2,109 Matching Annotations
  1. Feb 2021
    1. Paper by TFC updating their paper of 17 December 2020 on children, schools and transmission. It was considered at SAGE 80 on 11 February 2021. This paper should be read alongside the Juniper consortium paper on the impact of partial school openings, also presented at SAGE 80. These documents are released as pre-print publications that have provided the government with rapid evidence during an emergency. These documents have not been peer-reviewed and there is no restriction on authors submitting and publishing this evidence in peer-reviewed journals.
    2. 2021-02-22

    3. TFC: Children and transmission - update paper, 10 February 2021
    1. 2021-02-22

    2. Tim Colbourn. (2021, February 22). It’s good that opening up will be done in stages, though more could be done to ensure we don’t fail after the 1st stage and end up back in lockdown due to hospitals filling up again with unvaccinated people. I hope the government don’t end up regretting not doing the above. END [Tweet]. @timcolbourn. https://twitter.com/timcolbourn/status/1363989485516693508

    3. It's good that opening up will be done in stages, though more could be done to ensure we don’t fail after the 1st stage and end up back in lockdown due to hospitals filling up again with unvaccinated people. I hope the government don't end up regretting not doing the above. END
    4. 4. Cases may not be going down so quickly anymore – look at the last ~2 weeks data - so infections and hospitalisations could go up rapidly, especially without 1-3 above.
    5. 3. Why not stagger school opening rather than send all year groups back at once?
    1. UK is with EU. (2021, January 18). ..The reason we are in this third lockdown is because of the anti lockdowners like Lord Sumption ..We are going in circles, countries who have done well controlled the virus and now have an economic recovery ..And every life matters #GMB @devisridhar speaking truth to power https://t.co/U3BBV0uUSb [Tweet]. @ukiswitheu. https://twitter.com/ukiswitheu/status/1351089812799950850

    2. 2021-01-18

    3. The reason we are in this third lockdown is because of the anti lockdowners like Lord Sumption ..We are going in circles, countries who have done well controlled the virus and now have an economic recovery ..And every life matters #GMB @devisridhar speaking truth to power
    1. 2021-02-23

    2. Hanea, A., Wilkinson, D. P., McBride, M., Lyon, A., Ravenzwaaij, D. van, Thorn, F. S., Gray, C. T., Mandel, D. R., Willcox, A., Gould, E., Smith, E., Mody, F., Bush, M., Fidler, F., Fraser, H., & Wintle, B. (2021). Mathematically aggregating experts’ predictions of possible futures. MetaArXiv. https://doi.org/10.31222/osf.io/rxmh7

    3. 10.31222/osf.io/rxmh7
    4. Experts are often asked to represent their uncertainty as a subjective probability. Structured protocols offer a transparent and systematic way to elicit and combine probability judgements from multiple experts. As part of this process, experts are asked to individually estimate a probability (e.g., of a future event) which needs to be combined/aggregated into a final group prediction. The experts' judgements can be aggregated behaviourally (by striving for consensus), or mathematically (by using a mathematical rule to combine individual estimates). Mathematical rules (e.g., weighted linear combinations of judgments) provide an objective approach to aggregation. However, the choice of a rule is not straightforward, and the aggregated group probability judgement's quality depends on it. The quality of an aggregation can be defined in terms of accuracy, calibration and informativeness. These measures can be used to compare different aggregation approaches and help decide on which aggregation produces the "best" final prediction. In the ideal case, individual experts' performance (as probability assessors) is scored, these scores are translated into performance-based weights, and a performance-based weighted aggregation is used. When this is not possible though, several other aggregation methods, informed by measurable proxies for good performance, can be formulated and compared. We use several data sets to investigate the relative performance of multiple aggregation methods informed by previous experience and the available literature. Even though the accuracy, calibration, and informativeness of the majority of methods are very similar, two of the aggregation methods distinguish themselves as the best and worst.
    5. Mathematically aggregating experts' predictions of possible futures
    1. Oreskes, N. (2019). Systematicity is necessary but not sufficient: On the problem of facsimile science. Synthese, 196(3), 881–905. https://doi.org/10.1007/s11229-017-1481-1

    2. 10.1007/s11229-017-1481-1
    3. 2017-07-20

    4. Paul Hoyningen-Huene argues that what makes scientific knowledge special is its systematic character, and that this can be used to solve the demarcation problem. He labels this STDC: “Systematicity Theory’s Demarcation Criterion.” This paper argues that STDC fails, because there are areas of intellectual activity that are highly systematic, but that the great majority of scientists and historians and philosophers of science do not accept as scientific. These include homepathy, creationism, and climate change denial. I designate these activities “facsimile sciences” because they mimic the appearance of science but are not, by the standards of philosophers and scientists, scientific. This suggests that we need additional criteria to demarcate science from non-science and/ or nonsense.
    1. 2021-01-18

