1.
Univariate logistic and ordinal regression analyses–associations between social network characteristics and infection prevention behaviors.
2.
Characteristics of the SaNAE study population (n = 5,128).
Social network characteristics of the SaNAE study population (n = 5,128).
Multivariate model I—associations between social network characteristics and preventive behaviors in SaNAE study population.
Multivariate model II–independent associations between social network characteristics and preventive behaviors in SaNAE study population, adjusted for confounders.
Additional file 1 of Predicting medical usage rate at mass gathering events in Belgium: development and validation of a nonlinear multivariable regression model
Additional file 2 of Predicting medical usage rate at mass gathering events in Belgium: development and validation of a nonlinear multivariable regression model
Additional file 3 of Predicting medical usage rate at mass gathering events in Belgium: development and validation of a nonlinear multivariable regression model
Additional file 4 of Predicting medical usage rate at mass gathering events in Belgium: development and validation of a nonlinear multivariable regression model
Additional file 5 of Predicting medical usage rate at mass gathering events in Belgium: development and validation of a nonlinear multivariable regression model