Six experts explain how to recognize the many new faces of grief during a pandemic.

All the Things We Have to Mourn Now

During the current COVID-19 pandemic, racial minorities in the United States, particularly Blacks and Hispanics, account for a disproportionate percent of deaths. The unequal distribution of COVID-related fatalities along the racial lines may result from the segregation of Blacks and Hispanics in neighborhoods afflicted with poverty and all accompanying health-compromising conditions (e.g., discrimination, poor hygiene, congested housing, poor chronic health of residents, and limited access to medical services). We thus anticipated that American cities would be especially vulnerable to COVID-19, thereby exhibiting an accelerated rate of growth of the disease, if they had elevated levels of both economic disparity and racial segregation. To test this expectation, we examined the growth rate of both confirmed COVID-19 cases and deaths in the first 30-day period of the outbreak in the counties subsumed under each of the 100 largest metropolitan cities. We observed that the growth curve was particularly steep in counties with high economic disparity that were located in cities that segregated Blacks and Hispanics. The current evidence underscores an urgent need to build a less segregated, more equal, and thus, more virus-resilient society.

The lethal spiral: Racial segregation and economic disparity jointly exacerbate the COVID-19 fatality in large American cities

Why waiting for scientific evidence before taking decisions means always being behind the curve on risk.

What is wrong with evidence-based policy making?

One in four of the most popular English-language YouTube videos about the coronavirus contains misinformation, according to a study published Wednesday in the journal BMJ Global Health.For the study, researchers from the University of Ottawa analyzed 69 of the most widely-viewed English language videos from a single day in March and found 19 contained non-factual information, garnering more than 62 million views. Misinformation, according to the researchers, included any video that contained false information on the transmission, symptoms, prevention strategies, treatments and epidemiology of the coronavirus.Internet news sources were most likely to misinform, though entertainment, network and internet news outlets were all sources of misinformation, according to the study. None of the most popular professional and government videos contained misinformation. The new study implies that because of YouTube’s size and continued growth, misinformation about the coronavirus has reached more people than in past public health crises, including H1N1 and Ebola.

One in four popular YouTube coronavirus videos contain misinformation, study finds

The biggest social network in the world has the wrong idea for how to fight Covid-19 conspiracies.

Why Is Facebook So Afraid of Checking Facts?

Speech droplets generated by asymptomatic carriers of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are increasingly considered to be a likely mode of disease transmission. Highly sensitive laser light scattering observations have revealed that loud speech can emit thousands of oral fluid droplets per second. In a closed, stagnant air environment, they disappear from the window of view with time constants in the range of 8 to 14 min, which corresponds to droplet nuclei of ca. 4 μm diameter, or 12- to 21-μm droplets prior to dehydration. These observations confirm that there is a substantial probability that normal speaking causes airborne virus transmission in confined environments.

The airborne lifetime of small speech droplets and their potential importance in SARS-CoV-2 transmission

To study the spatiotemporal COVID-19 spread, we use the Global Epidemic and Mobility Model (GLEAM), an individual-based, stochastic, and spatial epidemic model [1, 2, 3, 4]. GLEAM uses real-world data to perform in-silico simulations of the spatial spread of infectious diseases at the global level.  We use the model to analyze the spatiotemporal spread and magnitude of the COVID-19 epidemic in Italy. The model generates an ensemble of possible epidemic projections described by the number of newly generated infections, times of disease arrival in different regions, and the number of traveling infection carriers. Approximate Bayesian Computation is used to estimate the posterior distribution of the basic parameters of the model. The calibration of the global model for COVID-19 is reported in Science. The Italy model considers the timeline of mitigation interventions that are integrated as detailed in the following model description. The projections will be regularly updated as new data and information about mitigation policies become available. Sensitivity analysis on the basic parameters is routinely performed along with the baseline projections considered. In order to calculate the number of deaths the model uses estimates of COVID-19 severity from available data [5, 6].

