Using mathematical models to understand the AIDS epidemic

Hyman, James M.; Stanley, E. Ann

doi:10.1016/0025-5564(88)90078-8

Cited by 216 publications

(103 citation statements)

References 28 publications

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“…We have analyzed the growth of HIV in a simplified version of the model presented by Hyman and Stanley [15] for a homosexual community 147 wherein sexual behavior is assumed to be heterogeneous.…”

Section: Discussionmentioning

confidence: 99%

“…However, recent surveys show that the total number of AIDS cases reported to the Centers for Disease Control (CDCI in the United States has grown as the cube of time [9,11,15,161, which implies that the growth rate is decreasing inversely with time. These data relate to AIDS patients infected before the publicity campaigns for AIDS prevention began; thus it is improbable that cubic growth is due to modified sexual behavior.…”

Section: Introductionmentioning

confidence: 99%

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Analysis of a risk-based model for the growth of AIDS infection

Young

Maini

Nakamaye

1991

Mathematical Biosciences

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Analysis of a risk-based model for the growth of AIDS infection

Young

Maini

Nakamaye

1991

Mathematical Biosciences

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“…Individual risk-based models of the dynamics of the spread of HIV infection require data on the behavioural patterns of MSM and injection drug users [28]. In particular, these models require estimates of the number of new partners per year, the number and type of sexual contacts, the viral load of each infected partner, the proportion of sexual contacts where a condom was used, the number of instances of needle sharing, and the probability of infection from a single sexual contact or a single instance of needle sharing.…”

Section: Models Of Hiv Transmissionmentioning

confidence: 99%

Assessing the Cost Effectiveness of Pre-Exposure Prophylaxis for HIV Prevention in the US

Hellinger

2013

PharmacoEconomics

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About 50,000 people are infected with HIV in the US each year and this number has remained virtually the same for the past decade. Yet, in the last few years, evidence from several multinational randomized clinical trials has shown that the provision of antiretroviral drug to uninfected persons (i.e. pre-exposure prophylaxis) reduces the incidence of HIV by about 50 %. However, evidence from cost-effectiveness studies conducted in the US yield widely varying estimates of the cost per quality-adjusted life-year (QALY) gained, and this variation reflects the substantial uncertainty surrounding the determinants of HIV transmission (e.g. adherence rates to prophylactic medications, the average number of sexual partners, the number and types of sexual acts, the viral load of infected partners, and the proportion of contacts where condoms are used), as well as different approaches to translating a reduction in HIV cases into an estimate of the increase in the number of QALYs. Key Points for Decision Makers• Pre-exposure prophylaxis programs have the potential to lower the cost of the HIV epidemic in the US.• Studies of the cost effectiveness of pre-exposure prophylaxis programs should explain and justify assumptions underlying their economic model of HIV transmission.• It is important to recognize that different assumptions about the patterns of sexual behaviour of men who have sex with men may produce very different estimates of the cost effectiveness of pre-exposure prophylaxis programs.

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“…However, Hyman and Stanley (1988) found such estimates to be very sensitive to the assumed nature of the probability distribution of the length of the incubation period;…”

Section: Back-calculationmentioning

confidence: 99%

“…Recently, Hyman and Stanley (1989) explored the sensitivity of an HIV transmission model to different social mixing patterns. This model was more general than that in Hyman and Stanley (1988) since it simultaneously included both continuous distributions for sexual partner change rates and also variable infectivity as a function of time since infection. A Weibull distribution was used for the AIDS incubation period.…”

Section: Multigroup Modelsmentioning

confidence: 99%

Statistical and Mathematical Approaches in HIV/AIDS Modeling: A Review

Schwager

Castillo‐Chavez

Hethcote

1989

Lecture Notes in Biomathematics

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This paper provides a brief introduction to the field and the literature of statistical and mathematical approaches to HIV I AIDS modeling. The emphasis is on succinct description of the methodology and on discussion of the work of some researchers who were unable to contribute to this volume. This review is not complete; however, it is complemented to a great degree by the partial reviews of the literature provided by several authors in their contributions to this volume. An additional objective of this introductory chapter is to describe to nonspecialists, in general terms, some of the main statistical and mathematical approaches currently used in problems related to AIDS epidemiology. This paper provides a brief introduction to the field and the literature of statistical and mathematical approaches to HIV /AIDS modeling. The emphasis is on succinct description of the methodology and on discussion of the work of some researchers who were unable to contribute to this volume. This review is not complete; however, it is complemented to a great degree by the partial reviews of the literature provided by several authors in their contributions to this volume. An additional objective of this introductory chapter is to describe to nonspecialists, in general terms, some of the main statistical and mathematical approaches currently used in problems related to AIDS epidemiology.

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Using mathematical models to understand the AIDS epidemic

Cited by 216 publications

References 28 publications

Analysis of a risk-based model for the growth of AIDS infection

Analysis of a risk-based model for the growth of AIDS infection

Assessing the Cost Effectiveness of Pre-Exposure Prophylaxis for HIV Prevention in the US

Statistical and Mathematical Approaches in HIV/AIDS Modeling: A Review

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