obtained. • The results provide new insights about the long-term effect of STI and PrEP on the disease control. Structured treatment interruptions (STI) were proposed to reduce costs and side effects for HIV infected individuals, but whether the possible viral rebound within hosts after treatment interruption would lead to more new infections and additional costs among the population remains unknown. Oral pre-exposure prophylaxis (PrEP) is shown as an effective but expensive strategy to prevent the acquisition of HIV infection. To investigate the effectiveness and cost-effectiveness of STI and PrEP, we develop a multi-scale model linking within-host and between-host dynamics in the presence of drug resistance. Lyapunov functionals are constructed to analyze the global dynamics of the coupled system. We fit this model to the annual AIDS incidence and death data from 1980 to 2014 among men who have sex with men (MSM) in San Francisco and compare the impact of six various intervention scenarios (low, medium, high PrEP coverage with or without STI) on new infections and cost-effectiveness over the next 20 years. We estimate the PrEP efficacy needed to eliminate the disease for different fraction of acquired drug resistance under the above six scenarios. Numerical simulations show that expanding PrEP coverage is very cost-effective, but whether implementing STI is cost-saving depends on the efficacy of second-line drugs. That is to say, STI could always save money, but it may lead to more (less) new infections than continuous therapy and thus less (more) health benefit for high (low) efficacy of second-line drugs. These results provide insights about the long-term effect of STI and PrEP on the disease control and cost-effectiveness.

Early antiretroviral therapy and potent second-line drugs could decrease HIV incidence of drug resistance.

Early initiation of antiretroviral therapy (ART) reduces the risk of drug-sensitive HIV transmission but may increase the transmission of drug-resistant HIV. We used a mathematical model to estimate the long-term population-level benefits of ART and determine the scenarios under which earlier ART (treatment at 1 year post-infection, on average) could decrease simultaneously both total and drug-resistant HIV incidence (new infections). We constructed an infection-age-structured mathematical model that tracked the transmission rates over the course of infection and modelled the patients' life expectancy as a function of ART initiation timing. We fitted this model to the annual AIDS incidence and death data directly, and to resistance data and demographic data indirectly among men who have sex with men (MSM) in San Francisco. Using counterfactual scenarios, we assessed the impact on total and drug-resistant HIV incidence of ART initiation timing, frequency of acquired drug resistance, and second-line drug effectiveness (defined as the combination of resistance monitoring, biomedical drug efficacy and adherence). Earlier ART initiation could decrease the number of both total and drug-resistant HIV incidence when second-line drug effectiveness is sufficiently high (greater than 80%), but increase the proportion of new infections that are drug resistant. Thus, resistance may paradoxically appear to be increasing while actually decreasing.

Age-period cohort analysis of AIDS incidence rates in Rio de Janeiro, Brazil, 1985-2009.

IntroductionThe long average incubation time from HIV infection to AIDS makes it difficult to estimate the recent tendencies of HIV from AIDS incidence data. The objective of this study was to investigate the effects of three temporal components in AIDS incidence in the state of Rio de Janeiro, Brazil - age, period, and cohort.MethodsAge-specific AIDS incidence rates per 100,000 from Rio de Janeiro (Brazil) were calculated for both sexes using five-year age classes from 1985 to 2009 based on reported data from the Notifiable Disease Information System of the Brazilian Ministry of Health and from census population counts. Multivariate negative binomial models were used to analyze the risk of AIDS by age, period, and birth cohort.ResultsFrom 1985 to 2009, AIDS incidence initially increased with age in each birth cohort and then decreased (except for individuals born from 1971–1979 to 1986–1994). High peaks in the rates in each birth cohort were detected in 1995–1999 for males and in 2000–2004 for females. Multivariate analysis showed the maximum risk of AIDS in the 30–34 age group and 1958–1962 birth cohort.ConclusionAge, birth cohort, and period effects all may have influenced the AIDS incidence rates over the period investigated. From 1985 to 1999, comparison of the tendencies (by age) of the period with the birth cohort revealed opposing tendencies in individuals older than 29 years and in the youngest age groups (0 to 14 years). From 2000 to 2009, a strong age effect can be observed in both sexes. Consistent changes in period tendency curves suggest the occurrence of period effects. A reduction in the intensity of the risk of AIDS can be observed after 2000–2004.

