The hypothetical transmission network.

<p>The hypothetical transmission network of the entire population obtained from computing the intersection of the contact and the genetic network. Patients are colored based on their risk groups: MSM (yellow), Heterosexual (red), IDU (green) and blood products (cyan).</p

The inferred contact network coloured based on estimated year of seroconversion.

<p>The colouring trend in the patient's estimated seroconversion year, ranging from 1982 (blue) to 2008 (red).</p

Untreated infection period (UIP) versus out-degree.

<p><i>UIP</i> vs. the out-going degree of nodes in the MSM, Heterosexual, IDU and all risk groups populations. The Pearson's correlation coefficients, 95% confidence intervals and p-values are depicted on each graph.</p

Workflow for constructing networks using the filter-reduction method.

<p>Starting from an undirected fully-connected network of all HIV sequences in the data, a set of social/sexual filters is applied to obtain an undirected filtered network. To convert the network to a directed one a seroconversion function is applied, deriving a contact network.</p

Properties of the contact network.

<p>Properties of the contact network.</p

Basic parameters of the data and the power law fit.

<p>Basic parameters of the data (total-, in- and out-degree distributions of the MSM, heterosexual, IDU and all risk groups), along with their power-law fits and the corresponding p-value. Goodness-of-fit tests compare the observed data to the hypothesized power-law distribution. If the resulting p-value is greater than 0.1, power-law is plausible for the data (statistically significant values are denoted in bold).</p

Test of power law behavior in the data and likelihood ratios of alternative distributions.

<p>For each degree distribution we give a p-value for the fit to the power-law model and likelihood ratios (<i>LR</i>) for the alternatives. We also quote p-values for the significance of each of the likelihood ratio tests. Significant p-values are denoted in bold. Positive values of the likelihood ratios indicate that the power-law model is favored over the alternative. The final column of the table lists the judgment of the statistical support for the power-law hypothesis for each distribution. “Moderate” indicates that the power-law is a good fit but there are other plausible alternatives as well; “good” indicates that the power-law is a good fit and that none of the alternatives considered is plausible.</p

Properties of the hypothetical transmission network against random networks.

<p>Both inferred and randomized networks are of the same size in terms of number of nodes and edges. The properties of the randomized network is an average over the properties of 5 random networks.</p

Factors associated with out-degree nodes.

<p>Results of a multi-variable regression analysis showing the factors associated with high out-degree nodes. The out-degree is the dependent variable in the analysis, and age, viral load, UIP, gender, and In-degree are independent variables.</p

Properties of the hypothetical transmission network.

<p>Properties of the hypothetical transmission network.</p