412 Matching Annotations
  1. Aug 2022
    1. Kai Kupferschmidt. (2021, December 10). “the severity profile of Omicron cases must be interpreted along with an understanding of its capacity to re-infect (and infect the vaccinated)“ This is what I have been trying to explain the last few days. As usual @nataliexdean does it better (and in color)! [Tweet]. @kakape. https://twitter.com/kakape/status/1469270407995867139

    1. Yaniv Erlich. (2021, December 8). Updated table of Omicron neuts studies with @Pfizer results (which did the worst job in terms of reporting raw data). Strong discrepancy between studies with live vs pseudo. Https://t.co/InQuWMAm4l [Tweet]. @erlichya. https://twitter.com/erlichya/status/1468580675007795204

    1. ReconfigBehSci. (2021, December 12). RT @ryan_landay: > A new diverse genome has appeared within the B.1.1.529 lineage that has all of the shared mutations of B.1.1.529, some o… [Tweet]. @SciBeh. https://twitter.com/SciBeh/status/1470066521615605766

    1. ReconfigBehSci. (2021, November 26). vaccine equity has been a disaster, but I do wonder whether the exclusive focus on donations does the US/EU comparison justice. The EU allowed the export of huge numbers of EU produced doses at a time when the US did not (and EU itself was struggling to meet demand). [Tweet]. @SciBeh. https://twitter.com/SciBeh/status/1464255575416520749

    1. ReconfigBehSci. (2021, November 26). maybe this is a good moment to remind people that makers of mRNA vaccines have been extensively prepping for the possibility of new variants. Biontech/Pfizer have given a timeline of 100 days to the delivery of a retooled version of their vaccine [Tweet]. @SciBeh. https://twitter.com/SciBeh/status/1464225264523747359

    1. ReconfigBehSci. (2021, December 13). RT @DrEricDing: 11) Omicron is doubling every 1.6 days in UK 🇬🇧 according to @DrWilliamKu’s figure. That’s way faster growth than in South… [Tweet]. @SciBeh. https://twitter.com/SciBeh/status/1470451594378502154

    1. John Burn-Murdoch. (2021, November 25). Five quick tweets on the new variant B.1.1.529 Caveat first: Data here is very preliminary, so everything could change. Nonetheless, better safe than sorry. 1) Based on the data we have, this variant is out-competing others far faster than Beta and even Delta did 🚩🚩 https://t.co/R2Ac4e4N6s [Tweet]. @jburnmurdoch. https://twitter.com/jburnmurdoch/status/1463956686075580421

    1. ReconfigBehSci. (2021, December 9). a rather worrying development- a (local) newspaper “fact checking” the new German health minister simply by interviewing a virologist who happens to have a different view. There’s simply no established “fact” as to the severity of omicron in children at this point in time [Tweet]. @SciBeh. https://twitter.com/SciBeh/status/1469037817481334786

    1. ReconfigBehSci. (2021, December 9). a rather worrying development- a (local) newspaper “fact checking” the new German health minister simply by interviewing a virologist who happens to have a different view. There’s simply no established “fact” as to the severity of omicron in children at this point in time [Tweet]. @SciBeh. https://twitter.com/SciBeh/status/1469037817481334786

    1. ReconfigBehSci. (2021, November 26). Parts of Germany seem to have potentially introduced requirements that cannot practically be met as testing capacity is proving insufficient—A dangerous moment for rule compliance Nadelöhr Corona-Tests: “Es ist Wahnsinn” via @sz https://t.co/meLS79RTCw [Tweet]. @SciBeh. https://twitter.com/SciBeh/status/1464287412289511432

    1. ReconfigBehSci [@SciBeh]. (2021, December 20). This thread is sobering and informative with respect to what overloading health services means in terms of individual experience...worth popping into google translate fir non-German speakers [Tweet]. Twitter. https://twitter.com/SciBeh/status/1472983739890348045

    1. Jay Patel. (2021, December 12). Well captured by @snolen. Even as vaccine supply becomes more reliable, the uptake challenge across Africa is partly down to “vaccine indifference” rather than hesitancy––there are far more pressing problems across the region. [Tweet]. @PatelJay. https://twitter.com/Patel_Jay_/status/1470028858682400772

