453 Matching Annotations
  1. Last 7 days
    1. Nissim Mannathukkaren നിസ്സിം മണ്ണത്തൂക്കാരൻ. (2021, April 8). ‘The hand of God’—Nurses trying to comfort isolated patients in a Brazilian Covid isolation ward. Two disposable gloves tied, full of hot water, simulating impossible human contact. Salute to the front liners and a stark reminder of the grim situation our world is in!@sadiquiz https://t.co/eldzkT4JHa [Tweet]. @nmannathukkaren. https://twitter.com/nmannathukkaren/status/1380129214259720202

    2. 2021-04-08

    3. ‘The hand of God’ — nurses trying to comfort isolated patients in a Brazilian Covid isolation ward. Two disposable gloves tied, full of hot water, simulating impossible human contact. Salute to the front liners and a stark reminder of the grim situation our world is in!@sadiquiz
  2. Mar 2021
    1. You cannot practice public health without engaging in politics. (2021, March 29). The BMJ. https://blogs.bmj.com/bmj/2021/03/29/you-cannot-practice-public-health-without-engaging-in-politics/

    2. 2021-03-29

    3. We are living in extraordinary times. 2021 brings the covid-19 mortality to >2 million deaths worldwide and to >100,000 deaths in the UK. Steely eyed scientists are finding themselves the topic of political debate, independent government advisors are accused of succumbing to political pressures, and academics (particularly women) are subjected to vitriolic abuse on Twitter. 
    4. You cannot practice public health without engaging in politics
    1. Knowles, R., Mateen, B. A., & Yehudi, Y. (2021). We need to talk about the lack of investment in digital research infrastructure. Nature Computational Science, 1(3), 169–171. https://doi.org/10.1038/s43588-021-00048-5

    2. 10.1038/s43588-021-00048-5
    3. Research software infrastructure is critical for accelerating science, and yet, these digital public goods are often unsustainably funded. Solving this problem requires an appreciation of the intrinsic value of research software outputs, and greater investment of time and effort into effectively funding maintenance of software at scale.
    4. 2021-03-25

    5. We need to talk about the lack of investment in digital research infrastructure
    1. Nsoesie, E. O., Oladeji, O., Abah, A. S. A., & Ndeffo-Mbah, M. L. (2021). Forecasting influenza-like illness trends in Cameroon using Google Search Data. Scientific Reports, 11(1), 6713. https://doi.org/10.1038/s41598-021-85987-9

    2. 10.1038/s41598-021-85987-9
    3. Although acute respiratory infections are a leading cause of mortality in sub-Saharan Africa, surveillance of diseases such as influenza is mostly neglected. Evaluating the usefulness of influenza-like illness (ILI) surveillance systems and developing approaches for forecasting future trends is important for pandemic preparedness. We applied and compared a range of robust statistical and machine learning models including random forest (RF) regression, support vector machines (SVM) regression, multivariable linear regression and ARIMA models to forecast 2012 to 2018 trends of reported ILI cases in Cameroon, using Google searches for influenza symptoms, treatments, natural or traditional remedies as well as, infectious diseases with a high burden (i.e., AIDS, malaria, tuberculosis). The R2 and RMSE (Root Mean Squared Error) were statistically similar across most of the methods, however, RF and SVM had the highest average R2 (0.78 and 0.88, respectively) for predicting ILI per 100,000 persons at the country level. This study demonstrates the need for developing contextualized approaches when using digital data for disease surveillance and the usefulness of search data for monitoring ILI in sub-Saharan African countries.
    4. 2021-03-24

    5. Forecasting influenza-like illness trends in Cameroon using Google Search Data
    1. Iversen, P. L., & Bavari, S. (2021). Is there space for a three-dose vaccine to fight the spread of SARS-CoV-2? The Lancet Infectious Diseases, 0(0). https://doi.org/10.1016/S1473-3099(21)00149-3

    2. The ongoing responses to the COVID-19 pandemic have resulted in diverse vaccine-based solutions that are advancing our understanding of medical science.1WHODraft landscape and tracker of COVID-19 candidate vaccines.https://www.who.int/publications/m/item/draft-landscape-of-covid-19-candidate-vaccinesDate: March 1, 2021Date accessed: March 2, 2021Google Scholar Randomised, placebo-controlled clinical trials are providing a unique opportunity to compare the safety and immunogenicity of several different vaccine platforms, including vectored, DNA, inactivated virus, mRNA, and protein subunit vaccines. Strategic differences within each vaccine platform, such as dimer versus trimer protein subunits or modifications in protein design based on dynamic structural modelling, are providing deeper insights into the optimal vaccines of the future—a silver lining to the dark cloud of the COVID-19 pandemic.
    3. 2021-03-24

