Leveraging AI and data science techniques in harmonizing, sharing, accessing and analyzing SARS-COV-2/COVID-19 data in Rwanda

  • Funded by International Development Research Centre (IDRC)
  • Total publications:0 publications

Grant number: 109587

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Key facts

  • Disease

    COVID-19
  • Start & end year

    2020
  • Known Financial Commitments (USD)

    $962,175
  • Funder

    International Development Research Centre (IDRC)
  • Principal Investigator

    Charles Ruranga
  • Research Location

    Rwanda
  • Lead Research Institution

    Université du Rwanda
  • Research Priority Alignment

    N/A
  • Research Category

    Epidemiological studies

  • Research Subcategory

    Impact/ effectiveness of control measures

  • Special Interest Tags

    Data Management and Data Sharing

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Not Applicable

  • Vulnerable Population

    Not applicable

  • Occupations of Interest

    Not applicable

Abstract

Rwanda has been praised for its swift response and coordinated policy efforts to manage the COVID-19 crisis. The government and other public health institutions are calling for initiatives that can support the increased availability of data to support evidence-based policymaking and adjust to the changing pathways of the disease. However, much of the available data is fragmented, incomplete, and scattered across multiple institutions such as clinics, hospitals, and testing sites. In addition, data sharing can be affected by privacy requirements and differing data structures that can make it challenging to gain new insights. This project will pilot an approach to aggregate and harmonize COVID-19 data so that it respects privacy rights and supports new kinds of innovation. The data will be supplemented by additional household surveys. The project will also explore legal and social data rules around data sharing. Finally, the project will use artificial intelligence and traditional modelling techniques to improve understanding and predict the impacts of public health measures on the trajectory of the pandemic in Rwanda. The project will focus on overall infection rates, hospital admissions, the severity of disease, mental health, and other social and economic challenges. It will aim to provide a scalable approach that can be used to address other infectious diseases such as Ebola and influenza. Ultimately, the project aims to support the Rwandan public health ecosystem in harmonizing data and leveraging machine learning to prevent and address infectious diseases. This work will be carried out as part of the COVID-19 Global South Artificial Intelligence and Data Innovation Program, funded by IDRC and the Swedish International Development Cooperation Agency.