Projections Timeline Under The Lockdown Scenario

Cough, cough. Is that person sick, or do they just have a throat tickle? A growing body of research suggests pathogen threats shape key aspects of human sociality. However, less research has investigated specific processes involved in pathogen threat detection. Here, we examine whether perceivers can accurately detect pathogen threats using an understudied sensory modality—sound. Participants in four studies judged whether cough and sneeze sounds were produced by people infected with a communicable disease or not. We found no evidence that participants could accurately identify the origins of these sounds. Instead, the more disgusting they perceived a sound to be, the more likely they were to judge that it came from an infected person (regardless of whether it did). Thus, unlike research indicating perceivers can accurately diagnose infection using other sensory modalities (e.g., sight, smell), we find people overperceive pathogen threat in subjectively disgusting sounds.

Sounds of sickness: Can people identify infectious disease using sounds of coughs and sneezes?

Over the past decade and a half, several lines of research have investigated aspects of the smooth signalling redundancy hypothesis. This hypothesis proposes that speakers distribute the information in linguistic utterances as evenly as possible, in order to make the utterance more robust against noise for the hearer. Several studies have shown evidence for this hypothesis in limited linguistic domains, showing that speakers manipulate acoustic and syntactic features to avoid drastic spikes or troughs in information content. In theory, the mechanism behind this is that these spikes would make utterances more vulnerable to noise events, and thus, communicative failure. However, this previous work doesn't consider information density across entire utterances, and only rarely has this mechanism been directly explored. Here, we introduce a new descriptive statistic that quantifies the uniformity of information across an entire utterance, alongside an algorithm that can measure the uniformity of actual utterances against an optimized distribution. Using a simple simulation, we show that utterances optimized for more uniform distributions of information are, in fact, more robust against noise.

Noise resistance in communication: Quantifying uniformity and optimality

Lockdowns have been imposed around the world to contain the spread of the coronavirus pandemic. However, excessively stringent measures might be a threat to people’s mental health. This study examines the impact of the COVID-19 lockdown on psychological well-being and its relationship to habit and routine modifications in a sample of 584 participants on lockdown in Spain. Habits and routines were explored in relation to media and social media use, household chores, eating, drinking and sleeping habits, working and studying, exercise and leisure, and personal care. Participants reported an important increase in negative affect as well as an important decrease in positive affect during the lockdown period, compared to before the lockdown. The decline in psychological well-being was more pronounced in younger participants. There was also a notable increase in media and social media consumption, home cleaning and tidying up, eating and sleeping, cooking and baking, reading for leisure, talking or doing activities with other people in the home, and handwashing. Increases in media and social media use, eating, and doing nothing, were significantly associated with an increase in negative affect and a decrease in positive affect. The results contribute to understanding the impact of the lockdown on psychological well-being and its relationship to habit and routine modifications during this period.

COVID-19 lockdown: impact on psychological well-being and relationship to habit and routine modifications

Numerous governments, some democratic, have capitalized on the COVID-19 infodemic to justify repression of online expression

Op-Ed | The criminalization of COVID-19 clicks and conspiracies

We need to ensure that in our response to covid-19, the rights of those with hearing loss are not forgotten, say Helen Grote and Fizz Izagaren

Covid-19: The communication needs of D/deaf healthcare workers and patients are being forgotten

As countries look to ease school and play restrictions, what evidence is there that children react differently?

Are children less susceptible to coronavirus?

SARS-CoV-2 is the seventh coronavirus known to infect humans; SARS-CoV, MERS-CoV and SARS-CoV-2 can cause severe disease, whereas HKU1, NL63, OC43 and 229E are associated with mild symptoms6. Here we review what can be deduced about the origin of SARS-CoV-2 from comparative analysis of genomic data. We offer a perspective on the notable features of the SARS-CoV-2 genome and discuss scenarios by which they could have arisen. Our analyses clearly show that SARS-CoV-2 is not a laboratory construct or a purposefully manipulated virus.

The proximal origin of SARS-CoV-2

This is a rejoinder of Dr. Ian Mitroff's perspective titled "Corona Virus: A Prime Example of A Wicked Mess". While I agree with Dr. Mitroff on the complexity of the COVID-19 outbreak and the urgency to address it, I disagree with him on points related to the role of wet market in this specific outbreak and whether China had acknowledged the existence of the outbreak. I also consider key highlights of the outbreak are the importance of collaboration across national and state borders and a balance between privacy and public health under such situations.

