July 14 2020  (JMIR Medical Informatics)

The Role of Health Technology and Informatics in a Global Public Health Emergency: Practices and Implications From the COVID-19 Pandemic

Jiancheng Ye

https://medinform.jmir.org/2020/7/e19866/

In this viewpoint, the author argues that efforts are needed to treat critical patients, track and manage the health status of residents, and isolate suspected patients. The application of emerging health technologies and digital practices in health care, such as artificial intelligence, telemedicine or telehealth, mobile health, big data, 5G, and the Internet of Things, have become powerful tools to fight against the pandemic and provide strong support in pandemic prevention and control. He then highlights the applications of all these technologies, practices and health delivery services.

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July 13, 2020 (Physical and Engineering Sciences in Medicine)

Technique, radiation safety and image quality for chest X-ray imaging through glass and in mobile settings during the COVID-19 pandemic

Zoe Brady, Heather Scoullar, Ben Grinsted et al.

https://doi.org/10.1007/s13246-020-00899-8

The authors developed a technique to perform mobile chest X-ray imaging through a glass, allowing the X-ray unit to remain outside of the patient’s room, effectively reducing the cleaning time associated with disinfecting equipment. The technique also reduced the infection risk of radiographers. Radiation measurements were performed to determine the appropriate position for staff inside and outside the room to ensure occupational doses were kept as low as reasonably achievable. Image quality was acceptable and technical parameter information collated. This method has been implemented successfully.

 

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July 10, 2020 (The Lancet Digital Health)

Machine learning for COVID-19—asking the right questions

Patrik Bachtiger, Nicholas S Peters, Simon LF Walsh

​Enthusiasm around around machine learning-based technology in medical imaging has been present even prior to the COVID-19 pandemic. During this pandemic, chest x-ray and CT have quickly produced a large amount of data on COVID-19, enabling the development of machine learning algorithms, a form of artificial intelligence (AI). However, the question remains as to how many of these applications will prove to be clinically useful. In this article, the authors discuss questions s that need to be answered whilst developing machine learning algorithms.

 

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July 10 2020  (Journal of Fluid Mechanics) 

The flow physics of COVID-19

Rajat Mittal, Rui Ni and Jung-Hee Seo 

https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/flow-physics-of-covid19/476E32549012B3620D2452F30F2567F1

Flow physics plays a key role in nearly every facet of the COVID-19 pandemic. This includes the generation and aerosolization of virus-laden respiratory droplets from a host, its airborne dispersion and deposition on surfaces, as well as the subsequent inhalation of these bioaerosols by unsuspecting recipients. Fluid dynamics is also key to preventative measures such as the use of face masks, hand washing, ventilation of indoor environments and even social distancing. This article summarizes what we need to learn about the science underlying these issues so that we are better prepared to tackle the next outbreak of COVID-19.

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July 10, 2020  (The Lancet Haematology)

Haematological characteristics and risk factors in the classification and prognosis evaluation of COVID-19: a retrospective cohort study

Danying Liao, Fen Zhou, Lili Luo et al.

https://doi.org/10.1016/S2352-3026(20)30217-9

Changes in haematological characteristics in patients with COVID-19 are emerging as important features of the disease. In this retrospective study, the authors explored the haematological characteristics and related risk factors in patients with COVID-19. They found that rapid blood tests, including platelet count, prothrombin time, D-dimer, and neutrophil to lymphocyte ratio can help clinicians to assess severity and prognosis of patients with COVID-19. The sepsis-induced coagulopathy scoring system can be used for early assessment and management of patients with critical disease.

 

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July 10, 2020  (JAMA)

Pathophysiology, Transmission, Diagnosis, and Treatment of Coronavirus Disease 2019 (COVID-19): A Review

W, Joost Wiersinga, Andrew Rhodes, Allen C. Cheng et al.

https://doi.org/10.1001/jama.2020.12839

This comprehensive and up-to-date review discusses current evidence regarding the pathophysiology, transmission, diagnosis, and management of COVID-19.

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July 8, 2020  (JAMA Netw. Open)

Association of a Public Health Campaign About Coronavirus Disease 2019 Promoted by News Media and a Social Influencer With Self-reported Personal Hygiene and Physical Distancing in the Netherlands

Hamza Yousuf, Jonathan Corbin, Govert Sweep et al.

https://doi.org/10.1001/jamanetworkopen.2020.14323

This survey study examines a nationwide social media campaign about personal hygiene and physical distancing in the Netherlands and evaluates its effectiveness in improving behaviour and curbing the spread of the coronavirus disease 2019 (COVID-19) pandemic.

