Skip to main content
. 2010 Dec 2;6(12):e1001021. doi: 10.1371/journal.pcbi.1001021

Table 2. Results of fit to serological data.

q Deviance AIC R0
VZV Little Italy Type1 0.051 (0.047,0.055) 276.42 (1 df) 447.61 3.14
Little Italy Type 2 1.35 (1.29, 1.42) 111.37 (1 df) 282.57 4.94
Little Italy Type 3 1.42 (1.35,1.51) 190.15 (1 df) 361.34 3.43
Big Italy 12.35 (11.67,13.09) 101.11 (1 df) 272.30 4.80
Polymod 11.37 (10.80, 11.99) 67.34 (1 df) 238.53 4.77
Time-Use 4.28 (4.09,4.47) 114.32 (1 df) 285.51 4.11
Non-parametric 64.30 (4.92 df) 243.33
B19 Little Italy Type1 0.029 (0.028, 0.030) 135.61 (1 df) 402.11 1.72
Little Italy Type 2 0.73 (0.71, 0.75) 157.24 (1 df) 423.74 2.67
Little Italy Type 3 0.82 (0.80, 0.84) 159.90 (1 df) 426.39 1.98
Big Italy 5.39 (5.20, 5.60) 195.99 (1 df) 462.48 2.10
Polymod 5.26 (5.06, 5.48) 202.91 (1 df) 469.41 2.21
Time-Use 2.23 (2.16, 2.30) 195.60 (1 df) 462.09 2.14
Non-parametric 81.23 (3.95 df) 353.63

Results of the fit to Italian serological data for VZV and B19 by an SIR model based on the various contact matrices considered: q estimates and related 95% confidence intervals (column 3), deviance and related number of degrees of freedom (df, column 4), Akaike information criterion (AIC, column 5), R0 estimates (column 6). Deviance and AIC also reported for the non-parametric model.