1,518 Matching Annotations
  1. Mar 2021
    1. 2021-03-14

    2. Exactly a year ago we wrote this letter in the Times. We were gobsmacked! We just didn’t understand what the government was basing all its decisions on including stopping testing and the herd immunity by natural infection stuff. We wanted to see the evidence backing them.
    1. 2021-03-04

    2. 10.31234/osf.io/edw47
    3. How essential is trust in science to prevent the spread of COVID-19? People who trust in science are more likely to comply with official guidelines, suggesting that higher levels of compliance could be achieved by improving trust in science. However, analysis of a global dataset (N=4341) shows that this view is mistaken. Trust in science had a small, indirect effect on adherence to the rules. It affected adherence only insofar as it predicted people's approval of prevention measures. Trust in science also mediated the relationship between political ideology and approval of the measures. These effects varied across countries, and were especially different in the USA. Overall, these results mean that any increase in trust in science is unlikely to yield strong immediate improvements in physical distancing. Nonetheless, given its relationships with both ideology and individuals' attitudes to the measures, trust in science may be leveraged to yield longer-term and more sustained social benefits.
    4. Trust in science boosts approval, but not following of COVID-19 rules
    1. 2021-03-11

    2. 10.31234/osf.io/y9mnb
    3. Public opinion regarding scientific developments such as genetically modified (GM) food can be mixed. We suggest such science-based technological innovations are rejected by some because they are perceived to be advanced as part of a conspiracy. In nationally representative samples (Australia n=1,011; New Zealand n=754) we report the associations between five conspiracism facets and anti-science attitudes. Results indicate broad public opposition to GM food and use of nuclear power, but more acceptance of renewable power, potable recycled water, 5G networks, and childhood vaccinations. There were small to moderate associations between the rejection of scientific innovations and conspiracism. Multivariate models estimating unique associations of conspiracism facets with anti-science attitudes suggested several novel and important relationships, particularly for childhood vaccination, GM food, and 5G networks. We discuss the importance of examining factors such as conspiracism in understanding what may motivate and sustain rejection of scientific evidence-based claims about socially contentious technological innovations.
    4. Associations Between Conspiracism and the Rejection of Scientific Innovations
    1. 10.1073/pnas.2019034118
    2. Pollen exposure weakens the immunity against certain seasonal respiratory viruses by diminishing the antiviral interferon response. Here we investigate whether the same applies to the pandemic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is sensitive to antiviral interferons, if infection waves coincide with high airborne pollen concentrations. Our original hypothesis was that more airborne pollen would lead to increases in infection rates. To examine this, we performed a cross-sectional and longitudinal data analysis on SARS-CoV-2 infection, airborne pollen, and meteorological factors. Our dataset is the most comprehensive, largest possible worldwide from 130 stations, across 31 countries and five continents. To explicitly investigate the effects of social contact, we additionally considered population density of each study area, as well as lockdown effects, in all possible combinations: without any lockdown, with mixed lockdown−no lockdown regime, and under complete lockdown. We found that airborne pollen, sometimes in synergy with humidity and temperature, explained, on average, 44% of the infection rate variability. Infection rates increased after higher pollen concentrations most frequently during the four previous days. Without lockdown, an increase of pollen abundance by 100 pollen/m3 resulted in a 4% average increase of infection rates. Lockdown halved infection rates under similar pollen concentrations. As there can be no preventive measures against airborne pollen exposure, we suggest wide dissemination of pollen−virus coexposure dire effect information to encourage high-risk individuals to wear particle filter masks during high springtime pollen concentrations.
    3. Higher airborne pollen concentrations correlated with increased SARS-CoV-2 infection rates, as evidenced from 31 countries across the globe
    4. 2021-03-23

    1. Scheffer, J. A., Cameron, D., & Inzlicht, M. (2021). Caring is Costly: People Avoid the Cognitive Work of Compassion. PsyArXiv. https://doi.org/10.31234/osf.io/jyx6q

