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In collaboration with the , , University of Oxford and , the meeting focused on addressing challenges and opportunities relating to the application of decision tools such as the Bayesian Belief Networks (BBN) to generate actionable steps for the practical implementation of BBN tools and methodologies in relevant global health domains.

The GETCampy project is set to run for three years and aims to strengthen collaboration between researchers in The Gambia, Africa, and the United Kingdom. The surveillance network will identify the most effective interventions in the transmission dynamics of Campylobacter infection. This collaborative effort will facilitate effective local public health policies and interventions focused on reducing the burden of diarrheal diseases and Campylobacter infections, thus lessening childhood morbidity and mortality in The Gambia, Ghana, and Burkina Faso.

According to Honourable Amadou Camara, Chairperson of the Select Committee on Health, Refugees, Disaster & Humanitarian Relief at the , the project can count on support and capacity of the Select Committee. “As lawmakers, our contribution is crucial because we strive to represent and attain the best interest of the people we serve", he stated.

"We align with this project as it will allow us to take action based on evidence the research will provide, with the support of key stakeholders", Honourable Camara added.

, Deputy Director of the  highlighted her institution’s engagement in the GETCampy project and the significance of stakeholder engagement. “We have actively connected with stakeholders and listened to their insights. Engaging with stakeholders and getting their feedback has been an important part of the project. While GETCampy is fundamentally a genomics project which aims to understand where Campylobacter  comes from, and to try and understand what might really work to combat it, our stakeholder engagement has been essential in ultimately understanding public health effects on young people." she added.

Principal Investigator for The Gambia site at MRCG highlighted “we seek to investigate sources of infection. The project will also provide crucial information on effective prevention strategies against the bacteria that can cause diarrheal infection using machine learning tools such as the Bayesian Belief Networks (BBN).”

During the meeting, discussions extended beyond Campylobacter, exploring other important projects such as "road traffic awareness and accident prevention initiative for school children" and the "Enterics for Global Health (EFGH) Shigella Surveillance study." These initiatives seek to develop tools through Bayesian Belief Networks (BBN) to prevent road traffic accidents, address antibiotic overuse, and combat antibiotic resistance, all geared towards promoting public health.