Corpus overview


Overview

MeSH Disease

Human Phenotype

Pneumonia (19)

Fever (6)

Cough (6)

Anxiety (4)

Hypertension (4)


Transmission

Seroprevalence
    displaying 1 - 10 records in total 138
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    Suppression of COVID-19 infection by isolation time control based on the SIR model and an analogy from nuclear fusion research

    Authors: Osamu Mitarai; Nagato Yanagi; Gaurab Mukherjee; Monica S McAndrews; Elissa J Chesler; Judith A Blake; Sanduo Zheng; Jianping Wu; Devin J. Kenney; Douam Florian; Yimin Tong; Jin Zhong; Youhua Xie; Xinquan Wang; Zhenghong Yuan; Dongming Zhou; Rong Zhang; Qiang Ding; Kristen J Brennand; Katherine H Hullsiek; David R Boulware; SARAH M LOFGREN; Martirene A da Silva; Brian Custer; Manoel Barral-Netto; Moritz Kraemer; Rafael HM Pererira; Oliver G Pybus; Michael P Busch; Márcia C Castro; Christopher Dye; Vitor H Nascimento; Nuno R Faria; Ester C Sabino

    doi:10.1101/2020.09.18.20197723 Date: 2020-09-20 Source: medRxiv

    The coronavirus disease MESHD 2019 (COVID-19) has been damaging our daily life after declaration of pandemic. Therefore, we have started studying on the characteristics of Susceptible-Infectious-Recovered (SIR) model to know about the truth of infectious disease MESHD and our future. After detailed studies on the characteristics of the SIR model for the various parameter dependencies MESHD with respect to such as the outing restriction (lockdown) ratio and vaccination rate, we have finally noticed that the second term (isolation term) in the differential equation of the number of the infected is quite similar to the "helium ash particle loss term" in deuterium-tritium (D-T) nuclear fusion. Based on this analogy, we have found that isolation of the infected is not actively controlled in the SIR model. Then we introduce the isolation control time parameter q and have studied its effect on this pandemic. Required isolation time to terminate the COVID-19 can be estimated by this proposed method. To show this isolation control effect, we choose Tokyo for the model calculation because of high population density. We determine the reproduction number TRANS and the isolation ratio in the initial uncontrolled phase, and then the future number of the infected is estimated under various conditions. If the confirmed case TRANS can be isolated in 3~8 days by widely performed testing, this pandemic could be suppressed without awaiting vaccination. If the mild outing restriction and vaccination are taken together, the isolation control time can be longer. We consider this isolation time control might be the only solution to overcome the pandemic when vaccine is not available.

    A fractional order approach to modeling and simulations of the novel COVID-19

    Authors: Isaac Owusu-Mensah; Lanre Akinyemi; Bismark Oduro; Olaniyi S. Iyiola

    doi:10.21203/rs.3.rs-77269/v1 Date: 2020-09-14 Source: ResearchSquare

    The novel coronavirus (SARS-CoV-2.) has emerged and spread at fast speed globally; the disease has become an unprecedented threat to public health worldwide. It is one of the greatest public health challenges in modern times, with no proven cure or vaccine. In this paper, our focus is on a fractional order approach to modeling and simulations of the novel COVID-19. We introduce a fractional type Susceptible-Exposed-Infected-Recovered (SEIR) model to gain insight into the ongoing pandemic of COVID-19. Our proposed model incorporates transmission TRANS rate, testing rates, and transition rate (from asymptomatic TRANS to symptomatic population groups) for a holistic study of the coronavirus disease MESHD. The impacts of these parameters on the dynamics of the solution proles for the disease are simulated and discussed in detail. Furthermore, across all the different parameters, the effects of the fractional order derivative are also simulated and discussed in detail. Various simulations carried out enable us gain deep insights into the dynamics of the spread of COVID-19. The simulation results confirm that fractional calculus is an appropriate tool in modeling the spread of a complex infectious disease MESHD such as the novel COVID-19. In the absence of vaccine and treatment, our analysis strongly supports the significance reduction in the transmission TRANS rate as valuable strategy to curb the spread of the virus. Our results suggest that tracing TRANS and moving testing up has an important benefit. It reduces the number of infected individuals in the general public and thereby reduce the spread of the pandemic. Once the infected MESHD individuals are identified and isolated, the interaction between susceptible and infected individuals diminishes and transmission TRANS reduces. Furthermore, aggressive testing is also highly recommended.