  2. May 2022
    1. 2021-12-20

    2. this thread is sobering and informative with respect to what overloading health services means in terms of individual experience...worth popping into google translate fir non-German speakers
    1. 2021-08-06

    2. the pathologies of science Twitter are on full display in this thread featuring a non-expert blasting an epidemiologist for "stealing" an idea (a minor statistical insight) that is part of epidemiological basic understanding
  3. Apr 2022
    1. 2021-07-14

    2. The state of the UK’s statistical system 2020/21 by @StatsRegulation Thank you! See the report: https://osr.statisticsauthority.gov.uk/publication/the-state-of-the-uks-statistical-system-2020-21/pages/8/
    1. 2021-09-26

    2. Trisha Greenhalgh #IStandWithUkraine 🇺🇦 [@trishgreenhalgh]. (2021, September 26). Big Thread coming on ‘returning to on-site teaching’. Intended mainly for universities (because I work in one), but may also be useful for schools. Mute thread if not interested. I’ll base it around real questions I’ve been asked. 1/ [Tweet]. Twitter. https://twitter.com/trishgreenhalgh/status/1442162256779821060

    3. Big Thread coming on ‘returning to on-site teaching’. Intended mainly for universities (because I work in one), but may also be useful for schools. Mute thread if not interested. I’ll base it around real questions I’ve been asked. 1/
    1. 2021-10-13

    2. ReconfigBehSci [@SciBeh]. (2021, October 13). transparent public discourse is not easy, nor automatic. We need better tools, better community norms, and, generally, a better understanding of online discourse http://SciBeh.org [Tweet]. Twitter. https://twitter.com/SciBeh/status/1448305801446105088

    3. transparent public discourse is *not* easy, nor automatic. We need better tools, better community norms, and, generally, a better understanding of online discourse
    1. Polis is a real-time system for gathering, analyzing and understanding what large groups of people think in their own words, enabled by advanced statistics and machine learning.
    2. Input Crowd, Output Meaning
    1. 2021-09-02

    2. ReconfigBehSci [@SciBeh]. (2021, October 2). @alexdefig and that any attempt to bring to the table a fact that runs counter to a particular conclusion is some kind of lobbying. That really -to me- is not how science should work, nor is it how science-based policy should work. [Tweet]. Twitter. https://twitter.com/SciBeh/status/1444361815492726784

    3. and that any attempt to bring to the table a fact that runs counter to a particular conclusion is some kind of lobbying. That really -to me- is not how science should work, nor is it how science-based policy should work.
    1. 2021-11-01

    2. ReconfigBehSci [@SciBeh]. (2021, November 1). RT @HJWesteneng: Growth advantage and extrapolation of AY.4.2 based on Sanger Institute data in the UK (multilevel multinomial model). Base… [Tweet]. Twitter. https://twitter.com/SciBeh/status/1455467011509731332

    3. Growth advantage and extrapolation of AY.4.2 based on Sanger Institute data in the UK (multilevel multinomial model). Based on this data AY.4.2 seems to have a ~20% growth advantage/week over AY.4 and will become dominant in the UK in December.
    1. 2021-11-26

    2. I thank researchers from and for sharing information with @WHO & the world about B.1.1.529 variant that has been recently detected. We will convene our TAG-VE again today to discuss Everyone out there: do not discriminate against countries that share their findings openly
  4. Mar 2022
    1. 2022-03-10

    2. 10.1136/bmj.o631
    3. Many countries are declaring an end to this phase of the covid-19 pandemic, yet the underlying weaknesses that hampered our response remain unsolved, says Abraar Karan
    4. We cannot afford to repeat these four pandemic mistakes
    1. 2022-03-08

    2. Imaging before and after infection by the SARS-CoV-2 virus reveals substantial changes in the brain after infection. The work sets an example for the high standards required in large longitudinal neuroimaging studies.
    3. Brain changes after COVID revealed by imaging
  5. Feb 2022
    1. 2022-02-25

