International genomic definition of pneumococcal lineages, to contextualise disease, antibiotic resistance and vaccine impact

Background: Pneumococcal conjugate vaccines have reduced the incidence of invasive pneumococcal disease, caused by vaccine serotypes, but non-vaccine-serotypes remain a concern. We used whole genome sequencing to study pneumococcal serotype, antibiotic resistance and invasiveness, in the context of genetic background. / Methods: Our dataset of 13,454 genomes, combined with four published genomic datasets, represented Africa (40%), Asia (25%), Europe (19%), North America (12%), and South America (5%). These 20,027 pneumococcal genomes were clustered into lineages using PopPUNK, and named Global Pneumococcal Sequence Clusters (GPSCs). From our dataset, we additionally derived serotype and sequence type, and predicted antibiotic sensitivity. We then measured invasiveness using odds ratios that relating prevalence in invasive pneumococcal disease to carriage. / Findings: The combined collections (n = 20,027) were clustered into 621 GPSCs. Thirty-five GPSCs observed in our dataset were represented by >100 isolates, and subsequently classed as dominant-GPSCs. In 22/35 (63%) of dominant-GPSCs both non-vaccine serotypes and vaccine serotypes were observed in the years up until, and including, the first year of pneumococcal conjugate vaccine introduction. Penicillin and multidrug resistance were higher (p < .05) in a subset dominant-GPSCs (14/35, 9/35 respectively), and resistance to an increasing number of antibiotic classes was associated with increased recombination (R2 = 0.27 p < .0001). In 28/35 dominant-GPSCs, the country of isolation was a significant predictor (p < .05) of its antibiogram (mean misclassification error 0.28, SD ± 0.13). We detected increased invasiveness of six genetic backgrounds, when compared to other genetic backgrounds expressing the same serotype. Up to 1.6-fold changes in invasiveness odds ratio were observed. / Interpretation: We define GPSCs that can be assigned to any pneumococcal genomic dataset, to aid international comparisons. Existing non-vaccine-serotypes in most GPSCs preclude the removal of these lineages by pneumococcal conjugate vaccines; leaving potential for serotype replacement. A subset of GPSCs have increased resistance, and/or serotype-independent invasiveness

A mosaic tetracycline resistance gene tet(S/M) detected in an MDR pneumococcal CC230 lineage that underwent capsular switching in South Africa

Objectives: We reported tet(S/M) in Streptococcus pneumoniae and investigated its temporal spread in relation to nationwide clinical interventions. Methods: We whole-genome sequenced 12 254 pneumococcal isolates from 29 countries on an Illumina HiSeq sequencer. Serotype, multilocus ST and antibiotic resistance were inferred from genomes. An SNP tree was built using Gubbins. Temporal spread was reconstructed using a birth–death model. Results: We identified tet(S/M) in 131 pneumococcal isolates and none carried other known tet genes. Tetracycline susceptibility testing results were available for 121 tet(S/M)-positive isolates and all were resistant. A majority (74%) of tet(S/M)-positive isolates were from South Africa and caused invasive diseases among young children (59% HIV positive, where HIV status was available). All but two tet(S/M)-positive isolates belonged to clonal complex (CC) 230. A global phylogeny of CC230 (n=389) revealed that tet(S/M)-positive isolates formed a sublineage predicted to exhibit resistance to penicillin, co-trimoxazole, erythromycin and tetracycline. The birth–death model detected an unrecognized outbreak of this sublineage in South Africa between 2000 and 2004 with expected secondary infections (effective reproductive number, R) of ∼2.5. R declined to ∼1.0 in 2005 and <1.0 in 2012. The declining epidemic could be related to improved access to ART in 2004 and introduction of pneumococcal conjugate vaccine (PCV) in 2009. Capsular switching from vaccine serotype 14 to non-vaccine serotype 23A was observed within the sublineage. Conclusions: The prevalence of tet(S/M) in pneumococci was low and its dissemination was due to an unrecognized outbreak of CC230 in South Africa. Capsular switching in this MDR sublineage highlighted its potential to continue to cause disease in the post-PCV13 era

Visualizing variation within Global Pneumococcal Sequence Clusters (GPSCs) and country population snapshots to contextualize pneumococcal isolates

