GREAT-LIFE

The challenge

To respond to existing and emerging diseases, national health authorities need to have a good understanding of the pathogens circulating in their countries. Surveillance systems typically focus on individual pathogens, which is inefficient, can lead to the neglect of important disease-causing microbes, and does not help to identify emerging pathogens. Moreover, surveillance systems generally focus on a limited number of sites, which rarely include remote rural settings where new infections are particularly likely to emerge.

New genomic technologies can address these surveillance challenges. Portable sequencing technologies, such as Nanopore, can now be used almost anywhere, generating DNA sequence data that can reveal the presence of multiple pathogens. 

The Great Lakes region, which encompasses parts of Rwanda, the Democratic Republic of the Congo (DRC), Burundi, Uganda, Kenya and Tanzania, is densely populated, mostly rural and includes many displaced people. The region is a biodiversity hotpot and, with people living in close proximity to both domestic animals and wildlife, there is a high risk of spill-overs of infections from animals to humans. However, little surveillance is carried out in the region, so limited information is currently available about the causes of infectious disease and AMR.

The project

The GREAT-LIFE project is introducing systems to support the use of genomic surveillance in eight countries centred around the Great Lakes region. The project aims to maximise the value of this information, by enabling it to inform immediate clinical decision-making, to provide national authorities with data on the prevalence of particular pathogens and AMR genes, and to help track emerging infections.

The GREAT-LIFE project team has developed tools to support the collection and analysis of data generated using the Nanopore sequencing platform. The technology generates huge amounts of data, which requires the use of sophisticated bioinformatics tools to generate usable information. The GREAT-LIFE team has developed software that facilitates local analysis on a laptop and compresses the data so that it can be transmitted more easily to centralised data repositories.

Building on pilot work in Tanzania, the technology will be introduced at six or more sites in participating countries. The project is exploring three applications of the technology:

• Analysis of patient samples to identify the causes of diarrhoeal disease, to inform immediate treatment and longer-term public health responses.
• Characterisation of AMR genes in environmental samples, focusing on rural locations and camps for displaced people.
• Detection of new pathogens that emerge during the project. 

To ensure that the data is communicated in a form that is useful to policymakers, the team is working with representatives of ministries of health and other stakeholders at different levels of the health system to identify key data needs, preferred reporting processes, and the design of outputs to support decision-making. Field data will be transferred to an existing central repository in Tanzania. Genomic data will be combined with sampling metadata and epidemiological data in a form that can be shared with global databases. 

Impact

The GREAT-LIFE project will introduce genomic surveillance across multiple countries and generate evidence in areas that typically do not contribute to surveillance, leading to significant data gaps. It will:

• Support local data analyses, potentially facilitating tailored treatment of individual patients.
• Provide detailed insights into pathogens and AMR genes, supporting the updating of treatment guidelines and informing national public health responses to combat diarrhoeal disease, AMR and epidemics.
• Build capacity in multiple countries to apply genomic technologies in surveillance.
• Support multi-country coordination and sharing of experiences. 

Crucially, the GREAT-LIFE project will provide rapid insights into changing trends, enabling rapid action to be taken to mitigate the risk of epidemics of known or new pathogens, limiting potential health and economic impacts.