COVID最新文献

{"title":"Public Decision Policy for Controlling COVID-19 Outbreaks Using Control System Engineering","authors":"H. Patiño, J. Pucheta, Cristian Rodríguez Rivero, Santiago Tosetti","doi":"10.3390/covid4010005","DOIUrl":"https://doi.org/10.3390/covid4010005","url":null,"abstract":"This work is a response to the appeal of various international health organizations and the Automatic Control Community for collaboration in addressing Coronavirus/COVID-19 challenges during the initial stages of the pandemic. Specifically, this study presents scientific evidence supporting the efficacy of three primary non-pharmacological strategies for pandemic mitigation. We propose a control system to aid in formulating a public decision policy aimed at managing the spread of COVID-19 caused by the SARS-CoV-2 virus, commonly known as coronavirus. The primary objective is to prevent overwhelming healthcare systems by averting the saturation of intensive care units (ICUs). In the context of COVID-19, understanding the peak infection rate and its time delay is crucial for preparing healthcare infrastructure and ensuring an adequate supply of intensive care units equipped with automatic ventilators. While it is widely recognized that public policies encompassing confinement and social distancing can flatten the epidemiological curve and provide time to bolster healthcare resources, there is a dearth of studies examining this pivotal issue from the perspective of control system theory. In this study, we introduce a control system founded on three prevailing non-pharmacological tools for epidemic and pandemic mitigation: social distancing, confinement, and population-wide testing and isolation in regions experiencing community transmission. Our analysis and control system design rely on the susceptible-exposed–infected–recovered–deceased (SEIRD) mathematical model, which describes the temporal dynamics of a pandemic, tailored in this research to account for the temporal and spatial characteristics of SARS-CoV-2 behavior. This model incorporates the influence of conducting tests with subsequent population isolation. An On–off control strategy is analyzed, and a proportional–integral–derivative (PID) controller is proposed to generate a sequence of public policy decisions. The proposed control system employs the required number of critical beds and ICUs as feedback signals and compares these with the available bed capacity to generate an error signal, which is utilized as input for the PID controller. The control actions outlined involve five phases of “Social Distancing and Confinement” (SD&C) to be implemented by governmental authorities. Consequently, the control system generates a policy sequence for SD&C, with applications occurring on a weekly or biweekly basis. The simulation results underscore the favorable impact of these three mitigation strategies against the coronavirus, illustrating their efficacy in controlling the outbreak and thereby mitigating the risk of healthcare system collapse.","PeriodicalId":72714,"journal":{"name":"COVID","volume":"49 23","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139447231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Impact of Surgical Delay: A Single Institutional Experience at the Epicenter of the COVID Pandemic Treatment Delays in Women with Endometrial Cancer and Endometrial Intraepithelial Hyperplasia","authors":"Kieran Seay, Arielle H. Katcher, Maia Hare, Nina Kohn, Hannah Juhel, Gary Goldberg, M. Frimer","doi":"10.3390/covid4010004","DOIUrl":"https://doi.org/10.3390/covid4010004","url":null,"abstract":"The spread of COVID-19 led to a lockdown in New York in March of 2020. Nonemergent surgeries were postponed, including oncologic procedures. The backlog of surgeries was addressed starting May 2020. Our goal was to examine the change in waiting times for endometrial cancer surgeries during the COVID-19 pandemic in our institution. Data on surgery incidence and waiting time was gathered for patients diagnosed with endometrial intraepithelial neoplasia and endometrial cancer. The association between days from diagnosis to surgery was adjusted for age, obesity, presence of comorbid conditions, race, smoking history and diagnosis and was examined using a general linear model. A total of 190 patients were identified for this retrospective study. Five subjects were missing information on race and were excluded from all analyses, resulting in 185 subjects in the final analyses. Mean waiting time during COVID-19 was 70.9 days (95%CI 55.0, 91.3), compared to 49.3 (95%CI 49.8, 63.8) days during the reference period. No significant associations were seen between the time and any of the clinical or demographic factors.","PeriodicalId":72714,"journal":{"name":"COVID","volume":"28 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139148220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genomic Surveillance of SARS-CoV-2 Sequence Variants at Universities in Southwest Idaho","authors":"Jennifer R. Chase, Laura Bond, Daniel J. Vail, Milan Sengthep, Adriana Rodriguez, Joe Christianson, Stephanie F. Hudon, Julia Thom Oxford","doi":"10.3390/covid4010003","DOIUrl":"https://doi.org/10.3390/covid4010003","url":null,"abstract":"Although the impact of the SARS-CoV-2 pandemic on major metropolitan areas is broadly reported and readily available, regions with lower populations and more remote areas in the United States are understudied. The objective of this study is to determine the progression of SARS-CoV-2 sequence variants in a frontier and remote intermountain west state among university-associated communities. This study was conducted at two intermountain west universities from 2020 to 2022. Positive SARS-CoV-2 samples were confirmed by quantitative real-time reverse transcription-polymerase chain reaction and variants were identified by the next-generation sequencing of viral genomes. Positive results were obtained for 5355 samples, representing a positivity rate of 3.5% overall. The median age was 22 years. Viral genomic sequence data were analyzed for 1717 samples and phylogeny was presented. Associations between viral variants, age, sex, and reported symptoms among 1522 samples indicated a