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

were parameterized for the US to a timescale of units days by setting ζ = 3.23×10 −5 corresponding to a crude birth rate of 11.8 per 1000 per year, a baseline mortality rate ω b = 2.38 × 10 −7 corresponding to 8.685 per 1000 per year, an infectious mortality rate ω i = 2.62 × 10 −7 , incubation period γ −1 of 3 days, infectious period ν −1 of 10 days, and β parameterized to ensure I(t) grew with a specified exponential growth rate early in the epidemic. A total of 2,000 simulations were run for 275 each of the two growth rates (US and Italy) analyzed. Growth rates were drawn at random with r U S N (r U S , 0.1) and r IT N (r IT , 0.1). To illustrate the mutual dependence between estimates of growth rate, clinical rate, and the lag between the onset of infectiousness to presentation to a doctor with ILI, 2,000 simulations with uniform growth rates in the interval [0.173,0.365] corresponding to a range of doubling times between 1.9 days and 4 days.