    4. 10.1016/S1473-3099(21)00149-3
    5. Is there space for a three-dose vaccine to fight the spread of SARS-CoV-2?
    1. Vaughan, A. (n.d.). Covid-19 vaccine hesitancy is declining as global roll-out ramps up. New Scientist. Retrieved 25 March 2021, from https://www.newscientist.com/article/mg24933273-700-covid-19-vaccine-hesitancy-is-declining-as-global-roll-out-ramps-up/

    2. WHEN Margaret Keenan became the first person to receive a covid-19 vaccine outside a trial last December, she was among the 7 in 10 people surveyed globally who said they would be willing to receive a dose. But the significant minority unwilling to have a vaccine led public health experts to worry about how such hesitancy might hamper efforts to achieve herd immunity.
    3. 2021-03-24

    4. Covid-19 vaccine hesitancy is declining as global roll-out ramps up
    1. Breznau, N., Rinke, E. M., Wuttke, A., Adem, M., Adriaans, J., Alvarez-Benjumea, A., Andersen, H. K., Auer, D., Azevedo, F., Bahnsen, O., Balzer, D., Bauer, G., Bauer, P. C., Baumann, M., Baute, S., Benoit, V., Bernauer, J., Berning, C., Berthold, A., … Nguyen, H. H. V. (2021). Observing Many Researchers using the Same Data and Hypothesis Reveals a Hidden Universe of Data Analysis. MetaArXiv. https://doi.org/10.31222/osf.io/cd5j9

    2. 2021-03-24

    3. 10.31222/osf.io/cd5j9
    4. Findings from 162 researchers in 73 teams testing the same hypothesis with the same data reveal a universe of unique analytical possibilities leading to a broad range of results and conclusions. Surprisingly, the outcome variance mostly cannot be explained by variations in researchers’ modeling decisions or prior beliefs. Each of the 1,261 test models submitted by the teams was ultimately a unique combination of data-analytical steps. Because the noise generated in this crowdsourced research mostly cannot be explained using myriad meta-analytic methods, we conclude that idiosyncratic researcher variability is a threat to the reliability of scientific findings. This highlights the complexity and ambiguity inherent in the scientific data analysis process that needs to be taken into account in future efforts to assess and improve the credibility of scientific work.
    5. Observing Many Researchers using the Same Data and Hypothesis Reveals a Hidden Universe of Data Analysis
    1. Machine learning models for diagnosing COVID-19 are not yet suitable for clinical use. (2021, March 15). University of Cambridge. https://www.cam.ac.uk/research/news/machine-learning-models-for-diagnosing-covid-19-are-not-yet-suitable-for-clinical-use

    2. 2021-03-15

    3. 10.1038/s42256-021-00307-0
    4. Systematic review finds that machine learning models for detecting and diagnosing COVID-19 from medical images have major flaws and biases, making them unsuitable for use in patients. However, researchers have suggested ways to remedy the problem.
    5. Machine learning models for diagnosing COVID-19 are not yet suitable for clinical use
    1. Betsch, C., Schmid, P., Heinemeier, D., Korn, L., Holtmann, C., & Böhm, R. (2018). Beyond confidence: Development of a measure assessing the 5C psychological antecedents of vaccination. PLOS ONE, 13(12), e0208601. https://doi.org/10.1371/journal.pone.0208601

    2. Monitoring the reasons why a considerable number of people do not receive recommended vaccinations allows identification of important trends over time, and designing and evaluating strategies to address vaccine hesitancy and increase vaccine uptake. Existing validated measures assessing vaccine hesitancy focus primarily on confidence in vaccines and the system that delivers them. However, empirical and theoretical work has stated that complacency (not perceiving diseases as high risk), constraints (structural and psychological barriers), calculation (engagement in extensive information searching), and aspects pertaining to collective responsibility (willingness to protect others) also play a role in explaining vaccination behavior. The objective was therefore to develop a validated measure of these 5C psychological antecedents of vaccination.
    3. 2018-12-07

    4. 10.1371/journal.pone.0208601
    5. Beyond confidence: Development of a measure assessing the 5C psychological antecedents of vaccination
    1. ReconfigBehSci. (2020, November 9). Second session now underway at the SciBeh workshop: Session 2: Interfacing with Policy How can the wider science community be policy-relevant? Speaking now: Alison Wright from UCL #scibeh2020 https://t.co/Gsr66BRGcJ [Tweet]. @SciBeh. https://twitter.com/SciBeh/status/1325750355309830145