COVID-19: A revelation – A reply to Ian Mitroff

The COVID-19 pandemic is a seismically disruptive event. This commentary explores some of the key ways this seismic shift will interact with environmental law. It explores four types of change triggered by the pandemic: (1) behavioral changes (including of behaviors with environmental impacts); (2) demographic changes that affect levels of background risk against which laws (including environmental laws) operate; (3) changes in values (including regarding the environment); and (4) changing resources (including those that can be spent on environmental or other amenities). Each of these changes has potentially important implications for the assumptions built in to environmental law, for the ability of environmental law to effectively regulate the environment, and for the way that humans will interact with the environment in coming years and decades.

COVID-19 and Environmental Law

This study focuses on the embryonic stages of the COVID-19 pandemic in China, where most people affected opted to abide by the Chinese government’s national self-quarantine campaign. This resulted in major disruptions to one of the most common market processes in retail: food retailing. The research adopts the theory of planned behaviour to provide early empirical insights into changes in consumer behaviour related to food purchases during the initial stages of the COVID-19 outbreak in China. Data from the online survey carried out suggest that the outbreak triggered considerable levels of switching behaviours among customers, with farmers’ markets losing most of their customers, whilst local small independent retailers experienced the highest levels of resilience in terms of customer retention. This study suggests avenues for further scholarly research and policy making related to the impact this behaviour may be having around the world on society’s more vulnerable groups, particularly the elderly.

The changing grocery shopping behavior of Chinese consumers at the outset of the COVID-19 outbreak

Background In response to the COVID-19 outbreak, we aimed to investigate behavioural change on exposure to live animals before and during the outbreak, and public support and confidence for governmental containment measures. Methods A population-based cross-sectional telephone survey via random dialing was conducted in Wuhan (the epicentre) and Shanghai (an affected city with imported cases) between 1 and 10 February, 2020. 510 residents in Wuhan and 501 residents in Shanghai were randomly sampled. Differences of outcome measures were compared before and during the outbreak, and between two cities. Findings Proportion of respondents visiting wet markets at usual was 23.3% (119/510) in Wuhan and 20.4% (102/501) in Shanghai. During the outbreak, it decreased to 3.1% (16) in Wuhan (p<0.001), and 4.4% (22) in Shanghai (p<0.001). Proportion of those consuming wild animal products declined from 10.2% (52) to 0.6% (3) in Wuhan (p<0.001), and from 5.2% (26) to 0.8% (4) in Shanghai (p<0.001). 79.0% (403) of respondents in Wuhan and 66.9% (335) of respondents in Shanghai supported permanent closure of wet markets (P<0.001). 95% and 92% of respondents supported banning wild animal trade and quarantining Wuhan, and 75% were confident towards containment measures. Females and the more educated were more supportive for the above containment measures. Interpretation The public responded quickly to the outbreak, and reduced exposure to live animals, especially in Wuhan. With high public support in containment measures, better regulation of wet markets and healthy diets should be promoted.

Public Exposure to Live Animals, Behavioural Change, and Support in Containment Measures in response to COVID-19 Outbreak: a population-based cross sectional survey in China

During the last weeks we have been putting our ideas on such a knowledge base into practice (see also www.scibeh.org). Now we’re, of course, stoked to showcase here an emerging and growing proof-of-concept of such an eclectic knowledge base on COVID-19 related research and information, focusing on the behavioral sciences, but also including other topics that seem pertinent to properly understand the issues at hand. The knowledge base exists as a collection of annotations created using hypothes.is (see the screenshot in Figure 1), a “new effort to implement an old idea: A conversation layer over the entire web that works everywhere, without needing implementation by any underlying site”(see here for the basics of annotating with hypothes.is). Please take a moment and visit the knowledge base and explore what’s there. You can click on the tags on the right side to filter annotations or use the search bar at the top; see here for more information on how to search on hypothes.is.

