Report 5: Phylogenetic analysis of SARS-CoV-2

Volz, Erik; Baguelin, Marc; Bhatia, S; Boonyasiri, Adhiratha; Cori, Anne; Perez, Z Cucunuba; Cuomo-Dannenburg, Gina; Donnelly, C; Dorigatti, Ilaria; FitzJohn, Richard G.; Fú, Ho Shin; Gaythorpe, Katy A. M.; Ghani, Ahmad Bashawir Abdul; Hamlet, Arran; Hinsley, Wes; Imai, Natsuko; Laydon, Daniel J.; Gilani, G Nedjati; Okell, Lucy; Riley, Sheryl A.; Elsland, S Van; Wang, H; Wang, Y; Xi, Xin; Ferguson, Nadia

doi:10.25561/77169

Cited by 6 publications

(1 citation statement)

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“…The deterministic CP-EPI has provided a computationally efficient framework for studying the evolution and pathogenesis of SARS-CoV-2 via estimating R 0 (t) at the beginning of the pandemic (Volz et al, 2020, fine-scale spatiotemporal community-level transmission rate variation (Moreno et al, 2020), and the effects of control measures on epidemic spread (Miller et al, 2020.…”

Section: Phylodynamic Inference Relying Solely Onmentioning

confidence: 99%

Statistical Challenges in Tracking the Evolution of SARS-CoV-2

et al. 2022

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Genomic surveillance of SARS-CoV-2 has been instrumental in tracking the spread and evolution of the virus during the pandemic. The availability of SARS-CoV-2 molecular sequences isolated from infected individuals, coupled with phylodynamic methods, have provided insights into the origin of the virus, its evolutionary rate, the timing of introductions, the patterns of transmission, and the rise of novel variants that have spread through populations. Despite enormous global efforts of governments, laboratories, and researchers to collect and sequence molecular data, many challenges remain in analyzing and interpreting the data collected. Here, we describe the models and methods currently used to monitor the spread of SARS-CoV-2, discuss long-standing and new statistical challenges, and propose a method for tracking the rise of novel variants during the epidemic.

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Section: Phylodynamic Inference Relying Solely Onmentioning

confidence: 99%

Statistical Challenges in Tracking the Evolution of SARS-CoV-2

et al. 2022

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The Natural History, Pathobiology, and Clinical Manifestations of SARS-CoV-2 Infections

Machhi

Herskovitz

Senan

et al. 2020

J Neuroimmune Pharmacol

497

459

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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the etiological agent of coronavirus disease 2019 (COVID-19). SARS-CoV-2, is a positive-sense single-stranded RNA virus with epithelial cell and respiratory system proclivity. Like its predecessor, SARS-CoV, COVID-19 can lead to life-threatening disease. Due to wide geographic impact affecting an extremely high proportion of the world population it was defined by the World Health Organization as a global public health pandemic. The infection is known to readily spread from person-to-person. This occurs through liquid droplets by cough, sneeze, hand-to-mouth-to-eye contact and through contaminated hard surfaces. Close human proximity accelerates SARS-CoV-2 spread. COVID-19 is a systemic disease that can move beyond the lungs by bloodbased dissemination to affect multiple organs. These organs include the kidney, liver, muscles, nervous system, and spleen. The primary cause of SARS-CoV-2 mortality is acute respiratory distress syndrome initiated by epithelial infection and alveolar macrophage activation in the lungs. The early cell-based portal for viral entry is through the angiotensin-converting enzyme 2 receptor. Viral origins are zoonotic with genomic linkages to the bat coronaviruses but without an identifiable intermediate animal reservoir. There are currently few therapeutic options, and while many are being tested, although none are effective in curtailing the death rates. There is no available vaccine yet. Intense global efforts have targeted research into a better understanding of the epidemiology, molecular biology, pharmacology, and pathobiology of SARS-CoV-2. These fields of study will provide the insights directed to curtailing this disease outbreak with intense international impact. Keywords Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Coronavirus disease 2019 (COVID-19). Acute respiratory distress syndrome (ARDS). Angiotensin-converting enzyme 2 (ACE-2)

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Treating intrusive memories after trauma in healthcare workers: a Bayesian adaptive randomised trial developing an imagery-competing task intervention

Ramineni

Millroth

Iyadurai³

et al. 2023

Mol Psychiatry

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Intensive care unit (ICU) staff continue to face recurrent work-related traumatic events throughout the COVID-19 pandemic. Intrusive memories (IMs) of such traumatic events comprise sensory image-based memories. Harnessing research on preventing IMs with a novel behavioural intervention on the day of trauma, here we take critical next steps in developing this approach as a treatment for ICU staff who are already experiencing IMs days, weeks, or months post-trauma. To address the urgent need to develop novel mental health interventions, we used Bayesian statistical approaches to optimise a brief imagery-competing task intervention to reduce the number of IMs. We evaluated a digitised version of the intervention for remote, scalable delivery. We conducted a two-arm, parallel-group, randomised, adaptive Bayesian optimisation trial. Eligible participants worked clinically in a UK NHS ICU during the pandemic, experienced at least one work-related traumatic event, and at least three IMs in the week prior to recruitment. Participants were randomised to receive immediate or delayed (after 4 weeks) access to the intervention. Primary outcome was the number of IMs of trauma during week 4, controlling for baseline week. Analyses were conducted on an intention-to-treat basis as a between-group comparison. Prior to final analysis, sequential Bayesian analyses were conducted (n = 20, 23, 29, 37, 41, 45) to inform early stopping of the trial prior to the planned maximum recruitment (n = 150). Final analysis (n = 75) showed strong evidence for a positive treatment effect (Bayes factor, BF = 1.25 × 106): the immediate arm reported fewer IMs (median = 1, IQR = 0–3) than the delayed arm (median = 10, IQR = 6–16.5). With further digital enhancements, the intervention (n = 28) also showed a positive treatment effect (BF = 7.31). Sequential Bayesian analyses provided evidence for reducing IMs of work-related trauma for healthcare workers. This methodology also allowed us to rule out negative effects early, reduced the planned maximum sample size, and allowed evaluation of enhancements. Trial Registration NCT04992390 (www.clinicaltrials.gov).

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Report 5: Phylogenetic analysis of SARS-CoV-2

Cited by 6 publications

References 0 publications

Statistical Challenges in Tracking the Evolution of SARS-CoV-2

Statistical Challenges in Tracking the Evolution of SARS-CoV-2

The Natural History, Pathobiology, and Clinical Manifestations of SARS-CoV-2 Infections

Treating intrusive memories after trauma in healthcare workers: a Bayesian adaptive randomised trial developing an imagery-competing task intervention

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