Impact of Lifestyle Alteration on Non-COVID Deaths by Prevention Measures in the Region with a Low COVID-19 Transmission Rate

2020 ◽  
Author(s):  
Chengzong Li ◽  
Liang Wang ◽  
Peian Lou ◽  
Ming Chu ◽  
Bing Gu ◽  
...  
Keyword(s):  
Transmission Rate ◽  
Prevention Measures

scholarly journals Novel Prediction Model for COVID-19 in Saudi Arabia Based on an LSTM Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Eman H. Alkhammash ◽  
Haneen Algethami ◽  
Reem Alshahrani
Keyword(s):  
Saudi Arabia ◽  
Adaptive Learning ◽  
Performance Metrics ◽  
Hospital Admissions ◽  
Short Term Memory ◽  
Transmission Rate ◽  
Influential Factors ◽  
Statistical Hypothesis ◽  
Prevention Measures ◽  
Short Term

The rapid emergence of the novel SARS-CoV-2 poses a challenge and has attracted worldwide attention. Artificial intelligence (AI) can be used to combat this pandemic and control the spread of the virus. In particular, deep learning-based time-series techniques are used to predict worldwide COVID-19 cases for short-term and medium-term dependencies using adaptive learning. This study aimed to predict daily COVID-19 cases and investigate the critical factors that increase the transmission rate of this outbreak by examining different influential factors. Furthermore, the study analyzed the effectiveness of COVID-19 prevention measures. A fully connected deep neural network, long short-term memory (LSTM), and transformer model were used as the AI models for the prediction of new COVID-19 cases. Initially, data preprocessing and feature extraction were performed using COVID-19 datasets from Saudi Arabia. The performance metrics for all models were computed, and the results were subjected to comparative analysis to detect the most reliable model. Additionally, statistical hypothesis analysis and correlation analysis were performed on the COVID-19 datasets by including features such as daily mobility, total cases, people fully vaccinated per hundred, weekly hospital admissions per million, intensive care unit patients, and new deaths per million. The results show that the LSTM algorithm had the highest accuracy of all the algorithms and an error of less than 2%. The findings of this study contribute to our understanding of COVID-19 containment. This study also provides insights into the prevention of future outbreaks.

scholarly journals A surprising formula for the spread of Covid-19 under aggressive management

2020 ◽  
Author(s):  
Ivan Cherednik
Keyword(s):  
Bessel Functions ◽  
Transmission Rate ◽  
High Accuracy ◽  
Viral Fitness ◽  
Prevention Measures ◽  
Aggressive Management ◽  
Normal Frequency ◽  
The Usa ◽  
Momentum Management ◽  
Initial Transmission

AbstractWe propose an algebraic-type formula that describes with high accuracy the total number of detected infections for the Covid-19 pandemic in many countries. Our 2-phase formula can be used as a powerful forecasting tool. It is based on the author’s new theory of momentum management of epidemics; Bessel functions are employed. Its 3 parameters are the initial transmission rate, reflecting the viral fitness and “normal” frequency of contacts in the infected areas, and the intensity of prevention measures at phases 1, 2. Austria, Brazil, Germany, Japan, India, Israel, Italy, the Netherlands, Sweden, Switzerland, UK, and the USA are considered. For the USA, all states are processed independently and some “interaction” is added; the forecasting software is provided.

scholarly journals Network model and analysis of the spread of Covid-19 with social distancing

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Parul Maheshwari ◽  
Réka Albert
Keyword(s):  
Network Model ◽  
Transmission Rate ◽  
Real Data ◽  
Disease Spread ◽  
Prevention Measures ◽  
Social Distancing ◽  
Workplace Interactions ◽  
Human Interactions ◽  
Reproduction Numbers ◽  
Second Wave

AbstractThe first mitigation response to the Covid-19 pandemic was to limit person-to-person interaction as much as possible. This was implemented by the temporary closing of many workplaces and people were required to follow social distancing. Networks are a great way to represent interactions among people and the temporary severing of these interactions. Here, we present a network model of human–human interactions that could be mediators of disease spread. The nodes of this network are individuals and different types of edges denote family cliques, workplace interactions, interactions arising from essential needs, and social interactions. Each individual can be in one of four states: susceptible, infected, immune, and dead. The network and the disease parameters are informed by the existing literature on Covid-19. Using this model, we simulate the spread of an infectious disease in the presence of various mitigation scenarios. For example, lockdown is implemented by deleting edges that denote non-essential interactions. We validate the simulation results with the real data by matching the basic and effective reproduction numbers during different phases of the spread. We also simulate different possibilities of the slow lifting of the lockdown by varying the transmission rate as facilities are slowly opened but people follow prevention measures like wearing masks etc. We make predictions on the probability and intensity of a second wave of infection in each of these scenarios.

