Testing our way out of pandemics

Objectives: In the face of pandemics, a viable global strategy, beyond relying on the fast discovery of a vaccine or a cure, is needed. We study quantitatively the feasibility and effectiveness of mass testing to contain an epidemic. We also explore the implications of various smart testing strategies to decrease the needed testing rates. Methods: We use a modified SIR model with testing and extend the model to incorporate mobility patterns in a densely populated area. Results: For a pandemic like COVID-19, model simulations show that the rate of testing needed to squash the curve within a month varies between 20-30 percent of the population randomly tested daily to less than 5 percent, combining periodic and group testing. We also show that mobility restrictions can enhance the efficacy of testing. Scale could be as important as accuracy in testing, implying that an epidemiological rather than clinical approach for the approval of tests is needed. The estimated cost of testing is dwarfed by its return, mitigating the economic fallout of the pandemic. Conclusions: Without a vaccine or a cure, mass testing is the only viable and less costly strategy to indefinitely "squash the curve" while allowing for major economic activities to resume. Planning and executing a testing strategy is necessary and urgent as an insurance policy against future pandemics. It should be considered as an investment to build a testing and isolation infrastructure, which should be maintained as part of the pandemic preparedness.