scholarly journals Lockdown as a last resort option in case of COVID-19 epidemic rebound: a modelling study

2021 ◽  
Vol 26 (22) ◽  
Author(s):  
Cécile Tran Kiem ◽  
Pascal Crépey ◽  
Paolo Bosetti ◽  
Daniel Levy Bruhl ◽  
Yazdan Yazdanpanah ◽  
...  
Keyword(s):  
Time Management ◽  
Large Scale ◽  
Doubling Time ◽  
Compartmental Model ◽  
Societal Cost ◽  
Control Measures ◽  
Alternative Control ◽  
Healthcare Settings ◽  
Modelling Framework ◽  
Mixing Patterns

Background Given its high economic and societal cost, policymakers might be reluctant to implement a large-scale lockdown in case of coronavirus disease (COVID-19) epidemic rebound. They may consider it as a last resort option if alternative control measures fail to reduce transmission. Aim We developed a modelling framework to ascertain the use of lockdown to ensure intensive care unit (ICU) capacity does not exceed a peak target defined by policymakers. Methods We used a deterministic compartmental model describing transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the trajectories of COVID-19 patients in healthcare settings, accounting for age-specific mixing patterns and an increasing probability of severe outcomes with age. The framework is illustrated in the context of metropolitan France. Results The daily incidence of ICU admissions and the number of occupied ICU beds are the most robust indicators to decide when a lockdown should be triggered. When the doubling time of hospitalisations estimated before lockdown is between 8 and 20 days, lockdown should be enforced when ICU admissions reach 3.0–3.7 and 7.8–9.5 per million for peak targets of 62 and 154 ICU beds per million (4,000 and 10,000 beds for metropolitan France), respectively. When implemented earlier, the lockdown duration required to get back below a desired level is also shorter. Conclusions We provide simple indicators and triggers to decide if and when a last-resort lockdown should be implemented to avoid saturation of ICU. These metrics can support the planning and real-time management of successive COVID-19 pandemic waves.

Assessment of quality of life in patients with the effects of transient ischemic stroke

2016 ◽  
pp. 37-39
Author(s):  
A. Babirad
Keyword(s):  
Quality Of Life ◽  
Ischemic Stroke ◽  
Large Scale ◽  
Cerebrovascular Diseases ◽  
Control Measures ◽  
Sociological Research ◽  
Cerebrovascular Events ◽  
Sf 36 ◽  
Angioplasty And Stenting

Cerebrovascular diseases are a problem of the world today, and according to the forecast, the problem of the near future arises. The main risk factors for the development of ischemic disorders of the cerebral circulation include oblique and aging, arterial hypertension, smoking, diabetes mellitus and heart disease. An effective strategy for the prevention of cerebrovascular events is based on the implementation of large-scale risk control measures, including the use of antiagregant and anticoagulant therapy, invasive interventions such as atheromectomy, angioplasty and stenting. In this connection, the efforts of neurologists, cardiologists, angiosurgery, endocrinologists and other specialists are the basis for achieving an acceptable clinical outcome. A review of the SF-36 method for assessing the quality of life in patients with the effects of transient ischemic stroke is presented. The assessment of quality of life is recognized in world medical practice and research, an indicator that is also used to assess the quality of the health system and in general sociological research.

scholarly journals Universal Masking to Control Healthcare-Associated Transmission of SARS-CoV-2

2021 ◽  
pp. 1-24
Author(s):  
Eliza R. Thompson ◽  
Faith S. Williams ◽  
Pat A. Giacin ◽  
Shay Drummond ◽  
Eric Brown ◽  
...  
Keyword(s):  
Large Scale ◽  
Infection Prevention ◽  
Index Patient ◽  
Field Investigation ◽  
Point Prevalence ◽  
Control Measures ◽  
Prevention Measures ◽  
Infection Control Measures ◽  
Va Health Care System ◽  
Healthcare Associated

