How to scale Corona Tests capacity using Computer Algorithm theory?

Current Corona pandemic is world wide problem and every country is facing this as their primary issue. I would like to suggest something which may help and could be tested to scale Corona tests capacity in multifold. Disclaimer – This is just theoretical proposition, medical experts need to look at this from medical point of view for confirmation. I have never imagined that the algorithms learned in engineering can be used ever practically. But looks like there is time and place for everything.

According to information available on internet, Nasopharyngeal swab or Viral throat swab are required to perform Corona tests in 1 ml universal transport media (UTM). There are different methods as well but I have no details about how this can be executed. If you look at how different countries addressing this corona fight, most of them are limited in efforts due to capacity of how many tests they can perform in a day or any period. Of course countries are scaling up their capacity which is helping them to identify corona patients in early stage to treat them quickly and avoid further community spread of Corona virus.

My assumption is, these tests are performed on individual specimen which means eg. if there are 1024 specimens to be tested, this could take 1024 test and time required for that. Time is crucial here so if we can perform these tests faster then more tests can avoid further community spread of Corona virus.

Binary Search Principal is a search algorithm that finds the position of a target value within a sorted array. Binary search compares the target value to the middle element of the array. If they are not equal, the half in which the target cannot lie is eliminated and the search continues on the remaining half, again taking the middle element to compare to the target value, and repeating this until the target value is found. If the search ends with the remaining half being empty, the target is not in the array.

Binary Search Algorithm

Considering this Binary Search Principal, If the N specimens are mixed and tested together instead of testing individually then if results are positive then there is corona virus specimen present. The tests can then performed on split of group of specimens in half eg. If we have 1024 specimen together, then we can split into 2 group of 512 and again performed 2 tests. And whichever group found positive, would again split and tested further. The group which is found negative, that means there is no corona positive patient from that group. This can reduce our number of tests required to confirm if corona virus is present in given specimen or not.

For Countries like India where scaling this capacity to test maximum people is most important, this method should be tested. I am no expert in medical field but I request to respective authorities to consider this suggestion to be verified by experts. Correct me if anything wrong, any suggestions are welcome. Hope if this works, we would be able to boost up our fight against corona significantly and can make India safer sooner.

Share to reach this to respective authorities.