Fig. 4. Single cross-sectional distributions of observed cycle threshold (Ct) values can estimate growth rate and multiple cross-sectional distributions can estimate the complex statewide epidemic trajectory from hospital-based surveillance at Brigham & Women’s Hospital in Massachusetts.
(A) Daily confirmed new cases in Massachusetts (gray bars) and estimated time-varying effective reproductive number, Rt. (B) Estimated Rt from the case counts vs. median and skewness of observed Ct value distribution by weekly sampling times. (C) Distribution (violin plots and points) and smoothed median (blue line) of observed Ct values by sampling week. (D) Posterior median (yellow arrow) and distribution (blue shaded area) of estimated daily growth rate of incident infections from a susceptible-exposed-infectious-recovered (SEIR) model fit to a single cross-section of observed Ct value data from the week commencing 2020-05-24. Shading density is proportional to posterior density. (E) Posterior medians (yellow arrow) and full distributions (blue shaded area) of estimated daily growth rate of incident infections from SEIR models each fit to a single cross-section by sampling week used. Red box denotes the panel from (D). (F) Posterior distribution of relative probability of infection by date from a Gaussian Process (GP) model fit to all observed Ct values (ribbons show 95% and 50% credible intervals, line shows posterior median). (G) Comparison of estimated daily growth rate of incident infections from GP model (blue line and shaded ribbons show posterior median and 95% CrI) to that from Rt estimation using observed case counts (red and green line and shaded ribbons show posterior median and 95% CrI) by date. Note that the x-axis is truncated at 2020-04-01, but estimates stretch back to 202-03-01 (Fig. S13).