Using research to prepare for outbreaks of severe acute respiratory infection

The data were first checked for completeness and missing values. Data explorations were performed by running frequency checks and descriptive statistics. Data on primary study variables (outcomes, exposure metrics and derived covariates) were summarised using descriptive statistics, including measures of central tendency and dispersion for continuous variables (mean and SD, median and IQR) and frequencies with proportions for categorical variables. Univariate and multivariate logistic regressions were used to assess the association between mortality and main a priori proposed risk factors or adjusting for potential confounders. All statistical significance was assessed at the 5% level of significance (two-sided p<0.05). Analyses were performed using STATA V.14 statistical software. Regions were defined by income and geography according to World Bank country and lending groups criteria. 12 CrITICAl IllneSS due To Severe ACuTe reSPIrATory InfeCTIonS Data were collected from 1 January 2016 until 31 August 2017, from 682 patients admitted to 95 participating hospitals in 20 countries (see table 1 and figure 1). There was a bimodal distribution of age, with the majority of the sample children less than 10 years of age (30.0%) and those above 60 (39.9%) years (27.7%) (see figure 2 ).