A log-logistic survival analysis regression model was used to predict the time-to-reporting of the first confirmed 2009 A/H1N1 case to each country. Of all the models evaluated, a multivariate model with three predictors, (1) total country-level healthcare spending per capita, (2) estimated passenger volume arriving from Mexico via direct flights (direct flight capacity), and (3) passenger volume from Mexico via indirect, or two-leg, flights (indirect flight capacity), provided the best fit to the data using AIC, as detailed under Methods (Table 1 , DAIC = 0, overall x 2 = 54.33 on 5 degrees of freedom, p-value,0.0001). The correlation between total country-level healthcare spending and the flight data was low (r,0.4). Although the correlation between direct and indirect flight data was high for countries with direct flights (r.0.9), the indirect flight information provided critical additional information for areas without direct flights. The AIC scores demonstrated this, as the model that included only direct flight information and healthcare spending did not explain the data as well as the best fit model (DAIC = 9.044). Alternate socio-economic measures, even those directly related to healthcare, such as the number of physicians per capita, GDP, or population density were much less predictive than total healthcare spending per capita. Notably, out of univariate analyses, the model with healthcare spending per capita as the sole predictor fit better than models with flight information alone (Table 1) , demonstrating just how informative this data is in predicting the date of reporting. In the best fitting multivariate model, indirect flight capacity had the largest effect size, but including healthcare spending per capita substantially increased the fit to the data (Tables 1, 2 ). For Canadian provinces and American states, we conducted an analysis with just the flight data (Table 3 overall x 2 = 22.89 on 2 degrees of freedom, p-value ,0.001). While the direct flight information does not have a statistically significant effect, the indirect does, most likely because only a few key hubs had direct flights, and these hubs also have a large volume of indirect connections.