Objective:The UNAIDS modes of transmission model (MoT) is a user-friendly model, developed to predict the distribution of new HIV infections among different subgroups. The model has been used in 29 countries to guide interventions. However, there is the risk that the simplifications inherent in the MoT produce misleading findings. Using input data from Nigeria, we compare projections from the MoT with those from a revised model that incorporates additional heterogeneity.Methods:We revised the MoT to explicitly incorporate brothel and street-based sex-work, transactional sex, and HIV-discordant couples. Both models were parameterized using behavioural and epidemiological data from Cross River State, Nigeria. Model projections were compared, and the robustness of the revised model projections to different model assumptions, was investigated.Results:The original MoT predicts 21% of new infections occur in most-at-risk-populations (MARPs), compared with 45% (40–75%, 95% Crl) once additional heterogeneity and updated parameterization is incorporated. Discordant couples, a subgroup previously not explicitly modelled, are predicted to contribute a third of new HIV infections. In addition, the new findings suggest that women engaging in transactional sex may be an important but previously less recognized risk group, with 16% of infections occurring in this subgroup.Conclusion:The MoT is an accessible model that can inform intervention priorities. However, the current model may be potentially misleading, with our comparisons in Nigeria suggesting that the model lacks resolution, making it challenging for the user to correctly interpret the nature of the epidemic. Our findings highlight the need for a formal review of the MoT.

of sero-discordant partnerships and 'transactional sex' groups (a relatively large subset of the population, often ignored in modelling analysis) in the model, which are classified as 'high-risk'.The UNAIDS MoT remains an accessible and potentially useful model that can help inform intervention priorities. However, our findings strongly suggest that the current model may produce misleading findings, especially in more concentrated HIV epidemic settings. Results from this study indicate the need for UNAIDS to conduct a formal review of the MoT, and for further revisions to be made.

BackgroundThe HIV epidemic in Nigeria is complex with substantial heterogeneity in its distribution across different regions and diverse factors that drive the epidemic. Therefore, it is critical that HIV prevention programmes and strategies match the local context and that resources are allocated to interventions with the greatest impact. Nigeria’s National Agency for the Control of AIDS (NACA) is coordinating a large-scale initiative to conduct rapid epidemic appraisals across most states, including the mapping and size estimates of female sex workers (FSWs). Seven states have completed the appraisal of FSWs, and are now planning programmes accordingly.MethodologyMapping was done using a two-level process of identifying and validating locations where FSWs solicit and/or meet clients. The first level involved conducting interviews with secondary key informants to collect information on the location and profile of hotspots, size estimates and typology of FSWs. The second level was done by interviewing primary key informants (FSWs themselves) at each hotspot to validate the information collected and generate more detailed information.ResultsA total of 10,233 hotspots were identified across the states and 126,489 FSWs {Hotel/Lodge (29.6%) Bar/Nightclub (30%), Home based (4.1%), Brothel (14.6%) and Street based (16.6%)} were mapped. There was substantial variability in the population density of FSWs (per thousand adult men) across the states ranging from 17 in Abuja to 2 in Anambra. Furthermore, there were clear differences in the density of FSWs per spot with the mean number of FSWs/spot ranging from 17 in Abuja to 8 in Ondo.ConclusionThe FSW population in Nigeria is large and diverse, with substantial differences between and within states with respect to the population size, density and organisational typologies of sex work. This information is central to Nigeria’s planning process for scaling up focused HIV prevention programmes and services.