Background: Insights from epidemiologic models have helped to guide and improve understanding of mitigation policies for coronavirus disease 2019 (COVID-19) across the globe. As the pandemic progresses, models can be used to quantify what may unfold when such measures are relaxed.Objective: To explore the effect of physical distancing measures on COVID-19 transmission in the population of Ontario, Canada.Methods and Findings: We previously described a transmission model of COVID-19, stratified by age and health status, in the Canadian province of Ontario (1). It evaluated nonpharmaceutical interventions to control the COVID-19 pandemic and preserve intensive care unit (ICU) capacity. The model found that physical distancing effectively mitigated spread but needed to be applied for long durations in either a sustained manner or with periodic dialing up and down of restrictions to prevent resurgence of infections and keep the number of cases requiring ICU care below ICU capacity.

How might behavioural science help us tackle coronavirus as lockdowns ease throughout the world? Co-author of bestselling book Nudge and author of How Change Happens joins us to talk about why social movements catch on, the power of nudges, COVID and coping with change.

We use the synthetic control method to analyze the effect of face masks on the spread of Covid-19 in Germany. Our identification approach exploits regional variation in the point in time when face masks became compulsory. Depending on the region we analyse, we find that face masks reduced the cumulative number of registered Covid-19 cases between 2.3% and 13% over a period of 10 days after they became compulsory. Assessing the credibility of the various estimates, we conclude that face masks reduce the daily growth rate of reported infections by around 40%.

A dysfunctional political, media and educational system is a big part of the COVID problems in the UK, USA and Brazil. Unfortunately that is a part that science cannot change by itself.

COVID-19’s impacts on workers and workplaces across the globe have been dramatic. We present a broad review of prior research rooted in work and organizational psychology, and related fields, for making sense of the implications for employees, teams, and work organizations. Our review and preview of relevant literatures focuses on: (i) emerging changes in work practices (e.g., working from home, virtual teams) and (ii) economic and social-psychological impacts (e.g, unemployment, mental well-being). In addition, we examine the potential moderating factors of age, race and ethnicity, gender, family status, personality, and cultural differences to generate disparate effects. Illustrating the benefits of team science, our broad-scope overview provides an integrative approach for considering the implications of COVID-19 for work and organizations while also identifying issues for future research and insights to inform solutions.

Wearing face masks is one of the essential means to prevent the transmission of certain respiratory diseases such as COVID-19. Although acceptance of such masks increases in the Western hemisphere, many people feel that social interaction is affected by wearing a mask. In the present experiment, we tested the impact of face masks on the readability of emotions. The participants (N=41, calculated by an a priori power test; random sample; healthy persons of different ages, 18-87 years) assessed the emotional expressions displayed by twelve different faces. Each face was randomly presented with six different expressions (angry, disgusted, fearful, happy, neutral, sad) while being fully visible or partly covered by a face mask. Lower accuracy and lower confidence in one’s own assessment of the displayed emotions indicate that emotional reading was strongly irritated by the presence of a mask. We further detected specific confusion patterns, mostly pronounced in the case of misinterpreting disgusted faces as being angry plus assessing many other emotions (e.g. happy, sad and angry) as neutral. We discuss compensatory actions that can keep social interaction effective (e.g. body language, gesture and verbal communication), even when relevant visual information is crucially reduced.

The aim of this study was to assess the temporal evolution of the psychological impact of the COVID-19 crisis and lockdown from two surveys carried out in Spain with a time difference of about one month. Symptoms of depression, anxiety and stress, and the psychological impact of the situation were longitudinally analyzed using the Depression Anxiety and Stress Scale (DASS-21) and the Impact of Event Scale (IES) respectively. The Brief Resilient Coping Scale (BRCS) and the Mini-Social Phobia Inventory (Mini-SPIN) were also employed to evaluate resilience and social anxiety. There was a total of 4,724 responses from both surveys. Symptomatic scores of anxiety, depression and stress were exhibited by 37.22%, 46.42% and 49.66% of the second survey respondents, showing a significant increase compared to the first survey (32.45%, 44.11% and 37.01%, respectively). There was no significant longitudinal change of the IES scores, with 48.30% of the second survey participants showing moderate to severe impact of the confinement. Low resilience was shown by 40.5% of the respondents, and high social anxiety by 34.8%. Constant news consumption about COVID-19 was found to be positively associated with symptomatic scores in the different scales. On the other hand, daily physical activity was found to be negatively associated with DASS-21 scores. Results indicate that people with social anxiety might be especially vulnerable to the development of other mental disorders after the relaxation of the confinement measures.

