COVID-19: Tracking the Pandemic with A Simple Curve Approximation Tool (SCAT)

Jane Courtney

Traditional epidemiological models use variations on the susceptible-infected-recovered (SIR) model. 4 This model approximates the basic reproduction number, 0 , the expected number of new infections arising from each infection. To estimate this, the time delay between infection and diagnosis and between infection and infectiousness need to be known or assumed. The difficulty with this model is twofold. Firstly, it requires a good understanding of epidemiology to produce the elusive 'curve', and secondly, it can be misled by incorrect assumptions of initial conditions, and any errors will quickly propagate through the model. 5 As a result, many authors and reporters have reverted to much simpler models, typically exponential increases. 6 However, these models break down as the curve begins to flatten, 7 either due to interventions or as a natural progression of the disease. The assumption that the infection rate will only increase is also leading to unrealistic figures reported in the media. 8 Between inactive governments and irresponsible sources underplaying the numbers and describing the virus as 'just the flu' 9 and the exponential models describing an apocalyptic scenario, 10 it is difficult to eke the truth out from the reporting.