Outbreaks of gastroenteritis due to norovirus in schools and summer camps. Catalonia, 2017-2019
Prospective study of outbreaks reported in Catalonia from January 2017 to December 2019 in schools and summer camps.
Steps to reproduce
Prospective study of outbreaks reported in Catalonia from January 2017 to December 2019 in schools and summer camps. The clustering of ≥ 2 cases of AGE in schools or summer camps in which norovirus was identified in clinical samples by real-time semiquantitative reverse transcription polymerase chain reaction (RTqPCR) was considered an outbreak. Feces were collected to identify norovirus genogroups I, II and IV by RTqPCR. Samples were analyzed at the Microbiology Laboratory, Vall d'Hebron Hospital. The specific primers described by Kageyama et al. were used to detect norovirus GI and GII (15). A modification of the primer described by Farkas et al. (16) and Kageyama et al. (15) was used to detect norovirus GIV. For each outbreak, the number of exposed and affected people, the type of transmission (person-to-person or by common vehicle), the date of onset and the end of the outbreak and the date when the Epidemiological Surveillance unit was notified were collected. Percentages were compared using a linear trend chi-square test. Attack rates (AR) were calculated considering the total number of affected and exposed persons in the outbreaks and according to the causal genogroup, the rate ratio (RR) and 95% confidence intervals (CI) globally and according to type of transmission. To study the associations between sex, age, type of center, delay in reporting and season and the risk of becoming ill, crude odds ratios (OR) and adjusted odds ratios (aOR) were estimated with their 95% CI. To estimate the aOR, multivariate analysis was performed by logistic regression, adjusting using the backward stepwise procedure with a cut-off point of <0.2. The correlation between the delay in reporting and the duration of the outbreak was estimated using Pearson's correlation coefficient and 95% CI. For studied the relation between the size of the affected group and the attack rate was used a model of logarithmic transformation both the dependent and independent variables (log-log model) and the correlation between the transformed variables was estimated using Pearson’s correlation coefficient and 95% IC.