    2. Why the new ivermectin study doesn’t tell us much about whether the drug is effective for Covid-19
    3. A new large, controlled, randomized ivermectin study has come out, and depending on who you ask it either means that ivermectin works perfectly or has little to no benefit at all. Given that ivermectin remains the most hotly-debated topic of the last few years (coming second only to whether Britney Spears was unfairly treated), the new randomized trial seems pretty important.Unfortunately, in reality, this study gives us very little information about ivermectin and doesn’t answer our most important questions at all.
    4. The Jury is Still Out on Ivermectin
  6. Jan 2022
    1. 2022-01-07

    2. The armed forces are being deployed to help hospitals in London deal with a surge in Covid patients because the Omicron variant is leaving so many staff sick and unable to work.
    3. Military deployed at London hospitals due to Omicron staff shortagesSupport, which includes 40 army doctors, shows ministers can no longer ignore scale of understaffing, union leaders say
    1. 2021-06-15

    2. Zaidi, A. K., & Dehgani-Mobaraki, P. (2021). RETRACTED ARTICLE: The mechanisms of action of Ivermectin against SARS-CoV-2: An evidence-based clinical review article. The Journal of Antibiotics, 1–1. https://doi.org/10.1038/s41429-021-00430-5

    3. 10.1038/s41429-021-00430-5
    4. The Editor-in-Chief has retracted this article. Following publication, concerns were raised regarding the methodology and the conclusions of this review article. Postpublication review confirmed that while the review article appropriately describes the mechanism of action of ivermectin, the cited sources do not appear to show that there is clear clinical evidence of the effect of ivermectin for the treatment of SARS-CoV-2. The Editor-in-Chief therefore no longer has confidence in the reliability of this review article. None of the authors agree to this retraction. The online version of this article contains the full text of the retracted article as Supplementary Information.
    5. RETRACTED ARTICLE: The mechanisms of action of Ivermectin against SARS-CoV-2: An evidence-based clinical review article
    1. 2021-11-10

    2. Researchers at Yale School of Medicine have discovered that an RNA molecule that stimulates the body’s early antiviral defense system can protect mice from a range of emerging SARS-CoV-2 variants. The study, published today in the Journal of Experimental Medicine (JEM), could lead to new treatments for COVID-19 in immunocompromised patients, as well as providing an inexpensive therapeutic option for developing countries that currently lack access to vaccines.
    3. Yale researchers develop RNA-based therapy that clears SARS-CoV-2 from mice
    1. 2021-10-14

    2. Yonker, L. M., Boucau, J., Regan, J., Choudhary, M. C., Burns, M. D., Young, N., Farkas, E. J., Davis, J. P., Moschovis, P. P., Bernard Kinane, T., Fasano, A., Neilan, A. M., Li, J. Z., & Barczak, A. K. (2021). Virologic Features of Severe Acute Respiratory Syndrome Coronavirus 2 Infection in Children. The Journal of Infectious Diseases, 224(11), 1821–1829. https://doi.org/10.1093/infdis/jiab509

    3. 10.1093/infdis/jiab509
    4. BackgroundData on pediatric coronavirus disease 2019 (COVID-19) has lagged behind adults throughout the pandemic. An understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral dynamics in children would enable data-driven public health guidance.MethodsRespiratory swabs were collected from children with COVID-19. Viral load was quantified by reverse-transcription polymerase chain reaction (RT-PCR); viral culture was assessed by direct observation of cytopathic effects and semiquantitative viral titers. Correlations with age, symptom duration, and disease severity were analyzed. SARS-CoV-2 whole genome sequences were compared with contemporaneous sequences.ResultsOne hundred ten children with COVID-19 (median age, 10 years [range, 2 weeks–21 years]) were included in this study. Age did not impact SARS-CoV-2 viral load. Children were most infectious within the first 5 days of illness, and severe disease did not correlate with increased viral loads. Pediatric SARS-CoV-2 sequences were representative of those in the community and novel variants were identified.ConclusionsSymptomatic and asymptomatic children can carry high quantities of live, replicating SARS-CoV-2, creating a potential reservoir for transmission and evolution of genetic variants. As guidance around social distancing and masking evolves following vaccine uptake in older populations, a clear understanding of SARS-CoV-2 infection dynamics in children is critical for rational development of public health policies and vaccination strategies to mitigate the impact of COVID-19.
    5. Virologic Features of Severe Acute Respiratory Syndrome Coronavirus 2 Infection in Children
    1. 2022-01-05

