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East Africa

Kara Wools-Kaloustian and Constantin Yiannoutsos, Principal Investigators

Paula Braitstein and Rachel Vreeman, Co-Principal Investigators

Indiana University School of Medicine

East African IeDEA Regional Data & Coordinating Center

Indiana University School of Medicine serves as the East African IeDEA Regional Data & Coordinating Center in the United States. It provides overall coordination for the East African Consortium including data management and statistical analysis support. In addition the site provides mentoring and practical support to the data managers and biostatisticians at East Africa IeDEA sites.

Mission and Vision Statement:
With 67% of the estimated 33 million people living with HIV/AIDS globally, sub-Saharan Africa remains the region most significantly impacted by the epidemic. In Kenya, Uganda and Tanzania, the three countries within the East African IeDEA Consortium have adult HIV prevalence rates ranging between 5-10%. Since the advent of the global antiretroviral therapy (ART) rollout in 2003, there has been a dramatic increase in the percent coverage of those estimated in need of ART (based on the 2006 WHO guidelines), from essentially no patients on in 2003, to 65% coverage in Kenya, 53% in Uganda, and 44% in Tanzania by the end of 2009. Though this dramatic scale-up of HIV treatment has had a positive impact on mortality rates, key questions remain throughout the course of a patient’s engagement in care, from the pre- ART period through ART-initiation, initial clinical response to ART and regimen durability (occurrence of adverse events and drug resistance), to long-term maintenance, loss to follow-up (LTFU), and death. It is the long-range goal of this consortium to provide answers to the questions that clinicians, programs, and ministries of health consider fundamental to the evolution and sustainability of their long term HIV care and treatment strategies.

Our priority areas for the next phase of the EA-IeDEA Consortium are:
Determine the short and long-term outcomes of adults and children along the entire spectrum of HIV care and examine patient and site-level factors associated with these outcomes.

In ART-naïve patients:
Assess the incidence of ART initiation and quantify the impact of patient and site-level determinants of failure to initiate ART.

In patients initiating ART:
Quantify the types of regimens started, the incidence and determinants of treatment failure, and overall survival.
Assess the cost-effectiveness of various ART monitoring and HIV prevention strategies.

Issues related to loss to follow-up:
Because the rate of losses to follow-up in HIV treatment programs throughout sub-Saharan Africa is a significant threat to the validity of the work done by IeDEA, in East Africa we will enhance our data collection by expanding the sampling-based methods developed during the first grant period, to accommodate losses to follow-up at several sites in our region.

Penetrance and outcomes of prevention of mother to child transmission of HIV (PMTCT) strategies:

  • Assess the outcomes of women and their infants who are exposed to antiretrovirals for PMTCT including examining toxicity, birth outcomes, infant growth and response to subsequent ART (mothers and children).
  • Assess the uptake over time and adherence to the new WHO PMTCT guidelines and their impact on these outcomes.
  • Enhance the current data collection system by merging PMTCT databases with the pediatric care databases at several sites in our region.
  • Monitor the translation of evidence into practice for managing co-infections with an emphasis on Tuberculosis (TB):
  • Evaluate the use and determinants of isoniazid preventative therapy for HIV-infected patients in East Africa screened negative for active TB.
  • Characterize the rate and determinants of ART initiation for HIV-infected, ART naïve patients with newly diagnosed active TB.
  • Evaluate the effect of IPT use and time to ART initiation on survival using a sampling based approach to estimate mortality in setting where loss to follow-up is high.
  • Determine the prevalence, incidence, determinants and outcomes of malignancies in East Africa with a focus on Kaposi’s sarcoma (KS) and cervical cancer.
  • Continue to improve KS diagnostics at three sites within the consortium and utilize these enhanced surveillance programs to assess the incidence and determinants of KS among ART-treated patients.
  • Explore the prevalence and incidence of cervical cancer and its determinants among HIV-infected women receiving care at two sites with cervical cancer screening programs.
  • #mce_temp_url# Used at AIDS 2012

    East Africa Sites

    Red Marker Kibaha, Tanzania

    Site Name: Tumbi Special Hospital
    Site PI: Kapella Mark Ngonyani

    -6.7813218 38.9928898
    Red Marker Morogoro, Tanzania

    Site Name: Morogoro Regional Hospital
    Site PI: Rita Elias Lyamuya

    -6.8275902 37.6705205
    Red Marker Dar Es Salaam, Tanzania

    Site Name: Ocean Road Cancer Institute
    Site PI: Emanuel Lugina

    -6.8105431 39.2966485
    Red Marker Masaka, Uganda

    Site Name: Masaka Regional Hospital
    Site PI: Dr. John Ssali

    -0.3293095 31.7345073
    Red Marker Mbarara, Uganda

    Site Name: Mbarara University Immune Suppressed Clinic
    Site PI: Mwebesa Bosco Bwana
    Co-PI: Winnie Muyindike

    -0.616370471562 30.6583356857
    Red Marker Kampala, Uganda

    Site Name: Infectious Disease Institute
    Site PI: Andrew Kambugu, Prof. Philippa Easterbrook

    0.3387795 32.5762908
    Red Marker Kalisizo, Uganda

    Site Name: Rakai Health Sciences Program
    Site PI: Fred Nalugoda
    Co-Investigators: Valerian Kiggundu, Steve Reynolds