Knowledge of pneumococcal lineages, their geographic distribution and antibiotic resistance patterns, can give insights into global pneumococcal disease. We provide interactive bioinformatic outputs to explore such topics, aiming to increase dissemination of genomic insights to the wider community, without the need for specialist training. We prepared 12 country-specific phylogenetic snapshots, and international phylogenetic snapshots of 73 common Global Pneumococcal Sequence Clusters (GPSCs) previously defined using PopPUNK, and present them in Microreact. Gene presence and absence defined using Roary, and recombination profiles derived from Gubbins are presented in Phandango for each GPSC. Temporal phylogenetic signal was assessed for each GPSC using BactDating. We provide examples of how such resources can be used. In our example use of a country-specific phylogenetic snapshot we determined that serotype 14 was observed in nine unrelated genetic backgrounds in South Africa. The international phylogenetic snapshot of GPSC9, in which most serotype 14 isolates from South Africa were observed, highlights that there were three independent sub-clusters represented by South African serotype 14 isolates. We estimated from the GPSC9-dated tree that the sub-clusters were each established in South Africa during the 1980s. We show how recombination plots allowed the identification of a 20kb recombination spanning the capsular polysaccharide locus within GPSC97. This was consistent with a switch from serotype 6A to 19A estimated to have occured in the 1990s from the GPSC97-dated tree. Plots of gene presence/absence of resistance genes (tet, erm, cat) across the GPSC23 phylogeny were consistent with acquisition of a composite transposon. We estimated from the GPSC23-dated tree that the acquisition occurred between 1953 and 1975. Finally, we demonstrate the assignment of GPSC31 to 17 externally generated pneumococcal serotype 1 assemblies from Utah via Pathogenwatch. Most of the Utah isolates clustered within GPSC31 in a USA-specific clade with the most recent common ancestor estimated between 1958 and 1981. The resources we have provided can be used to explore to data, test hypothesis and generate new hypotheses. The accessible assignment of GPSCs allows others to contextualize their own collections beyond the data presented here

A critical review of the research literature on Six Sigma, Lean and StuderGroup's Hardwiring Excellence in the United States: the need to demonstrate and communicate the effectiveness of transformation strategies in healthcare

<p>Abstract</p> <p>Background</p> <p>U.S. healthcare organizations are confronted with numerous and varied transformational strategies promising improvements along all dimensions of quality and performance. This article examines the peer-reviewed literature from the U.S. for evidence of effectiveness among three current popular transformational strategies: Six Sigma, Lean/Toyota Production System, and Studer's Hardwiring Excellence.</p> <p>Methods</p> <p>The English language health, healthcare management, and organizational science literature (up to December 2007) indexed in Medline, Web of Science, ABI/Inform, Cochrane Library, CINAHL, and ERIC was reviewed for studies on the aforementioned transformation strategies in healthcare settings. Articles were included if they: appeared in a peer-reviewed journal; described a specific intervention; were not classified as a pilot study; provided quantitative data; and were not review articles. Nine references on Six Sigma, nine on Lean/Toyota Production System, and one on StuderGroup meet the study's eligibility criteria.</p> <p>Results</p> <p>The reviewed studies universally concluded the implementations of these transformation strategies were successful in improving a variety of healthcare related processes and outcomes. Additionally, the existing literature reflects a wide application of these transformation strategies in terms of both settings and problems. However, despite these positive features, the vast majority had methodological limitations that might undermine the validity of the results. Common features included: weak study designs, inappropriate analyses, and failures to rule out alternative hypotheses. Furthermore, frequently absent was any attention to changes in organizational culture or substantial evidence of lasting effects from these efforts.</p> <p>Conclusion</p> <p>Despite the current popularity of these strategies, few studies meet the inclusion criteria for this review. Furthermore, each could have been improved substantially in order to ensure the validity of the conclusions, demonstrate sustainability, investigate changes in organizational culture, or even how one strategy interfaced with other concurrent and subsequent transformation efforts. While informative results can be gleaned from less rigorous studies, improved design and analysis can more effectively guide healthcare leaders who are motivated to transform their organizations and convince others of the need to employ such strategies. Demanding more exacting evaluation of projects consultants, or partnerships with health management researchers in academic settings, can support such efforts.</p

Pneumococcal lineages associated with serotype replacement and antibiotic resistance in childhood invasive pneumococcal disease in the post-PCV13 era: an international whole-genome sequencing study

