Literature DB >> 1806103

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

H W Hethcote1, J W Van Ark, J M Karon.   

Abstract

The HIV and AIDS incidences each year for homosexual men in San Francisco are estimated from data. A computer simulation model for HIV transmission dynamics and progression to AIDS is used to reconstruct the HIV epidemic. Using some a priori parameter estimates, simulations are found that give good fits to the incidence data. In the stimulations the populations is divided into risk groups whose sexual activities are found to be strongly connected. There is saturation in the high-risk group, but changes in sexual behavior are more important in obtaining adequate fits. The simulation modeling yields useful parameter estimates, but the remaining uncertainty in parameter values implies that the simulation forecasts are also uncertain. Changes in HIV incidence lead to changes in AIDS incidence about 6-10 years later. Simulation models with and without zidovudine treatment both fit the incidence data; thus the effects of therapy on AIDS incidence are unclear. The fits of the simulation model are most sensitive to the yearly migration rate, the number of stages in the progression to AIDS, and the average number of new sexual partners per month; thus better estimates of these parameters would be desirable.

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Year:  1991        PMID: 1806103     DOI: 10.1016/0025-5564(91)90078-w

Source DB:  PubMed          Journal:  Math Biosci        ISSN: 0025-5564            Impact factor:   2.144


  5 in total

Review 1.  Sensitivity analysis of infectious disease models: methods, advances and their application.

Authors:  Jianyong Wu; Radhika Dhingra; Manoj Gambhir; Justin V Remais
Journal:  J R Soc Interface       Date:  2013-07-17       Impact factor: 4.118

Review 2.  Mathematical models for the study of HIV spread and control amongst men who have sex with men.

Authors:  Narat Punyacharoensin; William John Edmunds; Daniela De Angelis; Richard Guy White
Journal:  Eur J Epidemiol       Date:  2011-09-20       Impact factor: 8.082

3.  Modelling the effect of treatment and behavioral change in HIV transmission dynamics.

Authors:  J X Velasco-Hernandez; Y H Hsieh
Journal:  J Math Biol       Date:  1994       Impact factor: 2.259

4.  Thinking clearly about social aspects of infectious disease transmission.

Authors:  Caroline Buckee; Abdisalan Noor; Lisa Sattenspiel
Journal:  Nature       Date:  2021-06-30       Impact factor: 49.962

5.  Cost-effective control of chronic viral diseases: finding the optimal level of screening and contact tracing.

Authors:  Benjamin Armbruster; Margaret L Brandeau
Journal:  Math Biosci       Date:  2010-01-04       Impact factor: 2.144

  5 in total

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