Preparedness for the Spread of Influenza: Prohibition of Traffic, School Closure, and Vaccination of Children in the Commuter Towns of Tokyo

Abstract

In Greater Tokyo, many people commute by train between the suburbs and downtown Tokyo for 1 to 2 h per day. The spread of influenza in the suburbs of Tokyo should be studied, including the role of commuters and the effect of government policies on the spread of disease. We analyzed the simulated spread of influenza in commuter towns along a suburban railroad, using the individual-based Monte Carlo method, and validated this analysis using surveillance data of the infection in the Tokyo suburbs. This simulation reflects the mechanism of the real spread of influenza in commuter towns. Three measures against the spread of influenza were analyzed: prohibition of traffic, school closure, and vaccination of school children. Prohibition of traffic was not effective after the introduction of influenza into the commuter towns, but, if implemented early, it was somewhat effective in delaying the epidemic. School closure delayed the epidemic and reduced the peak of the disease, but it was not as effective in decreasing the number of infected people. Vaccination of school children decreased the numbers not only of infected children but also of infected adults in the regional communities.

Conjunction of factors triggering waves of seasonal influenza

“…Reductions in the cumulative attack rate (AR, ratio of the number of new cases to the size of the population at risk) were usually smaller than those in the peak incidence. Several studies predicted small ( 10%) or no reduction in the cumulative AR ( Ferguson et al, 2006 ; Haber et al, 2007 ; Yasuda et al, 2005 ; Ciofi degli Atti et al, 2008 ; Yasuda et al, 2008 ; Kelso et al, 2009 ; Davey et al, 2008 ; Rizzo et al, 2008 ; Vynnycky and Edmunds, 2008 ; Glass and Barnes, 2007 ; Lee et al, 2010 ; Yang et al, 2011 ; Zhang et al, 2012 ), whilst a few predicted substantial reductions (e.g. 90%) ( Glass et al, 2006 ; Davey et al, 2008 ; Elveback et al, 1976 ; Davey and Glass, 2008 ).…”

Conjunction of Factors Triggering Waves of Seasonal Influenza

“…Reductions in the cumulative attack rate (AR, ratio of the number of new cases to the size of the population at risk) were usually smaller than those in the peak incidence. Several studies predicted small (∼10%) or no reduction in the cumulative AR [18], [29], [64], [16], [63], [36], [14], [50], [60], [23], [38], [62], [65], whilst a few predicted substantial reductions (e.g. 90%) [24], [14], [17], [13].…”

An early warning system for detecting H1N1 disease outbreak – a spatio-temporal approach

“…The accelerated mutation of viruses and increased risks of animal-to-human transmission have made pandemic preparedness a top public health priority in many countries. Because the occurrence of a pandemic could cause widespread social and economic disruptions (Danziger 1994, Meltzer et al 1999, some researchers have asserted that pandemic prediction and simulation by modeling past events are important means of informing timely intervention to prevent the spread of diseases through a population (Yasuda et al 2008, Cooley et al 2011, Wu and Cowling 2011.…”