Global patterns in coronavirus diversity

Anthony, Simon J.; Johnson, Christine K.; Greig, Denise J.; Kramer, Sarah; Che, Xiaoyu; Wells, Heather; Hicks, Allison L.; Joly, Damien O.; Wolfe, Nathan D.; Daszak, Peter; Karesh, William; Lipkin, W. I.; Morse, Stephen S.; Mazet, Jonna A. K.; Goldstein, Tracey

The relationship between sampling effort and viral discovery was evaluated using a log-link Poisson regression model, fitted with the count of viruses for each species as the dependent variable and the number of animals sampled as the independent variable. This model is universally applied with count data. The coefficient of the sample number variable is the log of the ratio of the expected number of viruses with (n þ 1) samples collected to the expected number of viruses with n samples collected, where n can be any arbitrary positive integer. Using this estimated coefficient, we calculated the estimated numbers of viruses (viral sequence clusters) that can be found with respect to the sampling effort (i.e. all possible numbers of collected animals within a species), and they were then used to plot the estimated curve together with its 95% confidence band. We clarify that we use the term 'expected' to indicate the statistical expectation based on the estimate of the regression model. We acknowledge that the model fit is not as good as the model with an additional quadratic term of the independent variable, nonetheless it avoids the problem of over-fitting and realistically reflects the relationship between sampling effort and viral discovery when the number of animals collected is relatively lower.