Study’s findings highlight potential long-term damage of UK’s early testing strategy

Our World in Data presents the data and research to make progress against the world’s largest problems.This blog post draws on data and research discussed in our entry on the Coronavirus Pandemic. We update this chart – but not the text – daily

Forecasting the evolution of contagion dynamics is still an open problem to which mechanistic models only offer a partial answer. To remain mathematically and/or computationally tractable, these models must rely on simplifying assumptions, thereby limiting the quantitative accuracy of their predictions and the complexity of the dynamics they can model. Here, we propose a complementary approach based on deep learning where the effective local mechanisms governing a dynamic are learned automatically from time series data. Our graph neural network architecture makes very few assumptions about the dynamics, and we demonstrate its accuracy using stochastic contagion dynamics of increasing complexity on static and temporal networks. By allowing simulations on arbitrary network structures, our approach makes it possible to explore the properties of the learned dynamics beyond the training data. Our results demonstrate how deep learning offers a new and complementary perspective to build effective models of contagion dynamics on networks.

LONDON (Reuters) - Population-wide face mask use could push COVID-19 transmission down to controllable levels for national epidemics, and could prevent further waves of the pandemic disease when combined with lockdowns, according to a British study on Wednesday.

From lethal pandemic to common cold: what we can learn from the events of 1889-90

As the world begins to unlock, many of us will be seeing friends and family again - albeit with guidelines on how close you can get to one another. But why is it more difficult to stay physically apart from friends and family than a stranger in a supermarket queue? Nicola Davis speaks to Prof John Drury about the psychology of physical distancing and why we like to be near those we feel emotionally close with

Following on from its successful conception during the Curious 2019 summer events programme, the RSE has launched their ‘Tea & Talk‘ series as a podcast to provide access to experts talking on a wide range of subjects and provide the opportunity for listeners to learn something new, expand their horizons and hear from national and world experts in their respective disciplines. Hosted by Dr Rebekah Widdowfield, listen to a new episode every Friday.

A second wave of coronavirus cases would be disastrous – but there are ways to prevent this happening

Existing compartmental mathematical modelling methods for epidemics, such as SEIR models, cannot accurately represent effects of contact tracing. This makes them inappropriate for evaluating testing and contact tracing strategies to contain an outbreak. An alternative used in practice is the application of agent- or individual-based models (ABM). However ABMs are complex, less well-understood and much more computationally expensive. This paper presents a new method for accurately including the effects of Testing, contact-Tracing and Isolation (TTI) strategies in standard compartmental models. We derive our method using a careful probabilistic argument to show how contact tracing at the individual level is reflected in aggregate on the population level. We show that the resultant SEIR-TTI model accurately approximates the behaviour of a mechanistic agent-based model at far less computational cost. The computationally efficiency is such that it be easily and cheaply used for exploratory modelling to quantify the required levels of testing and tracing, alone and with other interventions, to assist adaptive planning for managing disease outbreaks.

There have been claims that #COVID19 has acquired mutations leading to more transmissible strains. We formally tested whether this was the case using 15,000 #SARSCoV2 genomes from all over the world:... and the answer is no, not at all!

Aims and Scope The British Journal of Health Psychology publishes original research on all aspects of psychology related to health, health-related behaviour and illness across the lifespan including: • experimental and clinical research on aetiology • management of acute and chronic illness • responses to ill-health • screening and medical procedures • psychosocial mediators of health-related behaviours • influence of emotion on health and health-related behaviours • psychosocial processes relevant to disease outcomes• health related behaviour change • psychological interventions in health and disease • emotional and behavioural responses to ill health, screening and medical procedures • psychological aspects of prevention It encourages submissions of papers reporting experimental, theoretical and applied studies using quantitative, qualitative and mixed-methods approaches. Research carried out at the individual, group and community levels is welcome. The journal also welcomes systematic reviews and meta-analyses. Submissions concerning clinical applications and interventions are particularly encouraged.

Aims and Scope The British Journal of Social Psychology publishes work from scholars based in all parts of the world, and manuscripts that present data on a wide range of populations inside and outside the UK. It publishes original papers in all areas of social psychology including: • social cognition• attitudes• group processes• social influence• intergroup relations• self and identity• nonverbal communication• social psychological aspects of personality, affect and emotion• language and discourse Submissions addressing these topics from a variety of approaches and methods, both quantitative and qualitative are welcomed. We publish papers of the following kinds: • empirical papers that address theoretical issues; • theoretical papers, including analyses of existing social psychological theories and presentations of theoretical innovations, extensions, or integrations; • review papers that provide an evaluation of work within a given area of social psychology and that present proposals for further research in that area; • methodological papers concerning issues that are particularly relevant to a wide range of social psychologists; • an invited agenda article as the first article in the first part of every volume. The editorial team aims to handle papers as efficiently as possible. In 2016, papers were triaged within less than a week, and the average turnaround time from receipt of the manuscript to first decision sent back to the authors was 47 days.

