Clinical, anamnestic, and sociodemographic predictors of positive SARS-CoV-2 testing in children: A cross sectional study in a tertiary hospital in Italy.

Abstract

We aimed to identify clinical, anamnestic, and sociodemographic characteristics associated with a positive swab for SARS-CoV2, and to provide a predictive score to identify at risk population in children aged 2-14 years attending school and tested for clinical symptoms of COVID-19. Cross sectional study. Outpatient clinic of the IRCCS Burlo Garofolo, a maternal and child health tertiary care hospital and research centre in Italy. Data were collected through a predefined form, filled out by parents, and gathered information on sociodemographic characteristics, and specific symptoms, which were analysed to determine their association with a positive SARS-CoV-2 swab. The regression coefficients of the variables included in the multivariate analysis were further used in the calculation of a predictive score of the positive or negative test. Between September 20th and December 23rd 2020, from 1484 children included in the study, 127 (8.6%) tested positive. In the multivariate analysis, the variables retained by the model were the presence of contact with a cohabiting, non-cohabiting or unspecified symptomatic case (respectively OR 37.2, 95% CI 20.1-68.7; 5.1, 95% CI 2.7-9.6; 15.6, 95% CI 7.3-33.2); female sex (OR 1.49, 95% CI 1.0-2.3); age (6-10 years old: OR 3.2, 95% CI 1.7-6.1 p<0.001; >10 years old: OR 4.8, 95% CI 2.7-8.8 p<0.001); fever (OR 3.9, 95% CI 2.3-6.4); chills (OR 1.9, 95% CI 1.1-3.3); headache (OR 1.45, 95% CI 0.9-2.4); ageusia (OR 1.3, 95% CI 0.5-4.0); sore throat (OR 0.48, 95% CI 0.3-0.8); earache (OR 0.4, 95% CI 0.1-1.3); rhinorrhoea (OR 0.8, 95% CI 0.5-1.3); and diarrhoea (OR 0.52, 95% CI 0.2-1.1). The predictive score based on these variables generated 93% sensitivity and 99% negative predictive value. The timely identification of SARS-CoV2 cases among children is useful to reduce the dissemination of the disease and its related burden. The predictive score may be adopted in a public health perspective to rapidly identify at risk children.