Hierarchical logistic regression models of mobility variables to predict arboviral prevalence.

Results of the hierarchical logistic regression models with statistically significant single predictors are shown. Column A shows the results from the single mobility predictor models, while column B shows the full adjusted model with the same mobility variable, adjusted for demographic variables (chosen as the models with the lowest Deviance Information Criterion value). Model 7 contains the mobility variable log-transformed weekly hours spent outside the home; Model 8 contains the mobility variable spending any amount of time over 5 hours at a work location (binary); Model 9 contains the mobility variable number of weekly hours (5 or more) spent at work; Model 10 contains the mobility variable spending any amount of time over 5 hours at a location indoors with air conditioning or screens (binary); and Model 11 contains the mobility variable number of weekly hours (5 or more) spent at a location indoors with air conditioning or screens. Statistically significant (confidence interval does not contain 1) coefficients are denoted with an asterisk (*). For estimates and/or confidence intervals that round to the null value (1), three or four significant digits are shown instead of two. OR = odds ratio; aOR = adjusted odds ratio; Ref. = reference level; log = log-transformed; AC = air conditioning; Lower/Upper = lower and upper bounds of 95% confidence interval; Sig. = statistically significant.