A 2009 novel predicted the Chinese people would forget a traumatic crisis. The puzzle, says its author, is how it happened so fast.

In a review of existing research, psychological scientist David Rapp (Northwestern University) explains that people encode the inaccurate statements into memory because it’s easier than critically evaluating and analyzing what they’ve heard

When effectively implemented at scale, Test, Trace, Isolate (TTI) can contribute to controlling the UK COVID-19 epidemic, but only as part of a wider package of public health interventions, including physical and social distancing, control of infection procedures, outbreak investigation and control. TTI is most effective in breaking chains of transmission, and reducing the effective reproductive number (Re), when there is maximum: (i) speed, i.e., quick turn-around of both index case testing and contact tracing (and testing); (ii) compliance, i.e., a high proportion of people in each chain are willing and able to follow guidance; and (iii) coverage, i.e., identification of most chains through integration of consistent case data and real-time, high-precision population surveillance. Each of these three aspects of TTI needs careful attention, as do the trade-offs implicit in choices of how precisely to implement TTI in terms of who to test, trace and isolate, and when to do so. Based on our modelling work, we confirm that social distancing and self-isolation of symptomatic individuals and quarantine of their household contacts has a substantial impact on the number of new infections generated by each index case. We further show that adding contact tracing for extra-household contacts of confirmed cases to this broader package of interventions reduces the number of new infections otherwise generated by 5-15%. The upper end of this range represents scenarios where the overall test and trace period for contacts has been reduced from five days to three days. Furthermore, the level of compliance with TTI guidance strongly affects its usefulness, as there are many steps in the TTI system at which cases and contacts can be lost. Phone-based apps may be able to increase TTI speed and compliance but is likely to be an adjunct to a manual TTI system. Both incentives and clear messaging relating to TTI participation and compliance with isolation measures are also likely to be needed to maximize TTI’s effectiveness. TTI and surveillance systems are mutually beneficial, since TTI can capture important data on index cases and contacts, while surveillance can provide indications of who/where to target for testing, even when they are not part of an identified transmission chain. Finally, TTI will require substantial coordination across a wide range of organizations, including central and local government departments, PHE, the NHS and business groups. In particular, local integration of systems is likely to maximize ability to conduct the agile, locally differentiated outbreak management that may be needed as the epidemic evolves.

Self-isolation is a vital element of efforts to contain COVID-19. We report an online experiment with a nationally representative sample (N=500) that tested behaviourally informed decision aids to support self-isolation. The experiment had three stages that tested interventions designed to help individuals to: (i) decide whether they need to self-isolate; (ii) be confident in their ability to self-isolate should they need to; and (iii) manage a household in which an individual needs to self-isolate. Relative to prevailing public health advice, displaying decision trees improved participants’ decisions about when self-isolation was necessary, although they systematically underestimated the need to self-isolate in the presence of less common COVID-19 symptoms (e.g. sore throat, fatigue). Interaction with an online planning tool increased confidence about coping with self-isolation among adults aged under 40. Presenting advice in the form of infographics improved recall and comprehension of how to manage self-isolation. The study demonstrates how public health policy can benefit from behavioural pre-testing of interventions.

This study anonymously examined 2,734 psychiatric patients worldwide for worsening of their pre-existing psychiatric condition during the COVID-19 pandemic. Valid responses mainly from 12 featured countries indicated self-reported worsening of psychiatric conditions in 2/3rd of the patients assessed that was validated through their significantly higher scores on scales for general psychological disturbance, posttraumatic stress disorder, and depression. Female gender, feeling no control of the situation and reporting dissatisfaction with the response of the state during the COVID- 19 pandemic, and reduced interaction with family and friends increased the worsening of pre-existing psychiatric conditions, whereas optimism, ability to share concerns with family and friends and using social media like usual were associated with less worsening. An independent clinical investigation from the USA confirmed worsening of psychiatric conditions during the COVID-19 pandemic based on identification of new symptoms that necessitated clinical interventions such as dose adjustment or starting new medications in more than half of the patients.

In The Lancet Public Health, Eloi Marijon and colleagues suggest that out-of-hospital cardiac arrest (OHCA) might be affected directly and indirectly by the COVID-19 pandemic.1Marijon E Karam N Jost D et al.Out-of-hospital cardiac arrest during the COVID-19 pandemic in Paris, France: a population-based, observational study.Lancet Public Health. 2020; (published online May 27.)https://doi.org/10.1016/S2468-2667(20)30117-1Google Scholar The authors used the Paris-Sudden Death Expertise Center registry to compare OHCA case incidence and patient characteristics from a 6-week period during the COVID-19 pandemic in Paris and its suburbs (March 16 to April 26, 2020) with corresponding periods over the preceding 8 years. The rapid publication of this Article shows the value of cardiac arrest registries and other disease registries in highlighting changes in practice and informing policy interventions.During the 6-week pandemic period in Paris, OHCA incidence approximately doubled from a baseline of 13·42 (95% CI 12·77–14·07) to 26·64 (25·72–27·53) per million inhabitants. The incidence of OHCA rose in parallel with the incidence of COVID-19 related hospital admissions. Similar patterns in OHCA incidence have been observed in the Lombardy region of Italy2Baldi E Sechi GM Mare C et al.Out-of-hospital cardiac arrest during the Covid-19 outbreak in Italy.N Engl J Med. 2020; (DOI:NEJMc2010418 published online April 29.)Crossref PubMed Google Scholar and California, USA.3Wong LE Hawkins JE Langness S et al.Where are all the patients? Addressing Covid-19 fear to encourage sick patients to seek emergency care.NEJM Catalyst Innovations in Care Delivery. 2020; 1: 3Google Scholar Importantly, in the study by Marijon and colleagues, OHCA incidence decreased towards baseline near the end of the 6-week period in line with a decrease in COVID-19 incidence.

Human behavior is one of the most important factors dictating the severity of pandemics for both the spread of the disease and the psychological impacts it triggers, such as anxiety, isolation, and uncertainty. Through an ongoing series of backgrounders, the Association for Psychological Science (APS) is exploring many of the psychological factors that can help the public understand and collectively combat the spread of COVID-19. Each backgrounder features the assessments, research, and recommendations of a renowned subject expert in the field of psychological science. This content has not undergone separate peer review and is provided as a service to the public during this time of pandemic. APS has published additional content on Myths and Misinformation.

When faced with a threat, peoples’ estimate of risk guides their response. When danger is to the self as well as to others two estimates are generated: the risk to oneself and the risk to others. As these estimates likely differ, it is unclear how exactly they drive a response. To answer this question, we studied a large representative sample of Americans facing the COVID-19 pandemic at two time points (N1=1145, N2=683). We discover a paradoxical duality: a tendency to be optimistic about one’s own risk of infection (private optimism) while at the same time to be pessimistic about the risk to others (public pessimism). These two estimates were found to be differentially related to affect and choice. First, private optimism, but not public pessimism, was associated with people’s positive feelings. The association between private optimism and positive affect was mediated by people’s sense of agency over their future. However, negative affect was related to both private risk perception and public risk perception. Second, people predominantly engaged in protective behaviors based on their estimated risk to the population rather than to themselves. This suggests that people were predominantly engaging in protective behaviors for the benefit of others. The findings are important for understanding how people’s beliefs about their own future and that of others are related to protective behaviors and well-being.

Jeremy Farrar explains why humanity may simply have to learn to live with Covid-19, why he wishes there were *more* government advisers in scientific meetings—and why he thinks it is still too early to reopen schools

This questionnaire explores the barriers and enablers to pre-registration. Pre-registration is the practice of submitting a research plan to a public online repository, prior to the research being undertaken.

As meta-analytic studies have come to occupy a sizable contingent of published work in the psychological sciences, clarity in the research and reporting practices of such work is crucial to the interpretability and reproducibility of research findings. The present study examines the state of research and reporting practices within a random sample of 384 published psychological meta-analyses across several important dimensions (e.g., search methods, exclusion criteria, statistical techniques). In addition, we surveyed the first authors of the meta-analyses in our sample to ask them directly about the research practices employed and reporting decisions made in their studies, including the assessments and procedures they conducted and the guidelines or materials they relied on. Upon cross-validating the first author responses with what was reported in their published meta-analyses, we identified numerous potential gaps in reporting and research practices. In addition to providing a survey of recent reporting practices, our findings suggest that (a) there are several research practices conducted by meta-analysts that are ultimately not reported; (b) some aspects of meta-analysis research appear to be conducted at disappointingly low rates; and (c) the adoption of the reporting standards, including the Meta-Analytic Reporting Standards (MARS), has been slow to nonexistent within psychological meta-analytic research.

When making decisions in complex environments we must selectively sample and process information with respect to task demands. Previous studies have shown that this requirement can manifest in the influence that extreme outcomes (i.e. values at the edges of a distribution) have on judgment and choice. We elucidate this influence via a task in which participants are presented, briefly, with an array of numbers and have to make one of two judgments. In ‘preferential’ judgments where the participants’ goal was to choose between a safe, known outcome, and an unknown outcome drawn from the array, extreme-outcomes had a greater influence on choice than mid-range outcomes, especially under shorter time-limits. In ‘perceptual’ judgments where the participants' goal was to estimate the arrays’ average, the influence of the extremes was less pronounced. A novel cognitive process model captures these patterns via a two-step selective-sampling and integration mechanism. Together our results shed light on how task goals modulate sampling from complex environments, show how sampling determines choice, and highlight the conflicting conclusions that arise from applying statistical and cognitive models to data.