 

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July 6, 2020 (Clin Inf Dis)

It is Time to Address Airborne Transmission of COVID-19 

Lidia Morawska, Donald K Milton

https://doi.org/10.1093/cid/ciaa939

The authors review existing evidence of transmission of COVID-19 and are of the viewpoint that it is important to recognize the potential for airborne spread of COVID-19.

 

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July 6, 2020  (JAMA)

Developing a SARS-CoV-2 Vaccine at Warp Speed

Kevin P. O’Callaghan, Allison M. Blatz, Paul A. Offit

https://doi.org/10.1001/jama.2020.12190

In this Viewpoint, we describe the proposed mechanisms and current status of each of these leading candidates, all of which are aimed at inducing antibodies directed against the receptor-binding domain of the surface spike (S) protein of SARS-CoV-2.

 

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July 3, 2020  (Cell)

Making sense of mutation: what D614G means for the COVID-19 pandemic remains unclear

Nathan D. Grubaugh, William P. Hanage, Angela L. Rasmussen

https://doi.org/10.1016/j.cell.2020.06.040

Korber et al. (2020) found that a SARS-CoV-2 variant in the spike protein, D614G, rapidly became dominant around the world. While clinical and in vitro data suggest that D614G changes the virus phenotype, the impact of the mutation on transmission, disease, vaccine and therapeutic development are largely unknown. Here the authors try to answer questions on the potential impacts, if any, that D614G has on the COVID-19 pandemic.

 

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July 3, 2020  (Science)

SARS-CoV-2 productively infects human gut enterocytes

Mart M. Lamers, Joep Beumer, Jelte van der Vaart et al.

https://doi.org/10.1126/science.abc1669

SARS-CoV-2 causes an influenza-like disease with a respiratory transmission route;, however, patients often present with gastrointestinal symptoms such as diarrhoea. Lamers et al. used human intestinal organoids, a “mini-gut” cultured in a dish, to demonstrate that SARS-CoV-2 readily replicates in an abundant cell type in the gut lining—the enterocyte—resulting in the production of large amounts of infective virus particles in the intestine. This work demonstrates that intestinal organoids can serve as a model to understand SARS-CoV-2 biology and infectivity in the gut.

 

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July 3, 2020  (The Lancet Haematology)

Effects of the COVID-19 pandemic on supply and use of blood for transfusion

Simon J Stanworth, Helen V New, Torunn O Apelseth et al.

https://doi.org/10.1016/S2352-3026(20)30186-1

The COVID-19 pandemic has major implications for blood transfusion. The authors systematically searched for relevant studies addressing the transfusion chain—from donor, through collection and processing, to patients—to provide a synthesis of the published literature and guidance during times of potential or actual shortage.

 

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July 2, 2020 (The Lancet Child & Adolescent Health)

Emergence of Kawasaki disease related to SARS-CoV-2 infection in an epicentre of the French COVID-19 epidemic: a time-series analysis

Naim Ouldali, Marie Pouletty, Patricia Mariani et al.

https://doi.org/10.1016/S2352-4642(20)30175-9

Kawasaki disease is an acute febrile systemic childhood vasculitis, which is suspected to be triggered by respiratory viral infections. The authors examined whether the ongoing COVID-19 epidemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is associated with an increase in the incidence of Kawasaki disease.

 

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July 2, 2020  (JAMA Neurology)

Risk of Ischemic Stroke in Patients With Coronavirus Disease 2019 (COVID-19) vs Patients With Influenza

Alexander E. Merkler, Neal S. Parikh, Saad Mir et al.

https://doi.org/10.1001/jamaneurol.2020.2730

This cohort study compares the rate of ischemic stroke among patients with COVID-19 vs patients with influenza in 2 hospitals in New York City, New York. They found that patients with COVID-19 appear to have a heightened risk of acute ischemic stroke compared with patients with influenza.

 

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July 2, 2020  (Science)

Primary exposure to SARS-CoV-2 protects against reinfection in rhesus macaques

Wei Deng, Linlin Bao, Jiangning Liu et al.

https://doi.org/10.1126/science.abc5343

As the COVID-19 pandemic evolves, there are still many questions we need to answer. Currently, it remains unclear whether convalescing patients have a risk of reinfection. The authors generated a rhesus macaque model of SARS-CoV-2 infection that was characterized by interstitial pneumonia and systemic viral dissemination mainly in the respiratory and gastrointestinal tracts. Rhesus macaques reinfected with the identical SARS-CoV-2 strain during the early recovery phase of the initial SARS-CoV-2 infection did not show detectable viral dissemination, clinical manifestations of viral disease, or histopathological changes. Comparing the humoral and cellular immunity between primary infection and rechallenge revealed notably enhanced neutralizing antibody and immune responses. These results suggest that primary SARS-CoV-2 exposure protects against subsequent reinfection in rhesus macaques.