    -0.535 31.6225
    Red Marker Migori, Kenya

    FACES Site: Migori District Hospital

    -1.06333826916 34.4774580002
    Red Marker Rongo, Kenya

    FACES Site: Rongo District Hospital

    -0.757734144368 34.600045681
    Red Marker Suba, Kenya

    FACES Site Name: Suba District Hospital

    -1.16309759945 34.4311523438
    Red Marker Kisumu, Kenya

    FACES Sites:

    Lumumba
    Tuungane
    Pandpieri
    Fhok
    Kisumu East District Hospital

    -0.1012721 34.7557372
    Red Marker Sio Port, Kenya

    Site Name: Academic Model Providing Access to Healthcare (AMPATH)
    Site PI: Samuel Ayaya

    0.224017526167 34.0216970444
    Red Marker Bumala, Kenya

    Site Name: Academic Model Providing Access to Healthcare (AMPATH)
    Site PI: Samuel Ayaya

    0.3041583 34.2060283
    Red Marker Eldoret, Kenya

    Site Name: Academic Model Providing Access to Healthcare (AMPATH)
    Site PI: Samuel Ayaya

    0.5165596 35.2794143
    Red Marker Bunyala, Kenya

    Site Name: Academic Model Providing Access to Healthcare (AMPATH)
    Site PI: Samuel Ayaya

    0.0787282 34.0297651
    Red Marker Busia, Kenya

    Site Name: Academic Model Providing Access to Healthcare (AMPATH), Nambale
    Site PI: Samuel Ayaya

    0.459618407294 34.1062617302
    Red Marker Eldoret West, Kenya

    Site Name: Academic Model Providing Access to Healthcare (AMPATH), Soy
    Site PI: Samuel Ayaya

    0.677188365151 35.1442337036
    Red Marker Moi University, Kenya

    Site Name: Academic Model Providing Access to Healthcare (AMPATH), Moi University, Wareng
    Site PI: Samuel Ayaya

    0.510664377641 35.2814555168
    Red Marker Moi's Bridge, Kenya

    Site Name: Academic Model Providing Access to Healthcare (AMPATH)
    Site PI: Samuel Ayaya

    0.875910971268 35.1191926003
    Red Marker Uasin Gishu, Kenya

    Site Name: Academic Model Providing Access to Healthcare (AMPATH), Uasin Gishu
    Site PI: Samuel Ayaya

    0.5527638 35.3027226
    Red Marker Khunyangu, Kenya

    Site Name: Academic Model Providing Access to Healthcare (AMPATH)
    Site PI: Samuel Ayaya

    0.3354312 34.2728578
    Red Marker Western, Kenya

    Site Name: Academic Model Providing Access to Healthcare (AMPATH), Port Victoria
    Site PI: Samuel Ayaya

    0.0972461233543 33.9732456207
    Red Marker Kabarnet, Kenya

    Site Name: Academic Model Providing Access to Healthcare (AMPATH), Kabarnet
    Site PI: Samuel Ayaya

    0.486289384812 35.7415294647
    Red Marker Iten, Kenya

    Site Name: Academic Model Providing Access to Healthcare (AMPATH), Iten District Hospital
    Site PI: Samuel Ayaya

    0.654659331313 35.4947018623
    Red Marker Mt. Elgon, Kenya

    Site Name: Academic Model Providing Access to Healthcare (AMPATH), Kapsokwany

    0.847905 34.702061
    Red Marker Kitale, Kenya

    Site Name: Academic Model Providing Access to Healthcare (AMPATH), Kitale

    1.019089 35.0023048
    Red Marker Teso, Kenya

    Site Name: Academic Model Providing Access to Healthcare (AMPATH), Kocholya

    0.6197525 34.3452623
    Red Marker Webuye, Kenya

    Site Name: Academic Model Providing Access to Healthcare (AMPATH) Webuye Hospital

    0.605174136842 34.773022413
    Red Marker Kisumu West, Kenya

    Site Name: Academic Model Providing Access to Healthcare (AMPATH), Chulaimbo

    -0.0379506 34.638404
    Red Marker Bungoma, Kenya

    Site Name: Academic Model Providing Access to Healthcare (AMPATH)

    0.569291999441 34.5646319384
    Red Marker Eldoret, Kenya

    Site Name: Academic Model Providing Access to Healthcare (AMPATH)
    Site: Moi Teaching and Referral Hospital

    0.511801588992 35.2805328369
    Red Marker Amukura, Kenya

    Site Name: Academic Model Providing Access to Healthcare (AMPATH)

    0.575838 34.270031
    Red Marker Burnt Forest, Kenya

    Site Name: Academic Model Providing Access to Healthcare (AMPATH)
    Site: Burnt Forest

    0.2153963 35.4316201
    Red Marker Turbo, Kenya

    Site Name: Academic Model Providing Access to Healthcare (AMPATH)
    Site: Turbo

    0.6342241 35.0470761
    Red Marker Mosoriot, Kenya

    Site Name: Academic Model Providing Access to Healthcare (AMPATH)
    Site: Mosoriot

    0.322421279582 35.1725149155