A survey of three nursing homes with view to planning a staffing pattern for a new nursing home

Thesis (M.S.)--Boston Universit

Using comparative genomics to reorder the human genome sequence into a virtual sheep genome

Using BAC-end sequences, a sparse marker map and the sequences of the human, dog and cow genomes, an accurate and detailed sub-gene level map of the sheep genome has been constructed

Surviving Sepsis Campaign: International guidelines for management of severe sepsis and septic shock: 2008

SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Changes in symptomatology, reinfection, and transmissibility associated with the SARS-CoV-2 variant B.1.1.7: an ecological study

Background The SARS-CoV-2 variant B.1.1.7 was first identified in December, 2020, in England. We aimed to investigate whether increases in the proportion of infections with this variant are associated with differences in symptoms or disease course, reinfection rates, or transmissibility. Methods We did an ecological study to examine the association between the regional proportion of infections with the SARS-CoV-2 B.1.1.7 variant and reported symptoms, disease course, rates of reinfection, and transmissibility. Data on types and duration of symptoms were obtained from longitudinal reports from users of the COVID Symptom Study app who reported a positive test for COVID-19 between Sept 28 and Dec 27, 2020 (during which the prevalence of B.1.1.7 increased most notably in parts of the UK). From this dataset, we also estimated the frequency of possible reinfection, defined as the presence of two reported positive tests separated by more than 90 days with a period of reporting no symptoms for more than 7 days before the second positive test. The proportion of SARS-CoV-2 infections with the B.1.1.7 variant across the UK was estimated with use of genomic data from the COVID-19 Genomics UK Consortium and data from Public Health England on spike-gene target failure (a non-specific indicator of the B.1.1.7 variant) in community cases in England. We used linear regression to examine the association between reported symptoms and proportion of B.1.1.7. We assessed the Spearman correlation between the proportion of B.1.1.7 cases and number of reinfections over time, and between the number of positive tests and reinfections. We estimated incidence for B.1.1.7 and previous variants, and compared the effective reproduction number, Rt, for the two incidence estimates. Findings From Sept 28 to Dec 27, 2020, positive COVID-19 tests were reported by 36 920 COVID Symptom Study app users whose region was known and who reported as healthy on app sign-up. We found no changes in reported symptoms or disease duration associated with B.1.1.7. For the same period, possible reinfections were identified in 249 (0·7% [95% CI 0·6–0·8]) of 36 509 app users who reported a positive swab test before Oct 1, 2020, but there was no evidence that the frequency of reinfections was higher for the B.1.1.7 variant than for pre-existing variants. Reinfection occurrences were more positively correlated with the overall regional rise in cases (Spearman correlation 0·56–0·69 for South East, London, and East of England) than with the regional increase in the proportion of infections with the B.1.1.7 variant (Spearman correlation 0·38–0·56 in the same regions), suggesting B.1.1.7 does not substantially alter the risk of reinfection. We found a multiplicative increase in the Rt of B.1.1.7 by a factor of 1·35 (95% CI 1·02–1·69) relative to pre-existing variants. However, Rt fell below 1 during regional and national lockdowns, even in regions with high proportions of infections with the B.1.1.7 variant. Interpretation The lack of change in symptoms identified in this study indicates that existing testing and surveillance infrastructure do not need to change specifically for the B.1.1.7 variant. In addition, given that there was no apparent increase in the reinfection rate, vaccines are likely to remain effective against the B.1.1.7 variant. Funding Zoe Global, Department of Health (UK), Wellcome Trust, Engineering and Physical Sciences Research Council (UK), National Institute for Health Research (UK), Medical Research Council (UK), Alzheimer's Society

Investigation of hospital discharge cases and SARS-CoV-2 introduction into Lothian care homes

Background The first epidemic wave of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in Scotland resulted in high case numbers and mortality in care homes. In Lothian, over one-third of care homes reported an outbreak, while there was limited testing of hospital patients discharged to care homes. Aim To investigate patients discharged from hospitals as a source of SARS-CoV-2 introduction into care homes during the first epidemic wave. Methods A clinical review was performed for all patients discharges from hospitals to care homes from 1st March 2020 to 31st May 2020. Episodes were ruled out based on coronavirus disease 2019 (COVID-19) test history, clinical assessment at discharge, whole-genome sequencing (WGS) data and an infectious period of 14 days. Clinical samples were processed for WGS, and consensus genomes generated were used for analysis using Cluster Investigation and Virus Epidemiological Tool software. Patient timelines were obtained using electronic hospital records. Findings In total, 787 patients discharged from hospitals to care homes were identified. Of these, 776 (99%) were ruled out for subsequent introduction of SARS-CoV-2 into care homes. However, for 10 episodes, the results were inconclusive as there was low genomic diversity in consensus genomes or no sequencing data were available. Only one discharge episode had a genomic, time and location link to positive cases during hospital admission, leading to 10 positive cases in their care home. Conclusion The majority of patients discharged from hospitals were ruled out for introduction of SARS-CoV-2 into care homes, highlighting the importance of screening all new admissions when faced with a novel emerging virus and no available vaccine