    2. 2021-03-12

    3. 10.31234/osf.io/jyx6q
    4. Compassion—the warm, caregiving emotion that emerges from witnessing the suffering of others—has long been considered an important moral emotion for motivating and sustaining prosocial behavior. Some suggest that compassion draws from empathic feelings to motivate prosocial behavior, while others try to disentangle these processes to examine their different functions for human pro-sociality. Many suggest that empathy, which involves sharing in others’ experiences, can be biased and exhausting, whereas warm compassionate concern is more rewarding and sustainable. If compassion is indeed a warm and positive experience, then people should be motivated to seek it out when given the opportunity. Here, we ask whether people spontaneously choose to feel compassion, and whether such choices are associated with perceiving compassion as cognitively costly. Across all studies, we found that people opted to avoid compassion when given the opportunity; reported compassion to be more cognitively taxing than empathy and objective detachment; and opted to feel compassion less often to the degree they viewed compassion as cognitively costly. We also revealed two important boundary conditions: first, people were less likely to avoid compassion for close (vs. distant) others, and this choice difference was associated with viewing compassion for close others as less cognitively costly. Second, in the final study we found that with more contextually enriched and immersive pleas for help, participants preferred to escape feeling compassion, though their preference did not differ from also escaping remaining objectively detached. These results temper strong arguments that compassion is an easier route to prosocial motivation.
    5. Caring is Costly: People Avoid the Cognitive Work of Compassion
    1. 2021-03-12

    2. 12 March 2020 "The public could be putting themselves *more* at risk from contracting coronavirus by wearing face masks." "Jenny Harries, England's deputy chief medical officer, said the masks could “actually trap the virus” and cause the person wearing it to breathe it in"
    1. 2021-03-12

    2. 10.31234/osf.io/m9afs
    3. Sustained mass behaviour change is needed to tackle the COVID-19 pandemic, but many of the required changes run contrary to existing social norms (e.g., physical closeness with ingroup members). This paper explains how social norms and social identities are critical to explaining and changing public behaviour. Recommendations are presented for how to harness these social processes to maximise adherence to COVID-19 public health guidance. Specifically, we recommend that public health messages clearly define who the target group is, are framed as identity-affirming rather than identity-contradictory, include complementary injunctive and descriptive social norm information, are delivered by ingroup members and that support is provided to enable the public to perform the requested behaviours.
    4. Social norms, social identities and the COVID-19 pandemic: Theory and recommendations
    1. 2021-03-11

    2. New summary report on SARS-CoV-2 variants of concern and variants of interest in the UK: https://gov.uk/government/publications/investigation-of-novel-sars-cov-2-variant-variant-of-concern-20201201… via @fact_covid
    1. 2021-03-08

    2. Today we are officially launching our Practical Health Psychology Free E-Book @EHPSociety @PractHealthPsy https://practicalhealthpsychology.com/e-book/ Translating behavioural research to practice, one blog post at a time #BehaviouralScience #HealthPsychology #Health
    1. We don't think scientists would think this is completely crazy :) Indeed, some people are already already enlisting the help of a Red Team! https://twitter.com/talyarkoni/status/1331320986860462088
    2. 2020-11-24

    1. 2020-11-25

    2. we didn't have explicit discussion of Red Team process at our SciBeh workshop, but I suspect it's an extremely useful way to manage criticism- simply because the recipient is *inviting it*
    1. 2020-07-13

    2. The COVID-19 pandemic, caused by the SARS-CoV-2, represents an unprecedented challenge for healthcare. COVID-19 features a state of hyperinflammation resulting in a “cytokine storm”, which leads to severe complications, such as the development of micro-thrombosis and disseminated intravascular coagulation (DIC). Despite isolation measures, the number of affected patients is growing daily: as of June 12th, over 7.5 million cases have been confirmed worldwide, with more than 420,000 global deaths. Over 3.5 million patients have recovered from COVID-19; although this number is increasing by the day, great attention should be directed towards the possible long-term outcomes of the disease. Despite being a trivial matter for patients in intensive care units (ICUs), erectile dysfunction (ED) is a likely consequence of COVID-19 for survivors, and considering the high transmissibility of the infection and the higher contagion rates among elderly men, a worrying phenomenon for a large part of affected patients.
    3. Addressing male sexual and reproductive health in the wake of COVID-19 outbreak
    1. 2020-11-25

    2. For many, the 2016 presidential election represented an existential threat to science and jolted large segments of the research workforce into street protest mode. More recently, the COVID-19 pandemic has thrust scientists into global prominence, while the Black Lives Matter uprising has forced a reckoning with science’s problematic past and present. In many ways, science itself was on the ballot this Election Day. Prominent scientific journals endorsed Democratic presidential candidate Joe Biden, scientific societies issued statements in the wake of the George Floyd killing, and thousands of scientists went on strike in solidarity with Black Lives Matter.

