The global spread of a novel A (H1N1) influenza virus in 2009 has highlighted the possibility of a devastating pandemic similar to the 'Spanish flu' of 1917-1918. Responding to such pandemics requires careful planning for the early phases where there is no availability of pandemic vaccine. We set out to compute a Neighborhood Influenza Susceptibility Index (NISI) describing the vulnerability of local communities of different geo-socio-physical structure to a pandemic influenza outbreak. We used a spatially explicit geo-physical model of Linköping municipality (pop. 136,240) in Sweden, and employed an ontology-modeling tool to define simulation models and transmission settings. We found considerable differences in NISI between neighborhoods corresponding to primary care areas with regard to early progress of the outbreak, as well as in terms of the total accumulated share of infected residents counted after the outbreak. The NISI can be used in local preparations of physical response measures during pandemics.