STRENGTHENING CAPACITY IN EPIDEMIC ANALYTICS AND MODELING IN CENTRAL AFRICA

Grant number: 101249016

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Key facts

  • Disease

    Disease X
  • Start & end year

    2026
    2029
  • Known Financial Commitments (USD)

    $1,471,646.73
  • Funder

    European Commission
  • Research Location

    Burundi, Congo (DRC)
  • Lead Research Institution

    EUROPEAN & DEVELOPING COUNTRIES CLINICAL TRIALS PARTNERSHIP
  • Research Priority Alignment

    N/A
  • Research Category

    Epidemiological studies
  • Research Subcategory

    N/A
  • Special Interest Tags

    N/A
  • Study Type

    Non-Clinical
  • Clinical Trial Details

    N/A
  • Broad Policy Alignment

    Pending
  • Age Group

    Unspecified
  • Vulnerable Population

    Unspecified
  • Occupations of Interest

    Unspecified

Abstract

Central Africa is vulnerable to recurrent and emerging epidemics such as Ebola, Mpox, malaria, and cholera, yet the region faces a critical shortage of professionals trained in epidemiology, biostatistics, and infectious disease modeling. The Strengthening Capacity in Epidemic Analytics and Modelling in Central Africa (SCEAM-CA) project addresses this challenge by scaling up the Master's program in Outbreak Analytics and Infectious Disease Modeling launched in 2025 at the One Health Institute for Africa (INOHA), University of Kinshasa, and extending it to other Francophone Central African countries. The program will train early-career experts while also delivering short-term workshops to strengthen the skills of professionals from Ministries of Health, National Public Health Institutes, and research organizations. A fellowship and mentorship scheme, including research stays in partner laboratories, will further support career development and foster both South-South and North-South collaboration. Regional networks such as CANTAM will provide clinical and genomic datasets, which students will use for modeling as part of their thesis projects. To enable advanced training and research, INOHA will be equipped with a high-performance computing laboratory and a bilingual e-learning platform, ensuring access to real-world datasets and collaborative tools.