    3. Scientists Are Becoming More Politically Engaged
  2. Feb 2021
    1. 2020-10

    2. Can social contextual factors explain international differences in the spread of COVID-19? It is widely assumed that social cohesion, public confidence in government sources of health information and general concern for the welfare of others support health advisories during a pandemic and save lives. We tested this assumption through a time-series analysis of cross-national differences in COVID-19 mortality during an early phase of the pandemic. Country data on income inequality and four dimensions of social capital (trust, group affiliations, civic responsibility and confidence in public institutions) were linked to data on COVID-19 deaths in 84 countries. Associations with deaths were examined using Poisson regression with population-averaged estimators. During a 30-day period after recording their tenth death, mortality was positively related to income inequality, trust and group affiliations and negatively related to social capital from civic engagement and confidence in state institutions. These associations held in bivariate and mutually controlled regression models with controls for population size, age and wealth. The results indicate that societies that are more economically unequal and lack capacity in some dimensions of social capital experienced more COVID-19 deaths. Social trust and belonging to groups were associated with more deaths, possibly due to behavioural contagion and incongruence with physical distancing policy. Some countries require a more robust public health response to contain the spread and impact of COVID-19 due to economic and social divisions within them.
    3. 10.1016/j.socscimed.2020.113365
    4. The trouble with trust: Time-series analysis of social capital, income inequality, and COVID-19 deaths in 84 countries
    1. 2020-10-29

    2. In the U.S., the coronavirus pandemic has driven a surge in bicycle sales and use. A more supportive federal policy toward non-car mobility could help it roll on. 
    3. Can the Bike Boom Keep Going?
    1. 2020-11-11

    2. There has been a “shocking” decline in primary school pupils’ levels of attainment in England after lockdown, testing has revealed, with younger children and those from disadvantaged backgrounds worst affected.
    3. England: 'shocking' decline in primary pupils' attainment after lockdown
    1. 2019-08-07

    2. Views of the role of hypothesis falsification in statistical testing do not divide as cleanly between frequentist and Bayesian views as is commonly supposed. This can be shown by considering the two major variants of the Bayesian approach to statistical inference and the two major variants of the frequentist one.
    3. De Finetti meets Popper
    1. 10.1038/s41562-020-00977-7
    2. Numerous polls suggest that COVID-19 is a profoundly partisan issue in the United States. Using the geotracking data of 15 million smartphones per day, we found that US counties that voted for Donald Trump (Republican) over Hillary Clinton (Democrat) in the 2016 presidential election exhibited 14% less physical distancing between March and May 2020. Partisanship was more strongly associated with physical distancing than numerous other factors, including counties’ COVID-19 cases, population density, median income, and racial and age demographics. Contrary to our predictions, the observed partisan gap strengthened over time and remained when stay-at-home orders were active. Additionally, county-level consumption of conservative media (Fox News) was related to reduced physical distancing. Finally, the observed partisan differences in distancing were associated with subsequently higher COVID-19 infection and fatality growth rates in pro-Trump counties. Taken together, these data suggest that US citizens’ responses to COVID-19 are subject to a deep—and consequential—partisan divide.
    3. Partisan differences in physical distancing are linked to health outcomes during the COVID-19 pandemic
    4. 2020-11-02