Background: Invasive pneumococcal disease remains an important health priority owing to increasing disease incidence caused by pneumococci expressing non-vaccine serotypes. We previously defined 621 Global Pneumococcal Sequence Clusters (GPSCs) by analysing 20 027 pneumococcal isolates collected worldwide and from previously published genomic data. In this study, we aimed to investigate the pneumococcal lineages behind the predominant serotypes, the mechanism of serotype replacement in disease, as well as the major pneumococcal lineages contributing to invasive pneumococcal disease in the post-vaccine era and their antibiotic resistant traits. / Methods: We whole-genome sequenced 3233 invasive pneumococcal disease isolates from laboratory-based surveillance programmes in Hong Kong (n=78), Israel (n=701), Malawi (n=226), South Africa (n=1351), The Gambia (n=203), and the USA (n=674). The genomes represented pneumococci from before and after pneumococcal conjugate vaccine (PCV) introductions and were from children younger than 3 years. We identified predominant serotypes by prevalence and their major contributing lineages in each country, and assessed any serotype replacement by comparing the incidence rate between the pre-PCV and PCV periods for Israel, South Africa, and the USA. We defined the status of a lineage as vaccine-type GPSC (≥50% 13-valent PCV [PCV13] serotypes) or non-vaccine-type GPSC (>50% non-PCV13 serotypes) on the basis of its initial serotype composition detected in the earliest vaccine period to measure their individual contribution toward serotype replacement in each country. Major pneumococcal lineages in the PCV period were identified by pooled incidence rate using a random effects model. / Findings: The five most prevalent serotypes in the PCV13 period varied between countries, with only serotypes 5, 12F, 15B/C, 19A, 33F, and 35B/D common to two or more countries. The five most prevalent serotypes in the PCV13 period varied between countries, with only serotypes 5, 12F, 15B/C, 19A, 33F, and 35B/D common to two or more countries. These serotypes were associated with more than one lineage, except for serotype 5 (GPSC8). Serotype replacement was mainly mediated by expansion of non-vaccine serotypes within vaccine-type GPSCs and, to a lesser extent, by increases in non-vaccine-type GPSCs. A globally spreading lineage, GPSC3, expressing invasive serotypes 8 in South Africa and 33F in the USA and Israel, was the most common lineage causing non-vaccine serotype invasive pneumococcal disease in the PCV13 period. We observed that same prevalent non-vaccine serotypes could be associated with distinctive lineages in different countries, which exhibited dissimilar antibiotic resistance profiles. In non-vaccine serotype isolates, we detected significant increases in the prevalence of resistance to penicillin (52 [21%] of 249 vs 169 [29%] of 575, p=0·0016) and erythromycin (three [1%] of 249 vs 65 [11%] of 575, p=0·0031) in the PCV13 period compared with the pre-PCV period. / Interpretation: Globally spreading lineages expressing invasive serotypes have an important role in serotype replacement, and emerging non-vaccine serotypes associated with different pneumococcal lineages in different countries might be explained by local antibiotic-selective pressures. Continued genomic surveillance of the dynamics of the pneumococcal population with increased geographical representation in the post-vaccine period will generate further knowledge for optimising future vaccine design. / Funding: Bill & Melinda Gates Foundation, Wellcome Sanger Institute, and the US Centers for Disease Control

International links between Streptococcus pneumoniae vaccine serotype 4 sequence type (ST) 801 in Northern European shipyard outbreaks of invasive pneumococcal disease

Background: Pneumococcal disease outbreaks of vaccine preventable serotype 4 sequence type (ST)801 in shipyards have been reported in several countries. We aimed to use genomics to establish any international links between them. Methods: Sequence data from ST801-related outbreak isolates from Norway (n = 17), Finland (n = 11) and Northern Ireland (n = 2) were combined with invasive pneumococcal disease surveillance from the respective countries, and ST801-related genomes from an international collection (n = 41 of > 40,000), totalling 106 genomes. Raw data were mapped and recombination excluded before phylogenetic dating. Results: Outbreak isolates were relatively diverse, with up to 100 SNPs (single nucleotide polymorphisms) and a common ancestor estimated around the year 2000. However, 19 Norwegian and Finnish isolates were nearly indistinguishable (0–2 SNPs) with the common ancestor dated around 2017. Conclusion: The total diversity of ST801 within the outbreaks could not be explained by recent transmission alone, suggesting that harsh environmental and associated living conditions reported in the shipyards may facilitate invasion of colonising pneumococci. However, near identical strains in the Norwegian and Finnish outbreaks does suggest that transmission between international shipyards also contributed to those outbreaks. This indicates the need for improved preventative measures in this working population including pneumococcal vaccination

