Population projections for AIDS using an actuarial model

doi:10.1098/rstb.1989.0075

Cited by 11 publications

(5 citation statements)

References 5 publications

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“…However, if the size of this group reduced rapidly due to AIDS, the endemic prevalence would be lower [10,12,102]. The profound effects of sexual contact rate reductions were confirmed [47,51,58,63,64,79,88,96,97,115,116], and even stronger impacts were reported if the reductions occurred in both infected and at-risk individuals, or earlier in the epidemic [37,39,42]. In terms of unsafe sex, both direct [24,27,32,36,70,116] and indirect effects (increasing prevalence other sexually transmitted infections [33,67,68,111]) on causing more HIV infections have been suggested.…”

Section: Effects Of Parameter Uncertainty On Hiv Epidemic Forecastsmentioning

confidence: 53%

“…Higher heterogeneity in sexual activity Faster spread in early state [12,39,58] Lower HIV prevalence in endemic state [10,12,102] Lower sexual contact rates Slower spread and lower HIV prevalence [47,51,58,63,64,79,88,96,97,115,116] Stronger positive effect if happening in either earlier epidemic or both susceptible and infected populations [37,39,40,42] Higher degree of unsafe sexual practices Higher HIV incidence and prevalence [24,27,32,36,70,116] Higher prevalence of other STIs and hence higher HIV incidence [33,67,68,111] Higher proportion of new infections caused by ARTresistant strains [104] Higher number of MSM who have casual partners…”

Section: Effects Of Parameter Uncertainty On Hiv Epidemic Forecastsmentioning

confidence: 99%

“…1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 forecasts of the HIV MSM epidemic [37][38][39][40] and all dated back to before 1991.…”

Section: Epidemic Projectionsmentioning

confidence: 99%

“…The importance of age heterogeneity was highlighted by a finding suggesting that ignoring AIDS-induced age-specific mortality, the initial epidemic growth rate and endemic HIV prevalence would be substantially underestimated [58]. Three studies incorporated age as a continuous variable [58,59,106] whereas most divided the age into groups [6,22,23,34,37,40,66,69,[107][108][109]. This grouping technique was often used to make models simpler to implement; two models, for example, were theoretically described with continuous sexual activity and age but in their practical application of sexual activity [58] and age [108] groups were used instead.…”

Section: Stratification By Agementioning

confidence: 99%

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Mathematical models for the study of HIV spread and control amongst men who have sex with men

et al. 2011

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For a quarter of century, mathematical models have been used to study the spread and control of HIV amongst men who have sex with men (MSM). We searched MEDLINE and EMBASE databases up to the end of 2010 and reviewed this literature to summarise the methodologies used, key model developments, and the recommended strategies for HIV control amongst MSM. Of 742 studies identified, 127 studies met the inclusion criteria. Most studies employed deterministic modelling methods (80%). Over time we saw an increase in model complexity regarding antiretroviral therapy (ART), and a corresponding decrease in complexity regarding sexual behaviours. Formal estimation of model parameters was carried out in only a small proportion of the studies (22%) while model validation was considered by an even smaller proportion (17%), somewhat reducing confidence in the findings from the studies. Nonetheless, a number of common conclusions emerged, including (1) identification of the importance of assumptions regarding changes in infectivity and sexual contact rates on the impact of ART on HIV incidence, that subsequently led to empirical studies to gather these data, and (2) recommendation that multiple strategies would be required for effective HIV control amongst MSM. The role of mathematical models in studying epidemics is clear, and the lack of formal inference and validation highlights the need for further developments in this area. Improved methodologies for parameter estimation and systematic sensitivity analysis will help generate predictions that more fully express uncertainty, allowing better informed decision making in public health.

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Section: Effects Of Parameter Uncertainty On Hiv Epidemic Forecastsmentioning

confidence: 53%

Section: Effects Of Parameter Uncertainty On Hiv Epidemic Forecastsmentioning

confidence: 99%

“…1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 forecasts of the HIV MSM epidemic [37][38][39][40] and all dated back to before 1991.…”

Section: Epidemic Projectionsmentioning

confidence: 99%

Section: Stratification By Agementioning

confidence: 99%

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Mathematical models for the study of HIV spread and control amongst men who have sex with men

et al. 2011

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“…The model has been widely published and full details can be found in , Wilkie (1988Wilkie ( , 1988aWilkie ( , 1989.…”

Section: Biased Partner Selectionmentioning

confidence: 99%

Actuarial review of models for describing and predicting the spread of HIV infection and AIDS

Haberman¹

1990

J. Inst. Actuar.

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AbstractThe paper reviews the mathematical models of transmission of infection that have been put forward for representing the spread of HIV infection and AIDS. It describes and compares the main models that have been proposed and thereby provides some guidance on how such models might be constructed and utilised. There is also discussion of the importance of constructing such mathematical models of transmission of infection which further our understanding of the transmission dynamics of the epidemic and help to identify important epidemiological parameters and their likely influence on the epidemic's course.

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Short and medium term projections of the aids/hiv epidemic by a dynamic model with an application to the risk group of homo/bisexual men in amsterdam

Heisterkamp

Haan

Jager

et al. 1992

Statistics in Medicine

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Several methods exist for short term projection of the numbers of AIDS cases. Some use extrapolation of empirical curves fitted to data up to a given time, whereas others such as the popular method of 'back projection' or actuarial methods also use information about the process. In this paper we describe a dynamic model based on a distributed modelling technique allowing for variability both in infectiousness and in age distribution of the population at risk. Some model parameters are taken from the literature, others are estimated from AIDS incidence data from the homo/bisexual population in Amsterdam. The model described here simulates prevalence and incidence of HIV infection. We present prediction intervals for two years from January 1990 onwards. We discuss three scenarios based on the estimated model, two of which consider early treatment with anti-viral drugs. Given the model and the state of the epidemic in Amsterdam, early treatment intervention must be combined with very drastic measures for reducing infectivity in order to have any serious impact on the course of the epidemic.

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Population projections for AIDS using an actuarial model

Cited by 11 publications

References 5 publications

Mathematical models for the study of HIV spread and control amongst men who have sex with men

Mathematical models for the study of HIV spread and control amongst men who have sex with men

Actuarial review of models for describing and predicting the spread of HIV infection and AIDS

Short and medium term projections of the aids/hiv epidemic by a dynamic model with an application to the risk group of homo/bisexual men in amsterdam

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