    1. 2012.09353
    2. The global spread of the novel coronavirus is affected by the spread of related misinformation -- the so-called COVID-19 Infodemic -- that makes populations more vulnerable to the disease through resistance to mitigation efforts. Here we analyze the prevalence and diffusion of links to low-credibility content about the pandemic across two major social media platforms, Twitter and Facebook. We characterize cross-platform similarities and differences in popular sources, diffusion patterns, influencers, coordination, and automation. Comparing the two platforms, we find divergence among the prevalence of popular low-credibility sources and suspicious videos. A minority of accounts and pages exert a strong influence on each platform. These misinformation "superspreaders" are often associated with the low-credibility sources and tend to be verified by the platforms. On both platforms, there is evidence of coordinated sharing of Infodemic content. The overt nature of this manipulation points to the need for societal-level rather than in-house mitigation strategies. However, we highlight limits imposed by inconsistent data-access policies on our capability to study harmful manipulations of information ecosystems.
    3. The COVID-19 Infodemic: Twitter versus Facebook
    4. 2020-12-17

    1. 2012.03991
    2. The friendship paradox is the observation that the degrees of the neighbors of a node in any network will, on average, be greater than the degree of the node itself. In common parlance, your friends have more friends than you do. In this paper we develop the mathematical theory of the friendship paradox, both in general as well as for specific model networks, focusing not only on average behavior but also on variation about the average and using generating function methods to calculate full distributions of quantities of interest. We compare the predictions of our theory with measurements on a large number of real-world network data sets and find remarkably good agreement. We also develop equivalent theory for the generalized friendship paradox, which compares characteristics of nodes other than degree to those of their neighbors.
    3. The friendship paradox in real and model networks
    4. 2020-12-07

    1. 10.1371/journal.pcbi.1008442
    2. Inter-hospital patient transfers (direct transfers) between healthcare facilities have been shown to contribute to the spread of pathogens in a healthcare network. However, the impact of indirect transfers (patients re-admitted from the community to the same or different hospital) is not well studied. This work aims to study the contribution of indirect transfers to the spread of pathogens in a healthcare network. To address this aim, a hybrid network–deterministic model to simulate the spread of multiresistant pathogens in a healthcare system was developed for the region of Lower Saxony (Germany). The model accounts for both, direct and indirect transfers of patients. Intra-hospital pathogen transmission is governed by a SIS model expressed by a system of ordinary differential equations. Our results show that the proposed model reproduces the basic properties of healthcare-associated pathogen spread. They also show the importance of indirect transfers: restricting the pathogen spread to direct transfers only leads to 4.2% system wide prevalence. However, adding indirect transfers leads to an increase in the overall prevalence by a factor of 4 (18%). In addition, we demonstrated that the final prevalence in the individual healthcare facilities depends on average length of stay in a way described by a non-linear concave function. Moreover, we demonstrate that the network parameters of the model may be derived from administrative admission/discharge records. In particular, they are sufficient to obtain inter-hospital transfer probabilities, and to express the patients’ transfers as a Markov process. Using the proposed model, we show that indirect transfers of patients are equally or even more important as direct transfers for the spread of pathogens in a healthcare network.
    3. Modelling pathogen spread in a healthcare network: Indirect patient movements
    4. 2020-11-30

    1. Kaiser, F., Ronellenfitsch, H., & Witthaut, D. (2020). Discontinuous transition to loop formation in optimal supply networks. Nature Communications, 11(1), 5796. https://doi.org/10.1038/s41467-020-19567-2

    2. 2011.11960
    3. The structure and design of optimal supply networks is an important topic in complex networks research. A fundamental trait of natural and man-made networks is the emergence of loops and the trade-off governing their formation: adding redundant edges to supply networks is costly, yet beneficial for resilience. Loops typically form when costs for new edges are small or inputs uncertain. Here, we shed further light on the transition to loop formation. We demonstrate that loops emerge discontinuously when decreasing the costs for new edges for both an edge-damage model and a fluctuating sink model. Mathematically, new loops are shown to form through a saddle-node bifurcation. Our analysis allows to heuristically predict the location and cost where the first loop emerges. Finally, we unveil an intimate relationship among betweenness measures and optimal tree networks. Our results can be used to understand the evolution of loop formation in real-world biological networks.
    4. Discontinuous transition to loop formation in optimal supply networks
    5. 2020-11-24

