Volume 13, Number 7—July 2007
Research
Effects of Internal Border Control on Spread of Pandemic Influenza
James G. Wood*†
, Nasim Zamani†, C. Raina MacIntyre*†, and Niels G. Becker‡
, Nasim Zamani†, C. Raina MacIntyre*†, and Niels G. Becker‡Table 1
Summary of parameter values, assumptions, and sources used in models of the effect of travel restrictions on pandemic influenza in Australia*
| Variable/concept | Value (range)/assumption | Source/interpretation |
|---|---|---|
| Reproduction no. (R0) | 1.5–3.5 | Mills (14) |
| Infectivity function (ρ) | Flat or peaked† | Longini, Ferguson (7,8) |
| Latent period | 1 (1–2 in sensitivity analysis) d(s) | Ferguson (6) |
| Infectious period | 5 d | Literature suggests 4–7 d in adults (6,7) |
| Mixing | Homogenous (within city) | Modeling literature (15) |
| Propensity to travel | Everyone equal | Assumption |
| Populations | Sydney (4.2 million), Melbourne (3.6 million), Darwin (110,000) | ABS figures (16) |
| Travel rate‡ Sydney ↔ Melbourne (weighted by stay length) | (4.7 × 103, 8.9 × 103) | BTRE figures (17,18), NSW, and Victoria Tourism reports (19,20) |
| Travel rate‡ Sydney ↔ Darwin (weighted by stay length) | (9.2 × 104, 4.4 × 103) | BTRE figures (17,18), NSW, and NT Tourism reports (19,21) |
| Travel restrictions | 20%,10%, or 1% of current levels | Assumption |
| Time between 20 current cases in city 1 and city 2 (T20) | Random variable (T20), different for each simulation. Median value over all simulations is given by m20. | Output variables used to measure effect of travel restrictions |
*ABS, Australian Bureau of Statistics; BTRE, Bureau of Transport and Regional Economics; NSW, New South Wales; NT, Northern Territory.
†See Figure 1, panel C, for shapes used.
‡This assumes a constant travel rate over the year with no seasonal variation in travel volumes.
