NIH-funded research NIH-funded research

Using data science to fight antibiotic resistance in Africa

Official title: Combatting AntiMicrobial Resistance in Africa Using Data Science (CAMRA)

Funded at Redeemer's University · NIH-10891488 · Data updated 2026-11-12

This study is looking at how some bacteria that cause infections in young children in Africa are becoming harder to treat, and it aims to find out which bacteria are involved and how they resist treatment, so we can improve how we diagnose and treat these infections.

Quick facts

Grant typeNIH-funded research
Study typeNIH-funded research
Funding institutionRedeemer's University
NIH-funded
Lab location1 site (Ede, NIGERIA)
Project startSeptember 15, 2021
Project endJune 30, 2026
Funding year2024
Award (this year)$1,264,691
NIH project number5U54TW012056-04
Project IDNIH-10891488 on NIH RePORTER

Who could benefit from this research

Could help

Ideal candidates for this research include infants and young children under the age of 11 who are experiencing bacterial infections.

Less likely to help

Patients with non-bacterial infections or those outside the age range of 0-11 years may not benefit from this research.

What this research studies

This research focuses on understanding and combating antimicrobial resistance (AMR) in bacterial infections prevalent in Africa, particularly among young children. By utilizing data science and molecular characterization of bacterial isolates, the project aims to identify the specific bacteria causing infections and their resistance patterns. The research will analyze clinical samples from Nigeria and Rwanda to gather objective data on AMR, which is currently limited. This approach will help in developing targeted strategies to improve diagnosis and treatment of bacterial infections.

Why it matters

Potential benefit: If successful, this research could lead to improved treatment options and reduced mortality rates from bacterial infections in children across Africa.

How similar studies have gone: Other research has shown success in using data science to address antimicrobial resistance, indicating that this approach has potential for impactful outcomes.

Where this research is happening

  • Redeemer's University
    Ede, Nigeria
    Active

Researchers

  • Principal investigator: Happi, Christian T. — Redeemer's University
  • Study coordinator: Happi, Christian T.

Related research

Other NIH-funded projects on the same topics.

  • Combating Antibiotic Resistance in Africa with Data Science

    A patient-friendly overview of a program using data and genomics to track and fight antibiotic resistance in Africa, with potential benefits for global health and future treatments.

    NIH research Redeemer's University · Ede, NIGERIA · NIH-11515605

  • Fighting antibiotic-resistant infections in Africa with data science

    Using lab testing and data tools to better understand and reduce antibiotic-resistant bacterial infections that affect newborns, children, and other patients in parts of Africa.

    NIH research Redeemer's University · Ede, NIGERIA · NIH-11397882

  • Using data to fight antibiotic-resistant infections in Africa

    This project combines lab testing of bacterial samples and data analysis to find and track drug-resistant infections that make people—especially newborns and hospitalized patients—very sick in African hospitals.

    NIH research Redeemer's University · Ede, NIGERIA · NIH-11162373

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page.
Last reviewed 2026-11-14 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.