BackgroundScoping reviews are a relatively new approach to evidence synthesis and currently there exists little guidance regarding the decision to choose between a systematic review or scoping review approach when synthesising evidence. The purpose of this article is to clearly describe the differences in indications between scoping reviews and systematic reviews and to provide guidance for when a scoping review is (and is not) appropriate.ResultsResearchers may conduct scoping reviews instead of systematic reviews where the purpose of the review is to identify knowledge gaps, scope a body of literature, clarify concepts or to investigate research conduct. While useful in their own right, scoping reviews may also be helpful precursors to systematic reviews and can be used to confirm the relevance of inclusion criteria and potential questions.ConclusionsScoping reviews are a useful tool in the ever increasing arsenal of evidence synthesis approaches. Although conducted for different purposes compared to systematic reviews, scoping reviews still require rigorous and transparent methods in their conduct to ensure that the results are trustworthy. Our hope is that with clear guidance available regarding whether to conduct a scoping review or a systematic review, there will be less scoping reviews being performed for inappropriate indications better served by a systematic review, and vice-versa.

Analysts are tracking false rumours about COVID-19 in hopes of curbing their spread.

In this commentary, I argue that the mental health impact of COVID-19 will show substantial variation across individuals, contexts, and time. Further, one key contributor to this variation will be the proximal and long-term impact of COVID-19 on the social environment. In addition to the mental health costs of the pandemic, it is likely that a subset of people will experience improved social and mental health functioning.

Masks and testing are necessary to combat asymptomatic spread in aerosols and droplets

Human proximity networks are temporal networks representing the close-range proximity among humans in a physical space. They have been extensively studied in the past 15 years as they are critical for understanding the spreading of diseases and information among humans. Here we address the problem of mapping human proximity networks into hyperbolic spaces. Each snapshot of these networks is often very sparse, consisting of a small number of interacting (i.e., non-zero degree) nodes. Yet, we show that the time-aggregated representation of such systems over sufficiently large periods can be meaningfully embedded into the hyperbolic space, using existing methods developed for traditional complex networks. We justify this compatibility theoretically and validate it experimentally. We produce hyperbolic maps of six different real systems, and show that the maps can be used to identify communities, facilitate efficient greedy routing on the temporal network, and predict future links with significant precision.

Heterogeneity is an important concept in psychiatric research and science more broadly. It negatively impacts effect size estimates under case-control paradigms, and it exposes important flaws in our existing categorical nosology. Yet, our field has no precise definition of heterogeneity proper. We tend to quantify heterogeneity by measuring associated correlates such as entropy or variance: practices which are akin to accepting the radius of a sphere as a measure of its volume. Under a definition of heterogeneity as the degree to which a system deviates from perfect conformity, this paper argues that its proper measure roughly corresponds to the size of a system’s event/sample space, and has units known as numbers equivalent. We arrive at this conclusion through focused review of more than 100 years of (re)discoveries of indices by ecologists, economists, statistical physicists, and others. In parallel, we review psychiatric approaches for quantifying heterogeneity, including but not limited to studies of symptom heterogeneity, microbiome biodiversity, cluster-counting, and time-series analyses. We argue that using numbers equivalent heterogeneity measures could improve the interpretability and synthesis of psychiatric research on heterogeneity. However, significant limitations must be overcome for these measures—largely developed for economic and ecological research—to be useful in modern translational psychiatric science.

Machine learning algorithms hold promise in revolutionizing how educators and clinicians make decisions. However, researchers in behavior analysis have been slow to adopt this methodology to further develop their understanding of human behavior and improve the application of the science to problems of applied significance. One potential explanation for the scarcity of research is that machine learning is not typically taught as part of training programs in behavior analysis. This tutorial aims to address this barrier by promoting increased research using machine learning in behavior analysis. First, we present how to apply the random forest, support vector machine, stochastic gradient descent, and k-nearest neighbors algorithms on a small dataset to better identify parents who would benefit from a behavior analytic online training. Second, we use artificial neural networks to develop a model that automatically analyzes ABAB graphs. Together, these examples should allow researchers to apply machine learning algorithms to novel research questions and datasets.

This chapter from the forthcoming NATO SAS-114 final report examines the standards used in the US and UK to communicate probability in intelligence analysis in light of the extant literature on the communication of uncertainty.

COVID-19 data is often presented using graphs with either a linear or logarithmic scale. Given the importance of this information, understanding how choice of scale changes interpretations is critical. To test this, we presented laypeople with the same data plotted using differing scales. We found that graphs with a logarithmic, as opposed to linear, scale resulted in laypeople making less accurate predictions of growth, viewing COVID-19 as less dangerous, and expressing both less support for policy interventions and less intention to take personal actions to combat COVID-19. Education reduces, but does not eliminate these effects. These results suggest that public communications should use logarithmic graphs only when necessary, and such graphs should be presented alongside education and linear graphs of the same data whenever possible.

The article ‘An analysis of SARS-CoV-2 viral load by patient age’ by Jones et al. claims that “viral loads in the very young do not differ significantly from those of adults. ”, and the authors “caution against an unlimited re-opening of schools and kindergartens in the present situation. Children may be as infectious as adults.” It has been widely reported as implying that viral loads in children are similar to adults, and yet the data in the article show children between 1 and 10 having on average 27% (conservative 95% interval 8% to 91%) of the viral load of adults aged over 20. We show how inappropriate statistical analysis led to the authors’ unjustified conclusions: essentially, in spite of initially finding a statistically significant difference between subgroups, they made it disappear by doing so many additional and uninteresting comparisons. We recommend that the error is acknowledged and the paper is withdrawn from circulation.

It was a tragedy for anyone hoping to see COVID-19 become a catalyst for international solidarity. On the first day of the first-ever virtual World Health Assembly, held during the worst acute global health crisis since WHO's creation in 1948, Alex Azar, US Secretary of Health and Human Services, further damaged the credibility of the US Government as a constructive member of the international community. “We must be frank”, he began. What followed was an astonishing series of unsubstantiated allegations. “There was a failure by this organisation”, Azar stated. He argued that WHO had conspired with a member state (he meant China) “in an apparent attempt to conceal this outbreak”. He accused WHO of unjustly blocking Taiwan's participation at the World Health Assembly. And he said “WHO must change.” It must be more transparent and more accountable. Earlier, WHO Director-General Tedros Adhanom Ghebreyesus gave a forceful defence of the agency. He accepted that “we all have lessons to learn”, but argued that WHO had stood “shoulder-to-shoulder with countries”. The agency had acted quickly, Tedros said. He promised to initiate an “independent evaluation” of the global response. “The world must never be the same.” There was no need for new plans, procedures, or institutions. What mattered now was to strengthen existing mechanisms, especially national public health capacities specified in the 2005 International Health Regulations. Investing in health was a prerequisite for development. To protect the world from future pandemics, Tedros called on member states to support a stronger WHO. In the speeches that followed, countries repeatedly backed WHO and the Director-General. China stressed that it acted in a timely, open, transparent, and responsible manner. Some countries went further, denouncing the unilateral and coercive actions of the US Government.

Objectives: In Germany, as in many other countries, several lockdown restrictions were put in place with the aim of curbing the spread of SARS-CoV-2 infections. This study investigated the impact of the coronavirus pandemic and the related lockdown restrictions on opportunities for social participation, social inclusion and psychological well-being for adults with and without mental disorders within a follow-up study based on pre- and post-lockdown assessments. Methods: Study participants (n=132) were assigned to one of three groups, depending on the mental health status at the initial survey. Parameters of interest were assessed using the Measure of Participation and Social Inclusion for Use in People with a Chronic Mental Disorder (F-INK), the Index for the Assessment of Health Impairments (IMET), and the Brief Symptom Inventory (BSI-18). Results: The impact on opportunities for social participation and social participation considerably differed depending on the participants’ mental health status at the first assessment. Independent of this, we found no detrimental effects on the psychological well-being of participants four weeks after the implementation of lockdown restrictions. Conclusion: Findings imply a general resilience in well-being during the preliminary stages of the coronavirus pandemic. This is in good accordance with the literature that has so far been published.

In this tutorial, we describe a workflow to ensure long-term reproducibility of R-based data analyses. The workflow leverages established tools and practices from software engineering. It combines the benefits of various open-source software tools including R Markdown, Git, Make, and Docker, whose interplay ensures seamless integration of version management, dynamic report generation conforming to various journal styles and full cross-platform and long-term computational reproducibility. The workflow ensures meeting the primary goals that 1) the reporting of statistical results is consistent with the actual statistical results (dynamic report generation), the analysis exactly reproduces at a later time even if the computing platform or software is changed (computational reproducibility), and 3) changes at any time (during development and post-publication) are tracked, tagged, and documented while earlier versions of both data and code remain accessible. While the research community increasingly recognizes dynamic document generation and version management as tools to ensure reproducibility, we demonstrate with practical examples that these alone are not sufficient to ensure long-term computational reproducibility. Leveraging containerization, dependence management, version management, and literate programming, the workflow increases scientific productivity by facilitating later reproducibility and reuse of code and data.

A novel coronavirus, SARS-CoV-2, has spread widely throughout the world. To reduce the spread of infection, children are prevented from going to school and have fewer opportunities for in-person communication. Although the pandemic has impacted the everyday lives of children, its impact on their development is unknown. This pre-registered study compared Japanese children’s socio-emotional skills and skills for operating digital devices before and during the pandemic. Parents completed a web-based questionnaire before and during the pandemic for children ages 0-9. The results indicated that during the pandemic, children were more prosocial, experienced more problems in their peer relationships, and had better digital skills, but no differences were found in emotional symptoms, conduct problems, hyperactivity between before and during the pandemic. The change in digital skills was mediated by the duration of children’s media use. Overall, our results suggest the pandemic may have immediate impact on children’s socio-emotional and digital skills.

