NoHIV stage is dominant in driving the HIV epidemic in sub-Saharan Africa
ABSTRACT To estimate the role of each of the HIV progression stages in fueling HIV transmission in sub-Saharan Africa by using the recent measurements of HIV transmission probability per coital per HIV stage in the Rakai study.
A mathematical model, parameterized by empirical data from the Rakai, Masaka, and Four-City studies, was used to estimate the proportion of infections due to each of the HIV stages in two representative epidemics in sub-Saharan Africa. The first setting represents a hyperendemic HIV epidemic (Kisumu, Kenya) whereas the second setting represents a generalized but not hyperendemic HIV epidemic (Yaoundé, Cameroon).
We estimate that 17, 51, and 32% of HIV transmissions in Kisumu were due to index cases in their acute, latent, and late stages, respectively. In Yaoundé, the fractions were 25, 44, and 31%. We found that the relative contribution of each stage varied with the epidemic evolution with the acute stage prevailing early on when the infection is concentrated in the high-risk groups with the late stage playing a major role as the epidemic matured and stabilized. The latent stage contribution remained largely stable throughout the epidemic and contributed about half of all transmissions.
No HIV stage dominated the epidemical though the latent stage provided the largest contribution. The role of each stage depends on the phase of the epidemic and on the prevailing levels of sexual risk behavior in the populations in which HIV is spreading. These findings may influence the design and implementation of different HIV interventions.
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ABSTRACT: Antiretroviral therapy (ART) reduces the infectiousness of HIV-infected persons, but only after testing, linkage to care, and successful viral suppression. Thus, a large proportion of HIV transmission during a period of high infectiousness in the first few months after infection ("early transmission") is perceived as a threat to the impact of HIV "treatment-as-prevention" strategies. We created a mathematical model of a heterosexual HIV epidemic to investigate how the proportion of early transmission affects the impact of ART on reducing HIV incidence. The model includes stages of HIV infection, flexible sexual mixing, and changes in risk behavior over the epidemic. The model was calibrated to HIV prevalence data from South Africa using a Bayesian framework. Immediately after ART was introduced, more early transmission was associated with a smaller reduction in HIV incidence rate-consistent with the concern that a large amount of early transmission reduces the impact of treatment on incidence. However, the proportion of early transmission was not strongly related to the long-term reduction in incidence. This was because more early transmission resulted in a shorter generation time, in which case lower values for the basic reproductive number (R0) are consistent with observed epidemic growth, and R0 was negatively correlated with long-term intervention impact. The fraction of early transmission depends on biological factors, behavioral patterns, and epidemic stage and alone does not predict long-term intervention impacts. However, early transmission may be an important determinant in the outcome of short-term trials and evaluation of programs.Proceedings of the National Academy of Sciences 10/2014; 111(45). DOI:10.1073/pnas.1323007111 · 9.81 Impact Factor
PLoS Medicine 03/2015; 12(3):e1001803. DOI:10.1371/journal.pmed.1001803 · 14.00 Impact Factor
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ABSTRACT: Circular migrations are the periodic movement of individuals between multiple locations, observed in parts of sub-Saharan Africa. Relationships between circular migrations and HIV are complex, entailing interactions between migration frequency, partnership structure, and exposure to acute HIV infection. Mathematical modeling is a useful tool for understanding these interactions. Two modeling classes have dominated the HIV epidemiology and policy literature for the last decade: one a form of compartmental models, the other network models. We construct models from each class, using ordinary differential equations and exponential random graph models, respectively. Our analysis suggests that projected HIV prevalence is highly sensitive to the choice of modeling framework. Assuming initial equal HIV prevalence across locations, compartmental models show no association between migration frequency and HIV prevalence or incidence, while network models show that migrations at frequencies shorter than the acute HIV period predict greater HIV incidence and prevalence compared to longer migration periods. These differences are statistically significant when network models are extended to incorporate a requirement for migrant men's multiple partnerships to occur in different locations. In settings with circular migrations, commonly-used forms of compartmental models appear to miss key components of HIV epidemiology stemming from interactions of relational and viral dynamics.Mathematical biosciences and engineering: MBE 10/2014; 11(5):1065-90. DOI:10.3934/mbe.2014.11.1065 · 0.87 Impact Factor