Notes

'Whole Organism', Systems The field of biology, as well as Top-Down Requirements regarding Analyzing Situations for that Origins involving Living.
pacity appears insufficient, highlighting the need for rapid capacity expansion.Implications of all the available evidence MCMA officials should prioritize rapid hospital capacity expansion. MCMA's ability to reopen schools in mid-January 2021 depends on sustaining social distancing and that contacts during the end-of-year holiday were well controlled.
The start of 2021 will be marked by a global vaccination campaign against the novel coronavirus SARS-CoV-2. Formulating an optimal distribution strategy under social and economic constraints is challenging. Optimal distribution is additionally constrained by the potential emergence of vaccine resistance. Analogous to chronic low-dose antibiotic exposure, recently inoculated individuals who are not yet immune play an outsized role in the emergence of resistance. Classical epidemiological modelling is well suited to explore how the behavior of the inoculated population impacts the total number of infections over the entirety of an epidemic.

A deterministic model of epidemic evolution is analyzed, with 7 compartments defined by their relationship to the emergence of vaccine-resistant mutants and representing three susceptible populations, three infected populations, and one recovered population. This minimally computationally intensive design enables simulation of epidemics across a broad parameter space. Ththat optimization of the vaccination rate and limiting post-vaccination contacts can affect the course of an epidemic. Given the relatively short window between inoculation and the acquisition of immunity, these results might merit consideration for an immediate, practical public health response.Electronic Health Records (EHR) are not designed for population-based research, but they provide access to longitudinal health information for many individuals. Many statistical methods have been proposed to account for selection bias, missing data, phenotyping errors, or other problems that arise in EHR data analysis. However, addressing multiple sources of bias simultaneously is challenging. Recently, we developed a methodological framework (R package, SAMBA ) for jointly handling both selection bias and phenotype misclassification in the EHR setting that leverages external data sources. These methods assume factors related to selection and misclassification are fully observed, but these factors may be poorly understood and partially observed in practice. As a follow-up to the methodological work, we explore how these methods perform for three real-world case studies. EX 527 research buy In all three examples, we use individual patient-level data collected through the University of Michigan Health System and various external population-based data sources. In case study (a), we explore the impact of these methods on estimated associations between gender and cancer diagnosis. In case study (b), we compare corrected associations between previously identified genetic loci and age-related macular degeneration with gold standard external estimates. In case study (c), we evaluate these methods for modeling the association of COVID-19 outcomes and potential risk factors. These case studies illustrate how to utilize diverse auxiliary information to achieve less biased inference in EHR-based research.
To characterize the SARS-CoV-2 testing cascade and associated barriers in three US states.

We recruited participants from Florida, Illinois, and Maryland (∼1000/state) for an online survey September 16 - October 15, 2020. The survey covered demographics, COVID-19 symptoms, and experiences around SARS-CoV-2 PCR testing in the prior 2 weeks. Logistic regression was used to analyze associations with outcomes of interest.

Overall, 316 (10%) of 3,058 respondents wanted/needed a test in the two weeks prior to the survey. Of these, 166 (53%) were able to get tested and 156 (94%) received results; 53% waited ≥ 8 days to get results from when they wanted/needed a test. There were no significant differences by state. Among those wanting/needing a test, getting tested was significantly less common among men (aOR 0.46) and those reporting black race (aOR 0.53) and more common in those reporting recent travel (aOR 3.35).

There is an urgent need for a national communication strategy on who should get tested and where one can get tested. Additionally, measures need to be taken to improve access and reduce turn-around-time.
There is an urgent need for a national communication strategy on who should get tested and where one can get tested. Additionally, measures need to be taken to improve access and reduce turn-around-time.
The COVID-19 pandemic has highlighted the importance of rapid dissemination of scientific and medical discovery. Social media (SoMe) has become an invaluable platform in science and medicine. This study analyzed activity of SoMe (Twitter), preprints, and publications related to COVID-19 and gastroenterology (GI) during the COVID-19 pandemic.

Data from Twitter, preprint servers and PubMed was collected and analyzed from December 2019 through May 2020. Global and regional geographic and gastrointestinal organ specific social media trends were compared to preprint and publication activity; any associations were identified.

Over the 6-month period, there were 73,079 tweets from 44,609 users, 7,164 publications, and 4,702 preprints. Twitter activity peaked during March while preprints and publications peaked in April 2020. Strong correlations were identified between Twitter and both preprints and publications activity (p<0.001 for both). While COVID-19 data across the 3 platforms concentrated on pulmonology/critical care, the majority of GI tweets pertained to pancreatology, most publications focused on hepatology, and most preprints covered hepatology and luminal GI (LGI). There were significant associations between Twitter activity and research for all GI subfields (p=0.009 for LGI, p=0.006 for hepatology and IBD, p=0.007 for endoscopy), except pancreatology (p=0.2). Twitter activity was highest in the US (7,331 tweets) whereas PubMed activity was highest in China (1,768 publications).

The COVID-19 pandemic has highlighted the utility of SoMe as a vehicle for disseminating scientific information during a public health crisis. Scientists and clinicians should consider the use of SoMe in augmenting public awareness of their scholarly pursuits.
The COVID-19 pandemic has highlighted the utility of SoMe as a vehicle for disseminating scientific information during a public health crisis. Scientists and clinicians should consider the use of SoMe in augmenting public awareness of their scholarly pursuits.
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