HIV/AIDS Projection in TamilNadu using back calculation method

The current prevalence of HIV infection and the corresponding pattern of incidence from the beginning of the epidemic to the present time are mainly estimated by means of back-calculation method. This back-calculation method reconstructs the past pattern of HIV infection and predicts the future number of AIDS cases with the present infection status. The basic data required for back-calculation methodology is the number of AIDS cases over a period of time. TANSACS publishes the reported number of AIDS cases in Tamil Nadu. In this paper, the various approaches for modeling the incubation distribution are compared using real data under various infection density distributions. The projected minimum and maximum AIDS cases in Tamil Nadu, a southern state of India, based on the reported data are 3702712 and 6936047 respectively. These estimates are based on the unadjusted AIDS incidence data. The purpose of this paper is to review the contribution of back-calculation method to our understanding of the AIDS and to summarize and interpret the epidemiological findings. Keywords: HIV/AIDS, Incubation period, Estimation, Infection distributions, Back calculation

HIV/AIDS Projection in Tamilnadu Using Back Calculation Method

The current prevalence of HIV infection and the corresponding pattern of incidence from the beginning of the epidemic to the present time are mainly estimated by means of back-calculation method. This back-calculation method reconstructs the past pattern of HIV infection and predicts the future number of AIDS cases with the present infection status. The basic data required for back-calculation methodology is the number of AIDS cases over a period of time. TANSACS publishes the reported number of AIDS cases in Tamil Nadu. In this paper, the various approaches for modeling the incubation distribution are compared using real data under various infection density distributions. The projected minimum and maximum AIDS cases in Tamil Nadu, a southern state of India, based on the reported data are 3702712 and 6936047 respectively. These estimates are based on the unadjusted AIDS incidence data. The purpose of this paper is to review the contribution of back-calculation method to our understanding of the AIDS and to summarize and interpret the epidemiological findings.

Comparing epidemic forecasts for European countries obtained from AIDS incidence and HIV prevalence data

Previously, the diffusion of HIV/AIDS among the countries of Europe has been reconstructed using a multiregion epidemic modelling system (Thomas 2000; Smith and Thomas 2001). This model was calibrated to WHO AIDS incidence series for each country which, in most instances, were replicated with a high degree of fit. The size of the epidemic implied by this procedure, however, did not conform to point estimates of cumulative HIV prevalence which indicate an eventual size at least three times greater than that attributable to recorded AIDS cases. This paper, therefore, investigates the consequences of this discrepancy for the space–time structure that is estimated for the epidemic in Europe. The first part considers how the modelling system is adapted to take account of national HIV statistics. To this end, an optimisation method is described for identifying disease transmission rates that are consistent with current cumulative HIV prevalence in each country. This method generates a range of feasible solutions where the eventual size of the epidemic is inversely related to this infectivity rate. The second part derives multiregion simulations for European countries using parameter sets calibrated according to both AIDS incidence and HIV prevalence. The outputs for each set include the predicted starting pathway of the epidemic together with a graph recording the direction of the principal infection vector for each country at the forecast time of peak HIV prevalence. For AIDS based scenarios, the diffusion of the epidemic generally flows across Europe from west to east. In contrast, for HIV scenarios at peak prevalence the direction of flow is partially reversed from east to west. The discussion considers the implications of these findings for disease control in the light of issues concerning the recording of HIV and AIDS statistics.

Data and projections of HIV/AIDS cases in Portugal: an unstoppable epidemic?

The size of the affected population with HIV/AIDS is a vital question asked by healthcare providers. A statistical procedure called Back-calculation has been the most widely used method to answer that question. Recent discussions suggest that this method is gradually becoming less appropriate for reliable incidence and prevalence estimates, as it does not take into account the effect of treatment. In spite of this, in the current paper that method and a worst-case scenario are used to assess the quality of previous projections and obtain new ones. The first problem faced was the need to account for reporting delays, no reporting and underreporting. The adjusted AIDS incidence data were then used to obtain lower bounds on the size of the AIDS epidemic, using the back-calculation methodology. A Weibull and Gamma distribution was considered for the latency period distribution. The EM algorithm was applied to obtain maximum likelihood estimates of the HIV incidence. The density of infection times was parameterized as a step function. The methodology is applied to AIDS incidence in Portugal for four different transmission categories (injecting drug users, heterosexual, homo/bisexual and other) to obtain short-term projections (2002–2005) and an estimate of the minimum size of the epidemic.

Non-parametric Back-projection of HIV Positive Tests using Multinomial and Poisson Settings

Back-projection is a commonly used method in reconstructing HIV incidence. Instead of using AIDS incidence data in back-projection, this paper uses HIV positive tests data. Both multinomial and Poisson settings are used. The two settings give similar results when a parametric form or step function is assumed for the infection curve. However, this may not be true when the HIV infection in each year is characterized by a different parameter. This paper attempts to use simulation studies to compare these two settings by constructing various scenarios for the infection curve. Results show that both methods give approximately the same estimates of the number of HIV infections in the past, whilst the estimates for HIV infections in the recent past differ a lot. The multinomial setting always gives a levelling-off pattern for the recent past, while the Poisson setting is more sensitive to the change in the shape of the HIV infection curve. Nonetheless, the multinomial setting gives a relatively narrower point-wise probability interval. When the size of the epidemic is large, the narrow probability interval may be under-estimating the true underlying variation.