Boosting COVID-19 related behavioral science by feeding and consulting an eclectic knowledge base

Distrust in scientific expertise1,2,3,4,5,6,7,8,9,10,11,12,13,14 is dangerous. Opposition to vaccination with a future vaccine against SARS-CoV-2, the causal agent of COVID-19, for example, could amplify outbreaks2,3,4, as happened for measles in 20195,6. Homemade remedies7,8 and falsehoods are being shared widely on the Internet, as well as dismissals of expert advice9,10,11. There is a lack of understanding about how this distrust evolves at the system level13,14. Here we provide a map of the contention surrounding vaccines that has emerged from the global pool of around three billion Facebook users. Its core reveals a multi-sided landscape of unprecedented intricacy that involves nearly 100 million individuals partitioned into highly dynamic, interconnected clusters across cities, countries, continents and languages. Although smaller in overall size, anti-vaccination clusters manage to become highly entangled with undecided clusters in the main online network, whereas pro-vaccination clusters are more peripheral. Our theoretical framework reproduces the recent explosive growth in anti-vaccination views, and predicts that these views will dominate in a decade. Insights provided by this framework can inform new policies and approaches to interrupt this shift to negative views. Our results challenge the conventional thinking about undecided individuals in issues of contention surrounding health, shed light on other issues of contention such as climate change11, and highlight the key role of network cluster dynamics in multi-species ecologies15.

Article Published: 13 May 2020 The online competition between pro- and anti-vaccination views

As the EU continues to face the COVID-19 pandemic, an unprecedented transboundary crisis, its member states resort to measures within the boundaries of the nation state. This situation questions the capacity of the EU to deploy public health instruments to cope with pandemics. One such instrument, the European Centre for Disease Control (ECDC), seems to show a discreet involvement in this crisis, suggesting emerging isolationist behaviours of the member states.

Where are the ECDC and the EU-wide responses in the COVID-19 pandemic?

Social networks continuously change as new ties are created and existing ones fade. It is widely acknowledged that our social embedding has a substantial impact on what information we receive and how we form beliefs and make decisions. However, most empirical studies on the role of social networks in collective intelligence have overlooked the dynamic nature of social networks and its role in fostering adaptive collective intelligence. Therefore, little is known about how groups of individuals dynamically modify their local connections and, accordingly, the topology of the network of interactions to respond to changing environmental conditions. In this paper, we address this question through a series of behavioral experiments and supporting simulations. Our results reveal that, in the presence of plasticity and feedback, social networks can adapt to biased and changing information environments and produce collective estimates that are more accurate than their best-performing member. To explain these results, we explore two mechanisms: 1) a global-adaptation mechanism where the structural connectivity of the network itself changes such that it amplifies the estimates of high-performing members within the group (i.e., the network “edges” encode the computation); and 2) a local-adaptation mechanism where accurate individuals are more resistant to social influence (i.e., adjustments to the attributes of the “node” in the network); therefore, their initial belief is disproportionately weighted in the collective estimate. Our findings substantiate the role of social-network plasticity and feedback as key adaptive mechanisms for refining individual and collective judgments.

Adaptive social networks promote the wisdom of crowds

About 20% of UK population vulnerable but not included in government’s shielding advice

Millions with health conditions at risk from Covid-19 'if forced back to work'

COVID-19 presents humanity with one of the greatest health and economic crises of the 21st Century. Because COVID-19 has already begun to precipitate a huge increase in mental health problems, we believe that clinical science must also play a leadership role in guiding a national response to this secondary crisis. In this article, we explain why COVID-19 is a game-changer, as a unique, compounding, multi-dimensional stressor that will create a vast need for intervention, and necessitate new paradigms for mental health service delivery and training. We highlight the most urgent challenge areas for clinical science, including managing potential spikes in depression, anxiety, and suicide, and address the unique COVID-19-related needs across the lifespan and the challenges that COVID-19 places on families and relationships. Clinical science also will need to address the mental health of medical care workers, mitigate health disparities, and address stigma among the most vulnerable as the pandemic unfolds. For each challenge area, we suggest research directions, clinical approaches, and policy issues that need to be considered. We then discuss how to enable multi-level deployment of potential solutions and how clinical science must itself adapt to identify and deliver these solutions. We conclude by highlighting new areas for clinical science discovery and additional funding needs. Advances in clinical science implementation—propelled by COVID-19—will likely endure long beyond the pandemic.

