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2009, :160

http://www.biomedcentral.com/1471-2334/9/160

Table 1: Probability of small islands in the South Pacific escaping a global influenza pandemic (for different values of R0 and different travel volume reductions for arriving travellers).

Country (year for traveler arrival data)

Total annual traveler arrivals

Island escape probability for

global influenza pandemic

99% travel reduction

79% travel reduction

R0 = 1.5

R0 = 2.25

R0 = 3.0

R0 = 1.5

R0 = 2.25

R0 = 3.0

<0.01

<0.01

<0.01

<0.01

<0.01

<0.01

<0.01

<0.01

<0.01

<0.01

<0.01

<0.01

<0.01

<0.01

<0.01

<0.01

<0.01

<0.01

0.02

<0.01

<0.01

<0.01

<0.01

<0.01

0.03

<0.01

<0.01

<0.01

<0.01

<0.01

0.06

<0.01

<0.01

<0.01

<0.01

<0.01

0.14

<0.01

<0.01

<0.01

<0.01

<0.01

0.16

0.01

<0.01

<0.01

<0.01

<0.01

0.21

0.02

<0.01

<0.01

<0.01

<0.01

0.27

0.04

0.01

<0.01

<0.01

<0.01

0.32

0.06

0.02

<0.01

<0.01

<0.01

0.71

0.43

0.32

<0.01

<0.01

<0.01

Guam (2007/08)

1,210,600†

Fiji (2004)

596,084

Northern Mariana Islands (2004)

589,244*

French Polynesia (2006)

221,549*

Samoa (2007)

196,627‡

Vanuatu (2006)

154,101§

Cook Islands (2007)

109,115

New Caledonia (2006)

100,491*

Palau (2006)

86,375*

American Samoa (2006)

72,800

Tonga (2003)

63,451¶

Federated States of Micronesia (FSM)

18,958*

(2005)

Solomon Islands (2007)

13,748*

Marshall Islands (2005)

9173*

Kiribati (2006)

4704#

Niue (2006)

4588**

Tuvalu (2007)

1130

Nauru

n/a

Wallis and Futuna

n/a

0.78

0.54

0.44

<0.01

<0.01

<0.01

0.85

0.66

0.57

0.03

<0.01

<0.01

0.92

0.81

0.75

0.17

0.01

<0.01

0.92

0.81

0.76

0.18

0.01

<0.01

0.98

0.95

0.93

0.65

0.34

0.24

-

-

-

-

-

-

-

-

-

-

-

-

Notes: The coding of the island escape probability: standard type, <10%; italics, 10 - 50%; bold, > 50%.

  • *

    Available data do not include island citizens returning from overseas travel (i.e., non-citizen arrivals only) though the former are usually a small

proportion of arrivals relative to non-citizens for most PICTs.

  • For Guam this figure was extrapolated from arrivals data for October 2007 to February 2008. Includes civilian and armed forces arrivals by air

(not by sea) and does not include data on returning citizens of Guam.

  • For Samoa this figure involves an extrapolation of arrivals data for January to July 2007 and includes a figure for returning residents based on the

assumption that all Samoan citizens who departed returned in the same year (2005 data). These figures include arrivals by sea (4.4% of total visitor arrivals). §For Vanuatu this figure includes day visitors from ships (n = 85,922). ¶For Tonga this figure includes an estimate for returning residents and arrivals by ship and yacht.

  • #

    For Kiribati this figure includes an estimate for returning residents based on the assumption that all "I-Kiribati" leaving also return in the same

year (n = 130 for the most recent year with data i.e., 2002). ** For Niue this figure includes an estimate for returning residents based on the assumption that all "residents not departing permanently" return in the same year. n/a: No data available.

Two of the 19 PICTs had no travel data and for the others much of the data were suboptimal in that they did not always include numbers of returning citizens, and often only the arrivals by air (i.e., ignoring arrivals by sea; for details, see Table 1).

asymptomatic througout the course of their infection, nearly 75% of infected visitors do not show any symp- toms upon arrival on a PICT. This value only depends on the natural history of the disease and on the propensity of sick people to travel, but it is independent on R0 (see the Technical Appendix for more details).

Figure 1 shows how the island escape probability depends on the total number of travellers arriving on a PICT during the course of the global pandemic. For R0 = 1.5, the critical number of travellers must not exceed 380, if the PICT aims to have an escape probability above 50%. For R0 = 2.25 and R0 = 3.0, these critical values are 155 and 115 travellers respectively.

Severely or moderately sick travellers were assumed to have a reduced probability of travel. Because of this, and because of the large fraction of individuals who remain

Discussion Main findings and interpretation This analysis suggests that only a few PICTs might be expected to avoid pandemic influenza by relying on extremely rigorous travel volume reductions alone. Con- sequently, most PICTs need to consider multiple addi- tional options in their pandemic planning (especially for pandemics with high case fatality ratios). These measures might include: entry screening using health question- naires and use of rapid diagnostic tests; routine facility

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