Abstract Objective: To assess extent of a healthcare-associated outbreak of SARS-CoV-2 and evaluate effectiveness of infection control measures, including universal masking Design: Outbreak investigation including 4 large-scale point-prevalence surveys Setting: Integrated VA Health Care System with 2 facilities and 330 beds Participants: Index patient and 250 exposed patients and staff Methods: We identified exposed patients and staff and classified them as probable and confirmed cases based on symptoms and testing. We performed a field investigation and assessment of patient and staff interactions to develop probable transmission routes. Infection prevention interventions implemented included droplet and contact precautions, employee quarantine, and universal masking with medical and cloth facemasks. Four point-prevalence surveys of patient and staff subsets were conducted using real-time reverse-transcriptase polymerase chain reaction for SARS-CoV-2. Results: Among 250 potentially exposed patients and staff, 14 confirmed cases of Covid-19 were identified. Patient roommates and staff with prolonged patient contact were most likely to be infected. The last potential date of transmission from staff to patient was day 22, the day universal masking was implemented. Subsequent point-prevalence surveys in 126 patients and 234 staff identified 0 patient cases and 5 staff cases of Covid-19, without evidence of healthcare-associated transmission. Conclusions: Universal masking with medical facemasks was effective in preventing further spread of SARS-CoV-2 in our facility in conjunction with other traditional infection prevention measures.

scholarly journals Heterogeneity and effectiveness analysis of COVID-19 prevention and control in major cities in China through time-varying reproduction number estimation

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Qing Cheng ◽  
Zeyi Liu ◽  
Guangquan Cheng ◽  
Jincai Huang
Keyword(s):  
Prevention And Control ◽  
Large Scale ◽  
Reproduction Number ◽  
Correlation Method ◽  
Control Measures ◽  
Time Varying ◽  
Short Period ◽  
Significant Difference ◽  
Prevention And Control Measures ◽  
And Control

AbstractBeginning on December 31, 2019, the large-scale novel coronavirus disease 2019 (COVID-19) emerged in China. Tracking and analysing the heterogeneity and effectiveness of cities’ prevention and control of the COVID-19 epidemic is essential to design and adjust epidemic prevention and control measures. The number of newly confirmed cases in 25 of China’s most-affected cities for the COVID-19 epidemic from January 11 to February 10 was collected. The heterogeneity and effectiveness of these 25 cities’ prevention and control measures for COVID-19 were analysed by using an estimated time-varying reproduction number method and a serial correlation method. The results showed that the effective reproduction number (R) in 25 cities showed a downward trend overall, but there was a significant difference in the R change trends among cities, indicating that there was heterogeneity in the spread and control of COVID-19 in cities. Moreover, the COVID-19 control in 21 of 25 cities was effective, and the risk of infection decreased because their R had dropped below 1 by February 10, 2020. In contrast, the cities of Wuhan, Tianmen, Ezhou and Enshi still had difficulty effectively controlling the COVID-19 epidemic in a short period of time because their R was greater than 1.

scholarly journals Assessing the Response of Snow Avalanche Runout Altitudes to Climate Fluctuations Using Hierarchical Modeling: Application to 61 Winters of Data in France

2010 ◽  
Vol 23 (12) ◽  
pp. 3157-3180 ◽  
Author(s):  
N. Eckert ◽  
H. Baya ◽  
M. Deschatres
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Hierarchical Modeling ◽  
Control Measures ◽  
Level Shift ◽  
Snow Avalanches ◽  
Winter Climate ◽  
Climate Fluctuations ◽  
High Magnitude ◽  
Proposed Model

Abstract Snow avalanches are natural hazards strongly controlled by the mountain winter climate, but their recent response to climate change has thus far been poorly documented. In this paper, hierarchical modeling is used to obtain robust indexes of the annual fluctuations of runout altitudes. The proposed model includes a possible level shift, and distinguishes common large-scale signals in both mean- and high-magnitude events from the interannual variability. Application to the data available in France over the last 61 winters shows that the mean runout altitude is not different now than it was 60 yr ago, but that snow avalanches have been retreating since 1977. This trend is of particular note for high-magnitude events, which have seen their probability rates halved, a crucial result in terms of hazard assessment. Avalanche control measures, observation errors, and model limitations are insufficient explanations for these trends. On the other hand, strong similarities in the pattern of behavior of the proposed runout indexes and several climate datasets are shown, as well as a consistent evolution of the preferred flow regime. The proposed runout indexes may therefore be usable as indicators of climate change at high altitudes.