In this first piece, I’ll unpack the assumptions and reasoning that underlie my current view of applied behavioural science. In the second piece, I build on this view by proposing a set of paths to consider going forward.

Open science has become a catch all term to describe the many different ways in which digital networked communication technologies have opened and begun to transform research and scholarship across different disciplines, even those outside of the sciences. Whilst this term has been useful, Marcel Knöchelmann argues that for the humanities to successfully adopt digital technologies, rather than have them imposed upon them, they need to develop an independent open humanities discourse.

The World Pandemic Research Network (WPRN) is a platform serving research communities. It maintains a searchable global directory of the scientific resources available on the societal and human impacts of the Covid-19 pandemic. It shows who works on what, where, in real time, at global level. Designed and maintained by researchers, WPRN is free, non-profit, public-funded, open (creative commons, open-source), GDPR compliant. It is steered by an international Advisory Board and supported by major scientific institutions and scientific networks worldwide. WPRN is the product of a collective scientific intelligence, with validation by senior scholars who act as referents in their fields. Register your project on the WPRN platform to get a time-stamped ID that will facilitate scientific collaboration and citation, even before publication.

While the pandemic has dealt travel a severe blow, some hope it can be an opportunity to introduce slower, fairer, more sustainable holidays

Defensive responses to threatening situations vary with threat imminence, but it is unknown how those responses affect decisions to help others. Here, we manipulated threat imminence to investigate the impact of different defensive states on helping behaviour. Ninety-eight participants made trial-by-trial decisions about whether to help a co-participant avoid an aversive shock, at the risk of receiving a shock themselves. Helping decisions were prompted under imminent or distal threat, based on temporal distance to the moment of shock administration to the co-participant. Results showed that, regardless of how likely participants were to also receive a shock, they helped the co-participant more under imminent than distal threat. Individual differences in empathic concern were specifically correlated with helping during imminent threats. These results suggest defensive states driving active escape from immediate danger also facilitate decisions to help others, potentially by engaging neurocognitive systems implicated in caregiving across mammals.

Universities around the world are incorporating online learning, often relying upon videos (asynchronous multimedia). We systematically reviewed the effects of video on learning in higher education. We searched five databases using 27 keywords to find randomised trials that measured the learning effects of video among college students. We conducted full-text screening, data-extraction, and risk of bias in duplicate. We calculated pooled effect-sizes using multi-level random-effects meta-analysis. Searches retrieved 9,677 unique records. After screening 329 full-texts, 103 met inclusion criteria, with a pooled sample of 7,776 students. Swapping video for existing teaching methods led to small improvements in student learning (g = 0.28). Adding video to existing teaching led to strong learning benefits (g = 0.80). Although results may be subject to some experimental and publication biases, they suggest that videos are unlikely to be detrimental and usually improve student learning.

Exclusive: Australian researchers query origin of data used for Lancet study, but stress there is no evidence drug is a safe or effective treatment

Macmillan warns of ‘ticking time bomb’ with evidence of treatment being delayed and cancelled due to Covid-19

Information is key during a crisis such as the current COVID-19 pandemic as it greatly shapes people opinion, behaviour and even their psychological state. It has been acknowledged from the Secretary-General of the United Nations that the infodemic of misinformation is an important secondary crisis produced by the pandemic. Infodemics can amplify the real negative consequences of the pandemic in different dimensions: social, economic and even sanitary. For instance, infodemics can lead to hatred between population groups that fragment the society influencing its response or result in negative habits that help the pandemic propagate. On the contrary, reliable and trustful information along with messages of hope and solidarity can be used to control the pandemic, build safety nets and help promote resilience and antifragility. We propose a framework to characterize leaders in Twitter based on the analysis of the social graph derived from the activity in this social network. Centrality metrics are used to identify relevant nodes that are further characterized in terms of users parameters managed by Twitter. We then assess the resulting topology of clusters of leaders. Although this tool may be used for surveillance of individuals, we propose it as the basis for a constructive application to empower users with a positive influence in the collective behaviour of the network and the propagation of information.

Citizens Advice warns of lack of safety net for many of the 2.5 million ordered to shield at home

A medical study in France suggests even mild cases of coronavirus infection, not requiring hospital treatment, produce antibodies in almost all patients, with the body’s defences against the virus increasing during the weeks of recovery.

Network-based intervention strategies can be effective and cost-efficient approaches to curtailing harmful contagions in myriad settings. As studied, these strategies are often impractical to implement, as they typically assume complete knowledge of the network structure, which is unusual in practice. In this paper, we investigate how different immunization strategies perform under realistic conditions where the strategies are informed by partially-observed network data. Our results suggest that global immunization strategies, like degree immunization, are optimal in most cases; the exception is at very high levels of missing data, where stochastic strategies, like acquaintance immunization, begin to outstrip them in minimizing outbreaks. Stochastic strategies are more robust in some cases due to the different ways in which they can be affected by missing data. In fact, one of our proposed variants of acquaintance immunization leverages a logistically-realistic ongoing survey-intervention process as a form of targeted data-recovery to improve with increasing levels of missing data. These results support the effectiveness of targeted immunization as a general practice. They also highlight the risks of considering networks as idealized mathematical objects: overestimating the accuracy of network data and foregoing the rewards of additional inquiry.

One of the most popular narratives about the evolution of law is its perpetual growth in size and complexity. We confirm this claim quantitatively for the federal legislation of two industrialised countries, finding impressive expansion in the laws of Germany and the United States over the past two and a half decades. Modelling 25 years of legislation as multidimensional, time-evolving document networks, we investigate the sources of this development using methods from network science and natural language processing. To allow for cross-country comparisons, we reorganise the legislative materials of the United States and Germany into clusters that reflect legal topics. We show that the main driver behind the growth of the law in both jurisdictions is the expansion of the welfare state, backed by an expansion of the tax state.

On this page you will find information about:WHO interim guidance for laboratory testingWHO interim guidance for laboratory biosafety related to COVID-19 virusMolecular assays to diagnose COVID-19 virusWHO refence laboratories providing confirmatory testing for COVID-19Guidance for laboratories shipping specimens to WHO reference laboratories that provide confirmatory testing for COVID-19 virusLaboratory Assessment Tool for laboratories implementing COVID-19 testingScientific brief: Advice on the use of point-of-care immunodiagnostic tests for COVID-19

北海道の鈴木直道知事は28日、新型コロナウイルスの感染拡大を受けて今週末の外出自粛を求める「新型コロナウイルス緊急事態宣言」を出した。北海道内の新型ウイルス感染者は28日も12人増え、66人と全国最多の水準。鈴木知事は道の対策会議で「これまでにない思い切った対策が必要。今が山場」と述べた。

Objective: To identify common features of cases with novel coronavirus disease (COVID-19) so as to better understand what factors promote secondary transmission including superspreading events. Methods: A total of 110 cases were examined among eleven clusters and sporadic cases, and investigated who acquired infection from whom. The clusters included four in Tokyo and one each in Aichi, Fukuoka, Hokkaido, Ishikawa, Kanagawa and Wakayama prefectures. The number of secondary cases generated by each primary case was calculated using contact tracing data. Results: Of the 110 cases examined, 27 (24.6%) were primary cases who generated secondary cases. The odds that a primary case transmitted COVID-19 in a closed environment was 18.7 times greater compared to an open-air environment (95% confidence interval [CI]: 6.0, 57.9). Conclusions: It is plausible that closed environments contribute to secondary transmission of COVID-19 and promote superspreading events. Our findings are also consistent with the declining incidence of COVID-19 cases in China, as gathering in closed environments was prohibited in the wake of the rapid spread of the disease.

InJapan,sporadiccasesofsmallnumbersofpatientshavebeenobserved.Atthisstage,thespreadofinfectioncanbepreventedbytracingtherouteoftransmission,especiallyforclosecontacts.The important thing is to minimize the spread of infection in the country by: preventing one cluster of patients from creating another cluster

Japan's basic strategy for preventing the spread of infection The three pillars of Japan's strategy are, "early detection of and early response to clusters," "early patient diagnosis and enhancement of intensive care and the securing of a medical service system for the severely ill," and "behavior modification of citizens." This strategy is in line with the strategy recommended by the World Health Organization (WHO).

A team of researchers unveiled the results of a new study last week that looked at how temperature and humidity may affect the transmission of COVID-19, the illness caused by the new coronavirus.

