Use of predictive models

Models have been developed to simulate the estimated impact of infectious diseases, and some have focused on air travel or have integrated data about air travel into the models (Brockmann etal., 2005, 2006; Colizza etal., 2006). The rapid spread of SARS showed that estimates on the spread of modern epidemics need to consider the pattern of travel, the global aviation network, the number of flights departing from and arriving at airports, the number of passengers carried, and the size of aircraft (Hufnagel et al., 2004). Simulations can be used to model the potential impact of different interventions on the control of epidemics - for example through vaccination (where reducing the susceptible population leads to fewer "reproducers") as well as travel restrictions, and especially by isolation of largest cities.

The present pattern of air travel is expected to alter the dynamics of an influenza pandemic compared to past pandemics. The pandemic influenza of 1918-19 spread by ships, over land, and reached some remote areas by dog sled. In 196869, the time of the Hong Kong pandemic, 160 million persons traveled internationally on commercial flights. The Hong Kong influenza strain diffused through the network of cities globally by air travel, first to northern and then to southern latitudes (Rvachev and Longini, 1985). Simulation of the epidemic using 2000 air-transportation data for 52 global cities showed the virus spread concurrently to cities in both northern and southern hemispheres, resulting in little seasonal swing and a very short time for public health intervention (Grais et al., 2003). The simulation showed that disease would spread first to nearby cities, but also to distant cities with high air-travel volumes, such as Sydney, Singapore, Johannesburg, Melbourne, Perth, and Wellington. The estimated time for the pandemic to reach northern-hemisphere cities, using the 2000 travel data, was 111 days shorter than in 1968 (Grais et al., 2003).

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