    2. Strickland, J. C., Stoops, W., Banks, M., & Gipson-Reichardt, C. D. (2022). Logical Fallacies and Misinterpretations that Hinder Progress in Translational Addiction Neuroscience. PsyArXiv. https://doi.org/10.31234/osf.io/frd5e

    3. 10.31234/osf.io/frd5e
    4. Substance use disorders (SUDs) are heterogenous and complex, making the development of translationally predictive rodent and non-human primate models to uncover their neurobehavioral underpinnings difficult. Neuroscience-focused outcomes have become highly prevalent, and with this, the notion that SUDs are disorders of the brain embraced as a dominant theoretical orientation to understand SUD etiology and treatment. These efforts, however, have led to few efficacious pharmacotherapies, and in some cases (as with cocaine or methamphetamine), no pharmacotherapies have translated from preclinical models for clinical use. In this review and theoretical commentary, we first describe the development of animal models of SUDs from a historical perspective. We then define and discuss three logical fallacies including 1) circular explanation, 2) affirming the consequent, and 3) reification that can apply to developed models. We then provide three case examples in which conceptual or logical issues exist in common methods (i.e., behavioral economic demand, escalation, and reinstatement). Alternative strategies to refocus behavioral models are suggested for the field in an attempt to better bridge the translational divide between animal models and the clinical condition of SUDs.
    5. Logical Fallacies and Misinterpretations that Hinder Progress in Translational Addiction Neuroscience
    1. Political scientists and sociologists have highlighted insecure work as a societal ill underlying individuals’ lack of social solidarity (i.e., concern about the welfare of disadvantaged others) and political disruption. In order to provide the psychological underpinnings connecting perceptions of job insecurity with societally-relevant attitudes and behaviors, we introduce the idea of perceived national job insecurity. Perceived national job insecurity reflects a person’s perception that job insecurity is more or less prevalent in his/her society (i.e., country). Across three countries (US, UK, Belgium), we find that higher perceptions of the prevalence of job insecurity in one’s country is associated with greater perceptions of government psychological contract breach and poorer perceptions of the government’s handling of the COVID-19 crisis, but at the same time is associated with greater social solidarity and compliance with COVID-19 social regulations. These findings are independent of individuals’ perceptions of threats to their own jobs.
    2. 2022-01-03

    3. Shoss, M., Hootegem, A. V., Selenko, E., & Witte, H. D. (2022). The Job Insecurity of Others: On the Role of Perceived National Job Insecurity During the COVID-19 Pandemic. PsyArXiv. https://doi.org/10.31234/osf.io/qhpu5

    4. 10.31234/osf.io/qhpu5
    5. The Job Insecurity of Others: On the Role of Perceived National Job Insecurity During the COVID-19 Pandemic
    1. 2022-01-02

    2. A few tweets on masks for kids (thanks @dgurdasani1). US schools were 3.5 x more likely to have COVID-19 outbreaks if they did not have a mask requirement at the start of school compared with schools that required universal masking on day one. 92/
    1. 2022-01-04

    2. ReconfigBehSci. (2022, January 4). “Importantly, higher study quality was associated with lower prevalence of all symptoms, except loss of smell & cognitive symptoms” ....as someone who studies cognition I didn’t find that as reassuring as possibly intended... [Tweet]. @SciBeh. https://twitter.com/SciBeh/status/1478341731707981829

    3. "Importantly, higher study quality was associated with lower prevalence of all symptoms, except loss of smell & cognitive symptoms" ....as someone who studies cognition I didn't find that as reassuring as possibly intended...
    1. 2022-01-03