    2. 2020-11-09

    3. Second session now underway at the SciBeh workshop: Session 2: Interfacing with Policy How can the wider science community be policy-relevant? speaking now: Alison Wright from UCL
    1. Dr Nisreen Alwan 🌻. (2021, January 18). Scientists don’t have total objectivity. We have beliefs, experiences & feelings that make us subjective & shape our interpretation of facts just like other humans. I trust the scientists who admit this more than the ones who pretend they’re above it. Best u can do is to be open. [Tweet]. @Dr2NisreenAlwan. https://twitter.com/Dr2NisreenAlwan/status/1351074354629668866

    1. ReconfigBehSci. (2020, November 9). Great talk by Chiara Varazzani from the OECD on the two speed systems of policy and ‘normal’ research and the challenge that poses to pandemic response #scibeh2020 https://t.co/Gsr66BRGcJ [Tweet]. @SciBeh. https://twitter.com/SciBeh/status/1325725690935832576

    2. 2020-11-09

    3. Great talk by Chiara Varazzani from the OECD on the two speed systems of policy and "normal" research and the challenge that poses to pandemic response
    1. 2020-11-09

    2. ReconfigBehSci. (2020, November 9). Videos and summary docs will be posted online to help those who missed the session get up to speed join us now for hackathon sessions (underway), and tomorrow, Day 2 https://t.co/Gsr66BRGcJ [Tweet]. @SciBeh. https://twitter.com/SciBeh/status/1325795290599858178

    3. videos and summary docs will be posted online to help those who missed the session get up to speed join us now for hackathon sessions (underway), and tomorrow, Day 2
    1. 2020-11-09

    2. ReconfigBehSci. (2020, November 9). final speaker in our ‘Open science and crisis knowledge management’ session: Michele Starnini on radically redesigning the peer review system #scibeh2020 https://t.co/Gsr66BRGcJ [Tweet]. @SciBeh. https://twitter.com/SciBeh/status/1325734449783443461

    3. final speaker in our "Open science and crisis knowledge management" session: Michele Starnini on radically redesigning the peer review system
    1. ReconfigBehSci. (2020, November 9). Now underway at SciBeh workshop are our 3 hackathons: 1. Combatting COVID-19 misinformation with lessons from climate change denial 2. Optimising research dissemination and curation 3. ReSearch Engine: Search Engine for SciBeh’s knowledge base & beyond [Tweet]. @SciBeh. https://twitter.com/SciBeh/status/1325796158887882752

    2. 2020-11-09

    3. now underway at SciBeh workshop are our 3 hackathons: 1. Combatting COVID-19 misinformation with lessons from climate change denial 2. Optimising research dissemination and curation 3. ReSearch Engine: Search Engine for SciBeh’s knowledge base & beyond
    1. Collabovid. (n.d.). Retrieved 6 March 2021, from https://www.collabovid.org/

    2. A lot of research articles concerning SARS-CoV-2/COVID-19 are published every day. Many of them, so-called pre-prints, are not reviewed in a professional reviewing process at the time of publication. Others are already reviewed and published in well-known journals. Collabovid helps researchers to identify the most relevant information by using Natural Language Processing. You can search for any topic you want below. Visit search to review all articles or browse a list of predefined categories. For additional help visit the frequently asked questions.
    3. Explore COVID-19 Publications
    1. Editorial Office · Rapid Reviews COVID-19. (n.d.). Rapid Reviews COVID-19. Retrieved 6 March 2021, from https://rapidreviewscovid19.mitpress.mit.edu/editors2

    2. RR:C19 relies on student-powered engine of graduate and undergraduate students, post-docs and fellows. A core team of Assistant Editors and specialists spearhead review teams across 5 subject domains. On a daily basis, teams search, screen and assess preprints across the domains: Biological and Chemical Sciences; Physical Sciences and Engineering; Social Sciences & Humanities; Public Health; and, Medical/Clinical Sciences. AI tools also support this work. Assistant Editors are also closely involved with outreach to the Editorial Board and peer review networks in subsequent stages of the RR:C19 process. See a list of students and early career researchers supporting each of our domains here.
    3. Editorial Team
    1. Welcome! You are invited to join a webinar: ‘Understanding Digital Racism After COVID-19’ with Professor Lisa Nakamura. After registering, you will receive a confirmation email about joining the webinar. (n.d.). Zoom Video. Retrieved 6 March 2021, from https://oii.zoom.us/webinar/register/2216016571338/WN_TrfmBBp-Rrm_ASHWL5e6nA

