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On the usefulness of restricting mobility during pandemics

Nov. 30, 2020

Pandemics caused by infectious diseases hit hardest the big cities with the highest population density. This density implies a greater number of citizens per area and therefore a greater number of contacts between citizens. On the other hand, rural areas are less crowded and more space is available to ensure social distance between inhabitants. However, as observed during the Covid-19 pandemic, these two types of populations are not watertight and there is a constant flow of people from cities to rural areas and vice versa. These movements have been limited by the political authorities in an attempt not to spread the pandemic from the big cities to the towns.

A group of researchers, including Massimiliano Zanin, researcher at IFISC (UIB-CSIC), has published an article in the journal Chaos in which they analyse how effective mobility restrictions are in the context of a pandemic such as Covid-19.

To do so, they simulated a classic model of infection in which people are divided into three groups: those susceptible to illness, those infected with the capacity to infect and those who have recovered and developed immunity. This model makes it possible to reproduce some basic results observed in epidemiology. They then divided this group of people into two areas, one with a significantly higher population density representing a city and the other less dense representing a rural area. To test how mobility restrictions affect the spread of the infection, they carried out different simulations with more or less restrictive policies and analyzed how these affect the total impact on the population. They assumed that people who leave the infected city intend to go to a less densely populated area and stay there until the pandemic situation is under control, as well as understanding that citizens who travel to less densely populated areas will minimize their social contacts by being there.

One of the keys to the model is the unidirectionality of movements. That is, citizens living in the most densely populated cities are allowed to leave their area, but not the other way around. By doing this, it is possible to homogenise the population density between the different urban centres, which means reducing it in the big cities at the cost of increasing it in the rural areas. Lower population density means less spread, as any two individuals are less likely to interact and become infected. Simulations showed that while these movements might be slightly less safe for people in small towns, in general, for a global pandemic situation, this reduction in density of densely populated areas is better for the overall population.

However, researchers note that implementing policies that would lead to this behaviour in the real world is complicated, and goes beyond what a simple mathematical model can tell us. For example, the model does not take into account the differences that may exist between different pressures on regional health systems; nor does it take into account the ethical problems associated with accepting increased cases in one region for the global good. This is a study carried out with a simplified model and therefore no hasty conclusions can or should be drawn without further studies confirming the observed behaviour. On the other hand, this study is also thought-provoking and underlines the importance of scientific research in managing the very critical situation we are experiencing.

Travel restrictions during pandemics: A useful strategy?. Zanin, Massimiliano; Papo, David. Chaos 30, 111103 (2020). DOI: https://doi.org/10.1063/5.0028091