The Diagnostic Network Optimisation Sub-community of Practice (DNO Sub-CoP) is a dedicated segment of ASLM’s LabCoP. The DNO Sub-CoP is a collaboration of ASLM and FIND, funded by the Bill & Melinda Gates Foundation. The DNO Sub-CoP gathers country teams (made up of laboratorians, clinicians, and representatives from ministries of health who support DNO activities in their country) and stakeholders (implementing partners, regulatory and technical agencies) who share challenges, solutions and best practices for optimising their diagnostic network.

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eLearning

Activity

LabCoP DNO Sub-CoP ECHO Sessions

View the latest ECHO sessions of LabCoP's DNO Sub-CoP

Session 01

Launching The Labcop Diagnostic Network Optimisation Sub-Community Of Practice

Session 02

Global Fund Priorities for DNO at Country Level: the What, How and When: Early insight from Gabon

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What is the DNO Sub-CoP?

The Diagnostic Network Optimisation Sub-community of Practice (DNO Sub-CoP) is a dedicated segment of ASLM’s LabCoP. The DNO Sub-CoP is a collaboration of ASLM and FIND, funded by the Bill & Melinda Gates Foundation. The DNO Sub-CoP gathers country teams (made up of laboratorians, clinicians, and representatives from ministries of health who support DNO activities in their country) and stakeholders (implementing partners, regulatory and technical agencies) who share challenges, solutions and best practices for optimising their diagnostic network.

Why a DNO Sub-CoP?

Globally, diagnosis is the biggest gap in the cascade of care. In low- and middle-income countries (LMICs), including in Africa, 35–62% of populations are lacking access to essential diagnostics for six common medical conditions. This gap in access is exacerbated at primary healthcare level. The situation is mirrored for outbreak response, where the capacity to detect outbreaks in the African region, as assessed through the Joint External Evaluation (JEE) process, was only scored at 44%.

These data evidence how laboratory networks in Africa do not effectively deliver services for clinical (UHC) and public health (IHR) functions and how diagnostic services are generally not equitably available or accessible to the population. Furthermore, investments for optimising laboratory networks in the context of limited resources are often lacking or are not driven by context relevant and geo-localised (GIS) data on laboratory capacity.