Multiple pathways of SARS-CoV-2 nosocomial transmission uncovered by integrated genomic and epidemiological analyses during the second wave of the COVID-19 pandemic in the UK

IntroductionThroughout the global COVID-19 pandemic, nosocomial transmission has represented a major concern for healthcare settings and has accounted for many infections diagnosed within hospitals. As restrictions ease and novel variants continue to spread, it is important to uncover the specific pathways by which nosocomial outbreaks occur to understand the most suitable transmission control strategies for the future.MethodsIn this investigation, SARS-CoV-2 genome sequences obtained from 694 healthcare workers and 1,181 patients were analyzed at a large acute NHS hospital in the UK between September 2020 and May 2021. These viral genomic data were combined with epidemiological data to uncover transmission routes within the hospital. We also investigated the effects of the introduction of the highly transmissible variant of concern (VOC), Alpha, over this period, as well as the effects of the national vaccination program on SARS-CoV-2 infection in the hospital.ResultsOur results show that infections of all variants within the hospital increased as community prevalence of Alpha increased, resulting in several outbreaks and super-spreader events. Nosocomial infections were enriched amongst older and more vulnerable patients more likely to be in hospital for longer periods but had no impact on disease severity. Infections appeared to be transmitted most regularly from patient to patient and from patients to HCWs. In contrast, infections from HCWs to patients appeared rare, highlighting the benefits of PPE in infection control. The introduction of the vaccine at this time also reduced infections amongst HCWs by over four-times.DiscussionThese analyses have highlighted the importance of control measures such as regular testing, rapid lateral flow testing alongside polymerase chain reaction (PCR) testing, isolation of positive patients in the emergency department (where possible), and physical distancing of patient beds on hospital wards to minimize nosocomial transmission of infectious diseases such as COVID-19

Multiple pathways of SARS-CoV-2 nosocomial transmission uncovered by integrated genomic and epidemiological analyses during the second wave of the COVID-19 pandemic in the UK

INTRODUCTION: Throughout the global COVID-19 pandemic, nosocomial transmission has represented a major concern for healthcare settings and has accounted for many infections diagnosed within hospitals. As restrictions ease and novel variants continue to spread, it is important to uncover the specific pathways by which nosocomial outbreaks occur to understand the most suitable transmission control strategies for the future. METHODS: In this investigation, SARS-CoV-2 genome sequences obtained from 694 healthcare workers and 1,181 patients were analyzed at a large acute NHS hospital in the UK between September 2020 and May 2021. These viral genomic data were combined with epidemiological data to uncover transmission routes within the hospital. We also investigated the effects of the introduction of the highly transmissible variant of concern (VOC), Alpha, over this period, as well as the effects of the national vaccination program on SARS-CoV-2 infection in the hospital. RESULTS: Our results show that infections of all variants within the hospital increased as community prevalence of Alpha increased, resulting in several outbreaks and super-spreader events. Nosocomial infections were enriched amongst older and more vulnerable patients more likely to be in hospital for longer periods but had no impact on disease severity. Infections appeared to be transmitted most regularly from patient to patient and from patients to HCWs. In contrast, infections from HCWs to patients appeared rare, highlighting the benefits of PPE in infection control. The introduction of the vaccine at this time also reduced infections amongst HCWs by over four-times. DISCUSSION: These analyses have highlighted the importance of control measures such as regular testing, rapid lateral flow testing alongside polymerase chain reaction (PCR) testing, isolation of positive patients in the emergency department (where possible), and physical distancing of patient beds on hospital wards to minimize nosocomial transmission of infectious diseases such as COVID-19

The early detection of postpartum depression: midwives and nurses trial a checklist

Objective: To evaluate the use of a standard pen-and-paper test versus the use of a checklist for the early identification of women at risk of postpartum depression and to investigate the experiences of nurses in using the checklist.Design: A prospective cohort design using repeated measures.Setting: The booking-in prenatal clinic at a regional hospital in Victoria, Australia, and the community-based postpartum maternal and child health service.Participants: 107 pregnant women over 20 years of age.Main Measures: Postpartum Depression Prediction Inventory (PDPI), Postpartum Depression Screening Scale (PDSS), Edinburgh Postnatal Depression Scale (EPDS), demographic questionnaire, and data on the outcome from the midwives and nurses.Results: The PDPI identified 45% of the women at risk of depression during pregnancy and 30% postpartum. The PDSS and EPDS both identified the same 8 women (10%), who scored highly for depression at the 8-week postpartum health visit. Nurses provided 80% of the women with anticipatory guidance on postpartum depression in the prenatal period and 46% of women at the 8-week postpartum health visit. Nurse counseling or anticipatory guidance was provided for 60% of the women in the prenatal period.Conclusion: The PDPI was found to be a valuable checklist by many nurses involved in this research, particularly as a way of initiating open discussion with women about postpartum depression. It correlated strongly with both the PDSS and the EPDS, suggesting that it is useful as an inventory to identify women at risk of postpartum depression.<br /

Socioeconomic correlates of quality of life for non-Māori in advanced age: Te Puāwaitanga o Nga Tapuwae Kia ora Tonu. Life and Living in Advanced Age: a cohort study in New Zealand (LiLACS NZ)

