AN Ayrshire woman has been accused of not self-isolating after her pals tested positive for coronavirus – and attending 'several house parties'.

Ayrshire 'super spreader' went to house parties with coronavirus

10.31234/osf.io/sfnb9

Public psychology is concerned with embedding meaningful connections between the public and psychologists. However, there may be tensions between experientially afforded ‘lived experience’ and conventional understanding of ‘expertise’ that must be navigated thoughtfully between lay audiences and psychologists. In this paper, we critically assess how the often ill-defined concept of conventional expertise may or may not be compatible with a framework of psychology that positions science and society as equally credible agents. We will use this core discussion to argue that a public psychology framework, and its inherent attempts to relocate power and voice within knowledge to members of wider society, may prompt us to rethink the notion of expertise. We argue that by reappraising concepts relating to expertise, scientific progress and impact can be made across the discipline. We conclude with a consideration of how these tensions can be eased; namely, through more embodied partnerships between society and science, such as participatory research methods, a fundamental reappraisal of what constitutes knowledge and expertise within the discipline, and an ongoing concern for intersectionality.

The Expertise Paradox: Opportunities and Challenges of a Public Psychology Framework

People infected at the pool party spread the virus to teammates, a sibling and people in their car pools, Health Commissioner Dr. Allison Arwady said.

13 People At Chicago Pool Party Get Coronavirus, Spread It To At Least 6 Others, Chicago’s Top Doc Says

The fact that severe acute respiratory syndrome coronavirus 2 derived from bat coronaviruses highlights inherent issues of the way we interact with the environment. Talha Burki reports.

10.1016/S1473-3099(20)30641-1

The origin of SARS-CoV-2

Considerations include where it is safe to go, what is the risk of travelling, and what new measures are in place to reduce the risk of COVID-19 for those who decide to travel.

10.1016/S1473-3099(20)30647-2

Air travel in the time of COVID-19

Parents should be "reassured" Covid-19 has not caused the deaths of any otherwise healthy schoolchildren in the UK, researchers say.

Coronavirus: 'Reassuring' study of children's 'tiny' risk

Processing information about probabilities is an integral part of decision making under risk. Even when objective probabilities are explicitly provided, people tend to distort them, which is reflected by an inverted S‐shaped probability weighting function. Such distortions depend on different factors such as numeracy and affect. The present study contributes to the understanding of how people use probabilities in risky decision making by introducing the concept of consistency in probability processing―a measure of how coherent people are in using objective probabilities. We hypothesized that consistency would depend on factors similar to those that influence the shape of the probability weighting function. Moreover, we predicted that probability processing consistency would be related to better decision outcomes in an experimental betting task. In three experiments, participants were presented with the probability of a potential gain/loss and had to place a bet on a given chance to maximize their total earnings. We defined probability processing consistency as the variance of bets placed on the same probability value, with higher variance indicating lower consistency. We found that consistency in probability processing was lower in relatively affect‐rich conditions and greater for people with higher numeracy. Additionally, people who exhibited more consistent processing of probabilities gained higher earnings from the experimental task irrespective of whether their betting strategy was optimal and of their risk preference. Our findings imply that consistency in processing probabilities may be an important factor in understanding betting strategies and the quality of decisions.

10.1002/bdm.2206

Consistency in probability processing as a function of affective context and numeracy

10.31234/osf.io/3nuzj

In this chapter, we provide a necessarily brief and partial survey of recent work in the cognitive sciences directly on or closely related to the psychology of fake news, in particular fake news in the political domain. We focus on whether and why people believe fake news. While we argue that it is likely that a large proportion of people who purport to believe fake news really do, we provide evidence that this proportion might be significantly smaller than is usually thought (and smaller than is suggested by surveys). Assertion of belief is inflated, we suggest, by insincere report, whether to express support for one side of political debate or simply for fun. It is also inflated by the use of motivated inference of one sort or another, which lead respondents to report believing things about which they had no opinion prior to being probed. We then turn to rival accounts that aim to explain why people believe in fake news when they do. While partisan explanations, turning on motivated reasoning, are probably best known, we show they face serious challenges from accounts that explain belief by reference to analytic thinking.