    2. Could mot find an uploading of this webinar

    3. 2020-11-11

    4. The Oxford Internet Institute hosts Lisa Nakamura, lisanakamura.net, Director, Digital Studies Institute, Gwendolyn Calvert Baker Collegiate Professor, Department of American Culture, University of Michigan, Ann Arbor. Professor Nakamura is the founding Director of the Digital Studies Institute at the University of Michigan, and a writer focusing on digital media, race, and gender.We are living in an open-ended crisis with two faces: unexpected accelerated digital adoption and an impassioned and invigorated racial justice movement. These two vast and overlapping cultural transitions require new inquiry into the entangled and intensified dialogue between race and digital technology after COVID. My project analyzes digital racial practices on Facebook, Twitter, Zoom, and TikTok while we are in the midst of a technological and racialized cultural breaking point, both to speak from within the crisis and to leave a record for those who come after us. How to Understand Digital Racism After COVID-19 contains three parts: Methods, Objects, and Making, designed to provide humanists and critical social scientists from diverse disciplines or experience levels with pragmatic and easy to use tools and methods for accelerated critical analyses of the digital racial pandemic.
    5. 'Understanding Digital Racism After COVID-19' with Professor Lisa Nakamura
    1. ReconfigBehSci on Twitter: ‘Session 1: “Open Science and Crisis Knowledge Management now underway with Chiara Varazzani from the OECD” How can we adapt tools, policies, and strategies for open science to provide what is needed for policy response to COVID-19? #scibeh2020’ / Twitter. (n.d.). Retrieved 5 March 2021, from https://twitter.com/SciBeh/status/1325720293965443072

    2. 2020-11-09

    3. Session 1: "Open Science and Crisis Knowledge Management now underway with Chiara Varazzani from the OECD" How can we adapt tools, policies, and strategies for open science to provide what is needed for policy response to COVID-19?
    1. PhD, D. D. (n.d.). Managing scientific discourse on Twitter. Retrieved 5 March 2021, from https://statsepi.substack.com/p/managing-scientific-discourse-on

    2. 2020-11-10

    3. Today I’ll be contributing to a session on Managing Online Discourse which is part of the SciBeh 2020 Virtual Workshop on Building an online information environment for policy relevant science. I have to come up with 10 minutes of “insights” about scientific discourse on Twitter, but I have no idea what I’m going to say yet, and this thing starts in a few hours. In a panic, I’ve decided to do a shit-ton of illegal drugs and then look at the session questions and write down whatever comes to mind.
    4. Managing scientific discourse on Twitter.
    1. r/BehSciAsk - Workshop hackathon: ReSearch Engine: Search Engine for SciBeh’s knowledge base & beyond. (n.d.). Reddit. Retrieved 5 March 2021, from https://www.reddit.com/r/BehSciAsk/comments/jkz7jx/workshop_hackathon_research_engine_search_engine/

    2. 2020-10-30

    3. We are inviting suggestions, comments, resources, or pointers for this hackathon:Target issue: To deal with the complex matter that is COVID-19, researchers, policymakers, and other stakeholders need a curated---even if not yet fully vetted---overview over the constantly emerging knowledge and discussions, which are scattered across the internet (e.g., preprints, webseminars, studies in progress, #academictwitter discussions, static and interactive visualizations of results and models, blog posts by researchers, policymakers, and others). To this end, SciBeh has created a living knowledge base using hypothes.is annotations. However, the search interface is designed to search for annotations and not to search the underlying documents.
    4. Workshop hackathon: ReSearch Engine: Search Engine for SciBeh’s knowledge base & beyond
    1. Rowland Manthorpe. (2020, December 16). What’s happening with the data about the vaccine? Well, let’s put it this way: There’s a lot to sort out A THREAD on my reporting today [Tweet]. @rowlsmanthorpe. https://twitter.com/rowlsmanthorpe/status/1339347825147195392

