Estimating resource needs, gaps, and associated mortality In our baseline scenario, resource gaps were estimated assuming that 12% of ''general'' hospital resources (beds, ventilators and human resources) are available for care of pandemic influenza cases, with the remaining 88% required for maintaining essential healthcare services, as in a previous pilot study for Thailand [20] , and based on previous reports [25] [26] . We also assumed that, in the event of a pandemic all available oseltamivir doses would be dedicated to severe influenza cases. These assumptions regarding resource spare capacity and oseltamivir usage were relaxed in a multivariate uncertainty analysis (described below). The resource data were aggregated at provincial level for all countries except Taiwan, where they were aggregated at county level, and Indonesia, where the data were kept at district level. (Counties in Taiwan and districts in Indonesia are of comparable population size to the provinces of the other four countries.) We then ran the model separately for each province (Lao PDR, Cambodia, Thailand, Vietnam), county (Taiwan) and district (Indonesia), with the appropriate resources for each of these administrative areas, assuming a closed population and that resources could not be shared between these areas in a timely manner. For the purposes of narrative flow, we henceforth use the term ''province'' for counties in Taiwan. All simulations started with one mild case entering a completely susceptible population.