    2. Li, F., Li, Y.-Y., Liu, M.-J., Fang, L.-Q., Dean, N. E., Wong, G. W. K., Yang, X.-B., Longini, I., Halloran, M. E., Wang, H.-J., Liu, P.-L., Pang, Y.-H., Yan, Y.-Q., Liu, S., Xia, W., Lu, X.-X., Liu, Q., Yang, Y., & Xu, S.-Q. (2021). Household transmission of SARS-CoV-2 and risk factors for susceptibility and infectivity in Wuhan: A retrospective observational study. The Lancet Infectious Diseases, 0(0). https://doi.org/10.1016/S1473-3099(20)30981-6

    3. 10.1016/S1473-3099(20)30981-6
    4. SummaryBackgroundWuhan was the first epicentre of COVID-19 in the world, accounting for 80% of cases in China during the first wave. We aimed to assess household transmissibility of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and risk factors associated with infectivity and susceptibility to infection in Wuhan.MethodsThis retrospective cohort study included the households of all laboratory-confirmed or clinically confirmed COVID-19 cases and laboratory-confirmed asymptomatic SARS-CoV-2 infections identified by the Wuhan Center for Disease Control and Prevention between Dec 2, 2019, and April 18, 2020. We defined households as groups of family members and close relatives who did not necessarily live at the same address and considered households that shared common contacts as epidemiologically linked. We used a statistical transmission model to estimate household secondary attack rates and to quantify risk factors associated with infectivity and susceptibility to infection, accounting for individual-level exposure history. We assessed how intervention policies affected the household reproductive number, defined as the mean number of household contacts a case can infect.Findings27 101 households with 29 578 primary cases and 57 581 household contacts were identified. The secondary attack rate estimated with the transmission model was 15·6% (95% CI 15·2–16·0), assuming a mean incubation period of 5 days and a maximum infectious period of 22 days. Individuals aged 60 years or older were at a higher risk of infection with SARS-CoV-2 than all other age groups. Infants aged 0–1 years were significantly more likely to be infected than children aged 2–5 years (odds ratio [OR] 2·20, 95% CI 1·40–3·44) and children aged 6–12 years (1·53, 1·01–2·34). Given the same exposure time, children and adolescents younger than 20 years of age were more likely to infect others than were adults aged 60 years or older (1·58, 1·28–1·95). Asymptomatic individuals were much less likely to infect others than were symptomatic cases (0·21, 0·14–0·31). Symptomatic cases were more likely to infect others before symptom onset than after (1·42, 1·30–1·55). After mass isolation of cases, quarantine of household contacts, and restriction of movement policies were implemented, household reproductive numbers declined by 52% among primary cases (from 0·25 [95% CI 0·24–0·26] to 0·12 [0·10–0·13]) and by 63% among secondary cases (from 0·17 [0·16–0·18] to 0·063 [0·057–0·070]).InterpretationWithin households, children and adolescents were less susceptible to SARS-CoV-2 infection but were more infectious than older individuals. Presymptomatic cases were more infectious and individuals with asymptomatic infection less infectious than symptomatic cases. These findings have implications for devising interventions for blocking household transmission of SARS-CoV-2, such as timely vaccination of eligible children once resources become available.FundingNational Natural Science Foundation of China, Fundamental Research Funds for the Central Universities, US National Institutes of Health, and US National Science Foundation.
    5. Household transmission of SARS-CoV-2 and risk factors for susceptibility and infectivity in Wuhan: a retrospective observational study
    1. 2020-01-27

    2. Renton, B. (2020, January 27). Coronavirus Updates. Off the Silk Road. http://offthesilkroad.com/2020/01/27/wuhan-coronavirus-updates/

    3. Greetings from Beijing, China! By now you have most likely heard of the coronavirus outbreak that has originated in Wuhan and has spread all over the country and internationally. I am currently studying abroad in Beijing and traveled to Harbin for the first few days of the Chinese New Year holiday, but have now gathered back in Beijing at the request of CET and the Middlebury Schools Abroad.  While I am by no means a public health expert, I have been keeping up to date with both Western and Chinese media and the U.S. Embassy and have written notes each day for the past week with updates. These reports include my own observations, as well as reports from over 500 contacts on the ground. You can follow the whole set below.
    4. Coronavirus Updates
    1. 2021-02-16

    2. Fake News and Conspiracy Theories. (2021, February 16). American Purpose. https://www.americanpurpose.com/blog/fukuyama/fake-news-and-conspiracy-theories/