    1. 2011.12162
    2. Fighting the COVID-19 pandemic, most countries have implemented non-pharmaceutical interventions like wearing masks, physical distancing, lockdown, and travel restrictions. Because of their economic and logistical effects, tracking mobility changes during quarantines is crucial in assessing their efficacy and predicting the virus spread. Chile, one of the worst-hit countries in the world, unlike many other countries, implemented quarantines at a more localized level, shutting down small administrative zones, rather than the whole country or large regions. Given the non-obvious effects of these localized quarantines, tracking mobility becomes even more critical in Chile. To assess the impact on human mobility of the localized quarantines in Chile, we analyze a mobile phone dataset made available by Telefónica Chile, which comprises 31 billion eXtended Detail Records and 5.4 million users covering the period February 26th to September 20th, 2020. From these records, we derive three epidemiologically relevant metrics describing the mobility within and between comunas. The datasets made available can be used to fight the COVID-19 epidemics, particularly for localized quarantines' less understood effect.
    3. A dataset to assess mobility changes in Chile following local quarantines
    4. 2020-11-24

    1. 2011.07165
    2. This chapter looks at the spatial distribution and mobility patterns of essential and non-essential workers before and during the COVID-19 pandemic in London and compares them to the rest of the UK. In the 3-month lockdown that started on 23 March 2020, 20% of the workforce was deemed to be pursuing essential jobs. The other 80%% were either furloughed, which meant being supported by the government to not work, or working from home. Based on travel journey data between zones (trips were decomposed into essential and non-essential trips. Despite some big regional differences within the UK, we find that essential workers have much the same spatial patterning as non-essential for all occupational groups containing essential and non-essential workers. Also, the amount of travel time saved by working from home during the Pandemic is roughly the same proportion -80%-as the separation between essential and non-essential workers. Further, the loss of travel, reduction in workers, reductions in retail spending as well as increases in use of parks are examined in different London boroughs using Google Mobility Reports which give us a clear picture of what has happened over the last 6 months since the first Lockdown. These reports also now imply that a second wave of infection is beginning.
    3. London in Lockdown: Mobility in the Pandemic City
    4. 2020-11-13

    1. Aletti, G., Crimaldi, I., & Saracco, F. (2020). A model for the Twitter sentiment curve. ArXiv:2011.05933 [Physics]. http://arxiv.org/abs/2011.05933

    2. 2020-11-11

    3. 2011.05933
    4. Twitter is among the most used online platforms for the political communications, due to the concision of its messages (which is particularly suitable for political slogans) and the quick diffusion of messages. Especially when the argument stimulate the emotionality of users, the content on Twitter is shared with extreme speed and thus studying the tweet sentiment if of utmost importance to predict the evolution of the discussions and the register of the relative narratives. In this article, we present a model able to reproduce the dynamics of the sentiments of tweets related to specific topics and periods and to provide a prediction of the sentiment of the future posts based on the observed past. The model is a recent variant of the Pólya urn, introduced and studied in arXiv:1906.10951 and arXiv:2010.06373, which is characterized by a "local" reinforcement, i.e. a reinforcement mechanism mainly based on the most recent observations, and by a random persistent fluctuation of the predictive mean. In particular, this latter feature is capable of capturing the trend fluctuations in the sentiment curve. While the proposed model is extremely general and may be also employed in other contexts, it has been tested on several Twitter data sets and demonstrated greater performances compared to the standard Pólya urn model. Moreover, the different performances on different data sets highlight different emotional sensitivities respect to a public event.
    5. A model for the Twitter sentiment curve
    1. 2020-11-30

    2. Vaccine developers who have already reported promising phase III trial results against COVID-19 estimate that, between them, they can make sufficient doses for more than one-third of the world’s population by the end of 2021. But many people in low-income countries might have to wait until 2023 or 2024 for vaccination, according to estimates from the Duke Global Health Innovation Center in Durham, North Carolina.
    3. How COVID vaccines are being divvied up around the world
    1. 2020-12-11

    2. Today, the U.S. Food and Drug Administration issued the first emergency use authorization (EUA) for a vaccine for the prevention of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in individuals 16 years of age and older. The emergency use authorization allows the Pfizer-BioNTech COVID-19 Vaccine to be distributed in the U.S.
    3. FDA Takes Key Action in Fight Against COVID-19 By Issuing Emergency Use Authorization for First COVID-19 Vaccine