MERS-CoV spillover at the camel-human interface

Gytis Dudas; Luiz Max Carvalho; Andrew Rambaut; Trevor Bedford; Ali M. Somily; Mazin Barry; Sarah S. Al Subaie; Abdulaziz A. BinSaeed; Fahad A. Alzamil; Waleed Zaher; Theeb Al Qahtani; Khaldoon Al Jerian; Scott J.N. McNabb; Imad A. Al-Jahdali; Ahmed M. Alotaibi; Nahid A. Batarfi; Matthew Cotten; Simon J. Watson; Spela Binter; Paul Kellam

. CC-BY-NC 4.0 International license is made available under a The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. Figure S6 . Monte Carlo simulation schematic. Case clusters are simulated according to Equation 1 until an outbreak size of 2000 cases is reached. We sample 174 cases from each simulation to represent sequencing of human MERS cases. 'Sequencing' is carried out by using multivariate hypergeometric sampling, representing sampling cases without replacement to be sequenced. Sequencing simulations take place at three levels of bias: 1.0, where every case is equally likely to be sequenced, and 2.0 and 3.0, where cases from larger clusters are increasingly more likely to be sequenced. The distribution of simulated sequence clusters is summarised by its mean, median and standard deviation. A simulation is considered to match if the mean, median and standard deviation of its sequence cluster sizes falls within the 95% highest posterior density interval of observed MERS-CoV sequence clusters. R 0 values that ultimately generate data matching empirical observations, as well as associated numbers of 'introductions' are retained as estimates. These estimates are summarised in Figure 3 .