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Register a new userSmart Healthcare for Diabetes: A COVID-19 Perspective
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Diabetes is considered as an critical comorbidity linked with the latest coronavirus disease 2019 (COVID-19) which spreads through Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-Cov-2). The diabetic patients have higher threat of infection from novel corona virus. Depending on the region in the globe, 20% to 50% of patients infected with COVID-19 pandemic had diabetes. The current article discussed the risk associated with diabetic patients and also recommendation for controlling diabetes during this pandemic situation. The article also discusses the case study of COVID-19 at various regions around the globe and the preventive actions taken by various countries to control the effect from the virus. The article presents several smart healthcare solutions for the diabetes patients to have glucose insulin control for the protection against COVID-19.
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This note describes a simple score to indicate the effectiveness of mitigation against infections of COVID-19 as observed by new case counts. The score includes normalization, making comparisons across jurisdictions possible. The smoothing employed provides robustness in the face of reporting vagaries while retaining salient features of evolution, enabling a clearer picture for decision makers and the public.
In this paper, we provide guidance on how standard safety analyses and reporting of clinical trial safety data may need to be modified, given the potential impact of the COVID-19 pandemic. The impact could include missed visits, alternative methods for assessments (such as virtual visits), alternative locations for assessments (such as local labs), and study drug interruptions. We focus on safety planning for Phase 2-4 clinical trials and integrated summaries for submissions. Starting from the recommended safety analyses proposed in white papers and a workshop, created as part of an FDA/PHUSE collaboration (PHUSE 2013, 2015, 2017, 2019), we assess what modifications might be needed. Impact from COVID-19 will likely affect treatment arms equally, so analyses of adverse events from controlled data can, to a large extent, remain unchanged. However, interpretation of summaries from uncontrolled data (summaries that include open-label extension data) will require even more caution than usual. Special consideration will be needed for safety topics of interest, especially events expected to have a higher incidence due to a COVID-19 infection or due to quarantine or travel restrictions (e.g., depression). Analyses of laboratory measurements may need to be modified to account for the combination of measurements from local and central laboratories.
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a variable clinical presentation that ranges from asymptomatic, to severe disease with cytokine storm. The mortality rates also differ across the globe, ranging from 0.5-13%. This variation is likely due to both pathogen and host factors. Host factors may include genetic differences in the immune response genes as well as variation in HLA and KIR allotypes. To better understand what impact these genetic variants in immune response genes may have in the differences observed in the immune response to SARS-CoV-2, a quantitative analysis of a dynamical systems model that considers both, the magnitude of viral growth, and the subsequent innate and adaptive response required to achieve control of infection is considered. Based on this broad quantitative framework it may be posited that the spectrum of symptomatic to severely symptomatic presentations of COVID19 represents the balance between innate and adaptive immune responses. In asymptomatic patients, prompt and adequate adaptive immune response quells infection, whereas in those with severe symptoms a slower inadequate adaptive response leads to a runaway cytokine cascade fueled by ongoing viral replication. Polymorphisms in the various components of the innate and adaptive immune response may cause altered immune response kinetics that would result in variable severity of illness. Understanding how this genetic variation may alter the response to SARS-CoV-2 infection is critical to develop successful treatment strategies.
How will the coronavirus disease 2019 (COVID-19) pandemic develop in the coming months and years? Based on an expert survey, we examine key aspects that are likely to influence COVID-19 in Europe. The future challenges and developments will strongly depend on the progress of national and global vaccination programs, the emergence and spread of variants of concern, and public responses to nonpharmaceutical interventions (NPIs). In the short term, many people are still unvaccinated, VOCs continue to emerge and spread, and mobility and population mixing is expected to increase over the summer. Therefore, policies that lift restrictions too much and too early risk another damaging wave. This challenge remains despite the reduced opportunities for transmission due to vaccination progress and reduced indoor mixing in the summer. In autumn 2021, increased indoor activity might accelerate the spread again, but a necessary reintroduction of NPIs might be too slow. The incidence may strongly rise again, possibly filling intensive care units, if vaccination levels are not high enough. A moderate, adaptive level of NPIs will thus remain necessary. These epidemiological aspects are put into perspective with the economic, social, and health-related consequences and thereby provide a holistic perspective on the future of COVID-19.
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus caused the novel coronavirus disease-2019 (COVID-19) affecting the whole world. Like SARS-CoV and MERS-CoV, SARS-CoV-2 are thought to originate in bats and then spread to humans through intermediate hosts. Identifying intermediate host species is critical to understanding the evolution and transmission mechanisms of COVID-19. However, determining which animals are intermediate hosts remains a key challenge. Virus host-genome similarity (HGS) is an important factor that reflects the adaptability of virus to host. SARS-CoV-2 may retain beneficial mutations to increase HGS and evade the host immune system. This study investigated the HGSs between 399 SARS-CoV-2 strains and 10 hosts of different species, including bat, mouse, cat, swine, snake, dog, pangolin, chicken, human and monkey. The results showed that the HGS between SARS-CoV-2 and bat was the highest, followed by mouse and cat. Human and monkey had the lowest HGS values. In terms of genetic similarity, mouse and monkey are halfway between bat and human. Moreover, given that COVID-19 outbreaks tend to be associated with live poultry and seafood markets, mouse and cat are more likely sources of infection in these places. However, more experimental data are needed to confirm whether mouse and cat are true intermediate hosts. These findings suggest that animals closely related to human life, especially those with high HGS, need to be closely monitored.
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