ABSTRACT
Early warning indicators based on critical slowing down have been suggested as a model-independent and low-cost tool to anticipate the (re)emergence of infectious diseases. We studied whether such indicators could reliably have anticipated the second COVID-19 wave in European countries. Contrary to theoretical predictions, we found that characteristic early warning indicators generally decreased rather than increased prior to the second wave. A model explains this unexpected finding as a result of transient dynamics and the multiple time scales of relaxation during a non-stationary epidemic. Particularly, if an epidemic that seems initially contained after a first wave does not fully settle to its new quasi-equilibrium prior to changing circumstances or conditions that force a second wave, then indicators will show a decreasing rather than an increasing trend as a result of the persistent transient trajectory of the first wave. Our simulations show that this lack of time scale separation was to be expected during the second European epidemic wave of COVID-19. Overall, our results emphasize that the theory of critical slowing down applies only when the external forcing of the system across a critical point is slow relative to the internal system dynamics.
ABSTRACT
BackgroundTo limit societal and economic costs of lockdown measures, public health strategies are needed that control the spread of SARS-CoV-2 and simultaneously allow lifting of disruptive measures. Regular universal random screening of large proportions of the population regardless of symptoms has been proposed as a possible control strategy. MethodsWe developed a mathematical model that includes test sensitivity depending on infectiousness for PCR-based and antigen-based tests, and different levels of onward transmission for testing and non-testing parts of the population. Only testing individuals participate in high-risk transmission events, allowing more transmission in case of unnoticed infection. We calculated the required testing interval and coverage to bring the effective reproduction number due to universal random testing (Rrt) below 1, for different scenarios of risk behavior of testing and non-testing individuals. FindingsWith R0 = 2.5, lifting all control measures for tested subjects with negative test results would require 100% of the population being tested every three days with a rapid test method with similar sensitivity as PCR-based tests. With remaining measures in place reflecting Re = 1.3, 80% of the population would need to be tested once a week to bring Rrt below 1. With lower proportions tested and with lower test sensitivity, testing frequency should increase further to bring Rrt below 1. With similar Re values for tested and non-tested subjects, and with tested subjects not allowed to engage in higher risk events, at least 80% of the populations needs to test every five days to bring Rrt below. The impact of the test-sensitivity on the reproduction number is far less than the frequency of testing. InterpretationRegular universal random screening followed by isolation of infectious individuals is not a viable strategy to reopen society after controlling a pandemic wave of SARS-CoV-2. More targeted screening approaches are needed to better use rapid testing such that it can effectively complement other control measures. FundingRECOVER (H2020-101003589) (MJMB), ZonMw project 10430022010001 (MK, HH), FCT project 131_596787873 (GR). ZonMw project 91216062 (MK)
