ABSTRACT
INTRODUCTION: Spain is the country with the highest number of health care workers affected by coronavirus disease 2019 (COVID-19) in the world. The aim of this study was to describe the epidemiology of severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) infection in health care worker (HCW) at the Gómez Ulla Military Hospital (HCDGU). MATERIALS AND METHODS: A case-control study was conducted during the first outbreak of COVID 19 at GUMH. The study was extended to the total number of HCW in the hospital who met the inclusion criteria. Health care worker of the HCDGU were civilian and military personnel that included nursing and medicine students of Spanish Military Academy, medicine specialty residents, and nursing residents of Medical Surgical Specialty in Operations (EMQO). A questionnaire of 33 items was prepared. The questionnaire was sent by e-mail to the entire population of study. With this questionnaire personnel were classified into sick (cases) or healthy. RESULTS AND CONCLUSIONS: One hundred fifty professionals answered the questionnaire. Cases were defined as those who tested positive in the diagnostic tests (n = 28, 20.7%) and no cases were those who tested negative (n = 107, 79.3%). Therefore, the percentage of SARS-CoV-2 in the GUMH was 20.7%. Of the total number of cases, 64.3% were men (P < .05), with a mean age of 47.1 years (SD 13.3), a mean BMI of 25.3 (SD 3.8), and 48.2% being overweight. Of the total cases, 59.3% had "A" blood group type and 69.2% were Rh positive. 50% were physicians, 32.1% were nurses, and 17.9% were auxiliary nurses (P < .05). Cases and controls with vitamin D deficiency and who took supplements had a lower risk of suffering COVID-19, with significant differences. Fever, cough, and diarrhea were found in at least 50% of the samples with significant differences.
ABSTRACT
Several works have proposed predictive models of the SEIRD (Susceptible, Exposed, Infected, Recovered, and Dead) variables to characterize the pandemic of COVID-19. One of the challenges of these models is to be able to follow the dynamics of the disease to make more precise predictions. In this paper, we propose an approach based on incremental learning to build predictive models of the SEIRD variables for the COVID-19 pandemic. Our incremental learning approach is a dynamic ensemble method based on a bagging scheme that allows the addition of new models or the updating of incremental models. The article proposes an incremental learning architecture composed of two components. The first component carries out an analysis of the interdependencies of the SEIRD variables and the second component is an incremental learning model that builds/updates the predictive models. The paper analyses the quality of the predictive models of our incremental learning approach using data of the COVID-19 from Colombia, and shows interesting results about the predictions of the SEIRD variables. These results are compared with an incremental learning approach based on random forests.
ABSTRACT
COVID-19 pandemic shifted the conventional working paradigms, forcing an accelerated adaptability to remote working, ensuring the wellbeing of the employees without sacrificing the effectiveness, in compliance to 100% HSE. To overcome this challenge, Drilling Real Time Operations Center (RTOC) transformed the conventional Monitoring Onsite Hub into a full virtual collaborative remote center operated from each individual's place. This paper describes how RTOC successfully, continued to support drilling operations off-site through secure portal during work-from-home period. RTOC ensured to have the sufficient connectivity resources and security protocols to access the IT company environment and execute the tasks at the same productivity level, as operating from the hub. The platform design involved virtual machine remoting in an integrated communication environment, in synergy with the conventional ways of communication. Several data access points were developed to ensure an unstoppable link between operational teams and the data deliverables. To grantee productivity, KPIs were established and closely monitored, e.g. active rigs count, connectivity issues, software support, real-time drilling performance reporting, engineering computations, with continuous quality audits. Despite several challenges at start due to change in the nature of the work, RTOC successfully overcame the difficulties by having proper procedures and infrastructure in place. The virtual collaborative environment allowed the team to operate the center remotely and meet the targets for deliverables. Defining a clear communication protocol created efficiency when addressing data aggregation problems. As a result, RTOC was able to maintain the resolution time for data aggregation issues and continue to produce drilling performance reports within time. RTOC launched a mobile application for drilling real-time monitoring to support user mobility prior to the mandate of work-from-home policy. RTOC continued to support drilling operations during work-from-home period by providing real-time computations for drilling operations, doing real-time interactions for drilling events and introducing data analytics platform for users to analyze drilling performance. In summary, systematic implementation of the workflows and following clear chain of command have proven to be effective in ensuring business continuity of RTOC. Building trust and respect helped boost the morale and productivity of the team while ensuring their safety and wellbeing. The pandemic has been, indeed, a tough period for the world but the shift of working lifestyle was indeed a unique experience. It broadened the horizon for RTOC to develop advanced collaboration tools and upgrade the infrastructure to be future-ready for higher mobility. This novelty can also be adopted as standard procedure for Emergency Response Plan. © Copyright 2021, Society of Petroleum Engineers