    COVID-19 Forecasting using Multivariate Linear Regression MESHD

    Authors: R. Suganya; R.Arunadevi; Seyed M.Buhari

    doi:10.21203/rs.3.rs-71963/v1 Date: 2020-09-04 Source: ResearchSquare

    Coronavirus disease 2019 (COVID-19) is an infectious disease MESHD caused by severe respiratory syndrome coronavirus 2 MESHD (SARS-CoV-2). It was first identified in December 2019 in Wuhan, the capital of China’s Hubei province. The objective of this research is to propose a forecasting model using the COVID-19 available dataset from top affected regions across the world using machine learning algorithms. Machine Learning algorithms MESHD help us achieve this objective. Regression models are one of the supervised machine learning techniques to classify large-scale data. This research aims to apply Multivariate Linear Regression to predict the number of confirmed and death COVID-19 cases for a span of one and two weeks. The experimental results explain 99\% variability in prediction with the R-squared statistics scores of 0.992. The algorithms are evaluated using the error matrix such as Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and accuracy for top affected regions across the world.  

    Early detection of seasonality and second waves prediction in the Covid-19 pandemic

    Authors: Marcio Alves de Souza Watanabe; Proton Rahman; J Concepcion Loredo-Osti; Saniya Minase; Namitha Sivadas; Ashutosh Mahajan; Michelle L. Allen; Genevieve B. Melton; Anthony Charles; Christopher J. Tignanelli; - the Yale IMPACT Research Team; Charles S. Dela Cruz; Shelli F. Farhadian; Akiko Iwasaki; Albert I. Ko; Nathan D. Grubaugh; Anne L. Wyllie

    doi:10.1101/2020.09.02.20187203 Date: 2020-09-03 Source: medRxiv

    Seasonality plays an essential role in the dynamics of many infectious diseases MESHD. In this study, we use statistical methods to show how to detect the presence of seasonality in a pandemic at the beginning of the seasonal period and that seasonality strongly affects SARS-coV-2 transmission TRANS. We measure the expected seasonality effect in the mean transmission TRANS rate of SARS-coV-2 MESHD and use available data to predict when a second wave of the Covid-19 will happen. In addition, we measure the average global effect of social distancing measures. The seasonal force of transmission TRANS of Covid-19 increases in September in the Northern hemisphere and in April in the Southern hemisphere. These predictions provide critical information for public health officials to plan their actions to combat the new coronavirus disease MESHD and to identify and measure seasonal effects in a future pandemic.

    Effects of Public Health Interventions on the Epidemiological Spread During the First Wave of the COVID-19 Outbreak in Thailand

    Authors: Sipat Dr. Triukose; Sirin Dr. Nitinawarat; Ponlapat Satian; Anupap Dr. Somboonsavatdee; Ponlachart Dr. Chotikarn; Thunchanok Thammasanya; Nasamon Wanlapakorn; Natthinee Dr. Sudhinaraset; Pitakpol Dr. Boonyamalik; Bancha Kakhong; Yong Poovorawan; Paula Casajust; Dalia Dawoud; Scott L DuVall; Thomas Falconer; Sergio Fernandez-Bertolin; Asieh Golozar; Mengchun Gong; Lana Yin Hui Lai; Jennifer C.E Lane; Kristine E Lynch; Michael E Matheny; Paras P Mehta; Daniel R Morales; Karthik Natarjan; Fredrik Nyberg; Jose D Posada; Christian G Reich; Lisa M Schilling; Karishma Shah; Nigham H Shah; Vignesh Subbian; Lin Zhang; Hong Zhu; Patrick Ryan; Daniel Prieto-Alhambra; Kristin Kostka; Talita Duarte-Salles

    doi:10.1101/2020.09.01.20182873 Date: 2020-09-03 Source: medRxiv

    A novel infectious respiratory disease MESHD was recognized in Wuhan (Hubei Province, China) in December 2019. In February 2020, the disease was named " coronavirus disease MESHD 2019" (COVID-19). COVID-19 became a pandemic in March 2020, and, since then, different countries have implemented a broad spectrum of policies. Thailand is considered to be among the top countries in handling its first wave of the outbreak -- 12 January to 31 July 2020. Here, we illustrate how Thailand tackled the COVID-19 outbreak, particularly the effects of public health interventions on the epidemiological spread. This study shows how the available data from the outbreak can be analyzed and visualized to quantify the severity of the outbreak, the effectiveness of the interventions, and the level of risk of allowed activities during an easing of a "lockdown." This study shows how a well-organized governmental apparatus can overcome the havoc caused by a pandemic.

