Two pre-arranged partner labs could remove nearly all PCR delays in Nepal

Summary

• Without coordination, more than one in five PCR samples waited over 24 hours before laboratory processing even started, adding to the time people waited to receive a diagnosis.

• In the simulation, coordinated sample transfers could reduce missed 24-hour targets to zero.

• Pairing each laboratory with two pre-arranged partner laboratories removed nearly all delays without requiring a fully centralised system.

  
  

How can testing capacity co-exist with long result delays?

A country can have enough testing capacity overall while still experiencing local bottlenecks. During outbreak peaks in Nepal, some laboratories received more samples than they could process quickly, while capacity remained available elsewhere.

Separate provincial funding arrangements and different public and private operating models also made it difficult to redistribute samples when demand shifted.

Why is this a prescriptive analytics problem?

The question is not only how many samples will arrive, but where each sample should be processed when laboratories have different workloads and available capacity.

Prescriptive analytics can compare coordination rules before they are used in practice, namely, whether overflow should move to a provincial laboratory, a nearby partner, or any laboratory with available capacity.

How did the team compare coordination strategies?

This project brought together Karlsruhe Institute of Technology, the World Health Organization country office in Nepal, the University of Amsterdam, ORTEC, CIRRELT, Polytechnique Montreal, Nepal's National Public Health Laboratory, the WHO South-East Asia Regional Office and the UK Health Security Agency.

Using real data from the 2021 Delta wave, the team developed a simulation of how samples moved through Nepal's laboratory network. It then tested strategies ranging from real-time national coordination to fixed arrangements in which laboratories could transfer overflow to one or two pre-arranged partner laboratories.

What did the findings show?

Without coordination, more than 20% of samples missed the 24-hour processing target during the peak. In the model, coordinated transfers could reduce that share to zero, indicating that distribution of samples - rather than total national capacity - was the main constraint in the scenarios tested.

A simpler arrangement performed almost as well as full real-time coordination. Pairing each laboratory with two pre-arranged partner laboratories removed nearly all delays in the simulation.

For people waiting for a diagnosis, the practical issue was time. Faster processing could shorten the period before they know whether to isolate, seek care or resume daily activities. The findings also show how health authorities can examine coordination before investing in additional laboratory capacity.

How can the findings inform other applications?

Pre-arranged laboratory partnerships can be tested as part of preparedness for future outbreaks, especially where sample volumes shift quickly between locations.

The same coordination logic can apply to other diagnostic networks in which demand is uneven, and facilities have different spare capacity. Future work could examine transport constraints, changing test types and how public and private laboratories could coordinate under different governance arrangements.