    3. We are at a very dangerous and unprecedented point in American politics today. As noted in my last post, something strange has happened to the Republican Party. It has been shifting from a party built around ideology and ideas, to one that resembles a cult of personality focused on one individual, former President Donald Trump. Its core support base is today furious about a fact that simply isn’t true: the notion that Trump won the Nov. 3 election by a landslide, and that it was stolen by “radical, far-Left Democrats” in one of the most outrageous frauds in American history. This is what Trump told the crowd before the January 6 storming of Congress, and why 43 Republican Senators were not willing to vote to impeach the former President in the vote last Saturday.
    4. Fake News and Conspiracy Theories
    1. 2021-02-12

    2. Study Identifies Risk Factors for Elevated Anxiety in Young Adults During COVID-19 Pandemic. (2021, February 12). National Institutes of Health (NIH). https://www.nih.gov/news-events/news-releases/study-identifies-risk-factors-elevated-anxiety-young-adults-during-covid-19-pandemic

    3. A new study has identified early risk factors that predicted heightened anxiety in young adults during the coronavirus (COVID-19) pandemic. The findings from the study, supported by the National Institutes of Health and published in the Journal of the American Academy of Child and Adolescent Psychiatry, could help predict who is at greatest risk of developing anxiety during stressful life events in early adulthood and inform prevention and intervention efforts.
    4. Study Identifies Risk Factors for Elevated Anxiety in Young Adults During COVID-19 Pandemic
    1. Estimating the impact of reopening schools on the reproduction number of SARS-CoV-2 in England, using weekly contact survey data. (2021, February 15). CMMID Repository. https://cmmid.github.io/topics/covid19/comix-schools.html

    2. 2021-02-15

    3. We measured social contacts when schools were either open or closed, amongst other restrictions. We combined these data with estimates of the susceptibility and infectiousness of children compared with adults to estimate the impact of reopening schools on the reproduction number. Our results suggest that reopening all schools could increase R from an assumed baseline of 0.8 to between 1.0 and 1.5, or to between 0.9 and 1.2 reopening primary or secondary schools alone.
    4. Estimating the impact of reopening schools on the reproduction number of SARS-CoV-2 in England, using weekly contact survey data
    1. 10-11-2020

    2. 10.3233/ISU-200094
    3. In content section. Select this link to jump to navigation ga('set', 'dimension6','Metadata: The accelerant we need'); ga('set', 'metric1', 1 ); ga('set', 'dimension3',"Information Services & Use"); ga('set', 'metric2', 1 ); ga('set', 'dimension4',"Volume 40"); ga('set', 'metric3', 1 ); ga('set', 'metric4', 1 ); ga('set', 'metric5', 1 ); ga('set', 'dimension5',"Issue 3"); ga('send', 'pageview', "/Information Services & Use/"); Cite Email Print Share Metadata: The accelerant we need
    4. Large-scale pandemic events have sent scientific communities scrambling to gather and analyze data to provide governments and policy makers with information to inform decisions and policies needed when imperfect information is all that may be available. Historical records from the 1918 influenza pandemic reflect how little improvement has been made in how government and policy responses are formed when large scale threats occur, such as the COVID-19 pandemic. This commentary discusses three examples of how metadata improvements are being, or may be made, to facilitate gathering and assessment of data to better understand complex and dynamic situations. In particular, metadata strategies can be applied in advance, on the fly or even after events to integrate and enrich perspectives that aid in creating balanced actions to minimize impacts with lowered risk of unintended consequences. Metadata can enhance scope, speed and clarity with which scholarly communities can curate their outputs for optimal discovery and reuse. Conclusions are framed within the Metadata 2020 working group activities that lay a foundation for advancement of scholarly communications to better serve all communities.
    1. Co-production of knowledge through research involves collaborations between researchers and end-users of research, including patients and the public, health professionals, health system managers, and policymakers. This approach is being advocated globally, and across sectors. But there remains uncertainty on what co-production of research entails, how to do it, when and when not to do it. More evidence on these issues is essential if the co-production of research is to deliver on its promise to produce knowledge and share power and responsibility from the start to the end of research and avoid wasting time, resources, and the good will of end-users. This BMJ collection on Increasing the Impact of Health Research through Co-production of Knowledge provides an overview of the evolution, potential, influence, learning and challenges in co-producing evidence to inform decision making in health policy and practice, and points to the core principles which should underpin it. In this collection, we define research co-production as where researchers work in partnership with knowledge users (comprising patients and caregivers, the public, clinicians, policy-makers, health system leaders and others) to identify a problem and produce knowledge, sharing power and responsibility from the start to the end of the research.
    2. Increasing the impact of health research through co-production of knowledge