Predicting the Extinction of HIV-2 in Rural Guinea-Bissau

Objective: This article predicts the future epidemiology of HIV-2 in Caió, a rural region of Guinea Bissau; and investigates whether HIV-2, which has halved in prevalence between 1990 and 2007 and is now almost absent in young adults in Caió, can persist as an infection of the elderly.

Design: A mathematical model of the spread of HIV-2 was tailored to the epidemic in Caió, a village in Guinea-Bissau.

Methods: An age-stratified difference equation model of HIV-2 transmission was fitted to age-stratified HIV-2 incidence and prevalence data from surveys conducted in Caió in 1990, 1997 and 2007. A stochastic version of the same model was used to make projections.

Results: HIV-2 infection is predicted to continue to rapidly decline in Caió such that new infections will cease and prevalence will reach low levels (e.g. below 0.1%) within a few decades. HIV-2 is not predicted to persist in the elderly.

Conclusion: HIV-2 is predicted go extinct in Caió during the second half of this century.

Below:  Fig. 1. Data and model predictions of the incidence and prevalence of HIV-2 infection in Caió.(a) The prevalence of HIV-2 infection amongst individuals aged over 15 years. Observations are represented as circular markers. Between 1990 and 2007, the deterministic result is shown. Beyond 2007, the median and 95% confidence intervals of 5000 stochastic simulations are shown as solid and dashed markers, respectively. (b) The prevalence of HIV-2 (including dual HIV-1/2) stratified by age in 1990, 1997 and 2007. Owing to the fact that the initial conditions of the model were fixed to observations, the observations and model predictions for 1990 are identical. (c) The yearly incidence per person of HIV-2 stratified by age in the periods 1990–1997 and 1997–2007. In (b) and (c), the model predictions are shown using dashed lines and crosses, whereas the data are shown with solid lines and circles. The univariate 95% CI surrounding the data is also provided. (d) The prevalence of HIV-1 assumed in the model. Between 1990, 1997 and 2007, the assumed prevalence is interpolated from observations (black circles). Beyond 2007, the black line represents our primary assumption that HIV-1 prevalence remains constant. The dark grey and light grey represent the assumption of the sensitivity analyses that the prevalence of HIV-1 is 50% larger or 30% smaller by 2027 and remains fixed thereafter. (e) The yearly incidence per person of HIV-2 in Caió amongst individuals aged over 15 years. The yearly incidences estimated during two periods (1990–1997 and 1997–2007) from data in Caió are plotted at the midpoints of these periods (circles). Between 1990 and 2007, the deterministic model predictions (solid black line) of yearly incidence are shown. Beyond 2007, the mean (solid black line), median (grey solid line) and 95% confidence intervals (dashed lines) of 5000 stochastic simulations are shown. Note that the lower 95% interval is zero for all years. (f) Stochastic model predictions and 95% confidence intervals of the prevalence of HIV-2 amongst different age groups in 2017 and 2027. For comparison, the 2007 prevalence data are also presented. (g) Model predictions of HIV-2 prevalence assuming HIV-1 is absent in the population (grey line). For comparison, our primary model prediction assuming HIV-1 is present in the population is shown in black.

  

Full article at:  http://goo.gl/i4etLH

By:  Fryer, Helen R.^a; Van Tienen, Carla^c,e; Van Der Loeff, Maarten Schim^f,g; Aaby, Peter^h; Da Silva, Zacarias J.^h; Whittle, Hilton^c,i; Rowland-Jones, Sarah L.^b; de Silva, Thushan I.^c,d

^aDepartment of Zoology, The Institute for Emerging Infections, The Oxford Martin School, Oxford University

^bNuffield Department of Medicine, Weatherall Institute of Molecular Medicine, John Radcliffe Hospital, Oxford, United Kingdom

^cMedical Research Council Laboratories (UK), Fajara, The Gambia

^dDepartment of Infection and Immunity, The University of Sheffield Medical School, Sheffield, United Kingdom

^eErasmus Medical Centre, Medical Microbiology and Infectious Diseases, Rotterdam

^fHealth Service of Amsterdam (GGD) and Academic Medical Center

^gDepartment of Internal Medicine, Division of Infectious Diseases, Center for Infection and Immunity Amsterdam (CINIMA), Academic Medical Center, Meibergdreef, Amsterdam, The Netherlands

^hProjecto de Saúde de Bandim, Apartado 861, Bissau Codex, Guinea-Bissau

ⁱFaculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom.

Correspondence to Helen R. Fryer, Department of Zoology, South Parks Road, Oxford OX13PS, UK. E-mail: helen.fryer@zoo.ox.ac.uk

 

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