# **SUMMARY**

Understanding and monitoring longitudinal HIV incidence trends is imperative for tracking progress towards HIV prevention goals, including how incidence trends have changed through increasing antiretroviral therapy (ART) coverage. There are several ways that HIV incidence can be assessed, empirical and modeled, and each method has its limitations. Incidence can be directly measured from prospective cohort studies, but logistical and financial restraints make this difficult to carry out at a scale that provides sufficient precision of the incidence estimate. Sampling of specimen within a population and using laboratory assays and testing algorithms that identify recent HIV infection can infer HIV incidence, though this method requires local validation against HIV incidence estimates obtained by other methods. Proxies of HIV incidence, such as HIV prevalence trends in young females, can also be used to infer incidence trends, as most HIV infections within this demographic are recent. However, this method requires repeat cross-sectional measurements over several years in order to infer any incidence trend. Finally, HIV incidence can be obtained through back-calculation models that use various HIV epidemiological data, including HIV prevalence and mortality rates, to estimate incidence within the adult population. Here, estimated incidence chiefly relies on prevalence estimates and factors that affect survival, including the effect of age and cofactors of transmission as well as the model’s accurate representation of sexual behavior and transmission dynamics.

Modeled incidence estimates provided by UNAIDS are key information that policy makers and HIV program managers use to monitor the dynamics of the HIV epidemics in various countries. Therefore, it is important to evaluate how these HIV incidence and proxies of it (HIV prevalence trends in young females) correspond to modeled incidence data. To date, no report has comprehensively triangulated and compared modelled HIV incidence against several forms and sources of directly and indirectly measured incidence across multiple countries.

We therefore compared UNAIDS incidence estimates from the Spectrum model to directly measured incidence from published studies and trials. We also compared UNAIDS modeled estimates to HIV prevalence trends in young females, as a proxy of incidence, using cross-sectional data from published studies and trials and national surveys, such as from antenatal sentinel surveillance and population-based surveys (Demographic and Health Survey/AIDS Indicator Survey data). This report represents a comprehensive source of both modeled and empirical incidence trends in several countries.

A select group of countries were chosen for this analysis due to their known generalized HIV epidemics (epidemics in which HIV is highly disseminated within the general population): Botswana, Burundi, Burkina Faso, Congo, Central African Republic, Ethiopia, Ghana, Kenya, Lesotho, Namibia, Nigeria, Malawi, Mozambique, Rwanda, South Africa, Swaziland, Tanzania, Uganda, Zambia, and Zimbabwe. Within each country, multiple forms and sources of incidence data, modeled and empirical, were graphed alongside ART coverage data, and longitudinal trends are described. Specifically, incidence trends 5