Comparing the impact of increasing condom use or HIV pre-exposure prophylaxis (PrEP) use among female sex workers.

In many settings, interventions targeting female sex workers (FSWs) could significantly reduce the overall transmission of HIV. To understand the role HIV pre-exposure prophylaxis (PrEP) could play in controlling HIV transmission amongst FSWs, it is important to understand how its impact compares with scaling-up condom use-one of the proven HIV prevention strategies for FSWs. It is important to remember that condoms also have other benefits such as reducing the incidence of sexually transmitted infections and preventing pregnancy. A dynamic deterministic model of HIV transmission amongst FSWs, their clients and other male partners (termed 'pimps') was used to compare the protection provided by PrEP for HIV-negative FSWs with FSWs increasing their condom use with clients and/or pimps. For different HIV prevalence scenarios, levels of pimp interaction, and baseline condom use, we estimated the coverage of PrEP that gives the same reduction in endemic FSW HIV prevalence or HIV infections averted as different increases in condom use. To achieve the same impact on FSW HIV prevalence as increasing condom use by 1%, the coverage of PrEP has to increase by >2%. The relative impact of PrEP increases for scenarios where pimps contribute to HIV transmission, but not greatly, and decreases with higher baseline condom use. In terms of HIV infections averted over 10 years, the relative impact of PrEP compared to condoms was reduced, with a >3% increase in PrEP coverage achieving the same impact as a 1% increase in condom use. Condom promotion interventions should remain the mainstay HIV prevention strategy for FSWs, with PrEP only being implemented once condom interventions have been maximised or to fill prevention gaps where condoms cannot be used

Modelling the effects of condom use and antiretroviral therapy in controlling HIV/AIDS among heterosexuals, homosexuals and bisexuals.

A deterministic compartmental sex-structured HIV/AIDS model for assessing the effects of homosexuals and bisexuals in heterosexual settings in which homosexuality and bisexuality issues have remained taboo is presented. We extend the model to focus on the effects of condom use as a single strategy approach in HIV prevention in the absence of any other intervention strategies. Initially, we model the use of male condoms, followed by incorporating the use of both the female and male condoms. The model includes two primary factors in condom use to control HIV which are condom efficacy and compliance. Reproductive numbers for these models are computed and compared to assess the effectiveness of male and female condom use in a community. We also extend the basic model to consider the effects of antiretroviral therapy as a single strategy. The results from the study show that condoms can reduce the number of secondary infectives and thus can slow the development of the HIV/AIDS epidemic. Further, we note from the study that treatment of AIDS patients may enlarge the epidemic when the treatment drugs are not 100% effective and when treated AIDS patients indulge in risky sexual behaviour. Thus, the treatment with amelioration of AIDS patients should be accompanied with intense public health educational programs, which are capable of changing the attitude of treated AIDS patients towards safe sex. It is also shown from the study that the use of condoms in settings with the treatment may help in reducing the number of secondary infections thus slowing the epidemic

Modelling the effect of market forces on the impact of introducing human immunodeficiency virus pre‐exposure prophylaxis among female sex workers

Pre-exposure prophylaxis (PrEP) to prevent human immunodeficiency virus (HIV) enables female sex workers (FSWs) to protect themselves from HIV without relying on clients using condoms. Yet, because PrEP reduces HIV risk, financial incentives to not use condoms may lead to risk compensation: reductions in condom use and/or increases in commercial sex, and may reduce the price of unprotected sex. In this analysis, we integrate market forces into a dynamic HIV transmission model to assess how risk compensation could change the impact of PrEP among FSWs and clients. We parameterise how sexual behavior may change with PrEP use among FSWs using stated preference data combined with economic theory. Our projections suggest the impact of PrEP is sensitive to risk compensatory behaviors driven by changes in the economics of sex work. Condom substitution could reduce the impact of PrEP on HIV incidence by 55%, while increases in the frequency of commercial sex to counter decreases in the price charged for unprotected sex among PrEP users could entirely mitigate the impact of PrEP. Accounting for competition between PrEP users and nonusers exacerbates this further. Alternative scenarios where increases in unprotected sex among PrEP users are balanced by decreases in non-PrEP users have the opposite effect, resulting in PrEP having much greater impact. Intervention studies need to determine how HIV prevention products may change the economics of sex work and provision of unprotected sex to enable a better understanding of their impact