Clinical Psychological Science’s Call To Action in the Time of COVID-19

Single empirical tests are always ambiguous in their implications for the theory under investigation, because non-corroborative evidence leaves us underdetermined in our decision as to whether the main theoretical hypothesis or one or more auxiliary hypotheses should bear the burden of falsification. Popperian methodological falsificationism tries to solve this problem by relegating certain kinds of auxiliary hypotheses to “unproblematic background knowledge” and disallowing others. Auxiliary hypotheses regarding operational definitions of theoretical terms are not only permissible but indispensable to increase the falsifiability of theories. However, decisions to accept such auxiliaries as unproblematic are seldom conclusively justified. This uncertainty is amplified in the social sciences, where operationalizations play a very central role, but are much less theory-driven and independently testable. This situation has direct consequences for the assessment of the outcomes of replication attempts. Neither close nor conceptual replications can mitigate underdetermination when they are conducted in isolation. To circumvent this problem, we propose Systematic Replications Framework (SRF) that organizes subsequent tests into a pre-planned series of logically interlinked close and conceptual replications. SRF aims to decrease underdetermination by disentangling the implications of non-corroborative findings for the main theoretical hypothesis and the operationalization-related auxiliary hypotheses. SRF can also strengthen hypothesis testing through systematically organized and pre-registered self-replications. We also discuss how applying this framework can scaffold judgments regarding the permissibility of ad hoc hypothesizing in reference to the Lakatosian notions of progressive and degenerative research programs.

Replication Under Underdetermination: Introducing Systematic Replications Framework

Hospital staff are carrying COVID-19 without realising they’re infected, a new study by researchers at the University of Cambridge has shown...

Hospital staff carrying COVID-19

France has been heavily affected by the SARS-CoV-2 epidemic and went into lockdown on the 17 March 2020. Using models applied to hospital and death data, we estimate the impact of the lockdown and current population immunity. We find 3.6% of infected individuals are hospitalized and 0.7% die, ranging from 0.001% in those <20 years of age (ya) to 10.1% in those >80ya. Across all ages, men are more likely to be hospitalized, enter intensive care, and die than women. The lockdown reduced the reproductive number from 2.90 to 0.67 (77% reduction). By 11 May 2020, when interventions are scheduled to be eased, we project 2.8 million (range: 1.8–4.7) people, or 4.4% (range: 2.8–7.2) of the population, will have been infected. Population immunity appears insufficient to avoid a second wave if all control measures are released at the end of the lockdown.

Estimating the burden of SARS-CoV-2 in France

Every workplace that has transitioned to work-from-home should adopt these principles https://t.co/S76u2GbUie

Every day, our volunteers compile the latest numbers on tests, confirmed cases, hospitalizations, and patient outcomes from every US state and territory.

The public deserves the most complete data available about COVID-19 in the US. No official source is providing it, so we are.

Our daily update is published. We’ve now tracked 9.7 million tests, up 306k from yesterday. Note that we can only track tests that a state reports. For details, see: http://covidtracking.com

What is already known about this topic? Superspreading events involving SARS-CoV-2, the virus that causes COVID-19, have been reported. What is added by this report? Following a 2.5-hour choir practice attended by 61 persons, including a symptomatic index patient, 32 confirmed and 20 probable secondary COVID-19 cases occurred (attack rate = 53.3% to 86.7%); three patients were hospitalized, and two died. Transmission was likely facilitated by close proximity (within 6 feet) during practice and augmented by the act of singing. What are the implications for public health practice? The potential for superspreader events underscores the importance of physical distancing, including avoiding gathering in large groups, to control spread of COVID-19. Enhancing community awareness can encourage symptomatic persons and contacts of ill persons to isolate or self-quarantine to prevent ongoing transmission.

High SARS-CoV-2 Attack Rate Following Exposure at a Choir Practice — Skagit County, Washington, March 2020

Many aspects of human and animal interaction, such as the frequency of contacts of an individual, the number of interaction partners, and the time between the contacts of two individuals, are characterized by heavy-tailed distributions. These distributions affect the spreading of, e.g., infectious diseases or rumors, often because of impacts of the right tail of the distributions (i.e., the large values). In this paper we show that when it comes to inter-event time distributions, it is not the tail but the small values that control spreading dynamics. We investigate this effect both analytically and numerically for different versions of the susceptible-infected-recovered model on different types of networks.