Nonparametric estimation of the location of a maximum in a response surface

We explore a nonparametric version of response surface analysis. Estimates for the location where maximum response occurs are proposed and their asymptotic distribution is investigated. The proposed estimates are based on kernel and local least squares methods. We construct asymptotic confidence regions for the location and include comparisons with the quadratic response surface approach. The methods are illustrated for the two-dimensional case with AIDS incidence data, where the point of maximum incidence is of interest.

Multinomial analysis of smoothed HIV back-calculation models incorporating uncertainty in the AIDS incidence.

Back-calculation models, developed to reconstruct the past trend of human immunodeficiency virus (HIV) and to project future acquired immunodeficiency syndrome incidence (AIDS), are usually and unrealistically based on the assumption that the observed AIDS counts are independently distributed according to a Poisson process. In contrast, we argue that a multinomial framework is more suitable to this situation, leading to a natural covariance structure. The ill-conditioned nature of the problem is solved by modelling the HIV parameters according to a cubic spline function to reduce the dimensionality of the parameter space and obtain smoother parameter estimates. We applied a regression spline technique which yields to a computationally stable basis incorporating the incubation period in the new design matrix. We directly incorporate the reporting delay distribution in the AIDS incidence data, leading to a more complex formulation of the variance and covariance model that is adapted to the iteratively reweighted least square (IRLS) algorithm. In this case we obtain more accurate estimates of the standard error of the HIV incidence, especially in the most recent time. Our model, which uses a cubic spline reparameterization based on a multinomial probability distribution, is applied to the AIDS epidemic data in Italy.

Economic deprivation and AIDS incidence in Massachusetts.

This study quantified AIDS incidence in Massachusetts in relation to economic deprivation. Using 1990 census block-group data, 1990 census population counts, and AIDS surveillance registry data for the years 1988 through 1994, we generated yearly and cumulative AIDS incidence data for the state of Massachusetts stratified by sex and by neighborhood measures of economic position for the total, Black, Hispanic, and White populations. Incidence of AIDS increased with economic deprivation, with the magnitude of these trends varying by both race/ethnicity and sex. The cumulative incidence of AIDS in the total population was nearly 7 times higher among persons in block-groups where 40% or more of the population was below the poverty line (362 per 100,000) than among persons in block-groups where less than 2% of the population was below poverty (53 per 100,000). Observing patterns of disease burden in relation to neighborhood levels of economic well-being elucidates further the role of poverty as a population-level determinant of disease burden. Public health agencies and researchers can use readily available census data to describe neighborhood-level socioeconomic conditions. Such knowledge expands options for disease prevention and increases the visibility of economic inequality as an underlying cause of AIDS.

Estimating HIV incidence using dates of both HIV and AIDS diagnoses

Knowledge of HIV incidence is important to formulate sensible strategies aimed at controlling the HIV/AIDS epidemic. Back-projection is one of the methods for reconstructing the HIV incidence curve from AIDS incidence data. However, because of the low risk of developing AIDS during the first few years after infection, precise estimates of HIV incidence for the recent past are unlikely if we use AIDS incidence data only. As a result there have been recent attempts to use, not only the date of AIDS diagnosis, but also to use the date of their first positive HIV test. The objective of this paper is to incorporate into back-projection the additional information provided by those individuals who have tested HIV positive but have not yet developed AIDS. This adds information on a very large number of other individuals, and provides the hope that the precision of back-projection is improved considerably. The date of a positive HIV test or an AIDS diagnosis of an individual, whichever comes first, is used in a generalized convolution equation for the purpose of back-projection. The method is illustrated by an application to Australian HIV and AIDS data. Study results show that dramatic improvement in precision is gained for estimates of HIV incidence in recent years when both HIV and AIDS diagnosis dates are used on all individuals. Copyright © 2000 John Wiley & Sons, Ltd.

Estimating HIV incidence using dates of both HIV and AIDS diagnoses.

Knowledge of HIV incidence is important to formulate sensible strategies aimed at controlling the HIV/AIDS epidemic. Back-projection is one of the methods for reconstructing the HIV incidence curve from AIDS incidence data. However, because of the low risk of developing AIDS during the first few years after infection, precise estimates of HIV incidence for the recent past are unlikely if we use AIDS incidence data only. As a result there have been recent attempts to use, not only the date of AIDS diagnosis, but also to use the date of their first positive HIV test. The objective of this paper is to incorporate into back-projection the additional information provided by those individuals who have tested HIV positive but have not yet developed AIDS. This adds information on a very large number of other individuals, and provides the hope that the precision of back-projection is improved considerably. The date of a positive HIV test or an AIDS diagnosis of an individual, whichever comes first, is used in a generalized convolution equation for the purpose of back-projection. The method is illustrated by an application to Australian HIV and AIDS data. Study results show that dramatic improvement in precision is gained for estimates of HIV incidence in recent years when both HIV and AIDS diagnosis dates are used on all individuals.

