Mount St. Helens at 40

This INSIGHTS Perspectives piece by scientist Jon J. Major highlights the societal and geologic impacts of the Mount St. Helens eruption on this day in 1980.

PERSPECTIVE VOLCANOLOGY

Mount St. Helens at 40, Jon J. Major

Science  15 May 2020:
Volume 368, Issue 6492, pp. 704-705.
doi: 10.1126/science.abb4120

Screening of healthcare workers for SARS-CoV-2 highlights the role of asymptomatic carriage in COVID-19 transmission

Dr. Michael Weekes and his colleagues at the Department of Infectious Diseases within the Cambridge University Hospitals NHS Trust identified SARS-CoV-2 positive health care workers (HCWs) in the wards in April of 2020. The overall percentage of asymptomatic positive HCWs was 5%. In one ward, identified as Ward Q, more than 25% of HCWs tested positive for SARS-CoV-2 by Real-Time RT-PCR. This study underscores the importance of regular viral surveillance screening for hospital staff and providing adequate training to prevent nosocomial spread of infectious disease pathogens including the novel coronavirus strain.

A link to the full text article e-published May 11, 2020 can be accessed here.

The authors conclude:

Our data demonstrates the utility of comprehensive screening of HCWs with minimal or no symptoms. This approach will be critical for protecting patients and hospital staff.

Aldebrook Cambridge Hospitals.jpg

AUTHORS: Lucy Rivett, MBBS 1,2*, Sushmita Sridhar, BS 3,4,5*, Dominic Sparkes, MBBS 1,2*, Matthew Routledge, MBBS 1,2 3 *, Nick K. Jones, MBBS 1,2,4,5*, Sally Forrest, BSc 4,5, Jamie Young, BSc 6 , Joana Pereira-Dias, MSc 4,5 L. Hamilton, PhD 1,2, Mark Ferris, MSc 7, M. Estee Torok, PhD 5,8, Luke Meredith, PhD 5, The CITIID-NIHR COVID-19 BioResource Collaboration, Martin Curran, PhD 2, Stewart Fuller, MSc 10, Afzal Chaudhry, PhD 11, Ashley Shaw, MBChB 11, Prof. Richard J. Samworth, PhD 12, Prof. John R. Bradley, DM 4,13, Prof. Gordon Dougan, FRS 4,5 7, Prof. Kenneth G.C. Smith, FMedSci 4,5, Prof. Paul J. Lehner, FMedSci 1,4,5, Nicholas J. Matheson, PhD 1,4,5,8 , Giles Wright, BA 7 , Prof. Ian Goodfellow, PhD 9¶ , Prof. Stephen Baker, PhD 4,5¶, Michael P. Weekes, PhD 1,4,5¶

AFFILIATIONS:
1 Department of Infectious Diseases, Cambridge University Hospitals NHS Trust, Cambridge, United Kingdom.

2 Cambridge Institute for Therapeutic Immunology and Infectious Disease, University of Cambridge, Cambridge, United Kingdom.

3 Academic Department of Medical Genetics, University of Cambridge, Cambridge, United Kingdom.

4 Department of Occupational Health and Wellbeing, Cambridge University Hospitals NHS Trust, Cambridge, United Kingdom.

5 Department of Medicine, University of Cambridge, Cambridge, United Kingdom.

6 Division of Virology, Department of Pathology, University of Cambridge, Cambridge, United Kingdom.

7 Clinical Microbiology & Public Health Laboratory, Public Health England (PHE), Cambridge, United Kingdom.

8 Clinical Research Facility, National Institutes for Health Research, Cambridge, United Kingdom.

9 Chief Medical Information Officer, Cambridge University Hospitals NHS Trust, Cambridge, United Kingdom.

10 Medical Director, Cambridge University Hospitals NHS Trust, Cambridge, United Kingdom.

11 Statistical Laboratory, Centre for Mathematical Sciences, University of Cambridge, Cambridge, United Kingdom.

12 Cambridge Institute for Medical Research, University of Cambridge, Cambridge, United Kingdom.

13 Department of Pathology, University of Cambridge, Cambridge, United Kingdom.

ABSTRACT: Significant differences exist in the availability of healthcare worker (HCW) SARS-CoV-2 testing between countries, and existing programmes focus on screening symptomatic rather than asymptomatic staff. Over a 3-week period (April 2020), 1,032 asymptomatic HCWs were screened for SARS-CoV-2 in a large UK teaching hospital. Symptomatic staff and symptomatic household contacts were additionally tested. Real-time RT-PCR was used to detect viral RNA from a throat+nose self-swab. 3% of HCWs in the asymptomatic screening group tested positive for SARS-CoV-2. 17/30 (57%) were truly asymptomatic/pauci-symptomatic. 12/30 (40%) had experienced symptoms compatible with coronavirus disease 2019 (COVID-19) >7 days prior to testing, most self-isolating, returning well. Clusters of HCW infection were discovered on two independent wards. Viral genome sequencing showed that the majority of HCWs had the dominant lineage B∙1. Our data demonstrates the utility of comprehensive screening of HCWs with minimal or no symptoms. This approach will be critical for protecting patients and hospital staff.

PMID: 32392129
doi: 10.7554/eLife.58728
© 2020, Rivett et al.

