I'm the creator of Origami Assays and am happy to answer any questions.

Screening for COVID19 is an urgent problem, but the infrastructure for running these assays is limited. While there are important efforts underway to make more tests available, one simple and low cost way to help is to use the assay infrastructure we already have more efficiently.

The idea is that rather than run 1 assay on 1 patient sample, we intelligently pool patients samples and run our limited assays on these pooled samples. It is analogous to data compression, but for assays instead of files.

Nonadaptive pooling designs are well studied branch of applied mathematics and engineering, and are well suited for COVID19 population screening for the following reasons:

(1) Binary assay (2) Low positive rate (3) Large number of samples

These three features mean that the data stream coming from COVID19 assays is nicely compressible.

I've put together a series of examples of nonadaptive pooling designs for COVID19 that I'm calling "Origami Assays". These designs provide a few things:

* Concrete examples, with performance metrics for a range of sizes of designs. * Software infrastructure for decoding designs with error estimates. * A low cost, DIY paper template system for constructing complex pooling design mixtures by hand.

Advantages:

* Yields up to an 11.9x improvement in patient testing throughput (for the XL3 assay design). * Can be rolled out immediately, on any existing assay platform (RT-PCR, antibody, LAMP, or qSANGER) * Pool design can be done by hand without extensive training.

Disadvantages:

* Pooled designs can call false positives if too many positives are present in the population. * Pooling can dilute samples * Constructing pooling designs is a mind numbing task for humans.

I'm trying to roll out Origami Assays to all who may benefit from them. Any questions, thoughts, or ideas are welcome!