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Psychological distress and trauma in doctors providing frontline care during the COVID-19 pandemic in the United Kingdom and Ireland: a prospective longitudinal survey cohort study.
OBJECTIVES: The psychological impact of the COVID-19 pandemic on doctors is a significant concern. Due to the emergence of multiple pandemic waves, longitudinal data on the impact of COVID-19 are vital to ensure an adequate psychological care response. The primary aim was to assess the prevalence and degree of psychological distress and trauma in frontline doctors during the acceleration, peak and deceleration of the COVID-19 first wave. Personal and professional factors associated with psychological distress are also reported. DESIGN: A prospective online three-part longitudinal survey. SETTING: Acute hospitals in the UK and Ireland. PARTICIPANTS: Frontline doctors working in emergency medicine, anaesthetics and intensive care medicine during the first wave of the COVID-19 pandemic in March 2020. PRIMARY OUTCOME MEASURES: Psychological distress and trauma measured using the General Health Questionnaire-12 and the Impact of Events-Revised. RESULTS: The initial acceleration survey distributed across networks generated a sample of 5440 doctors. Peak and deceleration response rates from the original sample were 71.6% (n=3896) and 56.6% (n=3079), respectively. Prevalence of psychological distress was 44.7% (n=1334) during the acceleration, 36.9% (n=1098) at peak and 31.5% (n=918) at the deceleration phase. The prevalence of trauma was 23.7% (n=647) at peak and 17.7% (n=484) at deceleration. The prevalence of probable post-traumatic stress disorder was 12.6% (n=343) at peak and 10.1% (n=276) at deceleration. Worry of family infection due to clinical work was the factor most strongly associated with both distress (R2=0.06) and trauma (R2=0.10). CONCLUSION: Findings reflect a pattern of elevated distress at acceleration and peak, with some natural recovery. It is essential that policymakers seek to prevent future adverse effects through (a) provision of vital equipment to mitigate physical and psychological harm, (b) increased awareness and recognition of signs of psychological distress and (c) the development of clear pathways to effective psychological care. TRIAL REGISTRATION NUMBER: ISRCTN10666798
Drosophila Evolution over Space and Time (DEST): A New Population Genomics Resource
Drosophila melanogaster is a leading model in population genetics and genomics, and a growing number of whole-genome data sets from natural populations of this species have been published over the last years. A major challenge is the integration of disparate data sets, often generated using different sequencing technologies and bioinformatic pipelines, which hampers our ability to address questions about the evolution of this species. Here we address these issues by developing a bioinformatics pipeline that maps pooled sequencing (Pool-Seq) reads from D. melanogaster to a hologenome consisting of fly and symbiont genomes and estimates allele frequencies using either a heuristic (PoolSNP) or a probabilistic variant caller (SNAPE-pooled). We use this pipeline to generate the largest data repository of genomic data available for D. melanogaster to date, encompassing 271 previously published and unpublished population samples from over 100 locations in >20 countries on four continents. Several of these locations have been sampled at different seasons across multiple years. This data set, which we call Drosophila Evolution over Space and Time (DEST), is coupled with sampling and environmental metadata. A web-based genome browser and web portal provide easy access to the SNP data set. We further provide guidelines on how to use Pool-Seq data for model-based demographic inference. Our aim is to provide this scalable platform as a community resource which can be easily extended via future efforts for an even more extensive cosmopolitan data set. Our resource will enable population geneticists to analyze spatiotemporal genetic patterns and evolutionary dynamics of D. melanogaster populations in unprecedented detail.We thank four reviewers and the handling editor for helpful comments on previous versions of our manuscript. We are grateful to the members of the DrosEU and DrosRTEC consortia for their long-standing support, collaboration, and for discussion. DrosEU was funded by a Special Topic Networks (STN) grant from the European Society for Evolutionary Biology (ESEB). M.K. was supported by the Austrian Science Foundation (grant no. FWF P32275); J.G. by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (H2020-ERC-2014-CoG-647900) and by the Spanish Ministry of Science and Innovation (BFU-2011-24397); T.F. by the Swiss National Science Foundation (SNSF grants PP00P3_133641, PP00P3_165836, and 31003A_182262) and a Mercator Fellowship from the German Research Foundation (DFG), held as a EvoPAD Visiting Professor at the Institute for Evolution and Biodiversity, University of Münster; AOB by the National Institutes of Health (R35 GM119686); M.K. by Academy of Finland grant 322980; V.L. by Danish Natural Science Research Council (FNU) (grant no. 4002-00113B); FS Deutsche Forschungsgemeinschaft (DFG) (grant no. STA1154/4-1), Project 408908608; J.P. by the Deutsche Forschungsgemeinschaft Projects 274388701 and 347368302; A.U. by FPI fellowship (BES-2012-052999); ET Israel Science Foundation (ISF) (grant no. 1737/17); M.S.V., M.S.R. and M.J. by a grant from the Ministry of Education, Science and Technological Development of the Republic of Serbia (451-03-68/2020-14/200178); A.P., K.E. and M.T. by a grant from the Ministry of Education, Science and Technological Development of the Republic of Serbia (451-03-68/2020-14/200007); and TM NSERC grant RGPIN-2018-05551. The authors acknowledge Research Computing at The University of Virginia for providing computational resources and technical support that have contributed to the results reported within this publication (https://rc.virginia.edu, last accessed September 6, 2021)
Drosophila evolution over space and time (DEST):A new population genomics resource
Drosophila melanogaster is a leading model in population genetics and genomics, and a growing number of whole-genome datasets from natural populations of this species have been published over the last years. A major challenge is the integration of disparate datasets, often generated using different sequencing technologies and bioinformatic pipelines, which hampers our ability to address questions about the evolution of this species. Here we address these issues by developing a bioinformatics pipeline that maps pooled sequencing (Pool-Seq) reads from D. melanogaster to a hologenome consisting of fly and symbiont genomes and estimates allele frequencies using either a heuristic (PoolSNP) or a probabilistic variant caller (SNAPE-pooled). We use this pipeline to generate the largest data repository of genomic data available for D. melanogaster to date, encompassing 271 previously published and unpublished population samples from over 100 locations in > 20 countries on four continents. Several of these locations have been sampled at different seasons across multiple years. This dataset, which we call Drosophila Evolution over Space and Time (DEST), is coupled with sampling and environmental meta-data. A web-based genome browser and web portal provide easy access to the SNP dataset. We further provide guidelines on how to use Pool-Seq data for model-based demographic inference. Our aim is to provide this scalable platform as a community resource which can be easily extended via future efforts for an even more extensive cosmopolitan dataset. Our resource will enable population geneticists to analyze spatio-temporal genetic patterns and evolutionary dynamics of D. melanogaster populations in unprecedented detail.DrosEU is funded by a Special Topic Networks (STN) grant from the European Society for Evolutionary Biology (ESEB). MK (M. Kapun) was supported by the Austrian Science Foundation (grant no. FWF P32275); JG by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (H2020-ERC-2014-CoG-647900) and by the Spanish Ministry of Science and Innovation (BFU-2011-24397); TF by the Swiss National Science Foundation (SNSF grants PP00P3_133641, PP00P3_165836, and 31003A_182262) and a Mercator Fellowship from the German Research Foundation (DFG), held as a EvoPAD Visiting Professor at the Institute for Evolution and Biodiversity, University of Münster; AOB by the National Institutes of Health (R35 GM119686); MK (M. Kankare) by Academy of Finland grant 322980; VL by Danish Natural Science Research Council (FNU) grant 4002-00113B; FS Deutsche Forschungsgemeinschaft (DFG) grant STA1154/4-1, Project 408908608; JP by the Deutsche Forschungsgemeinschaft Projects 274388701 and 347368302; AU by FPI fellowship (BES-2012-052999); ET Israel Science Foundation (ISF) grant 1737/17; MSV, MSR and MJ by a grant from the Ministry of Education, Science and Technological Development of the Republic of Serbia (451-03-68/2020-14/200178); AP, KE and MT by a grant from the Ministry of Education, Science and Technological Development of the Republic of Serbia (451-03-68/2020-14/200007); and TM NSERC grant RGPIN-2018-05551.Peer reviewe
Corrigendum to: Drosophila Evolution over Space and Time (DEST): a New Population Genomics Resource
