Evaluating large-scale HIV prevention interventions: study design for an integrated mathematical modelling approach.

BACKGROUND: There is an urgent need to evaluate HIV prevention interventions, thereby improving our understanding of what works, under what circumstances and what is cost effective. OBJECTIVES: To describe an integrated mathematical evaluation framework designed to assess the population-level impact of large-scale HIV interventions and applied in the context of Avahan, the Indian AIDS Initiative, in southern India. The Avahan Initiative is a large-scale HIV prevention intervention, funded by the Bill & Melinda Gates Foundation, which targets high-risk groups in selected districts of the six states most affected by the HIV/AIDS epidemic (Maharashtra, Karnataka, Tamil Nadu, Andhra Pradesh, Nagaland and Manipur) and along the national highways. METHODS: One important component of the monitoring and evaluation of Avahan relies on an integrated mathematical framework that combines empirical biological and behavioural data from different subpopulations in the intervention areas, with the use of tailor-made transmission dynamics models embedded within a Bayesian framework. RESULTS: An overview of the Avahan Initiative and the objectives of the monitoring and evaluation of the intervention is given. The rationale for choosing this evaluation design compared with other possible designs is presented, and the different components of the evaluation framework are described and its advantages and challenges are discussed, with illustrated examples. CONCLUSIONS: This is the first time such an approach has been applied on such a large scale. Lessons learnt from the CHARME project could help in the design of future evaluations of large-scale interventions in other settings, whereas the results of the evaluation will be of programmatic and public health relevance.

What is the achievable effectiveness of the India AIDS Initiative intervention among female sex workers under target coverage? Model projections from southern India.

BACKGROUND: The India AIDS Initiative (Avahan) prevention programme funded by the Bill and Melinda Gates Foundation aims to reduce HIV prevalence in high risk groups such as female and male sex workers and their clients, to limit HIV transmission in the general population. OBJECTIVES: To assess the potential effectiveness of the Avahan intervention at the level of coverage targeted, in different epidemiological settings in India. METHODS: A deterministic compartmental model of the transmission dynamics of HIV and two sexually transmitted infections, and sensitivity analysis techniques, were used, in combination with available behavioural and epidemiological data from Mysore and Bagalkot districts in the Indian state of Karnataka, to evaluate the syndromic sexually transmitted infection (STI) management (STI treatment), periodic presumptive treatment of STI (PPT), and condom components of the Avahan intervention targeted to female sex workers (FSW). RESULTS: If all components of the intervention reach target coverage (that is, PPT, STI treatment and condom use), the intervention is expected to prevent 22-35% of all new HIV infections in FSW and in the total population over 5 years in a low transmission setting like Mysore, and to be half as effective in high transmission settings such as Bagalkot. The results were sensitive to small variations in intervention coverage. The condom component alone is expected to prevent around 20% of all new HIV infections over 5 years in Mysore and around 6% for the STI component alone; compared with 7%-14% for the PPT component alone. Multivariate sensitivity analyses suggested that interventions may be more effective in settings with low FSW HIV prevalence and small FSW populations, whereas HIV prevalence was most influenced by sexual behaviour and condom use parameters for FSW. CONCLUSION: The Avahan intervention is expected to be effective. However, to be able to demonstrate effectiveness empirically in the different settings, it is important to achieve target coverage or higher, which in the case of PPT could take a number of years to achieve. These preliminary model predictions need to be validated with more detailed mathematical models, as better data on sexual behaviour, condom use, STI and HIV trends over time, and intervention coverage data accumulate over the course of the programme.