The geographic distribution of avoidable deaths, estimated by calculating the number of deaths that would be prevented by filling all resource gaps in each province, and standardized by population size, is presented in Figure 2 . (A corresponding map showing absolute numbers of estimated avoidable death is given in Figure S2 .) Figure 3 shows estimated avoidable death rates attributable to gaps in each resource type (antivirals, beds and ventilators) aggregated across all provinces in each country, and accounting for uncertainty in resource effectiveness and spare capacity. Avoidable deaths for a given resource gap were estimated by calculating the number of deaths that would be prevented by filling that resource gap only. Figures 2 and 3 highlight how resource gaps could have a substantial impact on mortality rates during an influenza pandemic. A combination of the large population size and shortage of ventilators results in the estimation that, out of the five countries for which nationwide data were collected, Vietnam would have the highest total number of avoidable deaths. However, the results for Jakarta and Bali suggest that Indonesia would have the highest avoidable death toll if the data is extrapolated across the entire population of this country. When standardized by population size, the highest rates of avoidable deaths were estimated in Cambodia and Lao PDR, accounting for over half of all pandemic-associated mortalities in these countries. The median avoidable death rates for these countries were over 15 times higher than that for Taiwan, where a relatively low proportion (median: 7.6%, IQR: 5.5-10.7%) of total deaths was estimated to be due to resource gaps. Almost all avoidable deaths in Taiwan were predicted to be due to local shortages of oseltamivir. In all other countries shortages of ventilators were estimated to be the biggest cause of avoidable deaths (Figure 3 ). In Indonesia, Lao PDR, and Vietnam, this result was largely robust to uncertainty surrounding resource effectiveness and spare capacity. For Cambodia and Thailand, however, the uncertainty analysis suggested that gaps in oseltamivir might also be a main cause of avoidable deaths (Figure 3 ). When adding an additional layer of uncertainty to the model assumptions, by allowing for up to 5% of mild cases to be treated with oseltamivir, the increased shortages of the latter further increased uncertainty surrounding the relative importance of gaps in oseltamivir ( Figure S3 ). Given such uncertainties and the sensitivity of results to model assumptions, the proportion of mortalities that can be attributed to gaps in specific resources should be interpreted with some caution.