Accelerated viral dynamics in bat cell lines, with implications for zoonotic emergence

Cara E. Brook; Mike Boots; Kartik Chandran; Andrew P. Dobson; Christian Drosten; Andrea L. Graham; Bryan T. Grenfell; Marcel A. Müller; Melinda Ng; Lin-Fa Wang; Anieke van Leeuwen

To generate an infectious time series of evenly distributed time steps against which to fit our mean field mechanistic model, we next fit a series of statistical models to the proportional data produced from the image processing methods described above. For the GFP-expressing data, we used the mgcv package in R (Wood 2001) to fit generalized additive models (GAMs) in the Gaussian family, with time elapsed (in hours) post infection as a predictor variable for proportion of infectious cells (the response variable). We fit a separate GAM model to each unique cell -virus -MOI combination, incorporating a random effect of well ID (such that each trial was modeled individually), and we fixed the smoothing parameter at k=7 for all trials, as recommended by the package author (Wood 2001). The gam.predict() function was used to return an estimate of infectious proportions per hour across the duration of each time series for each cell-virus-MOI combination.