DDT, epigenetic harm, and transgenerational environmental justice

Although the environmentally harmful effects of widespread dichlorodiphenyltrichloroethane (DDT) use became well-known following Rachel Carson’s Silent Spring (1962), its human health effects have more recently become clearer. A ban on the use of DDT has been in place for over 30 years, but recently DDT has been used for malaria control in areas such as Africa. Recent work shows that DDT has transgenerational effects in progeny and generations never directly exposed to DDT. These effects have health implications for individuals who are not able to have any voice in the decision to use the pesticide. The transgenerational effects of DDT are considered in light of some widely accepted ethical principles. We argue that this reframes the decision to use DDT, requiring us to incorporate new considerations, and new kinds of decision making, into the deliberative process that determines its ongoing use. Ethical considerations for intergenerational environmental justice are presented that include concern and respect for autonomy, nonmaleficence, and justice. Here, we offer a characterization of the kinds of ethical considerations that must be taken into account in any satisfactory decisions to use DDT

Risk of adverse outcomes in patients with underlying respiratory conditions admitted to hospital with COVID-19:a national, multicentre prospective cohort study using the ISARIC WHO Clinical Characterisation Protocol UK

Background Studies of patients admitted to hospital with COVID-19 have found varying mortality outcomes associated with underlying respiratory conditions and inhaled corticosteroid use. Using data from a national, multicentre, prospective cohort, we aimed to characterise people with COVID-19 admitted to hospital with underlying respiratory disease, assess the level of care received, measure in-hospital mortality, and examine the effect of inhaled corticosteroid use. Methods We analysed data from the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) WHO Clinical Characterisation Protocol UK (CCP-UK) study. All patients admitted to hospital with COVID-19 across England, Scotland, and Wales between Jan 17 and Aug 3, 2020, were eligible for inclusion in this analysis. Patients with asthma, chronic pulmonary disease, or both, were identified and stratified by age (<16 years, 16–49 years, and ≥50 years). In-hospital mortality was measured by use of multilevel Cox proportional hazards, adjusting for demographics, comorbidities, and medications (inhaled corticosteroids, short-acting β-agonists [SABAs], and long-acting β-agonists [LABAs]). Patients with asthma who were taking an inhaled corticosteroid plus LABA plus another maintenance asthma medication were considered to have severe asthma. Findings 75 463 patients from 258 participating health-care facilities were included in this analysis: 860 patients younger than 16 years (74 [8·6%] with asthma), 8950 patients aged 16–49 years (1867 [20·9%] with asthma), and 65 653 patients aged 50 years and older (5918 [9·0%] with asthma, 10 266 [15·6%] with chronic pulmonary disease, and 2071 [3·2%] with both asthma and chronic pulmonary disease). Patients with asthma were significantly more likely than those without asthma to receive critical care (patients aged 16–49 years: adjusted odds ratio [OR] 1·20 [95% CI 1·05–1·37]; p=0·0080; patients aged ≥50 years: adjusted OR 1·17 [1·08–1·27]; p<0·0001), and patients aged 50 years and older with chronic pulmonary disease (with or without asthma) were significantly less likely than those without a respiratory condition to receive critical care (adjusted OR 0·66 [0·60–0·72] for those without asthma and 0·74 [0·62–0·87] for those with asthma; p<0·0001 for both). In patients aged 16–49 years, only those with severe asthma had a significant increase in mortality compared to those with no asthma (adjusted hazard ratio [HR] 1·17 [95% CI 0·73–1·86] for those on no asthma therapy, 0·99 [0·61–1·58] for those on SABAs only, 0·94 [0·62–1·43] for those on inhaled corticosteroids only, 1·02 [0·67–1·54] for those on inhaled corticosteroids plus LABAs, and 1·96 [1·25–3·08] for those with severe asthma). Among patients aged 50 years and older, those with chronic pulmonary disease had a significantly increased mortality risk, regardless of inhaled corticosteroid use, compared to patients without an underlying respiratory condition (adjusted HR 1·16 [95% CI 1·12–1·22] for those not on inhaled corticosteroids, and 1·10 [1·04–1·16] for those on inhaled corticosteroids; p<0·0001). Patients aged 50 years and older with severe asthma also had an increased mortality risk compared to those not on asthma therapy (adjusted HR 1·24 [95% CI 1·04–1·49]). In patients aged 50 years and older, inhaled corticosteroid use within 2 weeks of hospital admission was associated with decreased mortality in those with asthma, compared to those without an underlying respiratory condition (adjusted HR 0·86 [95% CI 0·80−0·92]). Interpretation Underlying respiratory conditions are common in patients admitted to hospital with COVID-19. Regardless of the severity of symptoms at admission and comorbidities, patients with asthma were more likely, and those with chronic pulmonary disease less likely, to receive critical care than patients without an underlying respiratory condition. In patients aged 16 years and older, severe asthma was associated with increased mortality compared to non-severe asthma. In patients aged 50 years and older, inhaled corticosteroid use in those with asthma was associated with lower mortality than in patients without an underlying respiratory condition; patients with chronic pulmonary disease had significantly increased mortality compared to those with no underlying respiratory condition, regardless of inhaled corticosteroid use. Our results suggest that the use of inhaled corticosteroids, within 2 weeks of admission, improves survival for patients aged 50 years and older with asthma, but not for those with chronic pulmonary disease

Development and validation of the ISARIC 4C Deterioration model for adults hospitalised with COVID-19: a prospective cohort study.