significant association between age and the Delta variant (B 1.167.2), consistent with the findings for other regions. An outbreak event of AY122 was detected August–October 2021. A 2-month delay was observed with respect to the timing of the first documented viral infection within this region compared to major metropolitan regions of the US.","PeriodicalId":72714,"journal":{"name":"COVID","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139157620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association between Priority Conditions and Access to Care, Treatment of an Ongoing Condition, and Ability to Obtain Prescription Medications among Medicare Beneficiaries during the COVID-19 Pandemic","authors":"Matthew C. Dickson, Grant H. Skrepnek","doi":"10.3390/covid4010002","DOIUrl":"https://doi.org/10.3390/covid4010002","url":null,"abstract":"Several comorbid conditions have been observed to be associated with an increased risk of poor outcomes following a diagnosis of COVID-19. The purpose of this investigation was to assess associations between Centers for Medicare and Medicaid Services (CMS) designated priority conditions and an inability to access care, treat ongoing conditions, and obtain prescription medications among Medicare beneficiaries in the United States during the COVID-19 pandemic. Nationally representative CMS Medicare Current Beneficiary Survey (MCBS) COVID-19 Supplement Public Use Files (PUF) were analyzed via bivariable, binomial generalized linear models across three time periods: (1) Summer 2020; (2) Fall 2020; and (3) Winter 2021. Across an estimated 55.3–57.4 million Medicare beneficiaries, approximately one-fifth reported an inability to access at least one type of care at the onset of the pandemic. Significantly worse odds of an ability to get care across various time periods was observed among several priority conditions including immune disorders, cancer, depression, osteoporosis, diabetes, arthritis, and numerous cardiovascular and pulmonary conditions. Among those reporting an inability to access care, approximately one-third involved treatment of an ongoing condition, and under one-tenth involved prescription medications. To identify modifiable risk factors and to develop active interventions, future work should continue to assess the complex associations between outcomes, access to care, comorbidities, evolving healthcare infrastructures, computerization, and various public health initiatives.","PeriodicalId":72714,"journal":{"name":"COVID","volume":"16 36","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139168997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Video Games and the COVID-19 Pandemic: Virtual Worlds as New Playgrounds and Training Spaces","authors":"Xosé Somoza Medina, Marta Somoza Medina","doi":"10.3390/covid4010001","DOIUrl":"https://doi.org/10.3390/covid4010001","url":null,"abstract":"The COVID-19 pandemic forced the authorities to take an unprecedented measure in history: the house confinement of millions of people worldwide. Video games, especially open-world video games (OWVGs), became meeting spaces, a digital places to play, chat, learn and socialize due to the context of the health crisis, respecting the rules of social distancing. This article analyses the role of video games and, more specifically, OWVGs, as playgrounds and training spaces during the pandemic. Statistical data and analyses carried out by consulting companies and civil associations show the definitive insertion of these video games in our routine and social relations. The challenge is to take advantage of the skills and abilities that these video games develop within a new framework of individual and community learning. The conclusions of the research show that the virtual worlds of video games are for the new digital society, safe and comfortable meeting spaces, and that since the confinement, these digital places have greatly expanded their reach, previously only limited to the gamer community.","PeriodicalId":72714,"journal":{"name":"COVID","volume":" 25","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138963324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analytical Solution of the Susceptible-Infected-Recovered/Removed Model for the Not-Too-Late Temporal Evolution of Epidemics for General Time-Dependent Recovery and Infection Rates","authors":"Reinhard Schlickeiser, Martin Kröger","doi":"10.3390/covid3120123","DOIUrl":"https://doi.org/10.3390/covid3120123","url":null,"abstract":"The dynamical equations of the susceptible-infected-recovered/removed (SIR) epidemics model play an important role in predicting and/or analyzing the temporal evolution of epidemic outbreaks. Crucial input quantities are the time-dependent infection (a(t)) and recovery (μ(t)) rates regulating the transitions between the compartments S→I and I→R, respectively. Accurate analytical approximations for the temporal dependence of the rate of new infections J˚(t)=a(t)S(t)I(t) and the corresponding cumulative fraction of new infections J(t)=J(t0)+∫t0tdxJ˚(x) are available in the literature for either stationary infection and recovery rates or for a stationary value of the ratio k(t)=μ(t)/a(t). Here, a new and original accurate analytical approximation is derived for general, arbitrary, and different temporal dependencies of the infection and recovery rates, which is valid for not-too-late times after the start of the infection when the cumulative fraction J(t)≪1 is much less than unity. The comparison of the analytical approximation with the exact numerical solution of the SIR equations for different illustrative examples proves the accuracy of the analytical approach.","PeriodicalId":72714,"journal":{"name":"COVID","volume":"15 s1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138967541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Two Sides of the COVID-19 Pandemic","authors":"Ravinder Kumar, Vartika Srivastava, K. Nand","doi":"10.3390/covid3120121","DOIUrl":"https://doi.org/10.3390/covid3120121","url":null,"abstract":"On 5 May 2023, the World Health Organization (WHO) officially declared the end of the coronavirus disease-19 (or COVID-19) pandemic. Even before the official announcement from the