Aims of “Scuola Sicura” (SS) were to monitor the rate of COVID-19 and to contain its spread within the school population through early case isolation. We report the initial process and outcome evaluation results.
Descriptive study of an experimental screening testing program in children in Piedmont in the period January-March 2021. We used data from the COVID-19 platform and the Local Health Units, the archives of birth certificates (CedAP) and hospital discharge files (SDO).
Setting and participants
The screening program targeted second and third grade students in first level secondary schools. Participants were subdivided into four groups; one group each week underwent screening, yielding one test per student per month.
Main outcome measures
1. number of positive cases detected vs. total number of students tested in the SS program;
2. number of positive cases detected outside the SS program vs. total number of students in the target population.
We detected the number of quarantines due to SS and no-SS case identification. To investigate the spread of COVID-19 in households, the mother-child pairs were identified through record linkage between the CedAP and SDO archives, and positive mothers were identified.
Sixty-nine percent of schools and 19.5% of the students participated in the program. SS detected 114 positives cases for SARS-CoV-2. On 08.03.2021, the target classes started distance learning: 69 of the 114 positive students were identified before that date, leading to the activation of 67 quarantine measures. We were able to identify the mothers of 61 out of 69 of those students (88%); 46 mothers had performed a swab test after the positivity of their child with a positive result in 11 cases. Asymptomatic cases identified at screening during in-class learning period accounted for 26.5% of the total number of cases occurred in the participating classes.
This is one of the few studies (and the first in Italy) to describe the functioning and predictive capacity of school screening testing for SARS-CoV-2 in a real-world situation. Our findings provide data-driven suggestions for government agencies when planning large-scale school screening testing programs.