Examining Type 1 Diabetes Mathematical Models Using Experimental Data

Type 1 diabetes requires treatment with insulin injections and monitoring glucose levels in affected individuals. We explored the utility of two mathematical models in predicting glucose concentration levels in type 1 diabetic mice and determined disease pathways. We adapted two mathematical models, one with [Formula: see text]-cells and the other with no [Formula: see text]-cell component to determine their capability in predicting glucose concentration and determine type 1 diabetes pathways using published glucose concentration data for four groups of experimental mice. The groups of mice were numbered Mice Group 1–4, depending on the diabetes severity of each group, with severity increasing from group 1–4. A Markov Chain Monte Carlo method based on a Bayesian framework was used to fit the model to determine the best model structure. Akaike information criteria (AIC) and Bayesian information criteria (BIC) approaches were used to assess the best model structure for type 1 diabetes. In fitting the model with no [Formula: see text]-cells to glucose level data, we varied insulin absorption rate and insulin clearance rate. However, the model with [Formula: see text]-cells required more parameters to match the data and we fitted the [Formula: see text]-cell glucose tolerance factor, whole body insulin clearance rate, glucose production rate, and glucose clearance rate. Fitting the models to the blood glucose concentration level gave the least difference in AIC of [Formula: see text] , and a difference in BIC of [Formula: see text] for Mice Group 4. The estimated AIC and BIC values were highest for Mice Group 1 than all other mice groups. The models gave substantial differences in AIC and BIC values for Mice Groups 1–3 ranging from [Formula: see text] to [Formula: see text]. Our results suggest that the model without [Formula: see text]-cells provides a more suitable structure for modelling type 1 diabetes and predicting blood glucose concentration for hypoglycaemic episodes

Assessing the Potential Impact of Hormonal-Based Contraceptives on HIV Transmission Dynamics Among Heterosexuals.

HIV susceptibility linked to hormonal contraception (HC) has been studied before, but with mixed results. Reports from some of the recent findings have prompted the World Health Organisation to encourage women who use HC to concurrently use condoms in order to prevent HIV infection in the light of possible increased HIV risk of infection associated with hormone-based contraceptives. A two-sex HIV model classifying women into three risk groups consisting of individuals who use condoms, natural methods, and hormone-based contraceptives is formulated and analysed to assess the possible effects of various birth control strategies on the transmission dynamics of the disease. Our model results showed that women who use HC could be key drivers of the epidemic and that their increased infectivity may be critical in driving the epidemic. Women who use hormone-based contraceptives potentially act as a core group from which men get infected and in turn transmit the disease to other population groups. We fitted the model to HIV prevalence data for Zimbabwe reported by UNAIDS and Zimbabwe Ministry of Health and Child Care and used the model fit to project HIV prevalence. Predictions using HIV data for Zimbabwe suggest that a hypothesised increase in susceptibility and infectivity of two-, three-, and fourfold would result in a 25, 50, and 100% increase in baseline HIV prevalence projection, respectively, thus suggesting possible increased disease burden even in countries reporting plausible HIV prevalence declines. Although a possible causal relationship between HIV susceptibility and HC use remains subject of continuing scientific probe, its inclusion as part of birth control strategy has been shown in this study, to possibly increase HIV transmission. If proven, HC use may potentially explain the inordinate spread of HIV within the sub-Saharan Africa region and therefore compel for urgent assessment with a view to reorienting birth control methods in use in settings with generalised epidemics

Is modelling complexity always needed?:Insights from modelling PrEP introduction in South Africa

BACKGROUND: Mathematical models can be powerful policymaking tools. Simple, static models are user-friendly for policymakers. More complex, dynamic models account for time-dependent changes but are complicated to understand and produce. Under which conditions are static models adequate? We compare static and dynamic model predictions of whether behavioural disinhibition could undermine the impact of HIV pre-exposure prophylaxis (PrEP) provision to female sex workers in South Africa. METHODS: A static model of HIV risk was developed and adapted into a dynamic model. Both models were used to estimate the possible reduction in condom use, following PrEP introduction, without increasing HIV risk. The results were compared over a 20-year time horizon, in two contexts: at epidemic equilibrium and during an increasing epidemic. RESULTS: Over time horizons of up to 5 years, the models are consistent. Over longer timeframes, the static model overstates the tolerated reduction in condom use where initial condom use is reasonably high ($\ge$50%) and/or PrEP effectiveness is low ($\le$45%), especially during an increasing epidemic. CONCLUSIONS: Static models can provide useful deductions to guide policymaking around the introduction of a new HIV intervention over short-medium time horizons of up to 5 years. Over longer timeframes, static models may not sufficiently emphasise situations of programmatic importance, especially where underlying epidemics are still increasing

Temporal stability of HIV prevalence in high-burden areas regardless of declines in national HIV prevalence in Malawi and Zimbabwe.