WHO, signs of recovery from the pandemic started appearing, especially after rapid worldwide vaccination. As society is getting back to its usual with each passing day, with the increasing socio-economic activities, discussion of the negative and positive outcomes of the COVID-19 pandemic remain the predominant topic of debate. Through this review, we discuss the bright side of the pandemic without undermining the pain and suffering everyone has gone through in this pandemic. The review also examined the painful side of the pandemic. Therefore, this review can be looked at as a comparison between this pandemic’s positive and negative effects. The review discussed aspects ranging from technological development, including mRNA-based vaccines, artificial intelligence-based screening, and telemedicine, to social behavior, from individual to global and from health to the environment. The review also examined the areas needing more attention for managing future pandemics. The review also highlighted what should be followed or continued for our preparedness for any possible pandemic. Toward the end, we also discussed how this pandemic has better prepared the world for future pandemics, as predicted by experts.","PeriodicalId":72714,"journal":{"name":"COVID","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138602979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analyzing County-Level COVID-19 Vaccination Rates in Texas: A New Lindley Regression Model","authors":"Nicollas S. S. da Costa, Maria do Carmo S. de Lima, G. Cordeiro","doi":"10.3390/covid3120122","DOIUrl":"https://doi.org/10.3390/covid3120122","url":null,"abstract":"This work aims to study the factors that explain the COVID-19 vaccination rate through a generalized odd log-logistic Lindley regression model with a shape systematic component. To accomplish this, a dataset of the vaccination rate of 254 counties in the state of Texas, US, was used, and simulations were performed to investigate the accuracy of the maximum likelihood estimators in the proposed regression model. The mathematical properties investigated provide important information about the characteristics of the distribution. Diagnostic analysis and deviance residuals are addressed to examine the fit of the model. The proposed model shows effectiveness in identifying the key variables of COVID-19 vaccination rates at the county level, which can contribute to improving vaccination campaigns. Moreover, the findings corroborate with prior studies, and the new distribution is a suitable alternative model for future works on different datasets.","PeriodicalId":72714,"journal":{"name":"COVID","volume":"1 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138603963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Incorporating Virtual Problem-Based Learning in Instrumental Chemistry during the COVID-19 Pandemic","authors":"Xiaoping Li, Ying Guo, Simon M. Mwongela, Michael Kirberger","doi":"10.3390/covid3120120","DOIUrl":"https://doi.org/10.3390/covid3120120","url":null,"abstract":"The COVID-19 pandemic has presented substantial challenges to higher education, leading to economic loss and disruptions in STEM courses. This study addresses these issues through the successful implementation of a problem-based learning research project within the Instrumental Chemistry course at Georgia Gwinnett College (GGC). Focused on instrumental chemistry, the project spans various categories, requiring students to propose solutions to real-case scenarios using specific analytical instruments. Despite the shift to a hybrid teaching modality, students exhibited commendable preparation and investigation skills, as demonstrated by their projects. Assessment data, including a student survey and written report evaluations, underscore significant skill improvements in literature survey, instrument selection, experimental design, and data analysis. This problem-based learning approach not only mitigated the disruptions caused by the pandemic but also fostered enhanced capabilities and motivation among students. The study’s findings contribute insights into the adaptability and effectiveness of problem-based learning in analytical chemistry education within a hybrid teaching framework, offering valuable considerations for future educational strategies in STEM disciplines and beyond.","PeriodicalId":72714,"journal":{"name":"COVID","volume":"129 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139212777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Eating Habits and Mental Health of College Students in Japan during the COVID-19 Pandemic","authors":"Tomoko Imoto, Yuichiro Hoshino, Yoshiyuki Sato, Yusuke Ohsaki, Hitoshi Shirakawa","doi":"10.3390/covid3120119","DOIUrl":"https://doi.org/10.3390/covid3120119","url":null,"abstract":"While the relationship between eating habits and mental health has been widely studied, there is limited research focusing on college students during emergency situations such as pandemics. We conducted an online questionnaire survey to address this gap. Clustering analysis was applied to identify students’ eating habits, which are possibly more complex than traditional eating habits. Based on the identified eating habits, the students were separated into five groups. We evaluated the relationship between eating habits and mental health in these five groups using University Personality Inventory scores. Based on the results, the largest group—corresponding to slightly less than half of the participants—had the highest vegetable intake and mental health levels. This aligns with findings from numerous prior studies. However, our novel discovery was the presence of another group within those with higher vegetable intake, who had lower levels of mental health. Conversely, a group with lower vegetable intake had higher levels of mental health; remarkably, students in this group frequently consumed soft drinks, suggesting that, during the COVID-19 emergency, indulgent food and drinks may have played a role in enhancing mental health.","PeriodicalId":72714,"journal":{"name":"COVID","volume":"355 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139235472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}