SARS-CoV-2 transmission in educational settings during an early summer epidemic wave in Luxembourg, 2020.

BACKGROUND: Following a first wave in spring and gradual easing of lockdown, Luxembourg experienced an early second epidemic wave of SARS-CoV-2 before the start of summer school holidays on 15th July. This provided the opportunity to investigate the role of school-age children and school settings for transmission. METHODS: We compared the incidence of SARS-CoV-2 in school-age children, teachers and the general working population in Luxembourg during two epidemic waves: a spring wave from March-April 2020 corresponding to general lockdown with schools being closed and May-July 2020 corresponding to schools being open. We assessed the number of secondary transmissions occurring in schools between May and July 2020 using routine contact tracing data. RESULTS: During the first wave in March-April 2020 when schools were closed, the incidence in pupils peaked at 28 per 100,000, while during the second wave in May-July 2020 when schools were open, incidence peaked 100 per 100,000. While incidence of SARS-CoV-2 was higher in adults than in children during the first spring wave, no significant difference was observed during the second wave in early summer. Between May and July 2020, we identified a total of 390 and 34 confirmed COVID-19 cases among 90,150 school-age children and 11,667 teachers, respectively. We further estimate that 179 primary cases caused 49 secondary cases in schools. While some small clusters of mainly student-to-student transmission within the same class were identified, we did not observe any large outbreaks with multiple generations of infection. CONCLUSIONS: Transmission of SARS-CoV-2 within Luxembourg schools was limited during an early summer epidemic wave in 2020. Precautionary measures including physical distancing as well as easy access to testing, systematic contact tracing appears to have been successful in mitigating transmission within educational settings.

Challenges and benefits of integrating diverse sampling strategies in the observation of cardiovascular risk factors (ORISCAV-LUX 2) study.

BACKGROUND: It is challenging to manage data collection as planned and creation of opportunities to adapt during the course of enrolment may be needed. This paper aims to summarize the different sampling strategies adopted in the second wave of Observation of Cardiovascular Risk Factors (ORISCAV-LUX, 2016-17), with a focus on population coverage and sample representativeness. METHODS: Data from the first nationwide cross-sectional, population-based ORISCAV-LUX survey, 2007-08 and from the newly complementary sample recruited via different pathways, nine years later were analysed. First, we compare the socio-demographic characteristics and health profiles between baseline participants and non-participants to the second wave. Then, we describe the distribution of subjects across different strategy-specific samples and performed a comparison of the overall ORISCAV-LUX2 sample to the national population according to stratification criteria. RESULTS: For the baseline sample (1209 subjects), the participants (660) were younger than the non-participants (549), with a significant difference in average ages (44 vs 45.8 years; P = 0.019). There was a significant difference in terms of education level (P < 0.0001), 218 (33%) participants having university qualification vs. 95 (18%) non-participants. The participants seemed having better health perception (p < 0.0001); 455 (70.3%) self-reported good or very good health perception compared to 312 (58.2%) non-participants. The prevalence of obesity (P < 0.0001), hypertension (P < 0.0001), diabetes (P = 0.007), and mean values of related biomarkers were significantly higher among the non-participants. The overall sample (1558 participants) was mainly composed of randomly selected subjects, including 660 from the baseline sample and 455 from other health examination survey sample and 269 from civil registry sample (constituting in total 88.8%), against only 174 volunteers (11.2%), with significantly different characteristics and health status. The ORISCAV-LUX2 sample was representative of national population for geographical district, but not for sex and age; the younger (25-34 years) and older (65-79 years) being underrepresented, whereas middle-aged adults being over-represented, with significant sex-specific difference (p < 0.0001). CONCLUSION: This study represents a careful first-stage analysis of the ORISCAV-LUX2 sample, based on available information on participants and non-participants. The ORISCAV-LUX datasets represents a relevant tool for epidemiological research and a basis for health monitoring and evidence-based prevention of cardiometabolic risk in Luxembourg.