scholarly journals Fishing out collective memory of migratory schools

2014 ◽  
Vol 11 (95) ◽  
pp. 20140043 ◽  
Author(s):  
Giancarlo De Luca ◽  
Patrizio Mariani ◽  
Brian R. MacKenzie ◽  
Matteo Marsili
Keyword(s):  
Collective Memory ◽  
Large Scale ◽  
Group Formation ◽  
Individual Preference ◽  
Relative Number ◽  
Collective Behaviour ◽  
Control Group ◽  
Adaptive Networks ◽  
Modelling Framework ◽  
Migration Pathways

Animals form groups for many reasons, but there are costs and benefits associated with group formation. One of the benefits is collective memory. In groups on the move, social interactions play a crucial role in the cohesion and the ability to make consensus decisions. When migrating from spawning to feeding areas, fish schools need to retain a collective memory of the destination site over thousands of kilometres, and changes in group formation or individual preference can produce sudden changes in migration pathways. We propose a modelling framework, based on stochastic adaptive networks, that can reproduce this collective behaviour. We assume that three factors control group formation and school migration behaviour: the intensity of social interaction, the relative number of informed individuals and the strength of preference that informed individuals have for a particular migration area. We treat these factors independently and relate the individuals’ preferences to the experience and memory for certain migration sites. We demonstrate that removal of knowledgeable individuals or alteration of individual preference can produce rapid changes in group formation and collective behaviour. For example, intensive fishing targeting the migratory species and also their preferred prey can reduce both terms to a point at which migration to the destination sites is suddenly stopped. The conceptual approaches represented by our modelling framework may therefore be able to explain large-scale changes in fish migration and spatial distribution.

Mixing of Matter by a Rising Bubble Near a Wall

2011 ◽  
Author(s):  
Toru Koso ◽  
Hiroyuki Iwashita ◽  
Fumihiko Usuki
Keyword(s):  
Large Scale ◽  
Uv Light ◽  
Fluid Motion ◽  
Turbulent Diffusion Coefficient ◽  
Air Bubble ◽  
Rising Bubble ◽  
Mass Dispersion ◽  
Mixing Patterns ◽  
Bubble Rising ◽  
Near Wall

The turbulent mixing of liquid mass caused by an air bubble rising near a wall in a still liquid in a pipe is investigated experimentally using a photochromic dye. A part of the liquid is activated by UV light and subjected to the fluid motion caused by a zigzag rising bubble of which Reynolds number is 214. The visualized mixing patterns showed that the dye is mixed by vortex motions in the bubble wake that is similar to the case of a bubble rising in the center of the pipe. The concentration distributions were deduced from the dye images using Lambert-Beer’s law and the turbulent diffusion coefficient (TDC) was evaluated from the temporal changes in the mass dispersion. The TDCs showed that a near-wall bubble generates stronger mixing than for a bubble in the center of the pipe. This stronger mixing can be attributed to the large-scale vortices observed for a near-wall bubble, which remains active for a longer time due to the lack of oppositely rotating vortices and mixes more fluids.

Global scale hydrological modelling at 100 m, 1 h resolution, in Python

2021 ◽  
Author(s):  
Kor de Jong ◽  
Marc van Kreveld ◽  
Debabrata Panja ◽  
Oliver Schmitz ◽  
Derek Karssenberg
Keyword(s):  
Large Scale ◽  
Model Building ◽  
Flow Direction ◽  
Building Blocks ◽  
Global Scale ◽  
Data Availability ◽  
Hydrological Models ◽  
Continental Scale ◽  
Modelling Framework ◽  
Scale Models

