Abstract

Notable cross-country differences exist in the diffusion of the Covid-19 and in its lethality. Contact patterns in populations, and in particular intergenerational contacts, have been argued to be responsible for the most vulnerable, the elderly, getting infected more often and thus driving up mortality in some context, like in the southern European one. This paper asks a simple question: is it between whom contacts occur that matters or is it simply how many contacts people have? Due to the high number of confounding factors, it is extremely difficult to empirically assess the impact of single network features separately. This is why we rely on a simulation exercise in which we counterfactually manipulate single aspects of countries' age distribution and network structures. We disentangle the contributions of the kind and of the number of contacts while holding constant the age structure. More precisely, we isolate the respective effects of inter-age contact patterns, degree distribution and clustering on the virus propagation across age groups. We use survey data on face-to-face contacts for Great Britain, Italy, and Germany, to reconstruct networks that mirror empirical contact patterns in these three countries. It turns out that the number of social contacts (degree distribution) largely accounts for the higher infection rates of the elderly in the Italian context, while differences in inter-age contacts patterns are only responsible for minor differences. This suggests that policies specifically targeting inter-age contacts would be little effective.

Highlights

  • During the Sars-CoV-2 pandemic, scholars from different disciplines rushed to warn the world about the role played by that in-person social contacts have in spreading the virus and in determining the velocity of its diffusion

  • In this paper we address one more essential limitation of these studies: when scholars underline the role of national patterns of intergenerational relations—and in general of social relations—in explaining national differences in the spread of the virus among the elderly population, and overall Case Fatality Rates (CFR), they mix together the effects of different characteristics of networks of social relations: the degree distribution, i.e., how many contacts individuals have, and age-mixing, i.e., the ages of two or more persons in an interaction, which is a general proxy of intergenerational contacts

  • This first result indicates that there exist cultural differences that are significant enough to generate large cross-country differences which is in line with [18]

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Summary

Introduction

During the Sars-CoV-2 pandemic, scholars from different disciplines rushed to warn the world about the role played by that in-person social contacts have in spreading the virus and in determining the velocity of its diffusion. Our methodology allows us to generate networks with a degree distribution and an age mix calibrated on different countries.

Results
Conclusion
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