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Kigali, Rwanda

Nsanzimana S.,Institute of HIV Disease Prevention and Control | Nsanzimana S.,Swiss Tropical and Public Health Institute | Prabhu K.,Harvard University | McDermott H.,Partners in Health | And 7 more authors.
BMC Medicine | Year: 2015

The 1994 genocide against the Tutsi destroyed the health system in Rwanda. It is impressive that a small country like Rwanda has advanced its health system to the point of now offering near universal health insurance coverage. Through a series of strategic structural changes to its health system, catalyzed through international assistance, Rwanda has demonstrated a commitment towards improving patient and population health indicators. In particular, the rapid scale up of antiretroviral therapy (ART) has become a great success story for Rwanda. The country achieved universal coverage of ART at a CD4 cell count of 200 cells/mm3 in 2007 and increased the threshold for initiation of ART to ≥350 cells/mm3 in 2008. Further, 2013 guidelines raised the threshold for initiation to ≥500 cells/mm3 and suggest immediate therapy for key affected populations. In 2015, guidelines recommend offering immediate treatment to all patients. By reviewing the history of HIV and the scale-up of treatment delivery in Rwanda since the genocide, this paper highlights some of the key innovations of the Government of Rwanda and demonstrates the ways in which the national response to the HIV epidemic has catalyzed the implementation of interventions that have helped strengthen the overall health system. © 2015 Nsanzimana et al. Source


Rusine J.,Amsterdam Institute for Global Health and Development AIGHD | Rusine J.,National Reference Laboratory | Rusine J.,A+ Network | Asiimwe-Kateera B.,Amsterdam Institute for Global Health and Development AIGHD | And 10 more authors.
PLoS ONE | Year: 2013

Treatment outcomes of HIV patients receiving antiretroviral therapy (ART) in Rwanda are scarcely documented. HIV viral load (VL) and HIV drug-resistance (HIVDR) outcomes at month 12 were determined in a prospective cohort study of antiretroviral-naïve HIV patients initiating first-line therapy in Kigali. Treatment response was monitored clinically and by regular CD4 counts and targeted HIV viral load (VL) to confirm drug failure. VL measurements and HIVDR genotyping were performed retrospectively on baseline and month 12 samples. One hundred and fifty-eight participants who completed their month 12 follow-up visit had VL data available at month 12. Most of them (88%) were virologically suppressed (VL≤1000 copies/mL) but 18 had virological failure (11%), which is in the range of WHO-suggested targets for HIVDR prevention. If only CD4 criteria had been used to classify treatment response, 26% of the participants would have been misclassified as treatment failure. Pre-therapy HIVDR was documented in 4 of 109 participants (3.6%) with an HIVDR genotyping results at baseline. Eight of 12 participants (66.7%) with virological failure and HIVDR genotyping results at month 12 were found to harbor mutation(s), mostly NNRTI resistance mutations, whereas 4 patients had no HIVDR mutations. Almost half (44%) of the participants initiated ART at CD4 count ≤200cell/μl and severe CD4 depletion at baseline (<50 cells/μl) was associated with virological treatment failure (p = 0.008).Although the findings may not be generalizable to all HIV patients in Rwanda, our data suggest that first-line ART regimen changes are currently not warranted. However, the accumulation of acquired HIVDR mutations in some participants underscores the need to reinforce HIVDR prevention strategies, such as increasing the availability and appropriate use of VL testing to monitor ART response, ensuring high quality adherence counseling, and promoting earlier identification of HIV patients and enrollment into HIV care and treatment programs. © 2013 Rusine et al. Source


Amornkul P.N.,International AIDS Vaccine Initiative | Karita E.,Project San Francisco | Kamali A.,Medical Research Council Uganda Virus Research Unit | Rida W.N.,Biostatistics Consultant | And 14 more authors.
AIDS | Year: 2013

Objective: To describe immunologic, virologic, and clinical HIV disease progression by HIV-1 subtype among Africans with well documented estimated dates of HIV infection (EDIs). Design: Prospective cohort. Methods: Adults and youth with documented HIV-1 infection in the past 12 months were recruited from seroincidence cohorts in East and Southern Africa and followed at 3-6 month intervals. Blood for lymphocyte subset and viral load determination was collected at each visit. Pol was sequenced from the first positive specimen to ascertain subtype. Preantiretroviral therapy disease progression was measured by three time-toevent endpoints: CD4+ cell count 350 cells/ml or less, viral load measurement at least 1*105 copies/ml, and clinical AIDS. Results: From 2006 to 2011, 615 participants were enrolled at nine research centers in Kenya, Rwanda, South Africa, Uganda, and Zambia; 579 (94.1%) had viral subtyping completed. Predominant subtypes were C (256, 44.2%), A (209, 36.1%), and D (84, 14.5%). After adjustment for age, sex, and human leukocyte antigen alleles in Cox regression analyses, subtype C-infected participants progressed faster than subtype A to all three endpoints [CD4+ hazard ratio 1.60, 95% (confidence interval) CI 1.16, 2.20; viral load hazard ratio 1.59, 95% CI 1.12, 2.25; and AIDS hazard ratio 1.60, 95% CI 1.11, 2.31). Subtype D-infected participants reached high viral load more rapidly (hazard ratio 1.61, 95% CI 1.01, 2.57) and progressed nearly twice as fast to AIDS compared to subtype A (hazard ratio 1.93, 95% CI 1.21, 3.09). Conclusion: Subtype-specific differences in HIV disease progression suggest that the local subtype distribution be considered when planning HIV programs and designing and defining clinical endpoints for HIV prevention trials. © 2013 Wolters Kluwer Health | Lippincott Williams & Wilkins. Source


