Global HIV incidence remains unacceptably high and the Joint United Nations Programme on HIV/AIDS (UNAIDS) estimated that 2.7 million [2.4 million–3.0 million] people were newly infected with HIV in 2008 (1). About 70% of these infections occurred in sub-Saharan Africa. In South Africa alone, the number of new infections in 2008 was estimated to be between 400,000 and 500,000 (2). Although this number has declined since its peak in the late 1990s, there is little evidence that prevention efforts have had an impact on the epidemic.

Improved HIV prevention programmes based on an understanding of epidemic patterns

Effective planning and delivery of HIV prevention programs depends on an understanding of where new infections are occurring and on the behaviours associated with those infections. Thailand provides an example of how comprehensive prevention strategies aimed at the main modes of transmission in the early years of the epidemic, sex work and injecting drug use (IDU), lead to significant reductions in incidence and, by the mid-1990s, became one of the first countries to reduce HIV prevalence (3). Unfortunately such success stories are few and often the response in a country does not adequately match the epidemic patterns, resulting in missed opportunities to address those risk factors that drive HIV epidemics.

A simple mathematical model was developed by the UNAIDS Reference Group for Estimates, Modelling and Projections to help countries estimate the proportion of new infections that occur through key transmission modes including sex work, IDU, men who have sex with men (MSM), multiple heterosexual partnerships, stable (discordant) relationships and medical interventions, using basic epidemiological and behavioural data as input. Initial application of the model in 2003 (4) and 2005 (5) illustrated the variation in patterns of new infections between countries and argued that this type of in-country analysis could be used to inform the planning of appropriately targeted intervention programmes. At the same time, the papers called for improved biological and behavioural surveillance in countries that will provide more reliable data for input into such analyses.

Calculating HIV incidence by modes of transmission

The UNAIDS “incidence by modes of transmission” model assumes that the risk of HIV infection in a susceptible individual in a particular risk category is a function of the number of sexual/injecting partners and the number of contacts with each partner, and depends on the current prevalence of HIV infection among the partner populations. The calculation takes account of the proportion of acts that are protected through condom use or the use of sterile needles while the presence of sexually transmitted infections (STIs) is considered in estimating the probability of sexual transmission. The probability of female-to-male transmission of HIV is adjusted according to the level of male circumcision, assuming that circumcision reduces transmission by 60%.

Data needed to calculate the expected incidence per year in countries include the size of each of the risk groups, prevalence of HIV and STIs by risk group, average number of exposures to HIV (number of partners and number of acts of exposure per partner) per year and the proportion of exposures that are protected. Biological parameters include the probability of transmission per unprotected exposure to HIV within each risk group, taking account of the effects of STIs and male circumcision. The model and instructions for application are available on the UNAIDS website (6).

Results from countries participating in southern and East Africa

Since 2007, several countries in southern and East Africa have been participating in projects to estimate the number of new infections by mode of transmission, with support from UNAIDS and the World Bank. The studies are typically conducted by national teams and are usually accompanied by a thorough review and analysis of all HIV epidemiological data in a country. In the case of missing data, imputations can be made from regional estimates or data from neighbouring countries with similar epidemic patterns. Sensitivity analyses have been conducted in some countries where multiple data sources have resulted in a range of potential data inputs. South Africa is currently in the process of finalizing a similar study under the leadership of the South African National AIDS Council, with technical support from UNAIDS, the World Bank and SACEMA.

Reports on the epidemiological reviews and the results of some studies in southern and East Africa are available on the website of the UNAIDS Regional Support Team (7). Figure 1 shows the estimated proportion of new infections by modes of transmission for Lesotho, Kenya, Swaziland, Uganda and Zambia. As expected for generalized epidemics, the majority of new infections in countries in southern and East Africa occur in the general population through heterosexual transmission either as a result of people having multiple partners, or in stable discordant couples (couples in which only one of the partners is sero-positive for HIV). Sex work (including sex workers, clients of sex workers and their regular partners) accounted for between 3% and 16% of new infections in these countries, while MSM and IDU accounted for substantial proportions of new infections in Kenya.

Figure 1. Proportion of new HIV infections by risk category in five countries in southern and East Africa [Data source: MOT reports (7)]

Prevention and data collection priorities

The results of the incidence by modes of transmission analysis in southern and East Africa suggest that prevention efforts need to focus on reducing the risk of multiple partnerships, expanding testing programs to identify discordant couples, and increasing or maintaining high levels of condom use in sexual relationships. While data on MSM in Africa are limited and MSM behaviour is still stigmatized or illegal in many countries, it is recognized that such behaviour does occur throughout Africa. The modelling suggests that new infections among MSM might be higher than previously believed, so that prevention efforts should also reach these populations.

The main limitations of the model are associated with limitations in data availability, data quality and measurement procedures in countries. In countries with generalized HIV epidemics, data on groups that are particularly vulnerable such as sex workers and MSM are often limited, while behavioural data obtained from large population based surveys might be subject to social desirability bias. Despite these limitations, modelling the modes of transmission in countries with relevant and reliable data has provided valuable information and countries have reported that results are useful in guiding prevention efforts. At the same time, countries that have conducted the modelling exercise have all identified an urgent need for improved data in order to better understand and respond to specific risk behaviours. In Kenya, a national study is currently underway to collect better data on the extent of the MSM problem, while further modelling is conducted to estimate the increase in injecting drug use and its effect on HIV in recent years.

Modes of transmission studies are currently being conducted in different regions across the world. Study reports are being finalized in six countries in West Africa, while studies are ongoing or starting in several countries in Latin America, the Middle East and North Africa, and in Asia. In South Africa, the incidence by modes of transmission analysis is expected to provide substantive input for the prevention component of the mid-term review of the national strategic plan. As data sources and data quality improve over time, along with improvements in the modes of transmission model, analyses of this type are expected to be conducted in the coming years in an increasing number of countries with increasing precision, helping to guide prioritisation of prevention programmes.

Reference(s)

1. UNAIDS and WHO. AIDS Epidemic Update: 2009. Geneva: UNAIDS and WHO; 2009. Link to report
2. National Department of Health. The National HIV and Syphilis prevalence survey South Africa 2008. Pretoria: National Department of Health; 2009. Link to report
3. Ministry of Public Health Thailand, World Health Organization Regional Office for South-East Asia. External review of the health sector response to HIV/AIDS in Thailand. India: WHO; 2005. Link to report
4. Pisani E, Garnett GP, Brown T, et al. Back to basics in HIV prevention: focus on exposure. BMJ. 2003;326(7403):1384-1387. Link to article
5. Gouws E, White PJ, Stover J, Brown T. Short term estimates of adult HIV incidence by mode of transmission: Kenya and Thailand as examples. Sex Transm Infect. 2006;82 Suppl 3:iii51-55. Link to article
6. UNAIDS. Epidemiological software and tools (2009). http://www.unaids.org/en/KnowledgeCentre/HIVData/Epidemiology/EPI_software2009.asp Accessed March 8, 2010.
7. UNAIDS. Regional Support Team for Eastern and Southern Africa – modes of transmission. http://www.unaidsrstesa.org/hiv-prevention-modes-of-transmission Accessed March 8, 2010.