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Examples of detailed views of the sheep BAC mapping information on the human and virtual sheep genomes

A short section of human chromosome HSA3 from 0 to 1 Mb, showing human RefSeq genes, tail-to-head and tail-to-tail MegaBAC analysis BACs, and cMegaBAC-CGCs. A short section of human chromosome HSA3 from 23 to 23.8 Mb, showing tracks as above and the Dog net level 2 track. A region of low confidence in the virtual sheep genome. The region is from sheep chromosome OAR9. Tracks shown are the human RefSeq genes from NCBI, sheep markers from the Sheep Map version 4.6, the cMegaBACs, the tail-to-tail BACs from the MegaBAC analysis, and unpaired-in-cow, shown as high (single hits to the cow genome with the parameters used) and low (more than one hit to the cow genome with the parameters used) confidence sets. The dotted lines in the unpaired tracks indicate the predicted extent of the BACs in the genome assuming all BACs are 184 kb long (the average length of the BACs in the library). All images are from genome databases displayed using Gbrowse [45]. BAC, bacterial artificial chromosome; CGC, comparative genome contig; HSA, human chromosome; kb, kilobase; Mb, megabase; NCBI, National Center for Biotechnology Information; OAR, sheep chromosome.<p><b>Copyright information:</b></p><p>Taken from "Using comparative genomics to reorder the human genome sequence into a virtual sheep genome"</p><p>http://genomebiology.com/2007/8/7/R152</p><p>Genome Biology 2007;8(7):R152-R152.</p><p>Published online 30 Jul 2007</p><p>PMCID:PMC2323240.</p><p></p

Representative chromosomes from the human and virtual sheep genome browsers

Chromosome overview of HSA17 showing some of the datasets generated during the construction of the virtual sheep genome. The human genome browser overview tracks shown are as follows and are labelled as referred to in the text: unsequenced regions; gaps in the human genome assembly; cytogenetic markers; sheep markers version 4.6; cow-human conserved synteny; chicken-mammal conserved synteny; mammalian conserved synteny; sheep-dog-human conserved syntenic blocks calculated from the mapping of the sheep BACs to the dog and human genomes; consolidated MegaBAC-CGCs (the final set of 1,172 BAC-CGCs generated from the MegaBAC-CGCs) and the sheep-via-dog and sheep-via-cow BAC-CGCs; MegaBAC-CGCs (calculated from the MegaBAC analysis and before the final consolidation); sheep-via-dog BAC-CGCs (built on the dog genome and mapped onto the human genome); sheep-via-cow BAC-CGCs (built on the cow genome and mapped onto the human genome). Chromosome overview of OAR11 showing cMegaBAC-CGC sections color coded to indicate the method and likely robustness of assignment (Table 3). A selection of virtual sheep genome browser overview tracks is shown. Labelling is as above; in addition, the microsatellite tracks are shown. BACs are shown in the tail-head outsize track, tail-tail outsize track, and so on, on the basis of their group in the MegaBAC analysis, not their actual size and BAC-end sequence orientations in the virtual sheep genome. All images are from genome databases displayed using Gbrowse [45]. BAC, bacterial artificial chromosome; CGC, comparative genome contig; HSA, human chromosome; OAR, sheep chromosome.<p><b>Copyright information:</b></p><p>Taken from "Using comparative genomics to reorder the human genome sequence into a virtual sheep genome"</p><p>http://genomebiology.com/2007/8/7/R152</p><p>Genome Biology 2007;8(7):R152-R152.</p><p>Published online 30 Jul 2007</p><p>PMCID:PMC2323240.</p><p></p

Evolution of genes and genomes on the Drosophila phylogeny

Comparative analysis of multiple genomes in a phylogenetic framework dramatically improves the precision and sensitivity of evolutionary inference, producing more robust results than single-genome analyses can provide. The genomes of 12 Drosophila species, ten of which are presented here for the first time (sechellia, simulans, yakuba, erecta, ananassae, persimilis, willistoni, mojavensis, virilis and grimshawi), illustrate how rates and patterns of sequence divergence across taxa can illuminate evolutionary processes on a genomic scale. These genome sequences augment the formidable genetic tools that have made Drosophila melanogaster a pre-eminent model for animal genetics, and will further catalyse fundamental research on mechanisms of development, cell biology, genetics, disease, neurobiology, behaviour, physiology and evolution. Despite remarkable similarities among these Drosophila species, we identified many putatively non-neutral changes in protein-coding genes, non-coding RNA genes, and cis-regulatory regions. These may prove to underlie differences in the ecology and behaviour of these diverse species