Ondoa P.,Amsterdam Institute of Global Health and Development AIGHD | Gautam R.,University of Liverpool | Rusine J.,INTERACT Program | Rusine J.,National Reference Laboratory | And 2 more authors.
PLoS ONE | Year: 2015

Background Genital viral load (GVL) is the main determinant of sexual transmission of human immunedeficiency virus (HIV). The effect of antiretroviral therapy (ART) on local cervico-vaginal immunological factors associated with GVL is poorly described. We aimed to identify the risk factors of detectable GVL, and the impact of ART on HIV genital shedding and its correlates in a cohort of HIV-infected women, attending HIV care in Kigali, Rwanda. Materials and Methods All participants were evaluated for GVL, plasma viral load (PVL), CD4 count, various sexually-transmitted infections (STIs) at baseline and at month 12. Genital concentration of 19 cytokines and mRNA expression of APOBEC3G and BST2, two host HIV restriction factors, were evaluated at baseline in all participants. Cytokine levels were re-assessed at month 12 only in participants eligible for ART at baseline. Risk factors of GVL 40copies/mL at baseline and month 12 were assessed using logistic regression. Effect of 12-month ART on various local and systemic immunological parameters was examined using a paired t-test and McNemar as appropriate. Results 96 of the 247 women enrolled in the study were eligible for ART. After 12 months of ART, PVL and GVL decreased to undetectable level in respectively 74 and 88% of treated participants. ART did not affect cytokine levels. HIV genital shedding occurred only when PVL was detectable. At baseline, GVL was independently associated with IL-1β after controlling for PVL, age and N. gonorrhea infection (95% CI 1.32-2.15) and at month 12 with MIP-1β (95% CI 0.96-21.32) after controlling for baseline GVL, PVL and month 12 IL-8. Conclusion Suppressive ART does not necessarily reduce genital level of immune activation. Minimizing all conditions favoring genital inflammation, including active detection and treatment of STIs, might reduce the risk of HIV transmission as supplement to the provision of potent ART. © 2015 Ondoa et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Source


Pantazis N.,National and Kapodistrian University of Athens | Morrison C.,FHI 360 | Amornkul P.N.,International AIDS Vaccine Initiative IAVI | Lewden C.,University of Bordeaux Segalen | And 10 more authors.
PLoS ONE | Year: 2012

Introduction: It is unknown whether HIV treatment guidelines, based on resource-rich country cohorts, are applicable to African populations. Methods: We estimated CD4 cell loss in ART-naïve, AIDS-free individuals using mixed models allowing for random intercept and slope, and time from seroconversion to clinical AIDS, death and antiretroviral therapy (ART) initiation by survival methods. Using CASCADE data from 20 European and 3 sub-Saharan African (SSA) cohorts of heterosexually-infected individuals, aged ≥15 years, infected ≥2000, we compared estimates between non-African Europeans, Africans in Europe, and Africans in SSA. Results: Of 1,959 (913 non-Africans, 302 Europeans - African origin, 744 SSA), two-thirds were female; median age at seroconversion was 31 years. Individuals in SSA progressed faster to clinical AIDS but not to death or non-TB AIDS. They also initiated ART later than Europeans and at lower CD4 cell counts. In adjusted models, Africans (especially from Europe) had lower CD4 counts at seroconversion and slower CD4 decline than non-African Europeans. Median (95% CI) CD4 count at seroconversion for a 15-29 year old woman was 607 (588-627) (non-African European), 469 (442-497) (European - African origin) and 570 (551-589) (SSA) cells/μL with respective CD4 decline during the first 4 years of 259 (228-289), 155 (110-200), and 199 (174-224) cells/μL (p<0.01). Discussion: Despite differences in CD4 cell count evolution, death and non-TB AIDS rates were similar across study groups. It is therefore prudent to apply current ART guidelines from resource-rich countries to African populations. © 2012 Pantazis et al. Source

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