    Subtypes of nurses' mental workload and interaction patterns with fatigue HP fatigue MESHD and work engagement during coronavirus disease MESHD 2019 (COVID-19) outbreak: A latent class analysis

    Authors: JING WU; HUSHENG LI; ZHAOHUI GENG; YANMEI WANG; XIAN WANG; JIE ZHANG

    doi:10.21203/rs.3.rs-70155/v1 Date: 2020-09-01 Source: ResearchSquare

    Background Nurses play critical roles when providing health care in high-risk situations, such as during the COVID-19 outbreak. However, no previous study had systematically assessed nurses’ mental workloads and its interaction patterns with fatigue HP fatigue MESHD, work engagement and COVID-19 exposure risk.Methods A cross-sectional study was conducted via online questionnaire. The NASA Task Load Index, Fatigue HP Scale-14, and Utrecht Work Engagement Scale were used to assess nurses’ mental workload, fatigue HP fatigue MESHD and work engagement, respectively. A total of 1337 valid questionnaires were received and analyzed. Nurses were categorized into different subgroups of mental workload via latent class analysis (LCA). Cross-sectional comparisons, analysis of covariance (ANCOVA), and multivariate (or logistic) regression were subsequently performed to examine how demographic variables, fatigue HP fatigue MESHD and work engagement differ among nurses belonging to different subgroups.Results Three latent classes were identified based on the responses to mental workload assessment: Class1 – low workload perception & high self-evaluation group (n = 41, 3.1%); Class 2 – medium workload perception & medium self-evaluation group (n = 455, 34.4%); and Class 3 – high workload perception & low self-evaluation group (n = 841, 62.5%). Nurses belonging into class 3 were most likely to be older and have longer professional years, and displayed higher scores of fatigue HP fatigue MESHD and work engagement compared with the other latent classes (p < 0.05). Multivariate analysis showed that high cognitive workload increased subjective fatigue HP fatigue MESHD, and mental workload may be positively associated with work engagement. Group comparison results indicated that COVID-19 exposure contributed to significantly higher mental workload levels.Conclusions The complex scenario for the care of patients with infectious diseases MESHD, especially during an epidemic, raises the need for improved consideration of nurses’ perceived workload, as well as their physical fatigue HP, work engagement and personal safety when working in public health emergencies.

    Effect of novel coronavirus disease MESHD 2019 infection on chronic HP infection on chronic MESHD kidney disease G1-G5, G5 Dialysis and G5 Transplantation

    Authors: Fateme Shamekhi Amiri

    doi:10.21203/rs.3.rs-66274/v1 Date: 2020-08-26 Source: ResearchSquare

    Background: The pneumonia HP pneumonia MESHD caused by the 2019 novel coronavirus (SARS-CoV-2) is a highly infectious disease MESHD that causes lethal disease and multiorgan failure MESHD. The aim of this research is to investigate association between covid-19 infection MESHD and kidney dysfunction MESHD.Methods and materials: In this retrospective study, sixty-eight patients with kidney dysfunction MESHD and covid-19 infection MESHD were investigated. Clinical features, laboratory data at initial presentation, management and outcomes were collected.The paper has written based on searching PubMed Central and Google Scholar to identify potentially relevant articles. Median, percentage, mean ± standard deviation (SD), two-tailed t and chi-square and Cohen᾽s-d tests were used for statistical analyses. Moreover, relative risk, odds ratio, pearson᾽s correlation for statistical analyses were used. Results: The average age TRANS of patients at time of diagnosis in covid-19 nephropathy HP nephropathy MESHD was 52.04 ± 14.42 years (ranging from 24 years to 88 years). There was not statistical significance correlation between lymphocytopenia MESHD and serum SERO creatinine (SCr) in covid-19 nephropathy HP nephropathy MESHD (R2=0.063; p-value= 0.33).  Effect size of elevated IL-6 on decreased estimated glomerular filtration rate (eGFR) in covid-19 nephropathy HP nephropathy MESHD was assessed 0.656 (medium effect size). Relative risk and odds ratio of acute kidney disease MESHD ( AKD MESHD) in covid-19 nephropathy HP nephropathy MESHD were assessed 0.57 and 0.4, respectively (p-value: 0.422). Correlation between SCr changes and time of emergent AKI MESHD ( acute kidney injury HP acute kidney injury MESHD), AKD MESHD and chronic kidney disease HP chronic kidney disease MESHD ( CKD MESHD) was assessed with R2 of 0.0003 and p-value of 0.94 (not significant).  Conclusion: The present study revealed medium effect size of elevated IL-6 on decreased eGFR. Future clinical research is required for investigating novel unknown findings in covid-19 nephropathy HP nephropathy MESHD

