The effect of travel restrictions on the spread of a moderately contagious disease

Abstract

Background: Much research in epidemiology has been focused on evaluating conventional methods of control strategies in the event of an epidemic or pandemic. Travel restrictions are often suggested as an efficient way to reduce the spread of a contagious disease that threatens public health, but few papers have studied in depth the effects of travel restrictions. In this study, we investigated what effect different levels of travel restrictions might have on the speed and geographical spread of an outbreak of a disease similar to severe acute respiratory syndrome (SARS).

Methods: We used a stochastic simulation model incorporating survey data of travel patterns between municipalities in Sweden collected over 3 years. We tested scenarios of travel restrictions in which travel over distances >50 km and 20 km would be banned, taking into account different levels of compliance.

Results: We found that a ban on journeys >50 km would drastically reduce the speed and geographical spread of outbreaks, even when compliance is < 100%. The result was found to be robust for different rates of intermunicipality transmission intensities.

Conclusion: This study supports travel restrictions as an effective way to mitigate the effect of a future disease outbreak.

Figure 1

The intermunicipal travel network. The intermunicipal travel network with travel intensities indicated by color lines. The scale is logarithmic in trips per day. SIM shows the complete dataset. In SIM50 and SIM20, all journeys > 50 km and 20 km, respectively, have been removed. The lines are drawn between the population centers of each municipality, so in many cases the trips are shorter than the lines representing them.

Figure 2

Epidemic spread for different restrictions and values of γ. Geographical plot of the municipalities, logarithmically color-coded according to the mean incidence after 60 days. SIM depicts the complete data set. In SIM50 and SIM20, all journeys > 50 km and 20 km, respectively, have been removed. The red circle signifies the mean extent of the epidemic from Stockholm.

Figure 3

Epidemic spread for different restrictions and compliance. Geographical distribution of the incidence after 60 days shown for SIM50 and SIM20 for different levels of compliance. The left plot shows the unrestricted case with Hufnagels original γ galue for comparison. This plot reflects the same data as that on the middle row, right column of Figure 2 but with scale to match the current figure.

Figure 4

Total incidence for varying compliance and restrictions. A surface plot showing incidence after 60 days with the parameters of compliance and distance restrictions on the data axes. 1000 realizations were made for each point. The surface has its highest values at high set distance limit and low compliance. Its low values are found at opposite corner.