The cognitive science of fake news

RT @arthomason: The Atlantic was right. This was always where we were headed.

We develop a theory to measure the variance and covariance of probability distributions defined on the nodes of a graph, which takes into account the distance between nodes. Our approach generalizes the usual (co)variance to the setting of weighted graphs and retains many of its intuitive and desired properties. Interestingly, we find that a number of famous concepts in graph theory and network science can be reinterpreted in this setting as variances and covariances of particular distributions: we show this correspondence for Kemeny's constant, the Kirchhoff index, network modularity and Markov stability. As a particular application, we define the maximum-variance problem on graphs with respect to the effective resistance distance, and characterize the solutions to this problem both numerically and theoretically. We show how the maximum-variance distribution can be interpreted as a core-periphery measure, illustrated by the fact that these distributions are supported on the leaf nodes of tree graphs, low-degree nodes in a configuration-like graph and boundary nodes in random geometric graphs. Our theoretical results are supported by a number of experiments on a network of mathematical concepts, where we use the variance and covariance as analytical tools to study the (co-)occurrence of concepts in scientific papers with respect to the (network) relations between these concepts.

arXiv:2008.09155

Variance and covariance of distributions on graphs

arXiv:2008.09011

Peer review is a cornerstone of modern scientific endeavor. However, there is growing consensus that several limitations of the current peer review system, from lack of incentives to reviewers to lack of transparency, risks to undermine its benefits. Here, we introduce the PRINCIPIA (http://www.principia.network/) framework for peer-review of scientific outputs (e.g., papers, grant proposals or patents). The framework allows key players of the scientific ecosystem -- including existing publishing groups -- to create and manage peer-reviewed journals, by building a free market for reviews and publications. PRINCIPIA's referees are transparently rewarded according to their efforts and the quality of their reviews. PRINCIPIA also naturally allows to recognize the prestige of users and journals, with an intrinsic reputation system that does not depend on third-parties. PRINCIPIA re-balances the power between researchers and publishers, stimulates valuable assessments from referees, favors a fair competition between journals, and reduces the costs to access research output and to publish.

PRINCIPIA: a Decentralized Peer-Review Ecosystem

10.1038/scientificamerican0920-84

Letting the rich pay for science that interests them is a bad idea—even if they aren’t convicted sex offenders

Jeffrey Epstein’s Harvard Connections Show How Money Can Distort Research

10.1126/sciadv.aba4934

Is there a universal economic pathway individual cities recapitulate over and over? This evolutionary structure—if any—would inform a reference model for fairer assessment, better maintenance, and improved forecasting of urban development. Using employment data including more than 100 million U.S. workers in all industries between 1998 and 2013, we empirically show that individual cities indeed recapitulate a common pathway where a transition to innovative economies is observed at the population of 1.2 million. This critical population is analytically derived by expressing the urban industrial structure as a function of scaling relations such that cities are divided into two economic categories: small city economies with sublinear industries and large city economies with superlinear industries. Last, we define a recapitulation score as an agreement between the longitudinal and the cross-sectional scaling exponents and find that nontradeable industries tend to adhere to the universal pathway more than the tradeable.

The universal pathway to innovative urban economies

Large-scale collaborative projects recently demonstrated that several key findings from the social-science literature could not be replicated successfully. Here, we assess the extent to which a finding’s replication success relates to its intuitive plausibility. Each of 27 high-profile social-science findings was evaluated by 233 people without a Ph.D. in psychology. Results showed that these laypeople predicted replication success with above-chance accuracy (i.e., 59%). In addition, when participants were informed about the strength of evidence from the original studies, this boosted their prediction performance to 67%. We discuss the prediction patterns and apply signal detection theory to disentangle detection ability from response bias. Our study suggests that laypeople’s predictions contain useful information for assessing the probability that a given finding will be replicated successfully.

