The public health informatics team led by Professor Takashi Okumura of Kitami Institute of Technology has used regional influenza patient number data to address the problem of how to distribute finite test kits to patients, and predicted the number of patients. We proposed a test kit distribution method based on the above and showed its usefulness.
In situations like a pandemic due to a new coronavirus infection, there are far more patients than can be tested.At that time, the limited distribution of inspections becomes a problem.Until now, there have been studies that maximize the effects of interventions using "vaccination" and "therapeutic agents", but "tests" that do not directly affect the decrease in the number of deaths are subject to resource allocation problems. Previous studies were limited to a very small number.
Therefore, the research team will use the data on the total number of influenza patients at medical institutions in the region, which the Kitami Medical Association has previously compiled, to explain how infectious disease patients will expand and terminate. Using (SIR model), we constructed a mathematical model that predicts the number of patient visits.When the effectiveness of the allocation incorporating this patient number prediction was evaluated, the effectiveness was shown in two points: the error from the optimum allocation was small, the situation where the inventory became zero was avoided, and it was not too much at the end of the season.
The application to the new coronavirus infectious disease, which has a different epidemic pattern from influenza, needs to respond to various realistic situations required for the revision of the patient consultation model and the implementation of tests in the future.This study shows that the problem of "how to efficiently distribute finite resources" in public health can be solved by an engineering approach.
