From: A model for the co-evolution of dynamic social networks and infectious disease dynamics
 | Empty | CIDM effects | Network effects | Interaction effects |
---|---|---|---|---|
Fixed effects (observed effects) | ||||
 Intercept | 2.27 (0.15) | 2.29 (0.08) | 2.29 (0.08) | 2.59 (0.07) |
Main effects | ||||
 I. CIDM parameters | ||||
  Benefit distance 2 (\(\beta\)) |  | 0.25 (0.02) | 0.25 (0.02) | 0.23 (0.02) |
  Cost increase for infected ties (\(\mu\)) |  | − 4.97 (0.30) | − 5.00 (0.30) | − 5.30 (0.21) |
  Disease severity (\(\frac{\sigma }{50}\)) |  | − 1.87 (0.17) | − 1.87 (0.17) | − 1.75 (0.11) |
  Risk perception (r) |  | − 2.74 (0.18) | − 2.75 (0.18) | − 3.16 (0.13) |
  Network size (\(\frac{N}{50}\)) |  | 5.56 (0.29) | 4.66 (0.37) | 6.23 (0.38) |
 II. Network properties (start of epidemics) | ||||
  Density (\({\text{den}}_{\text{start}}\)) |  |  | − 7.68 (1.00) | − 7.33 (0.97) |
  Degree of patient-0 (\({\text{deg}}^{0}_{\text{start}}\)) |  |  | 3.86 (0.32) | 6.46 (0.51) |
Interaction effects | ||||
 Benefit distance 2 (\(\beta\)) \(\times\) cost increase for infected ties (\(\mu\)) |  |  |  | 0.52 (0.06) |
 Cost increase for infected ties (\(\mu\)) \(\times\) disease severity (\(\frac{\sigma }{50}\)) |  |  |  | 3.16 (0.44) |
 Cost increase for infected ties (\(\mu\)) \(\times\) risk perception (r) |  |  |  | 6.40 (0.49) |
 Disease severity (\(\frac{\sigma }{50}\)) \(\times\) risk perception (r) |  |  |  | − 2.04 (0.27) |
 Risk perception (r) \(\times\) network density (\({\text{den}}_{\text{start}}\)) |  |  |  | 9.44 (1.49) |
 Network size (\(\frac{N}{50}\)) \(\times\) degree of patient-0 (\({\text{deg}}^{0}_{\text{start}}\)) |  |  |  | 13.80 (2.10) |
Random effects (unobserved effects; Intercept) | ||||
 \(s^{2}\) | 7.33 | 1.44 | 1.41 | 0.47 |
 Log likelihood (\(\ell\)) | − 12,079.15 | − 11,814.47 | − 11,734.67 | − 11,581.32 |
 Intraclass correlation (\(\rho\)) | 0.69 | 0.31 | 0.30 | 0.13 |
 Observations | 36000 | 36000 | 36000 | 36000 |
 Groups: parameter combinations | 360 | 360 | 360 | 360 |