2021
DOI: 10.3390/fi13050108
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Inferring Urban Social Networks from Publicly Available Data

Abstract: The definition of suitable generative models for synthetic yet realistic social networks is a widely studied problem in the literature. By not being tied to any real data, random graph models cannot capture all the subtleties of real networks and are inadequate for many practical contexts—including areas of research, such as computational epidemiology, which are recently high on the agenda. At the same time, the so-called contact networks describe interactions, rather than relationships, and are strongly depen… Show more

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Cited by 12 publications
(12 citation statements)
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“…We simulate epidemic outbreaks in the Municipality of Viterbo, Italy, represented as a rectangular bounding box, partitioned into a grid of n square tiles of fixed side l = 500 m, inhabited by a synthetic population V of N ≈ 60K agents. Each agent v has the following three attributes: a tile of residence i v , inferred from density estimates provided by the WorldPop Project [29]; an agetag g vchild (0 to 17), young (18 to 34), adult (35 to 64), or elder (65+) -drawn based on census data aggregated at the provincial level, provided by the Italian Institute of Statistics(ISTAT) (all details can be found in [30]); a social fitness score f u , drawn from a Lognormal distribution, as justified in [30]. We disregard tiles having less than 10 residents (see Figure 1).…”
Section: Sir Epidemics On a Real Territory Model And Methodsmentioning
confidence: 99%
See 3 more Smart Citations
“…We simulate epidemic outbreaks in the Municipality of Viterbo, Italy, represented as a rectangular bounding box, partitioned into a grid of n square tiles of fixed side l = 500 m, inhabited by a synthetic population V of N ≈ 60K agents. Each agent v has the following three attributes: a tile of residence i v , inferred from density estimates provided by the WorldPop Project [29]; an agetag g vchild (0 to 17), young (18 to 34), adult (35 to 64), or elder (65+) -drawn based on census data aggregated at the provincial level, provided by the Italian Institute of Statistics(ISTAT) (all details can be found in [30]); a social fitness score f u , drawn from a Lognormal distribution, as justified in [30]. We disregard tiles having less than 10 residents (see Figure 1).…”
Section: Sir Epidemics On a Real Territory Model And Methodsmentioning
confidence: 99%
“…We will initially consider two cases: homogeneous mixing (HM), characterized by p u,v = p for constant p > 0; distance-based mixing (DM), where p u,v ∝ d −1 i,j for all u ∈ V i and v ∈ V j only depends on the distance d i,j between V i and V j . We will then assess, through extensive simulations, whether the predictions obtained for the DM model remain valid when p u,v also depends on the social fitness, on the age and/or on the underlying social fabric, encoded into a static social network that combines synthetic households and acquaintances, modelled as described in [31] and [30]. In total, we consider five configurations, all having the same expected volume of daily contacts, summarized in Table 1 and described more in details as needed.…”
Section: The Tiling Of the City's Territory Induces A Partition Of Th...mentioning
confidence: 99%
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“…In this context, the sparse FCBM is well approximated by the phenomenological model presented in Refs. 8 , 9 .…”
Section: Introductionmentioning
confidence: 99%