    2. masking is not an "unevidenced intervention" and, at this point, it is outright disinformation to claim so. Sad coming from an academic at a respectable institution
    1. Douaud, G., Lee, S., Alfaro-Almagro, F., Arthofer, C., Wang, C., McCarthy, P., Lange, F., Andersson, J. L. R., Griffanti, L., Duff, E., Jbabdi, S., Taschler, B., Winkler, A. M., Nichols, T. E., Collins, R., Matthews, P. M., Allen, N., Miller, K. L., & Smith, S. M. (2021). Brain imaging before and after COVID-19 in UK Biobank (p. 2021.06.11.21258690). https://doi.org/10.1101/2021.06.11.21258690

    2. 10.1101/2021.06.11.21258690
    3. There is strong evidence for brain-related pathologies in COVID-19, some of which could be a consequence of viral neurotropism, or of neuroinflammation following viral infection. Most brain imaging studies have focused on qualitative, gross pathology in moderate to severe cases, most typically carried out on hospitalised patients. It remains unknown however whether the impact of SARS-CoV-2 infection can be detected in milder cases, in a quantitative and automated manner, and whether this can reveal possible mechanisms for the spread of the disease. UK Biobank scanned over 40,000 participants before the start of the COVID-19 pandemic, making it possible in 2021 to invite back hundreds of previously-imaged participants for a second imaging visit. Here, we studied the possible brain changes associated with the coronavirus infection using multimodal MRI data from 785 adult participants (aged 51–81) from the UK Biobank COVID-19 re-imaging study, including 401 adult participants who tested positive for SARS-CoV-2 infection between their two scans. We used structural, diffusion and functional brain scans from before and after infection, to compare longitudinal changes between these 401 SARS-CoV-2 cases and 384 controls who had either tested negative to rapid antibody testing or had no COVID-19 medical and public health record, and who were matched to the cases for age, sex, ethnicity and interval between scans. The controls and cases did not differ in blood pressure, body mass index, diabetes diagnosis, smoking, alcohol consumption, or socio-economic status. Using both hypothesis-driven and exploratory approaches, with false discovery rate multiple comparison correction, we identified respectively 68 and 67 significant longitudinal effects associated with SARS-CoV-2 infection in the brain, including, on average: (i) a more pronounced reduction in grey matter thickness and contrast in the lateral orbitofrontal cortex (min P=1.7×10-4, r=-0.14) and parahippocampal gyrus (min P=2.7×10-4, r=-0.13), (ii) a relative increase of diffusion indices, a marker of tissue damage, in the regions of the brain functionally-connected to the piriform cortex, anterior olfactory nucleus and olfactory tubercle (min P=2.2×10-5, r=0.16), and (iii) greater reduction in global measures of brain size and increase in cerebrospinal fluid volume suggesting an additional diffuse atrophy in the infected participants (min P=4.0×10-6, r=-0.17). When looking over the entire cortical surface, these grey matter thickness results covered the parahippocampal gyrus and the lateral orbitofrontal cortex, and extended to the anterior insula and anterior cingulate cortex, supramarginal gyrus and temporal pole. The increase of a diffusion index (mean diffusivity) meanwhile could be seen voxel-wise mainly in the medial and lateral orbitofrontal cortex, the anterior insula, the anterior cingulate cortex and the amygdala. These results were not altered after excluding cases who had been hospitalised. We further compared hospitalised (n=15) and non-hospitalised (n=386) infected participants, resulting in similar findings to the larger cases vs control group comparison, with, in addition, a marked reduction of grey matter thickness in fronto-parietal and temporal regions (all FDR-significant, min P=4.0×10-6). The 401 SARS-CoV-2 infected participants also showed larger cognitive decline between the two timepoints in the Trail Making Test compared with the controls (both FDR-significant, min P=1.0×10-4, r=0.17; and still FDR-significant after excluding the hospitalised patients: min P=1.0×10-4, r=0.17), with the duration taken to complete the alphanumeric trail correlating post hoc with the cognitive and olfactory-related crus II of the cerebellum (FDR-significant, P=2.0×10-3, r=-0.19), which was also found significantly atrophic in the SARS-CoV-2 participants (FDR-significant, P=6.1×10-5, r=-0.14). Our findings thus relate to longitudinal abnormalities in limbic cortical areas with direct neuronal connectivity to the primary olfactory system. Unlike in post hoc cross-sectional studies, the availability of pre- infection imaging data mitigates to some extent the issue of pre-existing risk factors or clinical conditions being misinterpreted as disease effects. We were therefore able to demonstrate that the regions of the brain that showed longitudinal differences post-infection did not already show any difference between (future) cases and controls in their initial, pre-infection scans. These brain imaging results may be the in vivo hallmarks of a degenerative spread of the disease — or of the virus itself — via olfactory pathways (a possible entry point of the virus to the central nervous system being via the olfactory mucosa), or of neuroinflammatory events due to the infection, or of the loss of sensory input due to anosmia. Whether this deleterious impact can be partially reversed, for instance after improvement of the hyposmic symptoms, or whether these are effects that will persist in the long term, remains to be investigated with additional follow up.
    4. Brain imaging before and after COVID-19 in UK Biobank
    1. 2022-01-05