scholarly journals Transmission of SARS-CoV-2 infection among children in summer schools applying stringent control measures in Barcelona, Spain

2021 ◽  
Author(s):  
Iolanda Jordan ◽  
Mariona Fernandez de Sevilla ◽  
Victoria Fumado ◽  
Quique Bassat ◽  
Elisenda Bonet-Carne ◽  
...  
Keyword(s):  
General Population ◽  
Transmission Rate ◽  
Control Measures ◽  
Surveillance Program ◽  
Prevention Measures ◽  
Rt Pcr ◽  
Primary Case ◽  
Summer Schools ◽  
Close Contacts

Abstract Background Understanding the role of children in SARS-CoV-2 transmission is critical to guide decision-making for schools in the pandemic. We aimed to describe the transmission of SARS-CoV-2 among children and adult staff in summer schools. Methods During July 2020 we prospectively recruited children and adult staff attending summer schools in Barcelona who had SARS-CoV-2 infection. Primary SARS-CoV-2 infections were identified through: (1) surveillance program in 22 summer schools’ of 1905 participants, involving weekly saliva sampling for SARS-CoV-2 RT-PCR during 2-5 weeks; (2)cases identified through the Catalonian Health Surveillance System of children diagnosed with SARS-CoV-2 infection by nasopharyngeal RT-PCR. All centres followed prevention protocols: bubble groups, hand washing, facemasks and conducting activities mostly outdoors. Contacts of a primary case within the same bubble were evaluated by nasopharyngeal RT-PCR. Secondary attack rates and effective reproduction number in summer schools(R*) were calculated. Results Among the over 2000 repeatedly screened participants, 30children and 9adults were identified as primary cases. A total of 253 close contacts of these primary cases were studied (median 9 (IQR 5-10) for each primary case), among which twelve new cases (4.7%) were positive for SARS-CoV-2. The R* was 0.3, whereas the contemporary rate in the general population from the same areas in Barcelona was 1.9. Conclusions The transmission rate of SARS-CoV-2 infection among children attending school-like facilities under strict prevention measures was lower than that reported for the general population. This suggests that under preventive measures schools are unlikely amplifiers of SARS-CoV-2 transmission and supports current recommendations for school opening.

scholarly journals 902 Safe Elective & Emergency Surgery During the COVID-19 Crisis: Experience of a Large Tertiary Centre During the First Wave of the Pandemic

2021 ◽  
Vol 108 (Supplement_6) ◽  
Author(s):  
A Giorga ◽  
J Thompson ◽  
T Lo ◽  
R Baker
Keyword(s):  
Infection Prevention ◽  
Operative Mortality ◽  
Elective Surgery ◽  
Transmission Rate ◽  
Nosocomial Transmission ◽  
Prevention Measures ◽  
Surgical Services ◽  
Tertiary Centre ◽  
Acute Admissions ◽  
Overall Mortality

Abstract Aim In addition to a reduction in elective surgery, the COVID-19 pandemic has been associated with concerning rates of post-operative mortality in COVID-19 patients highlighting the threat of nosocomial transmission. Relocation of elective patients into a protected cold wing of a tertiary centre, vigilant testing and staff test, and trace were implemented to address these issues. Method Retrospective analysis of 5069 consecutive patients who underwent procedures in theatre from 11/03/20 – 08/09/20 was performed. Comparison of numbers of procedures was compared with the same study dates in 2019. Detailed analysis of nosocomial transmission of COVID-19 and mortality was performed using patient notes and death certificates. Results 5854 procedures were performed in 2020 compared with 13219 in 2019, representing a reduction of 55.7%. The overall mortality in 2020 was 2.7% (135/5069). COVID-19 negative mortality was 2.36% (119/5033). 74 patients tested positive for COVID-19 at any time (1.3%); mortality amongst patients who tested positive seven days pre- to 30 days post-procedure was 5.4% (4/74). Nosocomial transmission rate was 0.27% in elective admissions (10/3773) and 0.97% in acute admissions (20/2052). Conclusions The first wave of the pandemic has predictably caused a significant reduction in elective activity. Our hospital infection prevention measures have kept nosocomial transmission rates low, particularly for elective admissions. We have observed lower rates of post-operative mortality in COVID-19 patients than published in other centres. Continuation of surgical services is important for patient outcomes, and essential for training the surgeons of tomorrow.

