STUDY DESIGN AND STATISTICAL ANALYSIS: Overall, 5058 respondents from Thailand, Malaysia, the UK, Italy and Slovenia completed the self-administered survey between May and June 2020. Poststratification weighting was applied, and associations between categorical variables assessed. Frequency counts and percentages were used to summarise categorical data. Associations between categorical variables were assessed using Pearson's χ2 test. Data were analysed in Stata 15.0 RESULTS: Among the five countries, Thai respondents reported having been most, and Slovenian respondents least, affected economically. The following factors were associated with greater negative economic impacts: being 18-24 years or 65 years or older; lower education levels; larger households; having children under 18 in the household and and having flexible/no income. Regarding social impact, respondents expressed most concern about their social life, physical health, mental health and well-being.There were large differences between countries in terms of voluntary behavioural change, and in compliance and agreement with COVID-19 restrictions. Overall, self-reported compliance was higher among respondents who self-reported a high understanding of COVID-19. UK respondents felt able to cope the longest and Thai respondents the shortest with only going out for essential needs or work. Many respondents reported seeing news perceived to be fake, the proportion varying between countries, with education level and self-reported levels of understanding of COVID-19.
CONCLUSIONS: Our data showed that COVID-19 and public health measures have uneven economic and social impacts on people from different countries and social groups. Understanding the factors associated with these impacts can help to inform future public health interventions and mitigate their negative consequences.
TRIAL REGISTRATION NUMBER: TCTR20200401002.
FINDINGS: In this study, we collected and tested 253 rectal swabs from pet dogs; of which 64 samples (25.3%) tested positive for AstVs with diarrhea and 15 more samples (5.9%) also was identified as AstVs, however without any clinical signs. Phylogenetic analysis of 39 partial ORF1b sequences from these samples revealed that they are similar to AstVs, which can be subdivided into three lineages. Interestingly, out of the 39 isolates sequenced, 16 isolates are shown to be in the Mamastrovirus 5/canine astrovirus (CAstV) lineage and the remaining 23 isolates displayed higher similarities with known porcine astrovirus (PoAstV) 5 and 2. Further, analysis of 13 capsid sequences from these isolates showed that they are closely clustered with Chinese or Italy CAstV isolates.
CONCLUSIONS: The findings indicate that CAstVs commonly circulate in pet dogs, and our sequencing results have shown the genomic diversity of CAstVs leading to increasing number of clusters.
METHODS: The international consensus meeting on post-traumatic CP was held during the International Conference on Recent Advances in Neurotraumatology (ICRAN), in Naples, Italy, in June 2018. This meeting was endorsed by the Neurotrauma Committee of the World Federation of Neurosurgical Societies (WFNS), the NIHR Global Health Research Group on Neurotrauma, and several other neurotrauma organizations. Discussions and voting were organized around 5 pre-specified themes: (1) indications and technique, (2) materials, (3) timing, (4) hydrocephalus, and (5) paediatric CP.
RESULTS: The participants discussed published evidence on each topic and proposed consensus statements, which were subject to ratification using anonymous real-time voting. Statements required an agreement threshold of more than 70% for inclusion in the final recommendations.
CONCLUSIONS: This document is the first set of practical consensus-based clinical recommendations on post-traumatic CP, focusing on timing, materials, complications, and surgical procedures. Future research directions are also presented.
METHODS: We source daily death registry data for 4100 municipalities in Italy's north and match them to Census data. We augment the dataset with municipality-level data on a host of co-factors of COVID-19 mortality, which we exploit in a differences-in-differences regression model to analyze COVID-19-induced mortality.
RESULTS: We find that COVID-19 killed more than 0.15% of the local population during the first wave of the epidemic. We also show that official statistics vastly underreport this death toll, by about 60%. Next, we uncover the dramatic effects of the epidemic on nursing home residents in the outbreak epicenter: in municipalities with a high share of the elderly living in nursing homes, COVID-19 mortality was about twice as high as in those with no nursing home intown.
CONCLUSIONS: A pro-active approach in managing the epidemic is key to reduce COVID-19 mortality. Authorities should ramp-up testing capacity and increase contact-tracing abilities. Adequate protective equipment should be provided to nursing home residents and staff.