10.1177/2515245920919667

Laypeople Can Predict Which Social-Science Studies Will Be Replicated Successfully

10.1017/S0140525X1800064X

Zwaan, Etz, Lucas, and Donnelan (2017) argue convincingly that replication needs to be more mainstream. Here, I suggest three practices for achieving that goal: Incremental Replications, which are replications built into each experiment in a series of experiments; Reciprocal Replications, which are reciprocal arrangements of co-replications across labs, and Didactic Replications, which are replications used for training.

Three ways to make replication mainstream

Survey respondents experience depression, anxiety and programme delays.

Pandemic harms Canadian grad students’ research and mental health

Beyond factors such as age and sex, underlying aspects of biology and society influence disease severity

Why Some People Get Terribly Sick from COVID-19

However, with inadequate details on the trials and only superficial scrutiny by the public and scientific decision makers, the consequences have had disastrous effects on other clinical trial funding, permissions, recruitment, and interpretation.

10.1016/S2214-109X(20)30365-X

Clinical trials of disease stages in COVID 19: complicated and often misinterpreted

A new saliva-based diagnostic does not require a “brain-tickling” swab, and it can be used with a range of chemical reagents

COVID-19 Spit Tests Used by NBA Are Now Authorized by FDA

Clusters of infections traced to apartments and frat houses

Virtual Classes Can't Stop Explosion of Off-Campus Virus Cases

The COVID-19 pandemic has seen health and medical research promoted as countries establish resilient health systems and rapidly responsive prevention, detection, and treatment methods. However, the pandemic will probably negatively affect the capacity and outcomes of the health and medical research sector itself.1

10.1016/S0140-6736(20)31533-6

COVID-19's impact on Australia's health research workforce

A crucial area in which information overload is experienced is news consumption. Ever increasing sources and formats are becoming available through a combination of traditional and new (digital) media, including social media. In such an information and media rich environment, understanding how people access and manage news during a global health epidemic like COVID-19 becomes even more important. The designation of the current situation as an infodemic has raised concerns about the quality, accuracy and impact of information. Instances of misinformation are commonplace due, in part, to the speed and pervasive nature of social media and messaging applications in particular. This paper reports on data collected using media diaries from 15 university students in the United Arab Emirates documenting their news consumption in April 2020. Faced with a potentially infinite amount of information and news, participants demonstrate how they are managing news overload (MNO) using a number of complementary strategies. Results show that while consumption patterns vary, all diaries indicate that users’ ability to navigate the news landscape in a way that fulfils their needs is influenced by news sources; platform reliability and verification; sharing activity; and engagement with news.

10.3390/info11080375

Managing News Overload (MNO): The COVID-19 Infodemic

10.1177/1359105320951603

Honest disclosures of COVID-19 behaviors and symptoms is critical. A sample of adults on MTurk (N = 451, 20–82 years of age) were asked if they have concealed social distancing practices, COVID-19 symptoms, and quarantine instructions, as well as how they evaluated others’ COVID-19 concealment. Those who believed they had contracted COVID-19 engaged in greater rates of concealment and evaluated concealment more positively compared to those without the virus. As age and communal orientation increased, COVID-19 concealment behaviors decreased, and evaluations of this concealment were rated more negatively. Implications for public health initiatives and psychological theory on concealing health information is discussed.

Dishonesty during a pandemic: The concealment of COVID-19 information

As California enters another dangerous fire season, the COVID-19 pandemic has depleted the ranks of inmate fire crews that are a key component of the state’s efforts to battle out-of-control wildfires

California severely short on firefighting crews after COVID-19 lockdown at prison camps

n this issue of JAMA, Wang et al present evidence that universal masking of health care workers (HCWs) and patients can help reduce transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections

10.1001/jama.2020.13107

Universal Masking to Prevent SARS-CoV-2 Transmission—The Time Is Now

A study documenting an alarming rise in abuse-related head injuries among children in the United Kingdom adds to increasing evidence that the novel coronavirus pandemic and efforts to contain it are taking a serious toll on children.