scholarly journals TP10.2.14Safe elective & emergency surgery: experience of a large tertiary centre during the first wave of the COVID-19 pandemic

2021 ◽  
Vol 108 (Supplement_7) ◽  
Author(s):  
Joseph Thompson ◽  
Andrea Giorga ◽  
Terence Lo ◽  
Richard Baker
Keyword(s):  
Infection Prevention ◽  
Operative Mortality ◽  
Elective Surgery ◽  
Transmission Rate ◽  
Nosocomial Transmission ◽  
Prevention Measures ◽  
Transmission Rates ◽  
Emergency Procedures ◽  
Tertiary Centre ◽  
The Impact

Abstract Aims To evaluate the impact of Trust infection prevention measures (including relocation of elective patients into a protected cold wing, vigilant testing and staff test and trace) on elective and emergency nosocomial transmission rates and to analyse post-operative mortality in COVID-19 patients. Additionally, we compared the numbers of elective and emergency procedures in 2020 to 2019. Method Retrospective analysis of 5069 consecutive patients who underwent procedures in theatre from 11/03/20 – 08/09/20. COVID-19 infection was defined by PCR and/or radiological confirmation. Analysis of nosocomial transmission of COVID-19 and mortality was conducted using patient notes and death certificates. The number of procedures was compared with the same study dates in 2019. Results Nosocomial transmission rate was 0.27% in elective admissions (10/3773) and 0.97% in acute admissions (20/2052). The overall mortality in 2020 was 2.7% (135/5069). Covid-negative mortality was 2.36% (119/5033). 74 patients tested positive for COVID-19 at any time (1.3%); mortality in patients who tested positive seven days pre- to 30 days post-procedure was 5.4% (4/74). There were 10282 elective procedures in 2019 compared with 3773 in the same period in 2020, representing a 63.3% reduction in elective activity. Conclusion Our hospital infection prevention measures have kept nosocomial transmission rates low, particularly for elective admissions. We have observed lower rates of post-operative mortality in COVID-19 patients than published in other centres. There has been a predictably significant reduction in elective activity, however based on our findings we believe our infection prevention measures could provide reassurances to safely increase elective surgery activity.

scholarly journals Characterizing COVID-19 Transmission: Incubation Period, Reproduction Rate, and Multiple-Generation Spreading

2021 ◽  
Vol 8 ◽  
Author(s):  
Lin Zhang ◽  
Jiahua Zhu ◽  
Xuyuan Wang ◽  
Juan Yang ◽  
Xiao Fan Liu ◽  
...  
Keyword(s):  
Incubation Period ◽  
Disease Transmission ◽  
Transmission Rate ◽  
Close Contact ◽  
Mainland China ◽  
Reproduction Rate ◽  
Prevention Measures ◽  
Multiple Generation ◽  
Log Normal ◽  
Close Contacts

Understanding the transmission process is crucial for the prevention and mitigation of COVID-19 spread. This paper contributes to the COVID-19 knowledge by analyzing the incubation period, the transmission rate from close contact to infection, and the properties of multiple-generation transmission. The data regarding these parameters are extracted from a detailed line-list database of 9,120 cases reported in mainland China from January 15 to February 29, 2020. The incubation period of COVID-19 has a mean, median, and mode of 7.83, 7, and 5 days, and, in 12.5% of cases, more than 14 days. The number of close contacts for these cases during the incubation period and a few days before hospitalization follows a log-normal distribution, which may lead to super-spreading events. The disease transmission rate from close contact roughly decreases in line with the number of close contacts with median 0.13. The average secondary cases are 2.10, 1.35, and 2.2 for the first, second, and third generations conditioned on at least one offspring. However, the ratio of no further spread in the 2nd, 3rd, and 4th generations are 26.2, 93.9, and 90.7%, respectively. Moreover, the conditioned reproduction number in the second generation is geometrically distributed. Our findings suggest that, in order to effectively control the pandemic, prevention measures, such as social distancing, wearing masks, and isolating from close contacts, would be the most important and least costly measures.