Small inter-event times govern epidemic spreading on networks

The integration of social science with computer science and engineering fields has produced a new area of study: computational social science. This field applies computational methods to novel sources of digital data such as social media, administrative records, and historical archives to develop theories of human behavior. We review the evolution of this field within sociology via bibliometric analysis and in-depth analysis of the following subfields where this new work is appearing most rapidly: (a) social network analysis and group formation; (b) collective behavior and political sociology; (c) the sociology of knowledge; (d) cultural sociology, social psychology, and emotions; (e) the production of culture; ( f ) economic sociology and organizations; and (g) demography and population studies. Our review reveals that sociologists are not only at the center of cutting-edge research that addresses longstanding questions about human behavior but also developing new lines of inquiry about digital spaces as well. We conclude by discussing challenging new obstacles in the field, calling for increased attention to sociological theory, and identifying new areas where computational social science might be further integrated into mainstream sociology.

Computational Social Science and Sociology

This video was written by John Cook (George Mason University), Stephan Lewandowsky (University of Bristol), Ullrich Ecker (University of Western Australia), and Sander van Der Linden (Cambridge University).

Plandemic and the seven traits of conspiratorial thinking

Chemist David King is no stranger to politics or epidemics. From 2000 to 2007, King was chief scientific adviser to Tony Blair and Gordon Brown, U.K. prime ministers from the Labour Party. During that time, an outbreak of foot-and-mouth disease led to the culling of millions of sheep and cattle. Meanwhile, in humans, the severe acute respiratory syndrome virus spread from China to two dozen countries, including the United Kingdom, before the epidemic was contained. In the current pandemic of SARS-CoV-2, King has criticized the way scientific advice has been handled by the Conservative U.K. government. He has charged, for instance, that the membership of the Scientific Advisory Group for Emergencies (SAGE) should be made public—along with its advice. King has assembled a dozen scientists into an unofficial panel that he calls an independent SAGE. Last week, it conducted its first meeting, which was livestreamed on YouTube.

U.K. government should not keep scientific advice secret, former chief adviser says

DEBATT. Flera datamodeller som har presenterats för att förutse smittspridning av covid-19 har varit väldigt komplexa – trots brist på validerat underlag. Det bör man vara varsam med, skriver 15 forskare.

Forskare: ”Se upp med komplexa coronamodeller – de kan överträffa verkligheten”

The Internet has evolved into a ubiquitous digital environment in which people communicate, seek information, and make decisions. Online environments are replete with smart, highly adaptive choice architectures designed primarily to maximize commercial interests, capture and sustain users’ attention, monetize user data, and predict and influence future behavior. This online landscape holds multiple negative consequences for society, such as a decline in human autonomy, rising incivility in online conversation, the facilitation of political extremism, and the spread of disinformation. Benevolent choice architects working with regulators may curb the worst excesses of manipulative choice architectures, yet the strategic advantages, resources, and data remain with commercial players. One way to address this imbalance is with interventions that empower Internet users to gain some control over their digital environments, in part by boosting their information literacy and their cognitive resistance to manipulation. Our goal is to present a conceptual map of interventions that are based on insights from psychological science. We begin by systematically outlining how online and offline environments differ despite being increasingly inextricable. We then identify four major types of challenges that users encounter in online environments: persuasive and manipulative choice architectures, AI-assisted information architectures, distractive environments, and false and misleading information. Next, we turn to how psychological science can inform interventions to counteract these challenges of the digital world. After distinguishing between three types of behavioral and cognitive interventions—nudges, technocognition, and boosts—we focus in on boosts, of which we identify two main groups: (1) those aimed at enhancing people’s agency in their digital environments (e.g., self-nudging, deliberate ignorance) and (2) those aimed at boosting competences of reasoning and resilience to manipulation (e.g., simple decision aids, inoculation). These cognitive tools are designed to foster the civility of online discourse and protect reason and human autonomy against manipulative choice architectures, attention-grabbing techniques, and the spread of false information.

Citizens Versus the Internet: Confronting Digital Challenges With Cognitive Tools

Cognitive scientists have ramped up online testing in response to the coronavirus pandemic. Although research conducted online solves the problem of data collection, a lack of internet access among low-income and minority communities may reduce the diversity of study samples and, thus, impact the generalizability of scientific findings.