The United States and Europe have stopped hitting the snooze button. After 2 months of mostly waiting and seeing while the coronavirus disease 2019 (COVID-19) alarm sounded ever more loudly, many countries have suddenly implemented strict measures to slow the spread of the disease, which the World Health Organization (WHO) officially declared a pandemic on 13 March. Thousands of events have been canceled; schools, restaurants, bars, and clubs have been closed; and transit systems are at a standstill.The countries saw little choice. The case numbers exploded, and, in turn, so did the number of deaths. Hospitals in Italy, the hardest hit European country, are overburdened, forcing doctors to make agonizing decisions about whom to treat and on whom to give up. “This is bad,” U.S. President Donald Trump finally acknowledged on 16 March. “This is war,” his counterpart Emmanuel Macron told the French people the same day.But how to fight that war is still under discussion. The hastily introduced measures vary widely between countries and even within countries. The U.S. government advises against gatherings of more than 10 people, but San Francisco has ordered everyone to stay at home. Italy, France, and Spain have put their populations on an almost complete lockdown, with police or the military in some places patrolling the streets, but as Science went to press, pubs in the United Kingdom remained open. Germany, like many countries, has shut its schools, but they remain open for younger children in Sweden.The patchwork reflects different phases of the epidemic, as well as differences in resources, cultures, governments, and laws. But there's also confusion about what works best, and how to balance what is necessary with what is reasonable, especially for an extended period. South Korea, Hong Kong, and Singapore seem to hold important lessons, having turned their epidemics around without the authoritarian tactics used by China. Yet some of the strategies adopted in those countries are missing elsewhere: widespread testing to find cases, tracing their contacts to test or quarantine them, and encouraging—or forcing—infected people to isolate themselves.No single step will suffice, WHO Director-General Tedros Adhanom Ghebreyesus stressed at a recent press conference. “Not testing alone. Not contact tracing alone. Not quarantine alone. Not social distancing alone. Do it all.”

A cluster of coronavirus cases connected to clubs frequented by South Korea's gay community has sparked an outpouring of hate speech towards the country's already-embattled LGBTQ population.

The novel coronavirus disease (COVID-19) has become a pandemic affecting health and wellbeing globally. In addition to the physical health, economic, and social implications, the psychological impacts of this pandemic are increasingly being reported in the scientific literature. This narrative review reflected on scholarly articles on the epidemiology of mental health problems in COVID-19. The current literature suggests that people affected by COVID-19 may have a high burden of mental health problems, including depression, anxiety disorders, stress, panic attack, irrational anger, impulsivity, somatization disorder, sleep disorders, emotional disturbance, posttraumatic stress symptoms, and suicidal behavior. Moreover, several factors associated with mental health problems in COVID-19 are found, which include age, gender, marital status, education, occupation, income, place of living, close contact with people with COVID-19, comorbid physical and mental health problems, exposure to COVID-19 related news and social media, coping styles, stigma, psychosocial support, health communication, confidence in health services, personal protective measures, risk of contracting COVID-19, and perceived likelihood of survival. Furthermore, the epidemiological distribution of mental health problems and associated factors were heterogeneous among the general public, COVID-19 patients, and healthcare providers. The current evidence suggests that a psychiatric epidemic is cooccurring with the COVID-19 pandemic, which necessitates the attention of the global health community. Future epidemiological studies should emphasize on psychopathological variations and temporality of mental health problems in different populations. Nonetheless, multipronged interventions should be developed and adopted to address the existing psychosocial challenges and promote mental health amid the COVID-19 pandemic.

Institutions are letting their financial and reputational worries cloud their judgment about when they can safely reopen.

Our health and lives cannot be ruled by market forces alone. Now thousands of scholars are calling for a way out of the crisis

All participants reported an increase in concern after reading articles about Triclosan. But participants in the stress group — who had higher levels of cortisol — were less influenced by the articles, showing a smaller increase in concern than those in the control group. They were also less likely to share alarming information in their messages to other participants. The bigger the increase in cortisol, the smaller the increase in concern. But those who reported subjective feelings of stress — even if unrelated to the task at hand — were both more concerned and more likely to share alarming information.

Covid-19 pandemic is exerting a tragic impact all around the world. First-person experience of life-threatening and stressful events can modify individuals’ risk perception, and, consequently, risk-taking behaviours. Here we investigated risk-taking profiles in 130 Italian residents, and compared healthcare to non-healthcare workers, during the lockdown phase. We ad hoc developed the “Covid-19 Risk Task”, including the classic monetary Holt-Laury Paired Lottery Task (Monetary Condition, MC) and two new ecological conditions exploring Covid-19 related risk-taking aptitudes in relation to different health (Health Status Condition, HsC) and employment (Employment Status Condition, EsC) outcomes. Results showed that, in the whole sample, individuals were more risk-averse in MC than in HsC and EsC. Moreover, a payoff increase produced a shift toward more risk-averse behaviours in MC, but not in HsC and EsC, where we found an opposite trend suggesting a more risk-loving behaviour. Finally, we found that healthcare workers were significantly less risk-averse compared to non-healthcare workers in EsC, but not in MC and HsC. These findings provided evidence of the possible effects of Covid-19 outbreak on risk-taking aptitudes. The negative impact on human choices and, consequently, on the whole world economy of this catastrophic life event must not be underestimated.

The coronavirus (COVID-19) pandemic is currently a global health threat attributed to negatively affecting the mental health and well-being of people globally. The purpose of the present study is to examine the mediating role of optimism-pessimism and psychological inflexibility in the relationship of coronavirus stress with psychological problems among Turkish adults. The sample of the study included 451 adults (55% women). Participants mainly consisted of young adults with a mean age of 23.30 years, ranging from 18 to 65 years (SD= 6.97). A mediation model indicated that coronavirus stress had a significant predictive effect on optimism-pessimism, psychological inflexibility, and psychological problems. Further, optimism-pessimism and psychological inflexibility mediated the effect of coronavirus stress on psychological problems in adults. Lastly, optimism-pessimism predicted the psychological problems of adults through psychological inflexibility. These results elucidate our understanding of the role of mediators in coronavirus stress and psychological health problems. The findings are useful in terms of providing evidence for tailoring interventions and implementing preventative approaches to mitigate the psychopathological consequences of COVID-19. Based on the present findings, the potential utility of Acceptance and Commitment Therapy is discussed within the context of COVID-19.

This paper presents an economic model of an epidemic in which susceptible individuals may engage in costly social distancing in order to avoid becoming infected. Infected individuals eventually recover and acquire immunity, thereby ceasing to be a source of infection to others. Under non-cooperative and forward-looking decision making, equilibrium social distancing arises endogenously around the peak of the epidemic, when disease prevalence reaches a critical threshold determined by preferences. Spontaneous, uncoordinated social distancing thus acts to flatten the curve of the epidemic by reducing peak prevalence. In equilibrium, social distancing stops once herd immunity sets in, but acts to extend the duration of the epidemic beyond the benchmark of a non-behavioral epidemiological model. Comparative statics with respect to the model parameters indicate that the curve becomes flatter (i) the more infectious the disease is and (ii) the more severe the health consequences of the disease are for the individuals.

Automated learning from data by means of deep neural networks is finding use in an ever-increasing number of applications, yet key theoretical questions about how it works remain unanswered. A physics-based approach may help to bridge this gap.

Researchers studying curiosity and interest note a lack of consensus in how these important concepts that motivate learning are defined. One proposal is that curiosity and interest are naïve concepts, intuitively and subjectively constructed by people to express underlying psychological processes to which they lack introspective access. Thus, there may not be definitive a priori definitions but there should still be common subjective definitions held by people. In the current studies, we use machine learning techniques to examine whether people naively distinguish between curiosity and interest as different subjective experiences, as an empirical yardstick for distinguishing the terms. In Study 1 (preregistered), we train a Naïve Bayes classification algorithm to distinguish between free-text definitions of curiosity and interest (n = 396 definitions), using cross-validation to test the classifier on two sets of data (dependent n = 196; independent n = 218). The classifier accurately distinguished curiosity and interest definitions considerably above chance levels, demonstrating that there is a naïve consensus in how they are distinguished. In Study 2, the classifier from Study 1 accurately distinguished definitions provided by experts who study curiosity and research (n = 92) suggesting that experts share the naïve consensus. However, we showed that experts who study curiosity shared the naïve consensus more closely than experts who study interest. These results suggest that there is a shared consensus that curiosity and interest represent different subjective experiences, providing a basis for much-needed conceptual clarity.

Investigating how echo chambers emerge in social networks is increasingly crucial, given their role in facilitating the retention of misinformation, inducing intolerance towards opposing views, and misleading public and political discourse (e.g., disbelief in climate change). Previously, the emergence of echo chambers has been attributed to psychological biases and inter-individual differences, requiring repeated interactions among network-users. In the present work we show that two core components of social networks—users self-select their networks, and information is shared laterally (i.e. peer-to-peer)—are causally sufficient to produce echo chambers. Crucially, we show that this requires neither special psychological explanation (e.g., bias or individual differences), nor repeated interactions—though these may be exacerbating factors. In fact, this effect is made increasingly worse the more generations of peer-to-peer transmissions it takes for information to permeate a network. This raises important questions for social network architects, if truly opposed to the increasing prevalence of deleterious societal trends that stem from echo chamber formation.

Progress in psychology has been frustrated by challenges concerning replicability, generalizability, strategy selection, inferential reproducibility, and computational reproducibility. Although often discussed separately, we argue that these five problems share a common cause: insufficient investment of resources into the typical psychology study. We argue that team science is a possible solution to these problems because it allows large groups of scientists to pool their resources, allowing higher resource investments than would be possible by solo PIs. As long as the unique barriers and risks are properly recognized and managed, we believe team science has unique potential to spur progress in psychology and beyond.

The present work posits that social motives, particularly status seeking in the form of moral grandstanding, are likely at least partially to blame for elevated levels of political polarization in the U.S. In Study 1, results from both undergraduates (N=981; Mean age =19.4; SD=2.1; 69.7% women) and a cross-section of U.S. adults matched to 2010 census norms (N=1,063; Mean age =48.20, SD=16.38; 49.8% women) indicated that prestige-motived grandstanding was consistently and robustly related to greater ideological polarization. In Study 2, results from a weighted nationally-representative cross-section of U.S. adults (N=2,519; Mean age =47.5, SD=17.8; 51.4% women) found that prestige motivated grandstanding was reliably related to both ideological and affective polarization.