Data and projections of HIV and AIDS in Portugal

Projections of AIDS incidence are critical for assessing future healthcare needs. This paper focuses on the method of back-calculation for obtaining forecasts. The first problem faced was the need to account for delays and underreporting in reporting of cases and to adjust the incidence data. The method used to estimate the reporting delay distribution is based on Poisson regression and involves cross-classifying each reported case by calendar time of diagnosis and reporting delay. The adjusted AIDS incidence data are then used to obtain short-term projections and lower bounds on the size of the AIDS epidemic. The estimation procedure 'back-calculates' from AIDS incidence data using the incubation period distribution to obtain estimates of the numbers previously infected. These numbers are then projected forward. The problem can be shown to reduce to estimating the size of a multinomial population. The expectation-maximization (EM) algorithm is used to obtain maximum-likelihood estimates when the density of infection times is parametrized as a step function. The methodology is applied to AIDS incidence data in Portugal for four different transmission categories: injecting drug users, sexual transmission (homosexual/bisexual and heterosexual contact) and other, mainly haemophilia and blood transfusion related, to obtain short-term projections and an estimate of the minimum size of the epidemic.

An age-period-cohort analysis of 50,875 AIDS cases among injecting drug users in Europe.

The long average incubation time from HIV infection to AIDS makes it difficult to estimate recent HIV transmission from AIDS incidence data. Age-period-cohort (APC) analysis can separate out the effects of age, calendar time and birth cohort to provide a clearer picture of transmission trends. AIDS incidence data from 1981 to 1994 among intravenous drug users (IDU) for 12 Western European countries were used. Yearly incidences per 100,000 population or 100,000 person-years were calculated by age at diagnosis and 5-year birth cohort (1950-1954, 1955-1959, 1960-1964, 1965-1969 and 1970-1974), and corrected for reporting delay. Incidence patterns were compared between birth cohorts and countries. For most countries the impact was greatest on the cohort born 1960-1964. Comparing incidence patterns in the 1965-1969 to 1960-1964 cohorts suggest the epidemic has plateaued at low to intermediate levels in Austria, Greece and the North-Western European countries, and at high levels in France, Italy and Switzerland. For most countries transmission amongst the 1970-1974 as compared to the 1965-1969 cohorts could not be assessed due to small numbers and short follow-up time. In Spain the epidemic was uncontrolled with a high incidence among recent birth cohorts. In Portugal the epidemic was still at an early and expanding phase. The APC analysis revealed large country differences in the dynamics of the HIV/AIDS epidemic among IDU. Full interpretation of these differences is dependent on information from other sources about the local public health response and trends in drug injecting behaviours. Earlier introduction of the virus and higher prevalence of injecting drug use may explain some of the generally higher incidence in Southern European countries, but the larger part of it is most likely explained by local characteristics of drug users, such as younger age and more frequent sharing of needles and syringes, and a less effective public health response.

The state-space model of the HIV epidemic with variable infection in the homosexual populations

In this paper we derive a state-space model for the HIV epidemic with variable infection in homosexual populations. In this model the stochastic dynamic system model is the stochastic model which is described in terms of chain multinomial distributions whereas the observation model is a statistic model based on the AIDS incidence data. As an example, we have applied the model to the San Francisco homosexual population to estimate and project the HIV prevalence and AIDS cases. Our results revealed that the Kalman filter estimates of AIDS cases had traced the observed numbers extremely well. For the HIV prevalence in the San Francisco homosexual population, our results showed that the curve peaked around 1985 and then decreased to a low level around 1992; after that the curve started to increase and provided another peak around the year 2000.

Snapshot Estimators of Recent HIV Incidence Rates

The recent HIV incidence rate (or hazard rate for infection) is an important quantity for use in monitoring the HIV/AIDS epidemic, evaluating HIV prevention programs, and allocating HIV prevention resources. Direct measurement of HIV incidence is difficult and time consuming, while estimating HIV incidence via backcalculation (deconvolution) using AIDS incidence data and the (presumed known) HIV incubation time distribution yields little information about recent infection. We propose a method for estimating recent HIV incidence in a population via a single sample at a single point in time. The method relies on understanding the progression of certain markers such as CD4 counts following infection. The actual formulas derived for the point and interval estimates of HIV incidence are simple and easy to use while the sample sizes needed to implement our approach are reasonable. We present two applications of our approach, comparing our results to those obtained from more conventional methods where possible.