Brief
The 7-1-7 target is easy to state and hard to hit, and this implementation-research study asks what really moves it. Analysing timeliness data from health events across several MPA countries, it decomposes the detect-notify-respond timeline to locate where days are lost and which system features — event-based surveillance, digital reporting, EOC activation, laboratory turnaround — are associated with meeting the target. It treats bottlenecks as the unit of learning, identifying the two or three enablers with the largest effect so that investment can be prioritised. The study is written to inform the regional framework and country plans, and its methods are shared so that countries can run the same analysis on their own data. It is a demonstration of the repository's research pillar working end to end: evidence generated, peer-reviewed and fed back into practice.
Question
Which system features are most strongly associated with meeting the 7-1-7 target, and where in the timeline are delays concentrated?
Approach
Timeliness data from real health events are decomposed across the detect-notify-respond stages and correlated with system features.
Use
Findings prioritise the highest-leverage enablers for investment and are reproducible on any country's own data.
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