10.1001/jama.2020.14433

Surge in Child Abuse, Harm During COVID-19 Pandemic Reported

10.1001/jama.2020.12187

Consideration of Mortality Related to Unemployment, Social Isolation, and Depression

Challenges Estimating Total Lives Lost in COVID-19 Decisions

10.31235/osf.io/58d6p

The COVID-19 pandemic has disordered the educational process across the globe, as schools suddenly had to provide their teaching in an online environment. One question that raised immediate concern is the potential effects of this forced and rapid digitalization on inequalities in the learning process by social class, migration background and sex. Elaborating on the literature on the digital divide, we study inequalities in digital preparedness of students and schools, before the pandemic took place. Using data from the International Computer and Information Literacy Study (ICILS) on seven countries, and the Teaching and Learning International Survey (TALIS) on 45 countries, both from 2018, we demonstrate that schools and students vary in their preparedness for digital education, but that school variation is not systematically related to the student composition by socioeconomic and migration background. More important drivers for a digital divide in corona-times are the ICT skills students have, which are strongly related to socioeconomic background (known as the second level of the digital divide). We found little evidence for a hypothesized ‘fourth level’ of the digital divide, which would result from social gradients in the preparedness of school environments for digital education.

The Digital Divide in Online Education. Inequality in Digital Preparedness of Students and Schools before the Start of the COVID-19 Pandemic

10.7326/M20-5126

My COVID-19

10.31234/osf.io/u74wc

Why do we adopt new rules, such as social distancing? While decades of psychology research stresses the importance of social influence on individual behaviour, many COVID-19 campaigns focused on convincing individuals that distancing is the right thing to do. In a global dataset (114 countries, n=6674), we investigated how social influences predict people’s adherence to distancing rules during the pandemic. Analyses showed that people practised distancing more when they thought their close social circle did so; this social influence mattered more than people thinking distancing was the right thing. People’s adherence also aligned with their fellow citizens’, but only if they deeply bonded with their country. Personal vulnerability to the disease predicted distancing more for people with larger social circles. Empathy, collective efficacy and collectivism also significantly predicted distancing. During crises, policymakers can achieve behavioural change by emphasising shared values and harnessing the social influence of close friends and relatives.

We distance most when we believe our social circle does

10.1038/s41562-020-0931-9

While severe social-distancing measures have proven effective in slowing the coronavirus disease 2019 (COVID-19) pandemic, second-wave scenarios are likely to emerge as restrictions are lifted. Here we integrate anonymized, geolocalized mobility data with census and demographic data to build a detailed agent-based model of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission in the Boston metropolitan area. We find that a period of strict social distancing followed by a robust level of testing, contact-tracing and household quarantine could keep the disease within the capacity of the healthcare system while enabling the reopening of economic activities. Our results show that a response system based on enhanced testing and contact tracing can have a major role in relaxing social-distancing interventions in the absence of herd immunity against SARS-CoV-2.

Modelling the impact of testing, contact tracing and household quarantine on second waves of COVID-19

10.31234/osf.io/q74e9

School closures due to the COVID-19 pandemic have disrupted the education of 91% of students worldwide. As a critical process in supporting young children’s resilience, play is increasingly recognised as a valuable pedagogical strategy within a shifting educational landscape during the pandemic. This study reports on findings from a survey on play in early childhood education of 309 early childhood teachers during primary school closures in Ireland. Eighty-two per cent of teachers recommended play strategies to parents during remote teaching and home schooling and almost all teachers (99%) intended to use play as a pedagogical strategy upon school reopening. Teachers believed play was an especially important pedagogical tool in supporting young children’s social-emotional development, learning and transition back to school. Over a third highlighted uncertainty surrounding capacity to use play upon school reopening given COVID-19 regulations, emphasizing the need for greater guidance to support teachers’ commitment to play-based pedagogical strategies.

