Using ILI surveillance to estimate state-specific case detection rates and forecast SARS-CoV-2 spread in the United States

Justin D Silverman; Alex D Washburne

Faster growth rates, however, require lower clinical rates to explain the ILI surge. If the US epidemic prior to March 14 grew at the rate of deaths in Italy, doubling every 2.65 days, it could better match the curvature of the ILI surge and would imply a clinical rate of 16.5% ( Figure 3B ). For a four-day lag between the onset of infectiousness and presentation with ILI, the doubling time of US deaths produces, on average, too few COVID cases to explain the excess ILI 130 on March 14. However, 29.8% of the stochastic simulations with a growth rate similar to that of US deaths produced enough COVID cases to explain the ILI surge and thus suggest either secondary introductions, super-spreading, or rapid transmission events in early transmission chains to exceed the ILI surge [11] . On the other hand, the doubling time of deaths in Italy could capture the US excess ILI with a 38.8% clinical rate. If researchers produce estimates of growth rates for the 135 US epidemic, the ILI surge can be used to estimate bounds and ranges of possible clinical rates ( Figure 3C ). If the entirety of the ILI surge is attributable to COVID, it suggests a slowest-possible doubling time of 3.5 days for the US epidemic starting on January 15.