No Participant Left Behind: Conducting Science During COVID-19

Never has there been a rallying point for science advice at a global scale as we are now experiencing with the COVID-19 pandemic.  With it come the hallmarks of advising in a time of crisis:  the evidence is uncertain, the science is fast-moving, the stakes are high and, in some public discussions at least, values are in dispute. Our goal is to mobilise the INGSA network to help keep track of  HOW policy interventions are being made by various national and sub-national (state, province, etc.) governments across the world. We are interested in the advice, evidence or other justifications that underpin governments’ decisions as the crisis unfolds.

COVID-19 Policy-Making Tracker

It seems many people are breathing some relief, and I’m not sure why. An epidemic curve has a relatively predictable upslope and once the peak is reached, the back slope can also be predicted. We have robust data from the outbreaks in China and Italy, that shows the backside of the mortality curve declines slowly, with deaths persisting for months. Assuming we have just crested in deaths at 70k, it is possible that we lose another 70,000 people over the next 6 weeks as we come off that peak. That's what's going to happen with a lockdown. As states reopen, and we give the virus more fuel, all bets are off. I understand the reasons for reopening the economy, but I've said before, if you don't solve the biology, the economy won't recover.

The Risks - Know Them - Avoid Them

To guard against rushed and sloppy science, build pressure testing into your research.

Pandemic researchers — recruit your own best critics

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Link prediction algorithms can help to understand the structure and dynamics of scientific collaborations and the evolution of Science. However, available algorithms based on similarity between nodes of collaboration networks are bounded by the limited amount of links present in these networks. In this work, we reduce the latter intrinsic limitation by generalizing the Adamic-Adar method to multiplex networks composed by an arbitrary number of layers, that encode diverse forms of scientific interactions. We show that the new metric outperforms other single-layered, similarity-based scores and that scientific credit, represented by citations, and common interests, measured by the usage of common keywords, can be predictive of new collaborations. Our work paves the way for a deeper understanding of the dynamics driving scientific collaborations, and provides a new algorithm for link prediction in multiplex networks that can be applied to a plethora of systems.

Prediction of scientific collaborations through multiplex interaction networks

COVID-19 has dramatically changed our lives and affected how we move, shop, work, and interact with each other. In this dashboard we provide a set of indicators that summarize how people's behaviors adapted in response to the ongoing outbreak.

Mobility, commuting, and contact patterns across the United States during the COVID-19 outbreak

These are very interesting initiatives, and a very useful post - it is quite heartening to see how much self-organisation has occurred in such a short space of time.One type of consideration that seems difficult to bring into the discussion is purely practical. So, for example, regarding policies of PPE equipment, and the speed with which testing might be expanded, there is almost certainly a great deal of expertise distributed around the policy, healthcare management, practitioner, and business community that would help identify what the current situation is, and what realistic options there are to help fix it.Many of these people may not be able to contribute except anonymously---it would be incredibly helpful to have some way of allowing insiders to safely (in terms of their careers) feed relevant information to the debate.It is not obvious how we do this, but perhaps something reminiscent of a prediction market, although surely with no money changing hands, might be helpful.Similarly, it would be great to have some way of aggregating experiences and judgements from relevant individuals (e.g., some kind of barometer for PPE/testing availability which could be based on judgements by frontline staff; or priorities from the frontline which may be very different from those perceived from the upper reaches of government, or indeed the academic community).

It is interesting what is being termed political. In a radio programme this morning, my common sense suggestion that school playing fields & golf courses be opened up for those without access to green space to walk on in lockdown was labelled #political.

How do we know " R "? We don't know for sure, but we can make educated guesses based on various data. We list our sources here

R in the UK is at most

Many social issues are complex and science is important when designing policies to address them. Yet scientific evidence is sometimes uncertain and this makes decision-making challenging. This opinion provides guidelines to Commission policy makers on the characteristics of good scientific advice under these conditions of complexity and uncertainty. Among others, the process must be transparent, advisors' impartial, advice based on comprehensive evidence, and developed in dialogue with policy makers.

Scientific Advice to European Policy in a Complex World