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How network analysis can help us out of the corona crisis

Dates:
  • Fri 22 Jan 2021 09.00 - 10.30
  Add to Calendar 2021-01-22 9:00 2021-01-22 10:30 Europe/Paris How network analysis can help us out of the corona crisis

A presentation within the Colloquium on Analytical Sociology

During the COVID-19 crisis, the predominant model used to predict infections and deaths and to assess non-pharmaceutical interventions is the compartmental model. I argue that this model can only lead to interventions that indifferently concern large subsets of the population or even the overall population. This is because the compartmental model looks at virus diffusion without modelling the topology of social interactions. Therefore, it cannot assess any targeted interventions that could surgically isolate specific individuals and/or cutting particular person-to-person transmission paths. Network scientists have proposed that infectious diseases involving person-to-person transmission may be effectively halted by targeting interventions at a minority of highly connected individuals. Can this strategy be effective in combating a virus partly transmitted in close-range contact, as many believe SARS-CoV-2 to be? Effectiveness critically depends on high between-person variability in the number of close-range contacts. We analyze population survey data showing that indeed the distribution of close-range contacts across individuals is characterized by a small fraction of individuals reporting very high frequencies. Strikingly, we find that the average duration of contact is mostly invariant in the number of contacts, reinforcing the criticality of hubs. We simulate a population embedded in a network with empirically observed contact frequencies. Simulations show that targeting hubs robustly improves containment.

via zoom - DD/MM/YYYY
  via zoom -

A presentation within the Colloquium on Analytical Sociology

During the COVID-19 crisis, the predominant model used to predict infections and deaths and to assess non-pharmaceutical interventions is the compartmental model. I argue that this model can only lead to interventions that indifferently concern large subsets of the population or even the overall population. This is because the compartmental model looks at virus diffusion without modelling the topology of social interactions. Therefore, it cannot assess any targeted interventions that could surgically isolate specific individuals and/or cutting particular person-to-person transmission paths. Network scientists have proposed that infectious diseases involving person-to-person transmission may be effectively halted by targeting interventions at a minority of highly connected individuals. Can this strategy be effective in combating a virus partly transmitted in close-range contact, as many believe SARS-CoV-2 to be? Effectiveness critically depends on high between-person variability in the number of close-range contacts. We analyze population survey data showing that indeed the distribution of close-range contacts across individuals is characterized by a small fraction of individuals reporting very high frequencies. Strikingly, we find that the average duration of contact is mostly invariant in the number of contacts, reinforcing the criticality of hubs. We simulate a population embedded in a network with empirically observed contact frequencies. Simulations show that targeting hubs robustly improves containment.


Location:
via zoom -

Affiliation:
Department of Political and Social Sciences

Type:
Working group

Contact:
Monika Rzemieniecka (EUI - Department of Political and Social Sciences) - Send a mail

Organiser:
Prof. Arnout van de Rijt (EUI - Department of Political and Social Sciences)

Speaker:
Gianluca Manzo (CNRS Paris)

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