Perspectives of early childhood teachers in Ireland on the role of play during the pandemic

10.31234/osf.io/su3nv

This study investigated the psychological impact of the COVID-19 pandemic in pregnant women from Bosnia and Herzegovina and Serbia during March and April 2020. 152 respondents filled out an online administered questionnaire assessing psychological impact of the COVID-19 pandemic, fear of COVID-19 infection and death, attachment styles, perceived social support and other relevant sociodemographic and life history variables. The results indicate that the COVID-19 pandemic significantly impacts the level of fear and overall psychological functioning of the pregnant women. Especially prone to increased stress reactions are those who have lower partner support, fearful and preoccupied attachment styles, and lower financial status. The results are discussed in terms of the need for a systemic approach to psychological screening for pregnant women. We also point out the need to carefully evaluate the use of the IES-R when applied to assess reactions to collectively experienced prolonged stressful events such as the pandemic.

Psychological impact of the COVID-19 pandemic on pregnant women in Bosnia and Herzegovina and Serbia

arXiv:2008.02413

Public transit is central to cultivating equitable communities. Meanwhile, the novel coronavirus disease COVID-19 and associated social restrictions has radically transformed ridership behavior in urban areas. Perhaps the most concerning aspect of the COVID-19 pandemic is that low-income and historically marginalized groups are not only the most susceptible to economic shifts but are also most reliant on public transportation. As revenue decreases, transit agencies are tasked with providing adequate public transportation services in an increasingly hostile economic environment. Transit agencies therefore have two primary concerns. First, how has COVID-19 impacted ridership and what is the new post-COVID normal? Second, how has ridership varied spatio-temporally and between socio-economic groups? In this work we provide a data-driven analysis of COVID-19's affect on public transit operations and identify temporal variation in ridership change. We then combine spatial distributions of ridership decline with local economic data to identify variation between socio-economic groups. We find that in Nashville and Chattanooga, TN, fixed-line bus ridership dropped by 66.9% and 65.1% from 2019 baselines before stabilizing at 48.4% and 42.8% declines respectively. The largest declines were during morning and evening commute time. Additionally, there was a significant difference in ridership decline between the highest-income areas and lowest-income areas (77% vs 58%) in Nashville.

Impact of COVID-19 on Public Transit Accessibility and Ridership

COVID Update June 28: August will be another twist in the road. That comes tomorrow. But I need to do something first. I’m reminded many people follow me for COVID info so I want to call out & atone for my mistakes. 1/

The evolutionary biologist on data manipulation, fake news, and the importance of using science as a lie detector

Carl Bergstrom: 'People are using data to bullshit'

We explore the role of social capital in the spread of the recent Covid-19 pandemic in independent analyses for Austria, Germany, Italy, the Netherlands, Sweden, Switzerland and the UK. Exploiting within-country variation, we show that a one standard deviation increase in social capital leads to 12% and 32% fewer Covid-19 cases per capita accumulated from mid-March until mid-May. Using Italy as a case study, we find that high-social-capital areas exhibit lower excess mortality and a decline in mobility. Our results have important implications for the design of local containment policies in future waves of the pandemic.

Social Capital and the Spread of COVID-19: Insights from European Countries

Exclusive: experts say decisions apparently being made on ideological grounds

Coronavirus: UK virologists criticise handling of Covid testing contracts

I was wrong. After reading many of the responses to my article, some of them outlining the risks in greater detail, I have concluded that (1) the risks are greater than I presented them, and (2) the benefits are not as great as I had thought.

