The Incidence Patterns Model to Estimate the Distribution of New HIV Infections in Sub-Saharan Africa: Development and Validation of a Mathematical Model

Annick Bórquez, Anne Cori, Erica L. Pufall, Jingo Kasule, Emma Slaymaker, Alison Price, Jocelyn Elmes, Basia Zaba, Amelia C. Crampin, Joseph Kagaayi, Tom Lutalo, Mark Urassa, Simon Gregson, Timothy B. Hallett

Programmatic planning in HIV requires estimates of the distribution of new HIV infections according to identifiable characteristics of individuals. In sub-Saharan Africa, robust routine data sources and historical epidemiological observations are available to inform and validate such estimates.

We developed a predictive model, the Incidence Patterns Model (IPM), representing populations according to factors that have been demonstrated to be strongly associated with HIV acquisition risk: gender, marital/sexual activity status, geographic location, “key populations” based on risk behaviours (sex work, injecting drug use, and male-to-male sex), HIV and ART status within married or cohabiting unions, and circumcision status. The IPM estimates the distribution of new infections acquired by group based on these factors within a Bayesian framework accounting for regional prior information on demographic and epidemiological characteristics from trials or observational studies. We validated and trained the model against direct observations of HIV incidence by group in seven rounds of cohort data from four studies (“sites”) conducted in Manicaland, Zimbabwe; Rakai, Uganda; Karonga, Malawi; and Kisesa, Tanzania. The IPM performed well, with the projections’ credible intervals for the proportion of new infections per group overlapping the data’s confidence intervals for all groups in all rounds of data. In terms of geographical distribution, the projections’ credible intervals overlapped the confidence intervals for four out of seven rounds, which were used as proxies for administrative divisions in a country. We assessed model performance after internal training (within one site) and external training (between sites) by comparing mean posterior log-likelihoods and used the best model to estimate the distribution of HIV incidence in six countries (Gabon, Kenya, Malawi, Rwanda, Swaziland, and Zambia) in the region. We subsequently inferred the potential contribution of each group to transmission using a simple model that builds on the results from the IPM and makes further assumptions about sexual mixing patterns and transmission rates. In all countries except Swaziland, individuals in unions were the single group contributing to the largest proportion of new infections acquired (39%–77%), followed by never married women and men. Female sex workers accounted for a large proportion of new infections (5%–16%) compared to their population size. Individuals in unions were also the single largest contributor to the proportion of infections transmitted (35%–62%), followed by key populations and previously married men and women. Swaziland exhibited different incidence patterns, with never married men and women accounting for over 65% of new infections acquired and also contributing to a large proportion of infections transmitted (up to 56%). Between- and within-country variations indicated different incidence patterns in specific settings.

It is possible to reliably predict the distribution of new HIV infections acquired using data routinely available in many countries in the sub-Saharan African region with a single relatively simple mathematical model. This tool would complement more specific analyses to guide resource allocation, data collection, and programme planning.

October 13, 2016
Year of publication
Resource types
Journal and research articles, Programmatic guidance, Tools
programmatic planning, program planning, data use, predictive models, HIV risk, risk factors, risk behavior, Gabon, Kenya, Malawi, Rwanda, Swaziland, Zambia, HIV distribution, data collection, mathematical modeling, incidence patterns

Similar Resources

Cochrane works collaboratively with contributors around the world to produce authoritative, relevant, and reliable evidence, in the form of Cochrane Reviews.

Despite considerable efforts to scale up voluntary medical male circumcision (VMMC) for HIV prevention in priority countries over the last five years, implementation has faced important challenges. Seeking to enhance the effect of VMMC programs for greatest and most immediate impact, the U. S.…

In late 2015, the Linkages Across the Continuum of HIV Services for Key Populations (LINKAGES) project established a global acceleration initiative to fast-track and strengthen delivery of a comprehensive package of health services for key populations (KPs) at scale. In this context, “…

The government of the Kingdom of Swaziland recognizes that it must urgently scale up HIV prevention interventions, such as voluntary medical male circumcision (VMMC). Swaziland has adopted a 2-phase approach to male circumcision scale-up.

Swaziland has the highest national HIV prevalence worldwide. The Swaziland HIV Incidence Measurement Survey (SHIMS) provides the first national HIV incidence estimate based on prospectively observed HIV seroconversions.

The Cochrane Library (ISSN 1465-1858) is a collection of six databases that contain different types of high-quality, independent evidence to inform healthcare decision-making, and a seventh database that provides information about Cochrane groups.

Timely access to antiretroviral treatment (ART) is vital to ensuring safe motherhood and reducing vertical transmission. Treatment guidance and programming has changed dramatically in recent years.

In 2014, USAID/Tanzania awarded the Tanzania Strengthening Police and Prison Comprehensive HIV Services (SPPCHS) project as an initiative under the AIDSFree project.

HIV prevalence data collected from routine HIV testing of pregnant women at antenatal clinics (ANC-RT) are potentially available from all facilities that offer testing services to pregnant women and can be used to improve estimates of national and subnational HIV prevalence trends.