Drosophila melanogaster is a leading model in population genetics and genomics, and a growing number of whole-genome datasets from natural populations of this species have been published over the last years. A major challenge is the integration of disparate datasets, often generated using different sequencing technologies and bioinformatic pipelines, which hampers our ability to address questions about the evolution of this species. Here we address these issues by developing a bioinformatics pipeline that maps pooled sequencing (Pool-Seq) reads from D. melanogaster to a hologenome consisting of fly and symbiont genomes and estimates allele frequencies using either a heuristic (PoolSNP) or a probabilistic variant caller (SNAPE-pooled). We use this pipeline to generate the largest data repository of genomic data available for D. melanogaster to date, encompassing 271 previously published and unpublished population samples from over 100 locations in > 20 countries on four continents. Several of these locations have been sampled at different seasons across multiple years. This dataset, which we call Drosophila Evolution over Space and Time (DEST), is coupled with sampling and environmental meta-data. A web-based genome browser and web portal provide easy access to the SNP dataset. We further provide guidelines on how to use Pool-Seq data for model-based demographic inference. Our aim is to provide this scalable platform as a community resource which can be easily extended via future efforts for an even more extensive cosmopolitan dataset. Our resource will enable population geneticists to analyze spatio-temporal genetic patterns and evolutionary dynamics of D. melanogaster populations in unprecedented detail.DrosEU is funded by a Special Topic Networks (STN) grant from the European Society for Evolutionary Biology (ESEB). MK (M. Kapun) was supported by the Austrian Science Foundation (grant no. FWF P32275); JG by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (H2020-ERC-2014-CoG-647900) and by the Spanish Ministry of Science and Innovation (BFU-2011-24397); TF by the Swiss National Science Foundation (SNSF grants PP00P3_133641, PP00P3_165836, and 31003A_182262) and a Mercator Fellowship from the German Research Foundation (DFG), held as a EvoPAD Visiting Professor at the Institute for Evolution and Biodiversity, University of Münster; AOB by the National Institutes of Health (R35 GM119686); MK (M. Kankare) by Academy of Finland grant 322980; VL by Danish Natural Science Research Council (FNU) grant 4002-00113B; FS Deutsche Forschungsgemeinschaft (DFG) grant STA1154/4-1, Project 408908608; JP by the Deutsche Forschungsgemeinschaft Projects 274388701 and 347368302; AU by FPI fellowship (BES-2012-052999); ET Israel Science Foundation (ISF) grant 1737/17; MSV, MSR and MJ by a grant from the Ministry of Education, Science and Technological Development of the Republic of Serbia (451-03-68/2020-14/200178); AP, KE and MT by a grant from the Ministry of Education, Science and Technological Development of the Republic of Serbia (451-03-68/2020-14/200007); and TM NSERC grant RGPIN-2018-05551.Peer reviewe
One Plus One Equals Two—will that do? A trial protocol for a Swedish multicentre randomised controlled trial to evaluate a clinical practice to reduce severe perineal trauma {1}
Background: Severe perineal trauma sustained during childbirth is a serious complication since it can lead to both short- and long-term consequences for women. Some of the methods used to prevent perineal injuries have been evaluated in clinical trials, but there are still gaps in the evidence. A new clinical practice has been introduced, adopted by more than half of the maternity wards in Sweden with the aim of reducing severe perineal trauma. This procedure involves two midwives assisting the woman during the second stage of labour. Methods/design: In this multicentre randomised controlled trial, 2946 women will be randomised to be assisted by one or two midwives during the second stage of labour. Women age 18–47, who plan for their first vaginal birth, with a singleton pregnancy in cephalic presentation, will be asked to participate when admitted to the maternity ward. Five maternity wards comprising 19,500 births/year in different parts of Sweden will participate in this study. The sample size is powered to demonstrate a 50% reduction (from 4.1–2.0%) in primary outcome, which is the prevalence of severe perineal trauma (3rd and 4th degree). Secondary outcomes will include maternal and neonatal outcomes, women’s experiences, midwives’ experiences of the intervention, incontinence, and pelvic floor symptoms. The primary analysis is intention to treat. Questionnaires will be sent to the women at 1 month and 1 year after the birth to assess women’s experiences, pain, incontinence, pelvic floor symptoms, sexual function, and mental health. Discussion: It is important for care during labour and birth to be evidence based. There is a strong desire among midwives to reduce the risk of severe perineal trauma. This may lead to new strategies and practices being implemented into practice without scientific evidence. The intervention might have negative side effects or unintended consequences. On the other hand, there is a possibility of the intervention improving care for women. Trial registration {2a}: ClinicalTrials.gov NCT03770962. Registered on 10 December 201