With globalization, digitalization, and the spread of information and communication technologies, rules regulating work have been softened or completely abolished. As a consequence, employees face additional cognitive demands to plan, structure, and coordinate their work. In order to capture these demands of contemporary work, we constructed and validated the Cognitive Demands of Flexible Work (CODE) scale. The scale comprises four subscales (i.e., structuring of work tasks, planning of working times, planning of working places, and coordinating with others). We validated the scale in three independent studies (overall N = 1129) in German and English. Confirmatory Factor Analyses supported the four- factor structure as well as the metric invariance of the different language versions. Moreover, the subscales showed convergent validity with related constructs such as requirements for problem solving or autonomy. Criterion validity for emotional exhaustion, engagement, and positive work rumination, negative work rumination, and problem-solving pondering suggests that cognitive demands of flexible work can be construed as challenge stressors. However, relationships with emotional exhaustion were only significant for one of the four subscales. Overall, the CODE scale was shown to be a reliable and valid instrument to measure cognitive demands of flexible work.

In this study, we reanalyze recent empirical research on replication from a meta-analytic perspective. We argue that there are different ways to define “replication failure,” and that analyses can focus on exploring variation among replication studies or assess whether their results contradict the findings of the original study. We apply this framework to a set of psychological findings that have been replicated and assess the sensitivity of these analyses. We find that tests for replication that involve only a single replication study are almost always severely underpowered. Among the 40 findings for which ensembles of multisite direct replications were conducted, we find that between 11 and 17 (28% to 43%) ensembles produced heterogeneous effects, depending on how replication is defined. This heterogeneity could not be completely explained by moderators documented by replication research programs. We also find that these ensembles were not always well-powered to detect potentially meaningful values of heterogeneity. Finally, we identify several discrepancies between the results of original studies and the distribution of effects found by multisite replications but note that these analyses also have low power. We conclude by arguing that efforts to assess replication would benefit from further methodological work on designing replication studies to ensure analyses are sufficiently sensitive. (PsycInfo Database Record (c) 2020 APA, all rights reserved)

Children as young as 3-4 years are already concerned about inequality and declare that equality is a norm that should be followed. From 3 to 8 years they develop a strong preference for equality, which is typically reflected in both “envy” and “compassion”, that is, aversion to disadvantageous and advantageous inequality, respectively4. Further studies suggest that inequality aversion does not continue increasing after that age, but rather exhibit an inverse-U shape relation with age in childhood and adolescence, with a peak at 8 years old. Since children are particularly sensitive to inequality at the age of 8, it is an open question how exposure to real economic inequality at this age modulates prosocial behaviour in adult life. Here we link generosity in dictator game experiments conducted among Spanish university students (n>400) with existing macro-level data on income inequality within their region when they were children. The data show that individuals who were exposed to higher levels of inequality at the age of 8 are more generous in adult life. Interestingly, exposure at older ages has no impact on generosity. Our results extend previous findings on the development of egalitarianism by showing long-lasting effects of childhood inequality experience into adult life. If prosocial behaviour is (partly) developed as a reaction to an unequal environment then, in the future, inequality might be counteracted.

This article describes the qualitative approach used to generate and interpret the quantitative study reported by Song and colleagues’ (2020) in their article, “What counts as an ‘environmental’ issue? Differences in environmental issue conceptualization across race, ethnicity, and socioeconomic status.” Song and colleagues (2020) describe the results of a survey documenting that, in the United States, White and high-SES respondents perceive environmental issues differently than their non-White and lower-SES counterparts, reflecting structural differences in environmental risks. While Song and colleagues (2020) discuss the survey results in detail, the discussion of the qualitative research that led to the creation of that survey was limited due to space constraints. The current article provides a more holistic account of the methods behind the Song and colleagues (2020) study by discussing the qualitative component of the research in detail. In addition to discussing how the qualitative research complements and critically informs the findings reported by Song et al., we also consider the broader implications and value of integrating qualitative and quantitative methods in environmental psychology.

There are a number of well-accepted ways to measure risk sensitivity, with researchers often making conclusions about individual differences based on a single task. Even though long-standing observations suggest that how risky outcomes are presented changes people's behavior, it is unclear whether risk sensitivity is a unitary trait that can be measured by any one of these instruments. To directly answer this question, we administered three tasks commonly used to elicit risk sensitivity within-subject to a large sample of participants on Amazon Mechanical Turk. Our findings revealed high individual variability in each measure, with little evidence of consistency among different tasks: many participants who were classified as "risk-averse'' in one task were "risk-seeking'' in another, and we observed no significant correlations between continuous measures of risk sensitivity as measured in each of the tasks. Our results cast doubt on the pervasive assumption that risk paradigms measure a single underlying trait, and suggest instead that behavior in risky situations is the result of heterogeneous, interacting, and possibly task-dependent cognitive mechanisms.

Interest in wisdom in the cognitive sciences, psychology, and education has been paralleled by conceptual confusions about its nature and assessment. To clarify these issues and promote consensus in the field, wisdom researchers met in Toronto in July of 2019, resolving disputes through discussion. Guided by a survey of scientists who study wisdom-related constructs, we established a common wisdom model, observing that empirical approaches to wisdom converge on the morally-grounded application of metacognition to reasoning and problem-solving. After outlining the function of relevant metacognitive and moral processes, we critically evaluate existing empirical approaches to measurement and offer recommendations for best practices. In the subsequent sections, we use the common wisdom model to selectively review evidence about the role of individual differences for development and manifestation of wisdom, approaches to wisdom development and training, as well as cultural, subcultural, and social-contextual differences. We conclude by discussing wisdom’s conceptual overlap with a host of other constructs and outline unresolved conceptual and methodological challenges.

Three experiments (N = 854) examined the effect of a four-step elicitation method used in several expert elicitation studies on judgment accuracy. Participants made judgments about topics that were either searchable or unsearchable online using one of two order variations of the four-step procedure. One group of participants provided their best judgment (one step) prior to constructing an interval (i.e., lower bound, upper bound, and a confidence rating that the correct value fell in the range provided), whereas another group of participants provided their best judgment last after the three-step confidence interval was constructed. The overall effect of this elicitation method was not significant. The accuracy of best estimates was not improved by prior interval construction, and the accuracy of confidence intervals was not affected by elicitation order either. The coherence of participants’ judgments, however, stably predicted more accurate best estimates and also wider credible intervals.

This document presents a method for eliciting and scoring rolling forecasts. Rolling forecasts ask when some event will occur; the question remains open and forecasters can update their forecasts until the event occurs.

Humans live in an uncertain world and often rely on social information in order to reduce uncertainty. However, the relationship between uncertainty and social information use is not yet fully understood. In this work we argue that previous studies have often neglected different degrees of uncertainty that need to be accounted for when studying social information use. We introduce a novel experimental paradigm to measure risky decision making, wherein social information and uncertainty are manipulated. We also developed a Bayesian model of social information use. We show that across different levels of uncertainty; social influence follows similar principles. Social information is more impactful when individuals are more uncertain. Notably, this relationship holds for experimental manipulations of uncertainty but also for subjective uncertainty within experimental conditions. We conclude with discussing that social influence can be better understood when paying credit to subjective uncertainties and preferences.

From stockpiling toilet roll to spending £3,000 on wine, supermarket workers have had to cope with a panicking public – while finding themselves unexpectedly on the frontline

The inefficiency of the current peer-review system has been discussed for many years, and now there is a surge of various countermeasures aiming to solve the problems. Post-publication peer review (PPPR) has emerged as one of them, and some scholars expected that it would be the definite solution. Unfortunately, a decade of trial has not turned out to be as fruitful as expected. We assessed that the biggest reason for this situation was the lack of incentives among contributors, and proposed that publishing review commentaries as independent and qualified publications in a dedicated section of a journal might solve the problem. Specifically, we took the open peer commentary section of Behavioral and Brain Sciences as a model of such an incentivised structure, and pictured a possible implementation of this idea in the current web-based environment. Potentials of this new PPPR format were suggested.

In the wake of the current COVID-19 health crisis, there is uncertainty and concern about the impact this pandemic will have on children’s health and educational outcomes. Play is a fundamental part of childhood and can be integral to children’s health in moments of crisis. Due to severe lockdown regulations around the world, typical play experiences have needed to adapt to school and playground closures, changes to peer interactions, and social distancing. We undertook a rapid literature review of the impact of quarantine, isolation, or other restrictive environments on children’s play and whether play may mitigate the adverse effects of such restrictions. Fifteen peer-reviewed studies were identified, spanning various environments in which children faced restriction, including hospitalisation, juvenile and immigration detention, and displacement to a refugee camp. We found that the literature provided evidence of changes in children’s access to play under restrictive circumstances, but less conclusive inferences regarding changes in frequency of play behaviours. These studies also indicated ways in which play might support children going through periods of isolation or quarantine, via promoting coping, expression, sociability, and skill development, but critically lacked robust investigations of play as a mechanism or intervention target in mitigating the negative impacts of restriction during childhood. Studies pertaining to children in isolation due to infectious disease outbreaks were notably absent from the literature reviewed in this search. We present these findings from the literature followed by recommendations for further research that may better support children in this and future moments of crisis.