To facilitate the dissemination of findings on psychologically relevant aspects of the COVID-19 crisis, the Association for Psychological Science and SAGE publications have joined together to fast-track the publication of articles in Psychological Science that deal with COVID-19. As always, Psychological Science welcomes the submission of papers presenting original research, theory, or applications on mind, brain, or behavior. Preference is given to papers that make a new and notable contribution—an idea, a discovery, a connection—to psychological science, broadly interpreted, and that are written to be relevant for and intelligible to a wide range of readers. These standards will not change. What is new in response to the crisis is that Psychological Science makes the commitment to expedite the peer review process for COVID-19 related submissions. As well, pre-copyedited manuscripts will be posted on SAGE’s site immediately upon acceptance and then will be replaced with the final version once it is ready. By taking these steps, APS and Psychological Science will speed dissemination of information that will help us deal with this unprecedented crisis. Best wishes for good health.

There is no business-as-usual during this uniquely challenging time. Here is what we are doing to help the scientific community both in providing much needed evidence to guide policy and in managing the personal impacts of the pandemic on individual researchers.

The COVID-19 pandemic is having many life-altering short- and likely long-term effects. There are many potential applications of psychological theory, practice, and research that can contribute to the public good at this time of national and international crisis. American Psychologist invites papers related directly to the pandemic. As for all American Psychologist manuscripts, we seek high-impact papers of broad interest covering science, practice, education, or policy. Manuscripts should be written in a style that is accessible to all psychologists and the public. For manuscripts that appear to be a good fit, we will follow our usual procedures and conduct a quick initial review of submissions to assure a fit with the type of articles published in this journal. Please note that American Psychologist does not publish independent commentaries (other than comments on recently published articles in the journal). Those manuscripts selected for further consideration will be peer reviewed and fast-tracked for publication if accepted. We will strive to provide editorial decision letters within one week of completed submission. Authors will be expected to revise manuscripts promptly. Accepted articles will be posted online within a short time frame and prioritized for publication. Manuscripts will be considered as they are received independently, not for a special issue. Authors should follow the American Psychologist manuscript submission guidelines and submit to the manuscript submission portal, selecting as article type "COVID-19". We ask that you indicate prominently in your cover letter that your manuscript is related to the COVID-19 pandemic. Submissions for this call will be received through August 31, 2020.

The goal of this Research Topic is to stimulate novel investigations and theoretical perspectives on how people are psychologically affected by and coping with the COVID-19 emergency. We intend for this article collection to be a discussion platform on how to help people cope with and adjust to the critical situation. Specific aims include reducing the risk of developing distress, improving well-being, as well as promoting preventive behaviors. Further, this Research Topic aims to offer governments and policymakers evidence-based strategies to improve public and clinical intervention systems. Finally, we aim to elucidate strategies to effectively manage mental health in the COVID-19 pandemic.

Why would people share news they think might not be accurate? We identify a factor that, alongside accuracy, drives the sharing of true and fake news: the ‘interestingness-if-true’ of a piece of news. In two pre-registered experiments (N = 604), participants were presented with a series of true and fake news, and asked to rate the accuracy of the news, how interesting the news would be if it were true, and how likely they would be to share it. Both interestingness-if-true and accuracy played an important role in explaining the sharing of true and fake news, with participants more willing to share news they thought interesting-if-true, and accurate. Participants also found fake news less accurate but more in-teresting-if-true than true news, and were more likely to share true news than fake news. Higher trust in mass media was associated with a greater ability to discern between true and fake news, and partic-ipants rated as more accurate news that they had already been exposed to (especially among true news). These results suggest that people may not share news of questionable accuracy by mistake, but instead because the news has qualities that make up for its potential inaccuracy, such as being interesting-if-true.

A crucial indicator of whether Americans feel safe returning to normal activities.

That American and European participants are overrepresented in psychological studies has been previously established. In addition, researchers also often tend to be similarly homogenous. This continues to be alarming, especially given that this research is being used to inform policies across the world. In the face of a global pandemic where behavioral scientists propose solutions, we ask who is conducting research and on what samples. Forty papers on COVID-19 published in PsyArxiV were analyzed; the nationalities of the authors and the samples they recruited were assessed. Findings suggest that an overwhelming majority of the samples recruited were from the US and the authors were based in US and German institutions. Next, men constituted a large proportion of primary and sole authors. The implications of these findings are discussed.

As the coronavirus pandemic forces people to keep their distance, could this be robots‘ time to shine? A group of scientists think so, and they’re calling for robots to do the “dull, dirty, and dangerous jobs” of infectious disease management.