    2. 10.31234/osf.io/b38rd
    3. Trust is a key component of social interaction. Older adults, however, often exhibit excessive trust relative to younger adults. One explanation is that older adults may learn to trust differently than younger adults. Here, we examine how younger (N=33) and older adults (N=30) learn to trust over time. Participants completed a classic iterative trust game with three partners. Younger and older adults shared similar amounts but differed in how they shared money. Compared to younger adults, older adults invested more with untrustworthy partners and less with trustworthy partners. As a group, older adults displayed less learning than younger adults. However, computational modeling shows that this is because older adults are more likely to forget what they have learned over time. Model-based fMRI analyses revealed several age-related differences in neural processing. Younger adults showed prediction error signals in social processing areas while older adults showed over-recruitment of several cortical areas. Collectively, these findings suggest that older adults attend to and learn from social cues differently from younger adults.
    4. Age Differences in the Social Associative Learning of Trust Information
    1. 10.31234/osf.io/fxkzc
    2. Misinformation often has a continuing influence on event-related reasoning even when it is clearly and credibly corrected; this is referred to as the continued influence effect. The present work investigated whether a correction’s effectiveness can be improved by explaining how the misinformation originated. Two experiments examined whether a correction that explained misinformation as originating from intentional deception, or an unintentional error were more effective than a correction that only identified the misinformation as false. Experiment 1 found that corrections which explained the misinformation as intentionally or unintentionally misleading were as effective as a correction that was not accompanied by an explanation for how the misinformation originated. We replicated this in Experiment 2 and found substantial attenuation of the continued influence effect in a novel scenario with the same underlying structure. Overall, the results suggest that informing people that the misinformation originated from a deliberate lie or accidental error may not be an effective correction strategy over and above stating that the misinformation is false.
    3. Does explaining the origins of misinformation improve the effectiveness of a given correction?
  7. Dec 2021
    1. The World Health Organization established that the risk of suffering severe symptoms from COVID-19 is higher for some groups, but this does not mean their chances of infection are higher. However, public health messages often highlight the “increased risk” for these groups such that the risk could be interpreted as being about contracting an infection rather than suffering severe symptoms from the illness (as intended). Stressing the risk for vulnerable groups may also prompt inferences that individuals not highlighted in the message have lower risk than previously believed. In five studies, we investigated how UK residents interpreted such risk messages about COVID-19 (n = 396, n = 399, n = 432, n = 474) and a hypothetical new virus (n = 454). Participants recognised that the risk was about experiencing severe symptoms, but over half also believed that the risk was about infection, and had a corresponding heightened perception that vulnerable people were more likely to be infected. Risk messages that clarified the risk event reduced misinterpretations for a hypothetical new virus, but existing misinterpretations of coronavirus risks were resistant to correction. We discuss the need for greater clarity in public health messaging by distinguishing between the two risk events.
    2. 10.31234/osf.io/w5rd6
    3. Ambiguity and unintended inferences about risk messages for COVID - 19
    1. 10.31234/osf.io/tnyh9
