Table 1 Summary statistics for networks used in Fig. 2.

From: Evolution and emergence of infectious diseases in theoretical and real-world networks

Type

Network

Source

N

‹ k ›

σ k

φ

Empirical

Social (FHS)

36, 37

5,253

6.5

6.8

0.68

 

School

38

740

6.5*

3.3

0.04

 

Hospital

39

68

6.5*

5.3

0.29

 

Sexual (NATSAL)

40, 41

7,578†

2.7

4.9

0.002

Theoretical

Uniform

N/A

104

4

0

≈10−4

 

Random

Erdös-Rényí/Gilbert33,34

104

4

2

≈10−4

 

Scale-free

Barabasi-Albert35

104

4

5.3

≈10−3

 

Small-world

Santos et al.22

104

4

0

0.49

  1. Four previously published network data sets were used along with four computationally generated networks. Reported characteristics include network size N, average degree ‹k›, s.d. in degree σk and clustering coefficient φ. Further details on data sets and algorithms are given in the Methods.
  2. *For the school and hospital networks, a static unweighted network was sampled from the data set, which allowed ‹k› to be defined (to match the FHS network) and resulted in N being slightly smaller than the full study population to ensure a fully connected network.
  3. †For the sexual network, only the degree distribution was available, which we fit to a power law function and used to construct a scale-free network with random attachment.
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