AIM: To establish socioeconomic and cultural profiles and correlates of quality of life (QoL) in non-Māori of advanced age. METHOD: A cross sectional analysis of the baseline data of a cohort study of 516 non-Māori aged 85 years living in the Bay of Plenty and Rotorua areas of New Zealand. Socioeconomic and cultural characteristics were established by face-to-face interviews in 2010. Health-related QoL (HRQoL) was assessed with the SF-12. RESULTS: Of the 516 non-Māori participants enrolled in the study, 89% identified as New Zealand European, 10% other European, 1% were of Pacific, Asian or Middle Eastern ethnicity; 20% were born overseas and half of these identified as 'New Zealand European.' More men were married (59%) and more women lived alone (63%). While 89% owned their own home, 30% received only the New Zealand Superannuation as income and 22% reported that they had 'just enough to get along on'. More than 85% reported that they had sufficient practical and emotional support; 11% and 6% reported unmet need for practical and emotional support respectively. Multivariate analyses showed that those with unmet needs for practical and emotional support had lower mental HR QoL (p<0.005). Reporting that family were important to wellbeing was associated with higher mental HR QoL (p=0.038). Those that did not need practical help (p=0.047) and those that reported feeling comfortable with their money situation (0.0191) had higher physical HRQoL. High functional status was strongly associated with both high mental and high physical HR QoL (p<0.001). CONCLUSION: Among our sample of non-Māori people of advanced age, those with unmet support needs reported low HRQoL. Functional status was most strongly associated with mental and physical HRQoL

Combining viral genomics and clinical data to assess risk factors for severe COVID-19 (mortality, ICU admission, or intubation) amongst hospital patients in a large acute UK NHS hospital Trust

Throughout the COVID-19 pandemic, valuable datasets have been collected on the effects of the virus SARS-CoV-2. In this study, we combined whole genome sequencing data with clinical data (including clinical outcomes, demographics, comorbidity, treatment information) for 929 patient cases seen at a large UK hospital Trust between March 2020 and May 2021. We identified associations between acute physiological status and three measures of disease severity; admission to the intensive care unit (ICU), requirement for intubation, and mortality. Whilst the maximum National Early Warning Score (NEWS2) was moderately associated with severe COVID-19 (A = 0.48), the admission NEWS2 was only weakly associated (A = 0.17), suggesting it is ineffective as an early predictor of severity. Patient outcome was weakly associated with myriad factors linked to acute physiological status and human genetics, including age, sex and pre-existing conditions. Overall, we found no significant links between viral genomics and severe outcomes, but saw evidence that variant subtype may impact relative risk for certain sub-populations. Specific mutations of SARS-CoV-2 appear to have little impact on overall severity risk in these data, suggesting that emerging SARS-CoV-2 variants do not result in more severe patient outcomes. However, our results show that determining a causal relationship between mutations and severe COVID-19 in the viral genome is challenging. Whilst improved understanding of the evolution of SARS-CoV-2 has been achieved through genomics, few studies on how these evolutionary changes impact on clinical outcomes have been seen due to complexities associated with data linkage. By combining viral genomics with patient records in a large acute UK hospital, this study represents a significant resource for understanding risk factors associated with COVID-19 severity. However, further understanding will likely arise from studies of the role of host genetics on disease progression

Combining viral genomics and clinical data to assess risk factors for severe COVID-19 (mortality, ICU admission, or intubation) amongst hospital patients in a large acute UK NHS hospital Trust.

Throughout the COVID-19 pandemic, valuable datasets have been collected on the effects of the virus SARS-CoV-2. In this study, we combined whole genome sequencing data with clinical data (including clinical outcomes, demographics, comorbidity, treatment information) for 929 patient cases seen at a large UK hospital Trust between March 2020 and May 2021. We identified associations between acute physiological status and three measures of disease severity; admission to the intensive care unit (ICU), requirement for intubation, and mortality. Whilst the maximum National Early Warning Score (NEWS2) was moderately associated with severe COVID-19 (A = 0.48), the admission NEWS2 was only weakly associated (A = 0.17), suggesting it is ineffective as an early predictor of severity. Patient outcome was weakly associated with myriad factors linked to acute physiological status and human genetics, including age, sex and pre-existing conditions. Overall, we found no significant links between viral genomics and severe outcomes, but saw evidence that variant subtype may impact relative risk for certain sub-populations. Specific mutations of SARS-CoV-2 appear to have little impact on overall severity risk in these data, suggesting that emerging SARS-CoV-2 variants do not result in more severe patient outcomes. However, our results show that determining a causal relationship between mutations and severe COVID-19 in the viral genome is challenging. Whilst improved understanding of the evolution of SARS-CoV-2 has been achieved through genomics, few studies on how these evolutionary changes impact on clinical outcomes have been seen due to complexities associated with data linkage. By combining viral genomics with patient records in a large acute UK hospital, this study represents a significant resource for understanding risk factors associated with COVID-19 severity. However, further understanding will likely arise from studies of the role of host genetics on disease progression