Zoonotic and infectious diseases by their very nature are complex and multifaceted. The presence of opportunistic, secondary and asymptomatic co-infections can remain undetected as they are masked behind the symptoms of the dominant primary infection. These ‘under-cover’ infections prolong the exposure of the animal or human to the pathogens and impede therapeutic interventions, affecting their recovery. Therefore, timely diagnosis of all pathogens present, is paramount for optimal treatment outcomes in the sick animal or human.

To address this ‘diagnostic gap’ this work package seeks to:

• Deploy diagnostic tests for over 14 different targeted zoonotic pathogens, plus common co-infections, in both humans and livestock;
• Develop new high-throughput, multiplexed laboratory assays including bead-based technologies, sequencing based approaches, paper-based assays, and improved immunologic and molecular tools (as a longer term goal aimed at developing ‘point-of-decision’ assays for use in the filed/clinic) and
• Establish a biobank of reference material for use by the wider scientific community.

Clinical diagnosis based on singleplex assays (single pathogen test methods), particularly where syndromic symptoms are indicated, yields insufficient evidence for diagnosis. Utilizing multiplex assays (multiple pathogen test methods) to detect zoonotic and infectious pathogens at first presentation will not only provide substantial time and cost savings to the health facilities and improve patient outcomes, but also in a surveillance setting, it will contribute to the understanding of the epidemiology of infection (how pathogens are adapting, spreading and reacting to current treatment), provide new information on resistance, distribution, and risk groups, to help better prepare against the threat of zoonotic and infectious diseases. This will further enable relevant animal and human authorities in Kenya to accurately monitor what pathogens are circulating in the community and adjust health and livestock policy accordingly.