Literature DB >> 21932033

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

Narat Punyacharoensin1, William John Edmunds, Daniela De Angelis, Richard Guy White.   

Abstract

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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Year:  2011        PMID: 21932033     DOI: 10.1007/s10654-011-9614-1

Source DB:  PubMed          Journal:  Eur J Epidemiol        ISSN: 0393-2990            Impact factor:   8.082


  97 in total

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Review 2.  Could widespread use of combination antiretroviral therapy eradicate HIV epidemics?

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Journal:  Lancet Infect Dis       Date:  2002-08       Impact factor: 25.071

3.  Modeling trends in HIV incidence among homosexual men in Australia 1995-2006.

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Journal:  J Acquir Immune Defic Syndr       Date:  2004-04-01       Impact factor: 3.731

4.  Modeling the population level effects of an HIV-1 vaccine in an era of highly active antiretroviral therapy.

Authors:  Wasima Rida; Sonja Sandberg
Journal:  Bull Math Biol       Date:  2009-02-12       Impact factor: 1.758

5.  The transmission dynamics of the human immunodeficiency virus type 1 in the male homosexual community in the United Kingdom: the influence of changes in sexual behaviour.

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Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  1989-09-05       Impact factor: 6.237

6.  The influence of concurrent partnerships on the dynamics of HIV/AIDS.

Authors:  C H Watts; R M May
Journal:  Math Biosci       Date:  1992-02       Impact factor: 2.144

Review 7.  Antiviral therapy and the transmission dynamics of HIV-1.

Authors:  G P Garnett; R M Anderson
Journal:  J Antimicrob Chemother       Date:  1996-05       Impact factor: 5.790

8.  A simulation model of AIDS in San Francisco: II. Simulations, therapy, and sensitivity analysis.

Authors:  H W Hethcote; J W Van Ark; J M Karon
Journal:  Math Biosci       Date:  1991-10       Impact factor: 2.144

9.  Endemic threshold results in an age-duration-structured population model for HIV infection.

Authors:  Hisashi Inaba
Journal:  Math Biosci       Date:  2006-02-08       Impact factor: 2.144

10.  A sex-role-preference model for HIV transmission among men who have sex with men in China.

Authors:  Jie Lou; Jianhong Wu; Li Chen; Yuhua Ruan; Yiming Shao
Journal:  BMC Public Health       Date:  2009-11-18       Impact factor: 3.295

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  7 in total

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Authors:  Louis MacGregor; Natasha K Martin; Christinah Mukandavire; Ford Hickson; Peter Weatherburn; Matthew Hickman; Peter Vickerman
Journal:  Int J Epidemiol       Date:  2017-10-01       Impact factor: 7.196

2.  Bayesian history matching of complex infectious disease models using emulation: a tutorial and a case study on HIV in Uganda.

Authors:  Ioannis Andrianakis; Ian R Vernon; Nicky McCreesh; Trevelyan J McKinley; Jeremy E Oakley; Rebecca N Nsubuga; Michael Goldstein; Richard G White
Journal:  PLoS Comput Biol       Date:  2015-01-08       Impact factor: 4.475

Review 3.  The Preventable Risk Integrated ModEl and Its Use to Estimate the Health Impact of Public Health Policy Scenarios.

Authors:  Peter Scarborough; Richard A Harrington; Anja Mizdrak; Lijuan Marissa Zhou; Aiden Doherty
Journal:  Scientifica (Cairo)       Date:  2014-09-25

4.  Assessing the use of surveillance data to estimate the impact of prevention interventions on HIV incidence in cluster-randomized controlled trials.

Authors:  Kate M Mitchell; Dobromir Dimitrov; James P Hughes; Mia Moore; Eric Vittinghoff; Albert Liu; Myron S Cohen; Chris Beyrer; Deborah Donnell; Marie-Claude Boily
Journal:  Epidemics       Date:  2020-11-20       Impact factor: 4.396

Review 5.  Impact of high-risk sex and focused interventions in heterosexual HIV epidemics: a systematic review of mathematical models.

Authors:  Sharmistha Mishra; Richard Steen; Antonio Gerbase; Ying-Ru Lo; Marie-Claude Boily
Journal:  PLoS One       Date:  2012-11-30       Impact factor: 3.240

6.  Who mixes with whom among men who have sex with men? Implications for modelling the HIV epidemic in southern India.

Authors:  K M Mitchell; A M Foss; H J Prudden; Z Mukandavire; M Pickles; J R Williams; H C Johnson; B M Ramesh; R Washington; S Isac; S Rajaram; A E Phillips; J Bradley; M Alary; S Moses; C M Lowndes; C H Watts; M-C Boily; P Vickerman
Journal:  J Theor Biol       Date:  2014-04-13       Impact factor: 2.691

7.  Calibration of individual-based models to epidemiological data: A systematic review.

Authors:  C Marijn Hazelbag; Jonathan Dushoff; Emanuel M Dominic; Zinhle E Mthombothi; Wim Delva
Journal:  PLoS Comput Biol       Date:  2020-05-11       Impact factor: 4.475

  7 in total

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