Multicenter Study for Surveillance of Hospitalizations Due to Rotavirus-Associated Diarrhea and Estimation of the Economic Burden of Rotavirus Hospitalizations

Objectives

1. To determine the burden and characteristics of rotavirus-associated hospitalizations among children under five years of age of northern Israel
2. To identify potential risk factors of rotavirus infections associated with hospitalizations among Jewish and Arab children younger than five years of age.

Methods:

Study design: A two-year prospective study and a nested case control study will be carried out Collection of data: Questionnaires will be filled in with demographic characteristics of patients and data on the clinical manifestation of the diarrheal episode leading to hospitalization. Stool specimens will be systematically collected from all children hospitalized because of diarrheal diseases and examined for rotavirus and for bacterial and protozoan enteropathogens. Positive samples for rotavirus will be tested for G and P genotypes.

For the nested case control study additional data will be obtained from parents' interviews on variables such as: parents' education, parents' age, parents' occupation, no. of siblings, age of siblings, breastfeeding etc. to identify potential risk factors for rotavirus diarrhea necessitating hospitalization.

Data analysis: Methods of descriptive statistics / epidemiology will be applied to determine the characteristics of the burden of rotavirus-associated hospitalizations (the distribution of diarrhea associated hospitalizations by etiology, rates of rotavirus diarrheal diseases in Jewish and Arab children, age specific rates of rotavirus infections, the percentage of hospitalizations due to rotavirus diarrhea by month, etc.

For the nested case control study, univariate analysis will be first performed using Student t test for continuous variables and chi square test for categorical variables to study the statistical significance of predictive factors of rotavirus diarrheal diseases necessitating hospitalization. Multivariate analysis using logistic regression models will be performed to study the independent effect of each variable. Odds ratios (OR) and 95% CI will be computed for each variable. Two tailed p < 0.05 will be considered significant.