# Topology of the World Tourism Web
## 3 Results and Discussion
### Network Diffusion Properties
This explains the necessity of lockdowns [42] and temporary improvements within the countries during the lockdowns. For complex systems, such as tourism, some parallels regarding the systems' robustness may be drawn from ecological systems. A short-term influence of the pandemic is undeniably present [42], which shifts the focus to the possibility of system recovery. Compartmentalized ecological complex systems show less sensitivity and long-term stability toward disturbances, such as a pandemic or fire--while the parallel may also be drawn with economic crises [1,2]. According to [PERSON] et al. [65], \"If there is strong interconnection among all elements, a perturbation will encounter nothing to stop it from spreading,\" and a similar interpretation seems to be valid for recessions and crises when observing economic and social networks [2]. Such approach is somewhat in opposition to observed trends of globalization and cohesion in tourism but might prove useful in the current situation. Due to the existence of a giant component, the tourism network is not compartmentalized. Nevertheless, the mentioned travel restrictions are one way to achieve compartmentalization of the network. To examine network compartmentalization possibilities, two approaches are attempted: arbitrary removal of the edges and removal of the nodes(Appendix A). For the first approach, 10%, 20%, and 25% of all possible links are randomly chosen and removed from the network. As long as the central countries retain most of their links, this approach does not lead to compartmentalization (Figure A1). Thus, the node or edge removal should be intentional and purposeful to achieve compartmentalization. The second approach involves removal of the top nodes ranked by betweenness centrality (countries that serve as bridges). Removed nodes are not part of the resulting network (temporarily, at least, as long as they have no links to other countries). The network of countries that remain after each iteration of removal of the top 10% nodes shows an increasing number of communities, a larger diameter, a longer geodesic, a smaller average degree, and a lower density (Figure A2). However, the nature of the formed relationships does not allow a conclusion about compartmentalization. The network of remaining nodes is somewhat compartmentalized after the removal of the top 50% nodes ranked by betweenness centrality. Such network has an average degree of 5.32, a diameter of 8, an average path length of 2.29, a density of 0.044, and it has 31 communities. After the removal of 60% of the nodes, the network is considered compartmentalized, with 97 nodes and 37 edges remaining. Such network has a density of 0.004, with many isolated nodes and nine components. With the achieved compartmentalization, the probability of creating a connection is also reduced below the threshold (\(p\leq 0.0053\)). While this is only a simulation, it can be assumed that something similar happens during the travel ban, so this is an appropriate measure for compartmentalizing the tourism network with the aim of diminishing (or stopping) the COVID-19 spread over the countries. However, travel bans occur only temporarily, meaning that afterward, the nodes restore their links and recreate the giant component. While compartmentalization of the tourism network can be achieved by enforced measures, it is not a natural property of this network. This means that without exogenous measures, COVID-19 would freely spread over the giant component, causing a trade-off between tourism benefits and health measures. From the tourism network perspective, one usually desirable property in the sense of information sharing, word of mouth, cultural transmission, or touristic promotion, might have played a role in its own temporary disintegration.