The Covid-19 pandemic has far-reaching implications for researchers. For example, many researchers cannot access their labs anymore and are hit by budget-cuts from their institutions. Luckily, there are a range of ways how high-quality research can be conducted without funding and face-to-face interactions. In the present paper, I discuss eight such possibilities, including meta-analyses, secondary data analyses, web-scrapping, scientometrics, or sharing one’s expert knowledge (e.g., writing tutorials). Most of these possibilities can be done from home, as they require only access to a computer, the internet, and time; but no state-of-the art equipment or funding to pay for participants. Thus, they are particularly relevant for researchers with limited financial resources beyond pandemics and quarantines.

On Wednesday, the number of new coronavirus cases reported in South Korea fell to less than 100 for the fourth day in a row, a figure markedly down from the peak of 909 new cases reported on February 29. While there are signs that the Korean outbreak is starting to ebb, the United States, on the other hand, is only beginning to confront the true magnitude of the global pandemic. Each day, it seems, brings news of new closures, increasingly stringent guidance on social distancing, and new proposals to combat the outbreak and prop up the tanking economy. Amid an increasingly dire crisis, public health experts in the United States are citing Korea as a success story. “Do we want to go the direction of South Korea and really be aggressive and lower our mortality rates, or do we want to go the direction of Italy?” US Surgeon General Jerome Adams asked in a TV interview this week.

San Francisco merchants battered by the coronavirus pandemic will soon be able to apply for free, fast-tracked permits to use portions of outdoor public spaces — sidewalks, streets, parks and plazas — for business activities. The new Shared Spaces Program represents the latest city initiative to support a gradual increase of economic activity while balancing mandates around social distancing, which remains crucial for stopping the spread of the virus until a vaccine is developed.

Do crises bring people together or pull them apart? Here we examine how people’s willingness to help others and their perceived interdependence with others changed during the COVID-19 pandemic, and assess what factors are associated with any change. We collected data at 4 time points from the same cohort of 497 paid participants, starting on March 6th, before the pandemic was declared, through April 2. We found that perceived interdependence with neighbors and with humanity increased over time on multiple measures. However, regarding cooperation, agreement with the statement that helping someone in need “is the right thing to do” decreased over time (towards both a neighbor and a citizen of another country). Although the changes per time period were small for some of these effects, cumulatively they were non-trivial (ranging from a .33 to a .75 change on a 7 point likert scale). There was no change over time in participants' reported willingness to help somebody in their neighborhood (cooperation) or their feelings that when “All of humanity succeeds” they feel good (interdependence). We found reliable associations of change in cooperation and interdependence with sex, age, and pre-existing medical condition. We are collecting data on an ongoing basis which will allow us to investigate how these variables continue to change or not as the pandemic unfolds.

Control of COVID-19 requires the ability to detect asymptomatic and mild infections, that would not present to healthcare and would otherwise remain undetected through existing surveillance systems. This is important to determine the true number of infections within the general population to understand transmission, to inform control measures such as social distancing and school closures and to provide a denominator for the estimation of severity measures such as infection fatality and infection hospitalisation ratios. A number of serological collections have been established by PHE to provide an age-stratified geographically representative sample across England over time. These include samples from healthy adult blood donors, supplied by the NHS Blood and Transplant (NHS BT). Donor samples from different geographic regions (approximately 1000 samples per region) in England are tested each week. The results presented here are based on testing using the Euroimmun assay.

Without enough test kits, the 1.3-billion-person country is using a gigantic surveillance network to trace and quarantine infected people.

Around the United States, states are easing the restrictions imposed to slow the spread of COVID-19. We asked Yale SOM’s Dr. Howard Forman if these moves are premature and what is needed for Americans to return to school and work safely.

The COVID-19 pandemic has altered every aspect of American life, from health and work to education and exercise. Over the long term, warns the American Psychological Association, the negative mental health effects of the coronavirus will be serious and long-lasting. To better understand how individuals are coping with the extreme stress of this crisis, APA has adapted its annual Stress in America poll into a monthly analysis of stressors and stress levels. Taking a monthly “pulse” to understand how individuals are processing these extreme events will help health leaders and policymakers better align advice and resources to address these evolving mental health needs. The Harris Poll conducted this survey on behalf of APA from April 24 to May 4, 2020; the online survey included 3,013 adults age 18+ who reside in the United States.

Experts are trying to figure out why the coronavirus is so capricious. The answers could determine how to best protect ourselves and how long we have to.

Despite the daily updates on number of cases, hospital admissions, and deaths around the world and the increasing number of hospital-based case series, some of the fundamental information about how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spreads in the population and who is really at risk of both infection and severe consequences is still missing. In The Lancet Infectious Diseases, Simon de Lusignan and colleagues1de Lusignan S Dorward J Correa A et al.Risk factors for SARS-CoV-2 among patients in the Oxford Royal College of General Practitioners Research and Surveillance Centre primary care network: a cross-sectional study.Lancet Infect Dis. 2020; (published online May 15.)https://doi.org/10.1016/S1473-3099(20)30371-6Google Scholar report on the characteristics of the first 3802 people tested for SARS-CoV-2 within the Royal College of General Practitioners (RCGP) sentinel primary care surveillance network. Unlike most previous studies that examined risk factors for poor prognosis,2Yang J Zheng Y Gou X et al.Prevalence of comorbidities and its effects in coronavirus disease 2019 patients: a systematic review and meta-analysis.Int J Infect Dis. 2020; 94: 91-95Google Scholar,  3Chen T Wu D Chen H et al.Clinical characteristics of 113 deceased patients with coronavirus disease 2019: retrospective study.BMJ. 2020; 368m1091Google Scholar de Lusignan and colleagues1de Lusignan S Dorward J Correa A et al.Risk factors for SARS-CoV-2 among patients in the Oxford Royal College of General Practitioners Research and Surveillance Centre primary care network: a cross-sectional study.Lancet Infect Dis. 2020; (published online May 15.)https://doi.org/10.1016/S1473-3099(20)30371-6Google Scholar report characteristics associated with susceptibility to SARS-CoV-2 infection.

In December, 2019, COVID-19 was recognised as a novel respiratory disease in Wuhan, China,1Guan WJ Ni ZY Hu Y et al.Clinical characteristics of coronavirus disease 2019 in China.N Engl J Med. 2020; (published online Feb 28.)DOI:10.1056/NEJMoa2002032Google Scholar caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).2Zhu N Zhang D Wang W et al.A novel coronavirus from patients with pneumonia in China, 2019.N Engl J Med. 2020; 382: 727-733Google Scholar Accurate and reliable data on SARS-CoV-2 incubation time, secondary attack rate, and transmission dynamics are key to successful containment. In late January, 2020, infection with SARS-CoV-2 was detected in Germany for the first time. By rapid response, the public health authorities identified a business meeting in a Bavarian company as the primary transmission site and a participating Chinese employee who had travelled from Shanghai to Munich as the index patient.3Rothe C Schunk M Sothmann P et al.Transmission of 2019-nCoV Infection from an asymptomatic contact in Germany.N Engl J Med. 2020; 382: 970-971Google Scholar Subsequently, the rigorous investigation of contacts led to detection of 16 people infected with SARS-CoV-2 and to successful containment of this outbreak. This well defined event with limited extent of transmission enabled Merle Böhmer and colleagues to provide a meticulous description of SARS-CoV-2 transmission dynamics in an Article published in The Lancet Infectious Diseases.4Böhmer MM Buchholz U Corman VM et al.Investigation of a COVID-19 outbreak in Germany resulting from a single travel-associated primary case: a case series.Lancet Infect Dis. 2020; (published online May 15.)https://doi.org/10.1016/S1473-3099(20)30314-5Google Scholar The authors did standard and in-depth interviews with case patients and household members to determine the characteristics and the onset of symptoms. Data were used for calculation of SARS-CoV-2 secondary attack rates, defined as the probability that an infection occurs among susceptible people within the incubation period.5Liu Y Eggo RM Kucharski AJ Secondary attack rate and superspreading events for SARS-CoV-2.Lancet. 2020; 395: e47Google Scholar In addition, whole genome sequencing of virus isolates was done in 15 of the 16 cases. As a result, Böhmer and colleagues report a detailed transmission network of the outbreak, which is accurately displayed in the main figure of the Article

A basic reproduction number, R0, of about 2 was estimated for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Wuhan, China, early in the outbreak.1Li Q Guan X Wu P et al.Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia.N Engl J Med. 2020; (published online Jan 29.)DOI:10.1056/NEJMoa2001316Crossref Scopus (426) Google Scholar,  2Riou J Althaus CL Pattern of early human-to-human transmission of Wuhan 2019 novel coronavirus (2019-nCoV), December 2019 to January 2020.Euro Surveill. 2020; 252000058Crossref Scopus (36) Google Scholar However, this value only captures the average dynamics of transmission; a crucial question for control is whether specific situations and settings might be driving the outbreak. The secondary attack rate (SAR), defined as the probability that an infection occurs among susceptible people within a specific group (ie, household or close contacts), can provide an indication of how social interactions relate to transmission risk.