High Contagiousness and Rapid Spread of Severe Acute Respiratory Syndrome Coronavirus 2

Emerging Infectious Diseases Volume 26, Number 7—July 2020

Disclaimer: Early release articles are not considered as final versions. Any changes will be reflected in the online version in the month the article is officially released. Accessed online: May 10, 2020

This article shows the data from Wuhan and 26 provinces. Described in Figure 3C, from January 18th to 26th, the growth of new cases in areas outside of Hubei, grew rapidly (over only 8 days) and exponentially. These data further support the public health imperative of limiting social interactions in areas of high SARS-CoV-2 transmission and discouraging travel from these areas to areas of no or low transmission.

The authors also underscore that while they have calculated an R0 , they have made a series of assumptions that may or may not prove correct. They summarize:

“The values estimated have important implications for predicting the effects of pharmaceutical and nonpharmaceutical interventions. For example, the threshold for combined vaccine efficacy and herd immunity needed for disease extinction is calculated as 1 – 1/R0 . At R0  = 2.2, this threshold is only 55%. But at R0  = 5.7, this threshold rises to 82% (i.e., >82% of the population has to be immune, through either vaccination or prior infection, to achieve herd immunity to stop transmission).”

“We further show that active surveillance, contact tracing, quarantine, and early strong social distancing efforts are needed to stop transmission of the virus.”

Figure 3. Estimates of the exponential growth rate and the date of exponential growth initiation of the 2019 novel coronavirus disease outbreak in China based on 2 different approaches. A) Schematic illustrating the export of infected persons from Wuhan. Travelers (dots) are assumed to be random samples from the total population (whole pie). Because of the growth of the infected population (orange pie) and the shrinking size of the total population in Wuhan over time, probability of infected persons traveling to other provinces increases (orange dots). B) The dates of documented first arrivals of infected persons in 26 provinces. C) Best fit of the case count model to daily counts of new cases (including only imported cases) in provinces other than Hubei. Error bars indicate SDs.

20-0282-F3 Figure 3.jpg

AUTHORS: Steven Sanche1, Yen Ting Lin1, Chonggang Xu, Ethan Romero-Severson, Nick Hengartner, and
Ruian Ke 

Author affiliations: Los Alamos National Laboratory, Los Alamos, New Mexico, USA
1 These authors contributed equally to this work

ABSTRACT: Severe acute respiratory syndrome coronavirus 2 is the causative agent of the 2019 novel coronavirus disease pandemic. Initial estimates of the early dynamics of the outbreak in Wuhan, China, suggested a doubling time of the number of infected persons of 6–7 days and a basic reproductive number (R0) of 2.2–2.7. We collected extensive individual case reports across China and estimated key epidemiologic parameters, including the incubation period. We then designed 2 mathematical modeling approaches to infer the outbreak dynamics in Wuhan by using high-resolution domestic travel and infection data. Results show that the doubling time early in the epidemic in Wuhan was 2.3–3.3 days. Assuming a serial interval of 6–9 days, we calculated a median R0 value of 5.7 (95% CI 3.8–8.9). We further show that active surveillance, contact tracing, quarantine, and early strong social distancing efforts are needed to stop transmission of the virus.

Rapid implementation of mobile technology for real-time epidemiology of COVID-19

Rapid implementation of mobile technology for real-time epidemiology of COVID-19

A friend and colleague Dr. Long H. Nguyen of the Harvard Medical School and the Clinical & Translational Epidemiology Unit at Massachusetts General Hospital has written about the new COronavirus Pandemic Epidemiology (COPE) consortium. As of May 2, 2020 2.8 million users have used the mobile application for symptom tracking. Also, as a side note, Dr. Long Nguyen knows the best vegan restaurants around any town he visits.

F2.large UK Maps.jpg

ABSTRACT: The rapid pace of the Severe Acute Respiratory Syndrome COronaVirus 2 (SARS-CoV-2) pandemic presents challenges to the robust collection of population-scale data to address this global health crisis. We established the COronavirus Pandemic Epidemiology (COPE) consortium to bring together scientists with expertise in big data research and epidemiology to develop a COVID-19 Symptom Tracker mobile application that we launched in the UK on March 24, 2020 and the US on March 29, 2020 garnering more than 2.8 million users as of May 2, 2020. This mobile application offers data on risk factors, herald symptoms, clinical outcomes, and geographical hot spots. This initiative offers critical proof-of-concept for the repurposing of existing approaches to enable rapidly scalable epidemiologic data collection and analysis which is critical for a data-driven response to this public health challenge.

David A. Drew1,*Long H. Nguyen1,*, Claire J. Steves2,3, Cristina Menni2, Maxim Freydin2, Thomas Varsavsky4, Carole H. Sudre4, M. Jorge Cardoso4, Sebastien Ourselin4, Jonathan Wolf5, Tim D. Spector2,5,, Andrew T. Chan1,6,,, COPE Consortium§

Corresponding author. Email: achan@mgh.harvard.edu

  1. Clinical & Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, 55 Fruit St., Boston, MA 02114, USA.

  2. Department of Twin Research and Genetic Epidemiology, King’s College London, Westminster Bridge Road, London SE17EH, UK.

  3. Department of Ageing and Health, Guys and St. Thomas’s NHS Foundation Trust, Lambeth Palace Road, London SE17EHIL, UK.

  4. School of Biomedical Engineering & Imaging Sciences, King’s College London, 1 Lambeth Palace Road, London SE1 7EU, UK.

  5. Zoe Global Limited, 164 Westminster Bridge Road, London SE17RW, UK.

  6. Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, 665 Huntington Avenue, Boston, MA 02114, USA.

  1. * These authors contributed equally to this work.

  2. † These authors contributed equally to this work.

  • § COPE Consortium members and affiliations are listed in the supplementary materials.

Science  05 May 2020: eabc0473
DOI: 10.1126/science.abc0473