BACKGROUND: Prognostic models to predict the risk of clinical deterioration in acute COVID-19 cases are urgently required to inform clinical management decisions. METHODS: We developed and validated a multivariable logistic regression model for in-hospital clinical deterioration (defined as any requirement of ventilatory support or critical care, or death) among consecutively hospitalised adults with highly suspected or confirmed COVID-19 who were prospectively recruited to the International Severe Acute Respiratory and Emerging Infections Consortium Coronavirus Clinical Characterisation Consortium (ISARIC4C) study across 260 hospitals in England, Scotland, and Wales. Candidate predictors that were specified a priori were considered for inclusion in the model on the basis of previous prognostic scores and emerging literature describing routinely measured biomarkers associated with COVID-19 prognosis. We used internal-external cross-validation to evaluate discrimination, calibration, and clinical utility across eight National Health Service (NHS) regions in the development cohort. We further validated the final model in held-out data from an additional NHS region (London). FINDINGS: 74 944 participants (recruited between Feb 6 and Aug 26, 2020) were included, of whom 31 924 (43·2%) of 73 948 with available outcomes met the composite clinical deterioration outcome. In internal-external cross-validation in the development cohort of 66 705 participants, the selected model (comprising 11 predictors routinely measured at the point of hospital admission) showed consistent discrimination, calibration, and clinical utility across all eight NHS regions. In held-out data from London (n=8239), the model showed a similarly consistent performance (C-statistic 0·77 [95% CI 0·76 to 0·78]; calibration-in-the-large 0·00 [-0·05 to 0·05]); calibration slope 0·96 [0·91 to 1·01]), and greater net benefit than any other reproducible prognostic model. INTERPRETATION: The 4C Deterioration model has strong potential for clinical utility and generalisability to predict clinical deterioration and inform decision making among adults hospitalised with COVID-19. FUNDING: National Institute for Health Research (NIHR), UK Medical Research Council, Wellcome Trust, Department for International Development, Bill & Melinda Gates Foundation, EU Platform for European Preparedness Against (Re-)emerging Epidemics, NIHR Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections at University of Liverpool, NIHR HPRU in Respiratory Infections at Imperial College London

Importance of patient bed pathways and length of stay differences in predicting COVID-19 hospital bed occupancy in England.

Background: Predicting bed occupancy for hospitalised patients with COVID-19 requires understanding of length of stay (LoS) in particular bed types. LoS can vary depending on the patient’s “bed pathway” - the sequence of transfers of individual patients between bed types during a hospital stay. In this study, we characterise these pathways, and their impact on predicted hospital bed occupancy. Methods: We obtained data from University College Hospital (UCH) and the ISARIC4C COVID-19 Clinical Information Network (CO-CIN) on hospitalised patients with COVID-19 who required care in general ward or critical care (CC) beds to determine possible bed pathways and LoS. We developed a discrete-time model to examine the implications of using either bed pathways or only average LoS by bed type to forecast bed occupancy. We compared model-predicted bed occupancy to publicly available bed occupancy data on COVID-19 in England between March and August 2020. Results: In both the UCH and CO-CIN datasets, 82% of hospitalised patients with COVID-19 only received care in general ward beds. We identified four other bed pathways, present in both datasets: “Ward, CC, Ward”, “Ward, CC”, “CC” and “CC, Ward”. Mean LoS varied by bed type, pathway, and dataset, between 1.78 and 13.53 days. For UCH, we found that using bed pathways improved the accuracy of bed occupancy predictions, while only using an average LoS for each bed type underestimated true bed occupancy. However, using the CO-CIN LoS dataset we were not able to replicate past data on bed occupancy in England, suggesting regional LoS heterogeneities. Conclusions: We identified five bed pathways, with substantial variation in LoS by bed type, pathway, and geography. This might be caused by local differences in patient characteristics, clinical care strategies, or resource availability, and suggests that national LoS averages may not be appropriate for local forecasts of bed occupancy for COVID-19. Trial registration: The ISARIC WHO CCP-UK study ISRCTN66726260 was retrospectively registered on 21/04/2020 and designated an Urgent Public Health Research Study by NIHR.</p