Background: A novel coronavirus disease (COVID-19) outbreak has now spread to a number of countries worldwide. While sustained transmission chains of human-to-human transmission suggest high basic reproduction number R0, variation in the number of secondary transmissions (often characterised by so-called superspreading events) may be large as some countries have observed fewer local transmissions than others. Methods: We quantified individual-level variation in COVID-19 transmission by applying a mathematical model to observed outbreak sizes in affected countries. We extracted the number of imported and local cases in the affected countries from the World Health Organization situation report and applied a branching process model where the number of secondary transmissions was assumed to follow a negative-binomial distribution. Results: Our model suggested a high degree of individual-level variation in the transmission of COVID-19. Within the current consensus range of R0 (2-3), the overdispersion parameter k of a negative-binomial distribution was estimated to be around 0.1 (median estimate 0.1; 95% CrI: 0.05-0.2 for R0 = 2.5), suggesting that 80% of secondary transmissions may have been caused by a small fraction of infectious individuals (~10%). A joint estimation yielded likely ranges for R0 and k (95% CrIs: R0 1.4-12; k 0.04-0.2); however, the upper bound of R0 was not well informed by the model and data, which did not notably differ from that of the prior distribution. Conclusions: Our finding of a highly-overdispersed offspring distribution highlights a potential benefit to focusing intervention efforts on superspreading. As most infected individuals do not contribute to the expansion of an epidemic, the effective reproduction number could be drastically reduced by preventing relatively rare superspreading events.

We can exploit randomized controlled trials, compartmental models, and spillovers.

Black, Asian and minority ethnic people in England are 54% more likely to be fined under coronavirus rules than white people, it can be revealed.

The COVID-19 pandemic requires rapid public compliance with advice from health authorities. Here, we ask who was most likely to do so during the first wave of the pandemic. We conducted surveys asking 26,508 citizens of eight Western democracies in the period between March 19 and April 3 about their protective behavior relating to COVID-19. Consistent with prior research on epidemics, we find that perceptions of threat and risk factors are crucial and culturally uniform determinants of protective behavior. On this basis, authorities could potentially foster further compliance by appealing to fear of COVID-19, but there may be normative and practical limits to such a strategy. Instead, we find that another major source of compliance are feelings of efficacy. Importantly, the effects of such feelings are especially strong among those who do not feel threatened, creating a path to compliance without fear. In contrast, two other major candidates for facilitating compliance from the social sciences, interpersonal trust and institutional evaluations, have surprisingly little motivational power. To combat future waves of the pandemic, health authorities should thus focus on facilitating efficacy in the public.

Socially responsible behavior is crucial for slowing the spread of infectious diseases. However, economic and epidemiological models of disease transmission abstract from prosocial motivations as a driver of behaviors that impact the health of others. In an incentivized study, we show that a large majority of people are very reluctant to put others at risk for their personal benefit. Moreover, this experimental measure of prosociality predicts health behaviors during the COVID-19 pandemic, measured in a separate and ostensibly unrelated study with the same people. Prosocial individuals are more likely to follow physical distancing guidelines, stay home when sick, and buy face masks. We also find that prosociality measured two years before the pandemic predicts health behaviors during the pandemic. Our findings indicate that prosociality is a stable, long-term predictor of policy-relevant behaviors, suggesting that the impact of policies on a population may depend on the degree of prosociality.

As COVID-19 is rapidly spreading across the globe, short-term modeling forecasts provide time-critical information for decisions on containment and mitigation strategies. A major challenge for short-term forecasts is the assessment of key epidemiological parameters and how they change when first interventions show an effect. By combining an established epidemiological model with Bayesian inference, we analyze the time dependence of the effective growth rate of new infections. Focusing on COVID-19 spread in Germany, we detect change points in the effective growth rate that correlate well with the times of publicly announced interventions. Thereby, we can quantify the effect of interventions, and we can incorporate the corresponding change points into forecasts of future scenarios and case numbers. Our code is freely available and can be readily adapted to any country or region.

We need to get children back into education, but a locally managed approach using testing and tracing is the only way

These engines of regional growth will struggle with state funding cuts, fewer foreign students and destroyed household finances. 

Major platforms are removing the discredited conspiracy video, but niche conspiracy communities and “alt-tech” start-ups are rapidly fueling its regeneration

Having two copies of e4 variant of ApoE gene linked to double risk of severe Covid-19, study suggests

How will the coronavirus pandemic be remembered? Neil Prior takes a look at the projects documenting history-in-the-making in the age of the internet.

The coronavirus COVID-19 pandemic is an unprecedented health crisis. Many governments around the world have responded by implementing lockdown measures of different degrees of intensity. To be effective, such measures must rely on citizens’ compliance and collaboration. In the present study (N = 1896), we examined predictors of compliance with social distancing norms, and intentions to disclose the disease to authorities and acquaintances/friends, in the US, Italy and South Korea. We investigated the role of cultural orientations of horizontal and vertical individualism and collectivism, trust in the government’s action, and self-conscious emotions of shame and guilt related to the disease. Across countries, vertical collectivism predicted stronger shame whereas horizontal collectivism predicted stronger trust in the government’s action. Only in the US, vertical collectivism was associated with stronger trust. Subsequently, shame predicted lower compliance and intentions to disclose the disease, guilt was associated with stronger intentions to disclose the disease to the authorities, and trust was associated with stronger compliance and intentions to disclose the disease to authorities. Unlike Italy and South Korea, the association between trust on compliance was not statistically significant in the US, Implications of the findings, and directions for future research are discussed.

YouTube doesn't allow content about COVID-19 that poses a serious risk of egregious harm.  YouTube doesn't allow content that spreads medical misinformation that contradicts the World Health Organization (WHO) or local health authorities’ medical information about COVID-19. This is limited to content that contradicts WHO or local health authorities’ guidance on: Treatment  Prevention Diagnostic  Transmission

The pursuit of money from wealthy donors distorts the research process—and yields flashy projects that don’t help and don’t work.

“Disinformation starts at home” series: When disinformation is discussed as part of the 2016 elections, the realignment of the global order, or overarching issues connected to adversarial states, it becomes an issue that seems huge and far away for many people. We are all prone to believing that disinformation is something that works on someone else, not on us. But the truth is, it works on all of us. And more importantly, it is at play in the communities around us, and impacting our neighbors, our behavior, how we make decisions, and the requests that we make of government, as well as the decisions that local governments and leaders are making. This series will explore how disinformation is impacting local communities, and why it matters.

As COVID-19 sweeps the world, the desire for scientific “good news” is stronger than ever. But with that comes the problem of false positive findings and false leads.To address this challenge, the journal Royal Society Open Science is expediting its Registered Report review process specifically for COVID-19 research.

Psychological research could play a critical role in informing policies during times of crisis and uncertainty. However, as stated in a previous post by Patrick Forscher, Simine Vazire, and Farid Anvari during this digital event, issues with generalisability, replicability, and validity may limit the practical implications of our research. The problems of reliability are compounded by the fact that in times of crisis, the rapid dissemination of evidence is as critical as its quality. Thus, the field finds itself in a challenging situation, where the need for quality and rapid knowledge challenges the utility of psychology research. As Ulrike Hahn put it in a previous post during this digital event; there is a need for proper science without the drag. But researchers have not sat idle. On the contrary, some have started building an infrastructure for crisis knowledge management, described in the earlier post by Stefan Herzog. Others have started posting their findings as “living documents”, as described by Yasmina Okan in her post. And many more have published their findings as preprints as soon as they emerge, without the “drag” introduced by peer review.

A preprint, posted on medRxiv, reports on air pollution in England and COVID-19 severity

Accurate antibody testing is a critical tool to determine if the pandemic has slowed enough to begin restarting the economy.

Research, published in the International Journal of Clinical Practice, reports on the number of people on the UK people who are likely to have already been infected by the COVID-19 virus.

Background: During the coronavirus disease (COVID-19) pandemic, governments issued movement restrictions and placed areas into quarantine to combat the spread of the disease. In addition, individuals were encouraged to adopt personal health measures such as social isolation. Information regarding the disease and recommended avoidance measures were distributed through a variety of channels including social media, news websites, and emails. Previous research suggests that the vast amount of available information can be confusing, potentially resulting in overconcern and information overload.Objective: This study investigates the impact of online information on the individual-level intention to voluntarily self-isolate during the pandemic. Using the protection-motivation theory as a framework, we propose a model outlining the effects of cyberchondria and information overload on individuals’ perceptions and motivations.Methods: To test the proposed model, we collected data with an online survey (N=225) and analyzed it using partial least square-structural equation modeling. The effects of social media and living situation were tested through multigroup analysis.Results: Cyberchondria and information overload had a significant impact on individuals’ threat and coping perceptions, and through them on self-isolation intention. Among the appraisal constructs, perceived severity (P=.002) and self-efficacy (P=.003) positively impacted self-isolation intention, while response cost (P<.001) affected the intention negatively. Cyberchondria (P=.003) and information overload (P=.003) indirectly affected self-isolation intention through the aforementioned perceptions. Using social media as an information source increased both cyberchondria and information overload. No differences in perceptions were found between people living alone and those living with their families.Conclusions: During COVID-19, frequent use of social media contributed to information overload and overconcern among individuals. To boost individuals’ motivation to adopt preventive measures such as self-isolation, actions should focus on lowering individuals’ perceived response costs in addition to informing them about the severity of the situation.

The COVID-19 pandemic has caused immediate changes in the food retailing environment, particularly for countries that have “locked down” and imposed strict physical distancing measures. Consumer behavior has changed, including an initial period of panic buying, likely to be followed by further changes caused by constraints on the shopping experience. We interpret recent findings on shopping under constraints, and research on the effects of the SARS epidemic, on consumer behavior. As consumers spend less time making decisions in supermarkets, they will likely rely more heavily on price and brand heuristics to choose products. This trend may be reinforced by a counter-intuitive increased expenditure on supermarket goods, as was seen during the Great Recession of 2008. Online shopping will experience extensive growth.

