Projecting the spread of AIDS in the United Kingdom: a sensitivity analysis

Daykin, C. D.; Clark, P. N. S.; Eves, M. J.; Haberman, Steven; Grys, D. J. Le; Lockyer, John; Michaelson, Robin; Wilkie, A. D.

doi:10.1017/s0020268100043031

Cited by 2 publications

(8 citation statements)

References 12 publications

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“…The exact choice of incubation period distribution was found to affect the peak of both HIV [40] and AIDS incidence [40,114] but the endemic prevalence was less affected. Conversely, one study showed that the long-term HIV incidence can be markedly decreased by only a slight increase in the mortality rate amongst HIV-infected MSM due to a smaller number of people that can pass infection to others [34].…”

Section: Effects Of Parameter Uncertainty On Hiv Epidemic Forecastsmentioning

confidence: 98%

“…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%

“…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%

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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: 98%

“…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%

Section: Effects Of Parameter Uncertainty On Hiv Epidemic Forecastsmentioning

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 put forward by the Institute of Actuaries AIDS Working Party (Daykin et al, 1988(Daykin et al, , 1990) is used as a representation of the transmission and spread of AIDS among male homosexuals.…”

Section: Introductionmentioning

confidence: 99%

HIV, AIDS and the approximate calculation of life insurance functions, annuities and net premiums

Haberman¹

1992

J. Inst. Actuar.

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The paper presents an application of the Markov chain as a tool for the calculation of life contingencies functions (e.g. assurance, annuity, net premium, policy value functions) arising from a multi-state model which represents the transmission and development of HIV and AIDS. The transmission model advocated by the Institute of Actuaries AIDS Working Party is modified and simplified and then applied to derive explicit formulae for these standard life contingencies functions. This investigation allows a thorough review of the properties of these functions to be conducted and assists with the calculation of premiums and reserves in the presence of HIV and AIDS.

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Projecting the spread of AIDS in the United Kingdom: a sensitivity analysis

Cited by 2 publications

References 12 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

HIV, AIDS and the approximate calculation of life insurance functions, annuities and net premiums

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