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July 2 2020  (PNAS)

The challenges of modeling and forecasting the spread of COVID-19

 Andrea L. Bertozzi, Elisa Franco, George Mohler,et al

https://www.pnas.org/content/early/2020/07/07/2006520117

Modeling and forecasting the spread of COVID-19 remain a challenge. In this paper the authors  present three models for forecasting and assessing the course of the pandemic. They aim to demonstrate the utility of these models for understanding the pandemic and to provide a framework for generating policy-relevant insights into its course. These models highlight the dangers of relaxing nonpharmaceutical public health interventions in the absence of a vaccine or therapeutic agent.

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July 2020   (Chaos, Solitons & Fractals)

Forecast and evaluation of COVID-19 spreading in USA with reduced-space Gaussian process regression

Ricardo Manuel, Arias Velásquez, Jennifer Vanessa et al

https://www.sciencedirect.com/science/article/pii/S0960077920303234

The authors analyze historical and forecast infections for COVID-19 death based on Reduced-Space Gaussian Process Regression associated  with chaotic Dynamical Systems with information obtained in 82 days with daily learning from January 21th, 2020 to April 12th.  The forecast places the peak in USA around July 14th 2020, with a peak number of 132,074 death with infected individuals of about 1,157,796 and a number of deaths at the end of the epidemics of about 132,800. Their findings suggest, new quarantine actions with more restrictions for containment strategies implemented in USA could be successfully.

 

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July 2020   (Chaos, Solitons & Fractals)

Optimal policies for control of the novel coronavirus disease (COVID-19) outbreak

AminYousefpour, Hadi Jahanshahi, Stelios Bekiros

https://www.sciencedirect.com/science/article/pii/S0960077920302836

The authors claim to be the first research that proposes policies for COVID-19 by considering its economic consequences. They used a mathematical model of the novel coronavirus to research on policy. A multi-objective genetic algorithm which suggests strategies to achieve high-quality schedules by adjusting various factors was attempted.

 

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July 1, 2020  (JAMA Psychiatry)

Telehealth for Substance-Using Populations in the Age of Coronavirus Disease 2019: Recommendations to Enhance Adoption

Lewei (Allison) Lin, Anne C. Fernandez, Erin E. Bonar

https://doi.org/10.1001/jamapsychiatry.2020.1698

This Viewpoint discusses the need for and implementation of telemedicine for patients with substance use disorder in the era of coronavirus disease 2019.

 

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July 1, 2020  (JAMA Network Open)

Prevalence of and Risk Factors Associated With Mental Health Symptoms Among the General Population in China During the Coronavirus Disease 2019 Pandemic

Le Shi, Zheng-An Lu, Jian-Yu Que, et al.

https://doi.org/10.1001/jamanetworkopen.2020.14053

This survey involving more than 50,000 participants estimated the prevalence of depression and anxiety, and also looked at the risk factors associated with mental health symptoms. The mental health burden associated with COVID-19 is considerable among the general population of China, suggesting that mental health interventions are in urgent demand during the COVID-19 pandemic, especially for some at-risk populations.

 

 

July 1, 2020  (Heliyon)

A one-step, one-tube real-time RT-PCR based assay with an automated analysis for detection of SARS-CoV2

Bhasker Dharavath, Neelima Yadav, Sanket Desai et al.

https://doi.org/10.1016/j.heliyon.2020.e4405

The authors present a rapid, easy to implement real-time PCR based assay with automated analysis using a novel COVID qPCR Analyzer tool with graphical user interface (GUI) to analyze the raw qRT-PCR data in an unbiased manner at a cost of under $3 per reaction and turnaround time of less than 2h, to enable in-house SARS-CoV-2 testing across laboratories.

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July 2020  (Infectious Disease Modelling)

Generalized logistic growth modeling of the COVID-19 pandemic in Asia

Elinor Aviv-Sharon, Asaph Aharoni

https://www.sciencedirect.com/science/article/pii/S2468042720300270

The authors report a modeling approach using the generalized logistic model (GLM) to predict the outbreak spreading potential and the pandemic cessation dates in Chinese mainland, Iran, the Philippines and Chinese Taiwan. The short-term predicted number of cumulative COVID-19 cases matched the confirmed reports of across the four countries and regions.  They suggest that GLM as a valuable tool for characterizing the transmission dynamics process and the trajectory of COVID-19 pandemic.

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