The coronavirus (COVID-19) pandemic and attendant lockdown measures present serious threats to psychological well-being worldwide. Here, we examined the extent to which being outdoors (versus indoors), the experience of loneliness, and screen-time are associated with psychological well-being during the COVID-19 pandemic using an experiencing sampling method. In April 2020, Austrian adults (N = 286, age M = 31.0 years) completed a 21-day experience sampling phase in which they reported their psychological well-being, whether they were indoors or outdoors, and loneliness at three random time-points each day, as well as their daily screen-time. Results indicated that being outdoors was associated with higher psychological well-being, whereas greater loneliness and greater daily screen-time were associated with poorer well-being. Additionally, the impact of loneliness on well-being was weaker when participants were outdoors than indoors. Temporal changes in well-being, loneliness, and screen-time across the 21 days were small. These results have health policy implications for the promotion of population well-being during pandemics.

Dr. Shikha Jain, co-founder of IMPACT, talks about her group's goal of getting trusted information to the public and shaping public policy to aid in awareness of COVID-19.

Understanding adaptive immunity to SARS-CoV-2 is important for vaccine development, interpreting coronavirus disease 2019 (COVID-19) pathogenesis, and calibration of pandemic control measures. Using HLA class I and II predicted peptide ‘megapools’, circulating SARS-CoV-2−specific CD8+ and CD4+ T cells were identified in ∼70% and 100% of COVID-19 convalescent patients, respectively. CD4+ T cell responses to spike, the main target of most vaccine efforts, were robust and correlated with the magnitude of the anti-SARS-CoV-2 IgG and IgA titers. The M, spike and N proteins each accounted for 11-27% of the total CD4+ response, with additional responses commonly targeting nsp3, nsp4, ORF3a and ORF8, among others. For CD8+ T cells, spike and M were recognized, with at least eight SARS-CoV-2 ORFs targeted. Importantly, we detected SARS-CoV-2−reactive CD4+ T cells in ∼40-60% of unexposed individuals, suggesting cross-reactive T cell recognition between circulating ‘common cold’ coronaviruses and SARS-CoV-2.

Empathy often feels automatic, but variations in empathic responding suggest that, at least some of the time, empathy is affected by one’s motivation to empathize in any particular circumstance. Here, we show that people can be motivated to engage in (or avoid) empathy-eliciting situations with strangers, and that these decisions are driven by subjective value-based estimations of the costs (e.g., cognitive effort) and benefits (e.g., social reward) inherent to empathizing. Across seven experiments (overall N = 1,348), and replicating previous work (Cameron et al., 2019), we found a robust empathy avoidance effect. We also find support for the hypothesis that individuals can be motivated to opt-in to situations requiring empathy that they would otherwise avoid. Participants were more likely to opt into empathy-eliciting situations if 1) they were incentivized monetarily for doing so (Experiments 1a and 1b), and 2) if a more familiar and liked empathy target was available (Experiments 2a and 2b). Framing empathy as explicitly related to one’s moral character and reputation did not motivate participants to engage in empathy (Experiment 3a and 3c), though these null results may be due to a weak manipulation. These findings suggest that empathy can be motivated in multiple ways, and is a process driven by context-specific value-based decision making.

How coronavirus research is being weaponized.

Objectives: Researchers have hypothesized that using Information and Communications Technology (ICT), such as email and social media, may buffer older adults from normative age-graded declines in psychological adjustment. However, past intervention research has been unable to conclusively evaluate this proposition, and no studies to date have examined this topic using naturalistic large-scale longitudinal methods. Methods: In this pre-registered study, we examined the co-development between three aspects of psychological adjustment (loneliness, satisfaction with life, and depressiveness) and three factor-analytically derived clusters of ICT use (instrumental, social, and media) using a longitudinal representative sample of 2,922 Dutch adults aged 65 and older that contributed data annually from 2012 to 2017. Results: Latent growth curve analyses indicated that ICT use was largely unrelated to psychological adjustment, both cross-sectionally and longitudinally. Of 36 associations tested, three were significant, and only one remained significant after including health and demographic covariates. Specifically, higher levels of media ICT use at baseline predicted steeper declines in satisfaction with life across the study period. Furthermore, results of random-intercept cross-lagged analyses indicated that change in ICT use did not predict future change in psychological adjustment, and vice-versa. Discussion: Results of this study help clarify the mixed results of past intervention research, indicating that effects of ICT use on psychological adjustment tend to be either null or much smaller than can be detected using typical intervention sample sizes. Overall, these results suggest that the association between technology use and psychological adjustment is negligible in older adults.

Registered Reports Chair Chris Chambers and COS Director of Policy Initiatives David Mellor answer questions about writing, reviewing, editing, and funding studies using the Registered Report format.

This is a live database of funded research projects across the world related to the current COVID-19 pandemic. By providing an overview of research projects mapped against the priorities identified in the WHO Coordinated Global Research Roadmap: 2019 Novel Coronavirus, we aim to support funders and researchers deliver a more effective and coherent global research response. Last updated: 13 May 2020 It includes: *NEW* Interactive heatmap of these projects against the research priorities set out in the WHO Coordinated Global Research Roadmap: 2019 Novel Coronavirus, March 2020 (see below) Interactive world map to search research projects by research location, funders and by WHO R&D priorities (see below) New research projects funded to date from the dataset sources (in downloadable Excel file) *NEW* The complete clinical trials dataset from the WHO ICTRP, with additional categorisation to allow detailed pivot analysis on DAC list countries (in downloadable Excel file) Supporting information on funding calls (in downloadable Excel file) Links to useful online resources (in downloadable Excel file) *Coming soon* List of COVID-19 Data Repositories (in downloadable Excel file)

Concurrent advances in information technology infrastructure and mobile computing power in many low and middle-income countries (LMICs) have raised hopes that artificial intelligence (AI) might help to address challenges unique to the field of global health and accelerate achievement of the health-related sustainable development goals. A series of fundamental questions have been raised about AI-driven health interventions, and whether the tools, methods, and protections traditionally used to make ethical and evidence-based decisions about new technologies can be applied to AI. Deployment of AI has already begun for a broad range of health issues common to LMICs, with interventions focused primarily on communicable diseases, including tuberculosis and malaria. Types of AI vary, but most use some form of machine learning or signal processing. Several types of machine learning methods are frequently used together, as is machine learning with other approaches, most often signal processing. AI-driven health interventions fit into four categories relevant to global health researchers: (1) diagnosis, (2) patient morbidity or mortality risk assessment, (3) disease outbreak prediction and surveillance, and (4) health policy and planning. However, much of the AI-driven intervention research in global health does not describe ethical, regulatory, or practical considerations required for widespread use or deployment at scale. Despite the field remaining nascent, AI-driven health interventions could lead to improved health outcomes in LMICs. Although some challenges of developing and deploying these interventions might not be unique to these settings, the global health community will need to work quickly to establish guidelines for development, testing, and use, and develop a user-driven research agenda to facilitate equitable and ethical use.

This article introduces an accessible approach to implementing unmoderated remote research in developmental science—research in which children and families participate in studies remotely and on their own, without directly interacting with researchers. Unmoderated remote research has the potential to strengthen developmental science by: (1) facilitating the implementation of studies that are easily replicable, (2) allowing for new approaches to longitudinal studies and studies of parent-child interaction, and (3) including families from more diverse backgrounds and children growing up in more diverse environments in research. We describe an approach we have used to design and implement unmoderated remote research that is accessible to researchers with limited programming expertise, and describe resources available on a new website to help researchers get started with this approach, http://discoveriesonline.org. We discuss the potential of this method for developmental science and highlight some challenges still to be overcome to harness the power of unmoderated remote research for advancing the field.

To make good decisions, we all need good evidence which is clearly communicated. At the Winton Centre we work with institutions and individuals to improve the way that important evidence is presented to all of us.For the latest analysis and charts about deaths during the COVID epidemic, see the following pages:COVID: trends in deaths and excess deaths (Updated 15th May)COVID: daily counts of deaths for different places of death (updated 15th May)COVID: death rates in the population, and comparison with 'normal' risk (updated 15th May) [also appeared as Medium blog What are the risks of COVID? And what is meant by ‘the risks of COVID’?]COVID: Trends in death rates by place of death (updated 15th May)COVID: Analysis of excess deaths (updated 15th May)

This digital event is focused on conducting research about crisis-related topics and disseminating the findings during the time of a crisis and is set to run from May 17-27 2020.

In this joint commission from The Lancet and Financial Times, we explore how AI and other digital advancements are being harnessed to improve healthcare in the world’s poorest regions

Our weekly round-up of the best psychology coverage from elsewhere on the web

COVID-19, like many issues, has a politics of knowledge. But in this period of deep uncertainty around health and economic instability, there seems to be an amplification and a multiplication of the ways in which secrecy and ignorance feature. As such, a number of students in the School of Sociology, Politics and International Studies along with members of SPIN have compiled a list of these issues as they have been or are playing out. A summary of some of these issues, along with links to relevant news articles, are included below for further information. 

Bishop and Gray conclude that, while the ethical challenges of gathering and, in particular, sharing social media data, are considerable, there is in fact much to learn from existing ethical frameworks, and there are already good resources available (see above). There is still a need for training around big data, research ethics and integrity which should be “practical, case-based and interactive”. The focus should not be on the individual researcher however and their undoubted responsibilities; institutions must be good and proper stewards of the data under their control which is, of course, emphasised by GDPR legislation which will serve to enforce greater consistency across Europe.