    A Comparative Study of International and Chinese Public Health Emergency Management from the Perspective of Mapping Knowledge Domains

    Authors: Juan Li; Yuhang Zhu; Jianing Feng; Weijing Meng; Kseniia Begma; Gaopei Zhu; Xiaoxuan Wang; Di Wu; Fuyan Shi; Suzhen Wang

    doi:10.21203/rs.3.rs-63718/v1 Date: 2020-08-21 Source: ResearchSquare

    Background: At the end of 2019, the outbreak of the coronavirus disease MESHD 2019 (COVID-19) had severely damaging people’s life. China’s public health emergency management system had played an essential role in the handling and response of it, which had been appreciated by the World Health Organization and some countries. Hence it is necessary to make an overall analysis of the development of China’s health emergency management system. It can provide a reference for scholars to understand the current situation and look for new research points. Methods: We collected 2247 international from the Web of Science database, 959 Chinese articles from China National Knowledge Infrastructure database. Bibliometric and mapping knowledge domains analysis methods were used in this study for temporal distribution analysis, cooperation network, co-word network analysis. Results: The first international article in this field was published in 1991, while Chinese in 2005. Research institutions mainly come from universities and health institutions. Developed countries and European countries published more articles, while east of China published more. There are 52 burst words for international articles from 1999–2018, while 18 burst words for Chinese articles from 2003–2018. International top-ranked articles by citation appeared in 2005, 2007, 2009, 2014, 2015, 2016, while Chinese appeared in 2003, 2004, 2009, 2011.Conclusions: There are differences in the regional or economic distribution of international and Chinese cooperation networks. International research often relates to hot issues, mainly focus on the emergency preparedness and monitoring for public health events, while China’s focus on the public health emergency and their disposal. International begins the research with terrorism MESHD and bioterrorism, followed by disaster planning and emergency preparedness, epidemics and infectious diseases MESHD. China takes severe acute respiratory syndrome MESHD as the research background and legal system construction as the research starting point, followed by mechanism, structure, system, and learning from abroad of public health emergency management.

    Differential impact of non-pharmaceutical public health interventions on COVID-19 epidemics in the United States

    Authors: Xiaoshuang Liu; Xiao Xu; Guanqiao Li; Xian Xu; Yuyao Sun; Fei Wang; Xuanling Shi; Xiang Li; Guotong Xie; Linqi Zhang

    doi:10.21203/rs.3.rs-60056/v1 Date: 2020-08-15 Source: ResearchSquare

    The widespread pandemic of novel coronavirus disease MESHD 2019 (COVID-19) poses an unprecedented global health crisis. In the United States (US), different state governments have adopted various combinations of non-pharmaceutical public health interventions (NPIs) to mitigate the epidemic from February to April, 2020. Quantitative assessment on the effectiveness of NPIs is in great need to assist in guiding the individualized decision making for adjustment of interventions in the US and around the world. However, the impact of these approaches remain uncertain. Based on the reported cases, the effective reproduction number TRANS of COVID-19 epidemic for 50 states in the US was estimated. The measurement on the effectiveness of eight different NPIs was conducted by assessing risk ratios (RRs) between and NPIs through a generalized linear model (GLM). Different NPIs were found to have led to different levels of reduction in. Stay-at-home contributed approximately 51% (95% CI 46%-57%), gathering ban (more than 10 people) 19% (14%-24%), non-essential business closure 16% (10%-21%), declaration of emergency 13% (8%-17%), interstate travel TRANS restriction 11% (5%-16%), school closure 10% (7%-13%), initial business closure 10% (6%-14%), and gathering ban (more than 50 people) 6% (2%-11%). This retrospective assessment of NPIs on has shown that NPIs played critical roles on epidemic control in the US in the past several months. The quantitative results could guide individualized decision making for future adjustment of NPIs in the US and other countries for COVID-19 and other similar infectious diseases MESHD.