    2. None of the systems talk to each other, so Dr Singer’s admin staff are making appointments with one system, then manually entering them into another, then doing it all again for the second vaccine Lots of potential for mistakes. Lots of wasted time
    3. f you're looking for a reason for the government hasn't been regularly releasing the numbers of people who are vaccinated, this issue is probably it I don’t want to speculate too much but from what I’m told the figures put out today may be *very* provisional
    4. "We’re all getting really frustrated. It’s just not helping to deliver the programme,” he said The practice keeps people outside as much as possible “It's not nice weather and we've got old people standing out in the cold waiting to get their vaccine because of these delays”
    5. As a result, a lot of the data capture is being done by hand, before being entered into the system. Yes, that’s right, in 2020, vaccine data is being coached with pen and paper From a data point of view, this is barbaric. But to Dr Singer, the real cost is the wasted time
    6. The data recording is done by a system called Pinnacle. It arrived last week and there've been problems ever since. There are issues with access. It also keeps crashing One senior health official told me the IT was “failing constantly”
    7. There are numerous software systems involved with vaccination, but two are central. 1. Recording who's had the vaccine (and which vaccine, what batch etc). 2. Inviting and booking patients for appointments - what's known as "call and recall" There are problems with both
    8. This is Dr Elliot Singer, a GP in Waltham Forest. If anyone can be called a community doctor, it’s him. He wasn’t just born locally, he was delivered by the GP who used to have his practice He’s delighted to be delivering the vaccine, but the tech is causing “huge frustration“
    1. The quality-adjusted life year or quality-adjusted life-year (QALY) is a generic measure of disease burden, including both the quality and the quantity of life lived.[1][2] It is used in economic evaluation to assess the value of medical interventions.[1] One QALY equates to one year in perfect health.[2] QALY scores range from 1 (perfect health) to 0 (dead).[3] QALYs can be used to inform health insurance coverage determinations, treatment decisions, to evaluate programs, and to set priorities for future programs.[3]
    2. Quality-adjusted life year
    1. 2021-02-26

    2. Baal, S. van, Walasek, L., & Hohwy, J. (2021). Staying home so you can keep going out: A multiplayer self-isolation game modelling pandemic behaviour. PsyArXiv. https://doi.org/10.31234/osf.io/mh69r

    3. The effectiveness of a nation’s COVID-19 response in limiting transmission depends on people complying with unfamiliar restrictions. The immediate cost of abiding by these restrictions (e.g., by staying home) to the individual is relatively clear, yet other outcomes are delayed and noisy. It is difficult to infer whether others have fallen ill because of one’s own actions, or whether one has played a part in causing a ‘lockdown’. This uncertainty leads people to take cues from their dynamic environment and social norms on the right course of action. This preregistered study investigates how people cooperate, and how the social context influences their decisions using an iterated multiplayer game (akin to a public goods game), wherein they encounter various levels of compliance of others, variations in disease prevalence, and differences in the costliness of a lockdown. Participants indicate how much they would hypothetically isolate themselves for each level of average self-isolation by others in the group, they predict how much others will self-isolate, and make a decision about their own self-isolation. We show that participants tend to self-isolate more when they predict others will self-isolate more, and when there are more infected players in the group; we show that participants suffer from illusory superiority, underestimating others’ self-isolation compared to their own, and we show that higher perceived cost of lockdown leads to more compliance, but that this effect is stronger when players predict that others will be compliant too.
    4. 10.31234/osf.io/mh69r
    5. Staying home so you can keep going out: A multiplayer self-isolation game modelling pandemic behaviour
    1. 2021-02-25

    2. Szabelska, A., Pollet, T. V., Dujols, O., Klein, R. A., & IJzerman, H. (2021). A Tutorial for Exploratory Research: An Eight-Step Approach. PsyArXiv. https://doi.org/10.31234/osf.io/cy9mz

    3. Currently in psychological science considerable effort is directed towards confirmatory practices. Much less attention has been devoted to how to do exploratory research. In this article, we support researchers in expanding their methodological toolbox by adding one more technique of exploratory research. The majority of this article is a hands-on tutorial that explains how exploration can be done using state-of-the-art statistical methods, ultimately leading to an in-depth demonstration of machine learning techniques. The practical part of this tutorial explores one of our own datasets, the Human Penguin Project (IJzerman, Lindenberg et al., 2018). The reader can follow the tutorial by recreating our analyses in their own RStudio, apply our annotated code to her own data or other secondary data, and repeat our steps. We show how to get familiar with datasets the researcher wants to use for machine learning, inspect it in many useful ways, and make predictions using machine learning algorithms. We close with describing the limitations related to causal inference and clarifying that finding robust patterns does not equate generating a comprehensive theory. Our tutorial requires basic knowledge of statistics and programming language R (R Core Team, 2016), but we provide resources for absolute beginners.
    4. 10.31234/osf.io/cy9mz
    5. A Tutorial for Exploratory Research: An Eight-Step Approach