Wulff Mygind (trunkstorm4)

We critically discuss questions that these models can and cannot answer and showcase controversial decisions around the early outbreak dynamics, outbreak control, and exit strategies. We anticipate that this summary will stimulate discussion within the modeling community and help provide guidelines for robust mathematical models to understand and manage the COVID-19 pandemic. EML webinar speakers, videos, and overviews are updated at https//imechanica.org/node/24098.In 2018 prion disease was detected in camels at an abattoir in Algeria for the first time. The emergence of prion disease in this species made it prudent to assess the probability of entry of the pathogen into the United Kingdom (UK) from this region. Potentially contaminated products were identified as evidenced by other prion diseases. The aggregated probability of entry of the pathogen was estimated as very high and high for legal milk and cheese imports respectively and very high, high and high for illegal meat, milk and cheese products respectively. This aggregated probability represents a qualitative assessment of the probability of one or more entry events per year into the UK; it gives no indication of the number of entry events per year. The uncertainty associated with these estimates was high due to the unknown variation in prevalence of infection in camels and an uncertain number and type of illegal products entering the UK. Potential public health implications of this pathogen are unknown although there is currently no evidence of zoonotic transmission of prion diseases other than bovine spongiform encephalopathy to humans.COVID-2019 has been recognized as a global threat, and several studies are being conducted in order to contribute to the fight and prevention of this pandemic. This work presents a scholarly production dataset focused on COVID-19, providing an overview of scientific research activities, making it possible to identify countries, scientists and research groups most active in this task force to combat the coronavirus disease. Omecamtiv mecarbil ic50 The dataset is composed of 40,212 records of articles' metadata collected from Scopus, PubMed, arXiv and bioRxiv databases from January 2019 to July 2020. Those data were extracted by using the techniques of Python Web Scraping and preprocessed with Pandas Data Wrangling. In addition, the pipeline to preprocess and generate the dataset are versioned with the Data Version Control tool (DVC) and are thus easily reproducible and auditable.The SARS-CoV-2 is a novel strain of coronavirus which is ravaging many countries, and this has become a global public health concern. With the increasing number of COVID-19 confirmed cases and deaths in Nigeria, the pandemic has led to massive public reactions. This data attempted to evaluate the knowledge, impacts, and government intervention during the pandemic. An online survey was conducted using a questionnaire shared via social media using a Snowball sampling technique. The data were analyzed using descriptive statistics and analysis of variance (ANOVA). A total of 387 responses was received. Results show that a significant number of respondents had adequate knowledge about COVID-19 modes of transmission, symptoms, and preventive measures. Respondents maintain personal hygiene as 67% wash their hands with soap. The pandemic has caused worry (65%), anxiety (42%), panic (35%), and depression (16%) among respondents, even as government intervention is seen as inadequate by 70%. There is a need for mental health support and increased information campaigns about COVID-19.The COVID-19 pandemic has produced an unprecedented change in the educational system worldwide. Besides the economic and social impacts, there is a dilemma of accepting the new educational system "e-learning" by students within educational institutions. In particular, universities students have to handle several kinds of environmental, electronic and mental struggles due to COVID-19. To ca