    Effect of Convalescent Plasma SERO on Mortality among Hospitalized Patients with COVID-19: Initial Three-Month Experience

    Authors: Michael J Joyner; Jonathon W Senefeld; Stephen A Klassen; John R Mills; Patrick W Johnson; Elitza S Theel; Chad C Wiggins; Katelyn A Bruno; Allan M Klompas; Elizabeth R Lesser; Katie L Kunze; Matthew A Sexton; Juan C Diaz Soto; Sarah E Baker; John R.A. Shepherd; Noud van Helmond; Camille M van Buskirk; Jeffrey L Winters; James R Stubbs; Robert F Rea; David O Hodge; Vitaly Herasevich; Emily R Whelan; Andrew J Clayburn; Kathryn F Larson; Juan G Ripoll; Kylie J Andersen; Matthew R Buras; Matthew N.P. Vogt; Joshua J Dennis; Riley J Regimbal; Philippe R Bauer; Janis E Blair; Nigel S Paneth; DeLisa Fairweather; R. Scott Wright; Rickey E Carter; Arturo Casadevall

    doi:10.1101/2020.08.12.20169359 Date: 2020-08-12 Source: medRxiv

    Importance: Passive antibody SERO transfer is a longstanding treatment strategy for infectious diseases MESHD that involve the respiratory system. In this context, human convalescent plasma SERO has been used to treat coronavirus disease MESHD 2019 (COVID-19), but the efficacy remains uncertain. Objective: To explore potential signals of efficacy of COVID-19 convalescent plasma SERO. Design: Open-label, Expanded Access Program (EAP) for the treatment of COVID-19 patients with human convalescent plasma SERO. Setting: Multicenter, including 2,807 acute care facilities in the US and territories. Participants: Adult TRANS participants enrolled and transfused under the purview of the US Convalescent Plasma SERO EAP program between April 4 and July 4, 2020 who were hospitalized with (or at risk of) severe or life threatening acute COVID-19 respiratory syndrome MESHD. Intervention: Transfusion of at least one unit of human COVID-19 convalescent plasma SERO using standard transfusion guidelines at any time during hospitalization. Convalescent plasma SERO was donated by recently-recovered COVID-19 survivors, and the antibody SERO levels in the units collected were unknown at the time of transfusion. Main Outcomes and Measures: Seven and thirty-day mortality. Results: The 35,322 transfused patients had heterogeneous demographic and clinical characteristics. This cohort included a high proportion of critically-ill MESHD patients, with 52.3% in the intensive care unit (ICU) and 27.5% receiving mechanical ventilation at the time of plasma SERO transfusion. The seven-day mortality rate was 8.7% [95% CI 8.3%-9.2%] in patients transfused within 3 days of COVID-19 diagnosis but 11.9% [11.4%-12.2%] in patients transfused 4 or more days after diagnosis (p<0.001). Similar findings were observed in 30-day mortality (21.6% vs. 26.7%, p<0.0001). Importantly, a gradient of mortality was seen in relation to IgG antibody SERO levels in the transfused plasma SERO. For patients who received high IgG plasma SERO (>18.45 S/Co), seven-day mortality was 8.9% (6.8%, 11.7%); for recipients of medium IgG plasma SERO (4.62 to 18.45 S/Co) mortality was 11.6% (10.3%, 13.1%); and for recipients of low IgG plasma SERO (<4.62 S/Co) mortality was 13.7% (11.1%, 16.8%) (p=0.048). This unadjusted dose-response relationship with IgG was also observed in thirty-day mortality (p=0.021). The pooled relative risk of mortality among patients transfused with high antibody SERO level plasma SERO units was 0.65 [0.47-0.92] for 7 days and 0.77 [0.63-0.94] for 30 days compared to low antibody SERO level plasma SERO units. Conclusions and Relevance: The relationships between reduced mortality and both earlier time to transfusion and higher antibody SERO levels provide signatures of efficacy for convalescent plasma SERO in the treatment of hospitalized COVID-19 patients. This information may be informative for the treatment of COVID-19 and design of randomized clinical trials involving convalescent plasma SERO. Trial Registration: ClinicalTrials.gov Identifier: NCT04338360

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MeSH Disease
Human Phenotype
Transmission
Seroprevalence


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