<p>Data availability at global scale is increasing exponentially. Although considerable challenges remain regarding the identification of model structure and parameters of continental scale hydrological models, we will soon reach the situation that global scale models could be defined at very high resolutions close to 100 m or less. One of the key challenges is how to make simulations of these ultra-high resolution models tractable ([1]).</p><p>Our research contributes by the development of a model building framework that is specifically designed to distribute calculations over multiple cluster nodes. This framework enables domain experts like hydrologists to develop their own large scale models, using a scripting language like Python, without the need to acquire the skills to develop low-level computer code for parallel and distributed computing.</p><p>We present the design and implementation of this software framework and illustrate its use with a prototype 100 m, 1 h continental scale hydrological model. Our modelling framework ensures that any model built with it is parallelized. This is made possible by providing the model builder with a set of building blocks of models, which are coded in such a manner that parallelization of calculations occurs within and across these building blocks, for any combination of building blocks. There is thus full flexibility on the side of the modeller, without losing performance.</p><p>This breakthrough is made possible by applying a novel approach to the implementation of the model building framework, called asynchronous many-tasks, provided by the HPX C++ software library ([3]). The code in the model building framework expresses spatial operations as large collections of interdependent tasks that can be executed efficiently on individual laptops as well as computer clusters ([2]). Our framework currently includes the most essential operations for building large scale hydrological models, including those for simulating transport of material through a flow direction network. By combining these operations, we rebuilt an existing 100 m, 1 h resolution model, thus far used for simulations of small catchments, requiring limited coding as we only had to replace the computational back end of the existing model. Runs at continental scale on a computer cluster show acceptable strong and weak scaling providing a strong indication that global simulations at this resolution will soon be possible, technically speaking.</p><p>Future work will focus on extending the set of modelling operations and adding scalable I/O, after which existing models that are currently limited in their ability to use the computational resources available to them can be ported to this new environment.</p><p>More information about our modelling framework is at https://lue.computationalgeography.org.</p><p><strong>References</strong></p><p>[1] M. Bierkens. Global hydrology 2015: State, trends, and directions. Water Resources Research, 51(7):4923–4947, 2015.<br>[2] K. de Jong, et al. An environmental modelling framework based on asynchronous many-tasks: scalability and usability. Submitted.<br>[3] H. Kaiser, et al. HPX - The C++ standard library for parallelism and concurrency. Journal of Open Source Software, 5(53):2352, 2020.</p>

A shift from science to politics : a content analysis of COVID-19 Videos on YouTube (Preprint)

2021 ◽  
Author(s):  
Chyun-Fung Shi ◽  
Matthew C So ◽  
Sophie Stelmach ◽  
Arielle Earn ◽  
David J D Earn ◽  
...  
Keyword(s):  
Public Health ◽  
Social Media ◽  
Content Analysis ◽  
Large Scale ◽  
Control Measures ◽  
Mitigation Measures ◽  
Health Campaigns ◽  
Public Attention ◽  
Conflicting Information ◽  
Social Media Platforms

BACKGROUND The COVID-19 pandemic is the first pandemic where social media platforms relayed information on a large scale, enabling an “infodemic” of conflicting information which undermined the global response to the pandemic. Understanding how the information circulated and evolved on social media platforms is essential for planning future public health campaigns. OBJECTIVE This study investigated what types of themes about COVID-19 were most viewed on YouTube during the first 8 months of the pandemic, and how COVID-19 themes progressed over this period. METHODS We analyzed top-viewed YouTube COVID-19 related videos in English from from December 1, 2019 to August 16, 2020 with an open inductive content analysis. We coded 536 videos associated with 1.1 billion views across the study period. East Asian countries were the first to report the virus, while most of the top-viewed videos in English were from the US. Videos from straight news outlets dominated the top-viewed videos throughout the outbreak, and public health authorities contributed the fewest. Although straight news was the dominant COVID-19 video source with various types of themes, its viewership per video was similar to that for entertainment news and YouTubers after March. RESULTS We found, first, that collective public attention to the COVID-19 pandemic on YouTube peaked around March 2020, before the outbreak peaked, and flattened afterwards despite a spike in worldwide cases. Second, more videos focused on prevention early on, but videos with political themes increased through time. Third, regarding prevention and control measures, masking received much less attention than lockdown and social distancing in the study period. CONCLUSIONS Our study suggests that a transition of focus from science to politics on social media intensified the COVID-19 infodemic and may have weakened mitigation measures during the first waves of the COVID-19 pandemic. It is recommended that authorities should consider co-operating with reputable social media influencers to promote health campaigns and improve health literacy. In addition, given high levels of globalization of social platforms and polarization of users, tailoring communication towards different digital communities is likely to be essential.

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