I Was Wrong: We Can’t Skip Phase 3 Vaccine Trials

The threat of coronavirus should kindle global cooperation, not a new cold war

This wave of anti-China feeling masks the west's own Covid-19 failures

BackgroundHealth-care workers are thought to be highly exposed to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We aimed to investigate the prevalence of antibodies against SARS-CoV-2 in health-care workers and the proportion of seroconverted health-care workers with previous symptoms of COVID-19.MethodsIn this observational cohort study, screening was offered to health-care workers in the Capital Region of Denmark, including medical, nursing, and other students who were associated with hospitals in the region. Screening included point-of-care tests for IgM and IgG antibodies against SARS-CoV-2. Test results and participant characteristics were recorded. Results were compared with findings in blood donors in the Capital Region in the study period.FindingsBetween April 15 and April 23, 2020, we screened 29 295 health-care workers, of whom 28 792 (98·28%) provided their test results. We identified 1163 (4·04% [95% CI 3·82–4·27]) seropositive health-care workers. Seroprevalence was higher in health-care workers than in blood donors (142 [3·04%] of 4672; risk ratio [RR] 1·33 [95% CI 1·12–1·58]; p<0·001). Seroprevalence was higher in male health-care workers (331 [5·45%] of 6077) than in female health-care workers (832 [3·66%] of 22 715; RR 1·49 [1·31–1·68]; p<0·001). Frontline health-care workers working in hospitals had a significantly higher seroprevalence (779 [4·55%] of 16 356) than health-care workers in other settings (384 [3·29%] of 11 657; RR 1·38 [1·22–1·56]; p<0·001). Health-care workers working on dedicated COVID-19 wards (95 [7·19%] of 1321) had a significantly higher seroprevalence than other frontline health-care workers working in hospitals (696 [4·35%] of 15 983; RR 1·65 [1·34–2·03]; p<0·001). 622 [53·5%] of 1163 seropositive participants reported symptoms attributable to SARS-CoV-2. Loss of taste or smell was the symptom that was most strongly associated with seropositivity (377 [32·39%] of 1164 participants with this symptom were seropositive vs 786 [2·84%] of 27 628 without this symptom; RR 11·38 [10·22–12·68]). The study is registered at ClinicalTrials.gov, NCT04356560.InterpretationThe prevalence of health-care workers with antibodies against SARS-CoV-2 was low but higher than in blood donors. The risk of SARS-CoV-2 infection in health-care workers was related to exposure to infected patients. More than half of seropositive health-care workers reported symptoms attributable to COVID-19.FundingLundbeck Foundation.

10.1016/S1473-3099(20)30589-2

Risk of COVID-19 in health-care workers in Denmark: an observational cohort study

AMID rising global numbers of daily coronavirus infections, a fresh flush of vaccine trial results is offering hope for the longer run

Coronavirus vaccine hope rises after a flurry of positive results

Restricting movement on the basis of biology threatens freedom, fairness and public health.

Ten reasons why immunity passports are a bad idea

arXiv:2007.06975

The contact structure of a population plays an important role in transmission of infection. Many ``structured models'' capture aspects of the contact structure through an underlying network or a mixing matrix. An important observation in such models, is that once a fraction 1−1/01-1/\mathcal{R}_0 has been infected, the residual susceptible population can no longer sustain an epidemic. A recent observation of some structured models is that this threshold can be crossed with a smaller fraction of infected individuals, because the disease acts like a targeted vaccine, preferentially immunizing higher-risk individuals who play a greater role in transmission. Therefore, a limited ``first wave'' may leave behind a residual population that cannot support a second wave once interventions are lifted. In this paper, we systematically analyse a number of mean-field models for networks and other structured populations to address issues relevant to the Covid-19 pandemic. In particular, we consider herd-immunity under several scenarios. We confirm that, in networks with high degree heterogeneity, the first wave confers herd-immunity with significantly fewer infections than equivalent models with lower degree heterogeneity. However, if modelling the intervention as a change in the contact network, then this effect might become more subtle. Indeed, modifying the structure can shield highly connected nodes from becoming infected during the first wave and make the second wave more substantial. We confirm this finding by using an age-structured compartmental model parameterised with real data and comparing lockdown periods implemented either as a global scaling of the mixing matrix or age-specific structural changes. We find that results regarding herd immunity levels are strongly dependent on the model, the duration of lockdown and how lockdown is implemented.

The impact of network properties and mixing on control measures and disease-induced herd immunity in epidemic models: a mean-field model perspective

Anatomy of digital contact tracing: role of age, transmission setting, adoption and case detection

10.1101/2020.07.22.20158352