: The current study aims to assess the subnational temporal trends in HIV prevalence in Malawi and Zimbabwe. Using data from three Demographic and Health Surveys (DHS) conducted in Malawi and Zimbabwe, we found that national HIV prevalence in both countries substantially declined, large declines occurred in areas where HIV prevalence was already low, and HIV prevalence in high-burden areas remained stable over time. Well designed HIV prevention programmes targeting hotspots are required for effective HIV control in countries with declining HIV prevalence

Projecting the impact of anal intercourse on HIV transmission among heterosexuals in high HIV prevalence settings.

Whereas penile vaginal intercourse (VI) is thought to be the dominant mode of HIV transmission in sub-Saharan Africa, cross-sectional studies in the region indicate the preponderance of heterosexual anal intercourse (AI) among high activity groups. A dynamic, heterosexual core group model with risk of infection through both vaginal and anal pathways is formulated and comprehensively analysed. The model is coupled to a general population model and fitted to HIV prevalence data for Zimbabwe in order to explore the parameter space related to heterosexual AI. The model fit supports a core group size ranging between 5-20% and exposure risk to AI in excess of 50%. The control effort quantified by the reproductive number (RA) at commencement of the epidemic corresponds to R0=4.40. With the contribution of heterosexual AI to Zimbabwe's (and that of the sub-Saharan African region) epidemic unknown, the study apportioned infections between the two infection pathways. New infections due to VI ranged from 2-4.5% and 0.5-2.7% from heterosexual AI. The study estimates infection probabilities ranging from 0.15 to 0.35 for both receptive and infective AI. By quantifying the incidence due to VI and AI risks, we put emphasis on the necessity for targeted interventions. To project the potential impact of heterosexual AI in high HIV prevalence settings, we raised the core group size to 20% in the year 2010 coinciding with reported heterosexual AI prevalence outside of Africa and allowed the proportion of infection risk associated with AI to vary. Prevalence and incidence projections were made up to the year 2020 starting from a baseline value of zero exposure to AI transmission risk per sex act, progressively increasing exposure to 50% and 70% respectively. A 50% exposure to AI would result in HIV prevalence scaling up by 23% from the baseline values in year 2020. Increasing exposure to 70% was projected to increase HIV prevalence by 38% in year 2020. The HIV infection risks associated with AI are recognised and inform HIV policy for men who have sex with men, yet the same risks are ignored in HIV intervention programmes for heterosexuals. This study highlights the potential danger of increasing prevalence of heterosexual AI in settings with high HIV prevalence. Evolving and globally cross pollinating sexual behaviors compel for dovetailing HIV policy making with sexology

Modelling the effect of market forces on the impact of introducing HIV pre-exposure prophylaxis among female sex workers

HIV pre-exposure prophylaxis (PrEP) enables female sex workers (FSWs) to protect themselves from HIV without relying on clients using condoms. Yet, because PrEP reduces HIV risk, financial incentives to not use condoms may lead to risk compensation: reductions in condom use and/or increases in commercial sex, and may reduce the price of unprotected sex. In this analysis, we integrate market forces into a dynamic HIV transmission model to assess how risk compensation could change the impact of PrEP among FSWs and clients. We parameterise how sexual behaviour may change with PrEP use among FSWs using stated preference data combined with economic theory. Our projections suggest the impact of PrEP is sensitive to risk compensatory behaviours driven by changes in the economics of sex work. Condom substitution could reduce the impact of PrEP on HIV incidence by 55%, while increases in the frequency of commercial sex to counter decreases in the price charged for unprotected sex among PrEP users could entirely mitigate the impact of PrEP. Accounting for competition between PrEP users and non-users exacerbates this further. Alternative scenarios where increases in unprotected sex among PrEP users are balanced by decreases in non-PrEP users have the opposite effect, resulting in PrEP having much greater impact. Intervention studies need to determine how HIV prevention products may change the economics of sex work and provision of unprotected sex to enable a better understanding of their impact