Interfacing of a TEM/STEM System to a Computer

1981 ◽  
Vol 39 ◽  
pp. 250-251
Author(s):  
P. Hagemann
Keyword(s):  
Image Analysis ◽  
Transmission Rate ◽  
Analytical Electron Microscopy ◽  
Signal Beam ◽  
Automated Image Analysis ◽  
Beam Deflection ◽  
External Control ◽  
Computer Input ◽  
Instrument Control ◽  
Data Acquisition And Processing

The use of computers in the analytical electron microscopy today shows three different trends (1) automated image analysis with dedicated computer systems, (2) instrument control by microprocessors and (3) data acquisition and processing e.g. X-ray or EEL Spectroscopy.While image analysis in the T.E.M. usually needs a television chain to get a sequential transmission suitable as computer input, the STEM system already has this necessary facility. For the EM400T-STEM system therefore an interface was developed, that allows external control of the beam deflection in TEM as well as the control of the STEM probe and video signal/beam brightness on the STEM screen.The interface sends and receives analogue signals so that the transmission rate is determined by the convertors in the actual computer periphery.

Perception of Smokers: Results from the Tobacco Monitoring Switzerland

2011 ◽  
Vol 57 (2) ◽  
pp. 131-139 ◽  
Author(s):  
Theda Radtke ◽  
Roger Keller ◽  
Andrea Bütikofer ◽  
Rainer Hornung
Keyword(s):  
Social Ties ◽  
Tobacco Consumption ◽  
School Transitions ◽  
Prevention Measures

Aim: The purpose of the study is to present adolescents’ perceptions of smokers and non-smokers among 1015 Swiss adolescents. Method: The analyses are based on data from Tobacco Monitoring Switzerland, which is a survey of tobacco consumption in Switzerland. To measure the perceptions of smokers and non-smokers, respondents were asked to attribute a series of adjectives to each group. It was also recorded when respondents mentioned that “there is no difference between smokers and non-smokers.” Results: Results show that regardless of whether the adolescents smoked or did not smoke – with the exception of more sociable – the image of smokers was more negative than the image of non-smokers. Findings also indicated that regular smokers in particular often stated that there are no differences between both groups. Conclusions: Overall, the image of smokers is more negative than the image of non-smokers, with the exception of the attribute more sociable. This perception of smokers could be important for prevention measures in new contexts (e. g., school transitions), where smoking could be a means of establishing new social ties.

Family-, Media-, and School-Related Risk Factors of Video Game Addiction

2013 ◽  
Vol 25 (3) ◽  
pp. 118-128 ◽  
Author(s):  
Florian Rehbein ◽  
Dirk Baier
Keyword(s):  
Risk Factors ◽  
Video Game ◽  
Age Groups ◽  
Well Being ◽  
Epidemiological Studies ◽  
Prevention Measures ◽  
School Life ◽  
Video Game Addiction ◽  
Effective Prevention ◽  
Game Addiction

In recent years, a variety of epidemiological studies have provided empirical data on the prevalence of video game addiction (GA) in different age groups. However, few studies investigated the causes of GA and could explain why video game playing as a widespread phenomenon leads to a comparatively small percentage of addicted players. Additionally, the existing longitudinal studies mainly consider psychological trait variables and neglect the possible explanatory value of predictors in socialization regarding media availability, media use, and family and everyday school life. In this paper, the results of a two-wave longitudinal study comprising a sample of students from Grades 4 to 9 (N = 406) are presented. The data show that 15-year-old video game addicts had already exhibited a number of specific risk factors at the age of 10. Students from single-parent families seem to be particularly at risk, as are students with low experienced school well-being and with a weaker social integration in class. The data also indicate that problematic use of video games in childhood increases the risk of GA in adolescence. Male students are especially vulnerable for developing GA. The results of this study are an important contribution to understanding risk factors for GA in adolescents, thereby laying the groundwork for effective prevention measures.

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