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The purpose of this paper is to attempt to assess the seismic vulnerability of the built environment in the Himalayan township of Mussoorie in the state of Uttarakhand (India), paying specific attention to hospitals. Also an attempt is made to assess the magnitude of minimum economic losses, so as to design and undertake measures for reducing human misery in the event of a major disaster.

Seismic vulnerability of the building stock is evaluated using FEMA technique rapid visual screening and the likely earthquake induced damage is depicted as a function of the damage grades of the European Macroseismic Scale (EMS‐98). In total, 3,344 buildings, including 14 hospitals, are surveyed. In the field the structures are mapped using IKONOS satellite imagery while the collected data are analysed under geographic information system environment.

It was found that 18 percent of surveyed structures fall in high probability of Grade 5 damage and very high probability of Grade 4 damage class. This is estimated to result in economic loss of US$52.47 million. Almost, 80 percent of the hospitals of Mussoorie are thus likely to be non‐functional in the post‐earthquake phase due to varying degrees of structural and non‐structural damage.

The study does not account for the cost of demolition or ground clearance cost for reconstruction, or losses likely to be incurred by public infrastructure. Thus, it is implied that retrofitting and replacement of vulnerable healthcare infrastructure should be facilitated on a priority basis along with development of suitable plans for mitigating losses in an earthquake event.

The study brings forth the importance of corrective actions (retrofitting/replacement) and detailed vulnerability assessment of all lifeline structures on priority basis.

The results are intended to reduce seismic vulnerability and human toll in the event of any earthquake in the area.

The work is based upon the original data generated by the authors through rigorous fieldwork in the area and the results are totally based on these.

Analysis of data on road accidents collected from different sources brings forth important characteristics related to the nature of accidents. Based on this, the fatality index (FI) is defined as the ratio of fatalities to injuries in accidents. An increase in FI is indicative of fatalities in accidents. High FI is observed to correlate positively with difficult terrain, slow response and poor medical facilities. FI therefore represents an important indicator for planning initiatives to reduce fatalities related to road accidents.