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BackgroundIt is of paramount importance to understand the transmission of SARS-CoV-2 in schools, which could support the decision-making about educational facilities closure or re-opening with effective prevention and control measures in place. MethodsWe conducted a systematic review and meta-analysis to investigate the extent of SARS-CoV-2 transmission in schools. We performed risk of bias evaluation of all included studies using the Newcastle-Ottawa Scale (NOS). Results2,178 articles were retrieved and 11 studies were included. Five cohort studies reported a combined 22 student and 21 staff index cases that exposed 3,345 contacts with 18 transmissions [overall infection attack rate (IAR): 0.08% (95% CI: 0.00%-0.86%)]. IARs for students and school staff were 0.15% (95% CI: 0.00%-0.93%) and 0.70% (95% CI: 0.00%-3.56%) respectively. Six cross-sectional studies reported 639 SARS-CoV-2 positive cases in 6,682 study participants tested [overall SARS-CoV-2 positivity rate: 8.00% (95% CI: 2.17%-16.95%)]. SARS-CoV-2 positivity rate was estimated to be 8.74% (95% CI: 2.34%-18.53%) among students, compared to 13.68% (95% CI: 1.68%-33.89%) among school staff. Gender differences were not found for secondary infection (OR: 1.44, 95% CI: 0.50-4.14, P= 0.49) and SARS-CoV-2 positivity (OR: 0.90, 95% CI: 0.72-1.13, P= 0.36) in schools. Fever, cough, dyspnea, ageusia, anosmia, rhinitis, sore throat, headache, myalgia, asthenia, and diarrhoea were all associated with the detection of SARS-CoV-2 antibodies (based on two studies). Overall, study quality was judged to be poor with risk of performance and attrition bias, limiting the confidence in the results. ConclusionsThere is limited high-quality evidence available to quantify the extent of SARS-CoV-2 transmission in schools or to compare it to community transmission. Emerging evidence suggests lower IAR and SARS-CoV-2 positivity rate in students compared to school staff. Future prospective and adequately controlled cohort studies are necessary to confirm this finding.
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A growing body of evidence shows that poor vitamin D status has been associated with an increased susceptibility to viral and bacterial respiratory infections. In this study, we aimed to examine the association between vitamin D and COVID-19 risk and outcomes, and to explore potential causal effects. We used logistic regression to identify associations between different vitamin D variables (25-hydroxyvitamin D concentration (25-OHD), ambient UVB and genetically-predicted 25-OHD concentrations) and COVID-19 (risk of infection, hospitalisation and death) in 495,780 participants from UK Biobank. We subsequently performed a Mendelian Randomisation (MR) study to test if there was any causal effect. In total, 1,746 COVID-19 cases and 399 COVID-19 deaths occurred between March and June 2020. We found significant inverse associations between COVID-19 infection and 25-OHD in univariable models, but these associations were non-significant after adjustment for confounders. Ambient UVB was strongly and inversely associated with hospitalization and death. Although the main MR analysis showed that genetically-predicted vitamin D levels were not causally associated with COVID-19 risk, MR sensitivity analysis using weighted mode method indicated a potential causal effect (OR=0.72, 95% CI:0.53-0.98; P=0.041). In conclusion, our study found suggestive evidence of association between vitamin D and the risk or severity of COVID-19 but further studies are needed.
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Physical activity (PA) is known to be a protective lifestyle factor against several non-communicable diseases while its impact on infectious diseases, including Coronavirus Disease 2019 (COVID-19) is not as clear. We performed univariate and multivariate logistic regression to identify associations between body mass index (BMI) and both objectively and subjectively measured PA collected prospectively and COVID-19 related outcomes (Overall COVID-19, inpatient COVID-19, outpatient COVID-19, and COVID-19 death) in the UK Biobank (UKBB) cohort. Subsequently, we tested causality by using two-sample Mendelian randomisation (MR) analysis. In the multivariable model, the increased acceleration vector magnitude PA (AMPA) was associated with a decreased probability of overall and outpatient COVID-19. No association was found between self-reported moderate-to-vigorous PA (MVPA) or BMI and COVID-19 related outcomes. Although no causal association was found by MR analyses, this may be due to limited power and we conclude policies to encourage and facilitate exercise at a population level during the pandemic should be considered.
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Understanding the trends in causes of death for different diseases during the current COVID-19 pandemic is important to determine whether there are excess deaths beyond what is normally expected. Using the most recent report from National Records Scotland (NRS) on 29 April 2020, we examined the percentage difference in crude numbers of deaths in 2020 compared to the average for 2015-2019 by week of death within calendar year. To determine if trends were similar, suggesting underreporting/underdiagnosed COVID-19 related deaths, we also looked at the trends in % differences for cardiovascular disease deaths. From the first 17 weeks of data, we found a peak in excess deaths at week 14 of 2020, about four weeks after the first case in Scotland was detected on 1 March 2020-- but by week 17 these excesses had returned to normal levels, 4 weeks after lockdown in the UK began. Similar observations were seen for cardiovascular disease-related deaths. These observations suggest that the short-term increase in excess cancer and cardiovascular deaths might be associated with undetected/unconfirmed deaths related to COVID-19. Both of these conditions make patients more susceptible to infection and lack of widespread access to testing for COVID-19 are likely to have resulted in under-estimation of COVID-19 mortality. These data further suggest that the cumulative toll of COVID-19 on mortality is likely undercounted. More detailed analysis is needed to determine if these excesses were directly or indirectly related to COVID-19. Disease specific mortality will need constant monitoring for the foreseeable future as changes occur in increasing capacity and access to testing, reporting criteria, changes to health services and different measures are implemented to control the spread of the COVID-19. Multidisciplinary, multi-institutional, national and international collaborations for complementary and population specific data analysis is required to respond and mitigate adverse effects of the COVID-19 pandemic and to inform planning for future pandemics.