    2. Infectious diseases have been an impending threat to the survival of individuals and groups throughout our evolutionary history. As a result, humans have developed psychological pathogen-avoidance mechanisms and groups have developed societal norms that respond to the presence of disease-causing microorganisms in the environment. In this work, we demonstrate that morality plays a central role in the cultural and psychological architectures that help humans avoid pathogens. We present a collection of studies which together provide an integrated understanding of the socio-ecological and psychological impacts of pathogens on human morality. Specifically, in Studies 1 (2,834 U.S. counties) and 2 (67 nations), we show that regional variation in pathogen prevalence is consistently related to aggregate moral Purity. In Study 3, we use computational linguistic methods to show that pathogen-related words co-occur with Purity words across multiple languages. In Studies 4 (n = 513) and 5 (n = 334), we used surveys and social psychological experimentation to show that pathogen-avoidance attitudes are correlated with Purity. Finally, in Study 6, we found that historical prevalence of pathogens is linked to Care, Loyalty, and Purity. We argue that particular adaptive moral systems are developed and maintained in response to the threat of pathogen occurrence in the environment. We draw on multiple methods to establish connections between pathogens and moral codes in multiple languages, experimentally induced situations, individual differences, U.S. counties, 67 countries, and historical periods over the last century.
    3. Pathogens Are Linked to Human Moral Systems Across Time and Space
    1. We estimate the willingness to taking the booster dose in a representative sample of Danes. We estimate an overall willingness in the adult Danish population of 85.5 percent and a willingness of 94.7 percent among primary vaccine takers. We, moreover, show that these percentages will be significantly lower among younger populations as well as among groups who do not see COVID-19 as a threat towards society and who do not perceive the advice of the health authorities as effective against disease spread.
    2. 10.31234/osf.io/wurz8
    3. Willingness to Take the Booster Vaccine in a Nationally Representative Sample of Danes
    1. 10.31234/osf.io/qjmct
    2. While the World has been busy mitigating the disastrous health and economic effects of the novel coronavirus, a less direct, but not less concerning peril has largely remained unexplored: the COVID-19 crisis may disrupt some of the most fundamental social and political relationships in democratic societies. We interviewed samples resembling the national population of Denmark, Hungary, Italy and the US three times: in April, June and December of 2020 (14K observations). We employed a broad set of survey questions tapping into perceptions about the two major relationships structuring society: Horizontal relationships between citizens, and vertical relationships between citizens and the state. We benchmarked these data against pre-COVID levels measured in the World Values Survey and the European Values Survey. We present strikingly similar findings across the four diverse countries. We show that support for the political system has markedly decreased already by April and fell further till December. Exploiting the panel setup, we demonstrate that within-respondent increases in indicators of pandemic fatigue (specifically, the perceived subjective burden of the pandemic and feelings of anomie) correspond to decreases in system support and increases in extreme anti-systemic attitudes. Meanwhile, we find much smaller changes in social solidarity and trust compared to pre-pandemic levels, and we find that these attitudes are largely unaffected by pandemic burden. Our results imply that the pandemic is not only a health-crisis, but poses a substantial challenge to the relationship between citizens and the state.
    3. The COVID-19 Pandemic Eroded System Support But Not Social Solidarity
    1. 2021-12-21

    2. Barely a month after it was discovered, there’s still quite a bit we don’t know about omicron. The three key areas to focus on are transmissibility, disease severity and immune evasion.
    3. Alongside this there has been a steady tide of coverage and commentary suggesting that omicron causes mostly mild disease — the implication being that it’s not much to worry about, that if we only stay the course we can ride this one out, too.Story continues below advertisementBut that’s premature. Let me be clear: I’m not stating definitively that omicron has some grim future in store for us. I’m saying that there are red flashing warning signs, that we underestimate this virus at our peril and that even the best-case scenario is still bad.
    4. Even the best-case scenario with omicron will still be bad
    1. 2021-12-23

    2. As the Omicron variant sprints to dominance across the United States, the country’s ability to track the resulting infections is about to evaporate. There are multiple reasons for this.
    3. We’re About to Lose Track of the PandemicAgain.