Ontario has the second highest number of cases of COVID-19 within Canada but it lags all other provinces in terms of testing when measured on a per capita basis. This concern has been raised multiple times by members of the press and finally, this week, the provincial government appears to be treating this issue with the same urgency they have been giving to the procurement of sufficient personal protective equipment for front-line healthcare workers and first responders.
There are many reasons why our testing volumes have lagged behind other jurisdictions, including having limited quantities of the reagents required for the tests, continuing to follow the WHO’s protocols for testing which seem to take much longer to provide results than antibody-detection tests, and the use of a high risk-based approach to determine who needs to be tested. This is in spite of the evidence from other countries which seem to have been relatively successful in reducing their elapsed time to hit the peaks of their first wave of infections through rapid testing of as many of their citizens as possible. Enforcing self-isolation of those who are showing symptoms helps, but this doesn’t address those infected people who might be asymptomatic and might still be venturing out for groceries or other essentials.
Rather than proceeding with the assumption that only those who appear to be sick or those in higher risk situations need to be tested, a better assumption might be that we don’t know who is sick and who isn’t, so let’s make it simple to test everyone and not just once, but repeatedly until a vaccine becomes available or herd immunity (assuming that applies to this virus) develops.
Cities, states or countries can be considered a complex adaptive system and COVID-19 has proven itself to be a somewhat complex, adaptive pathogen so it is reasonable to assume that traditional, testing strategies might not be effective in addressing the interactions between them.
When dealing with a sufficiently complex solution, traditional manual, test-after approaches don’t work. Emphasizing a test-first strategy, leveraging automation and embracing a continuous testing approach might be the only ways to gain confidence that the solution is continuing to meet stakeholder requirements as its capabilities evolve. And just as it will be much harder to implement such testing strategies the more dispersed or larger the population of a geographical jurisdiction is, if we wait to improve our testing capabilities after a solution has gone through a few releases, it will take that much longer and be that much costlier.
Pay me now or pay me (much more) later.
Easy in theory, difficult in practice 