We describe in this report our studies to understand the relationship between human mobility and the spreading of COVID-19, as an aid to manage the restart of the social and economic activities after the lockdown and monitor the epidemics in the coming weeks and months. We compare the evolution (from January to May 2020) of the daily mobility flows in Italy, measured by means of nation-wide mobile phone data, and the evolution of transmissibility, measured by the net reproduction number, i.e., the mean number of secondary infections generated by one primary infector in the presence of control interventions and human behavioural adaptations. We find a striking relationship between the negative variation of mobility flows and the net reproduction number, in all Italian regions, between March 11th and March 18th, when the country entered the lockdown. This observation allows us to quantify the time needed to "switch off" the country mobility (one week) and the time required to bring the net reproduction number below 1 (one week). A reasonably simple regression model provides evidence that the net reproduction number is correlated with a region's incoming, outgoing and internal mobility. We also find a strong relationship between the number of days above the epidemic threshold before the mobility flows reduce significantly as an effect of lockdowns, and the total number of confirmed SARS-CoV-2 infections per 100k inhabitants, thus indirectly showing the effectiveness of the lockdown and the other non-pharmaceutical interventions in the containment of the contagion. Our study demonstrates the value of "big" mobility data to the monitoring of key epidemic indicators to inform choices as the epidemics unfolds in the coming months.

No matter how well intentioned, sometimes hyper-precautionary rules can be deadly. By defaulting public policies to super-cautious mode and curtailing important innovations, laws and regulations can actually make the world less safe.    A new NBER working paper finds exactly this: the authors examined the “unintended effects from invoking the precautionary principle after the Fukushima Daiichi nuclear accident,” which occurred in Japan in March 2011 due to a tsunami. They find that the Japanese government’s decision to entirely abandon nuclear energy following the incident resulted in many unnecessary deaths, primarily due to increased energy costs and corresponding cold weather-related welfare effects. Japan’s decision also has had potentially serious environmental implications.   The precautionary principle, in other words, can cost more lives than it saves.

Réalisée depuis début mai auprès d’un échantillon représentatif de la population vaudoise, l’étude SérocoViD vise à comprendre la manière dont le coronavirus, qui provoque la COVID-19, se transmet au sein de la population, afin de guider les autorités politiques et de santé publique pour prendre les mesures adéquates de lutte contre l’épidémie.

One important response to the pandemic has been social distancing, that is, asking people to keep a minimum safe distance from others not in their household. How can you encourage individuals to keep the recommended minimal distance to others?

A pressing, non-health, question for policy-makers is how far behavioural changes during the lock-down period "stick." Specifically:What types of behaviours will stick and which might even re-bound. For example, which individuals/business will shift permanently to greater use of video conferencing? Will people remain averse to air travel? Public spaces, transport? Large gatherings? And for how long?How much does the length of the lockdown effect the "stickiness" of new behaviours?Lots of basic psychology relevant here - but also what do we know about relevant real-world cases?

Yes, to be maximally effective we should, as behavioural scientists be addressing either policy relevant questions, or be conducting research that will directly inform policy relevant questions.This poses a challenge for scientists not directly engaged in the policy process. However, I think there are a couple of additional considerations beyond what you list that might be in play for COVID-19. One is that the pandemic is global, but countries are going through it on different time tables. So even if we are interested primarily in the policy of our own country we can potentially look ahead, using resources such as the INGSA policy tracker (ingsa.org) to see what is coming.Second, our role as behavioural scientists might actually most effective at spotting issues, not providing answers (see here and here for discussion), that is, considering policy options and trying to identify problems/issues they might raise (a bit like here or here). Scibeh.org is about to launch a process involving these reddits that tries to make that a bit more systematic!

Public trust in the authorities has been recognised in risk research as a crucial component of effective and efficient risk management. But in a pandemic, where the primary responsibility of risk management is not centralised within institutional actors but defused across society, trust can become a double-edged sword. Under these conditions, public trust based on a perception of government competence, care and openness may in fact lead people to underestimate risks and thus reduce their belief in the need to take individual action to control the risks. In this paper, we examine the interaction between trust in government, risk perceptions and public compliance in Singapore in the period between January and April 2020. Using social media tracking and online focus group discussions, we present a preliminary assessment of public responses to government risk communication and risk management measures. We highlight the unique deployment of risk communication in Singapore based on the narrative of ‘defensive pessimism’ to heighten rather than lower levels perceived risk. But the persistence of low public risk perceptions and concomitant low levels of compliance with government risk management measures bring to light the paradox of trust. This calls for further reflection on another dimension of trust which focuses on the role of the public; and further investigation into other social and cultural factors that may have stronger influence over individual belief in the need to take personal actions to control the risks.

Since the emergence of HIV/AIDS in the 1980s, social scientists and sociologists of health and illness have been exploring the metaphorical framing of this infectious disease in its social context. Many have focused on the militaristic language used to report and explain this illness, a type of language that has permeated discourses of immunology, bacteriology and infection for at least a century. In this article, we examine how language and metaphor were used in the UK media's coverage of another previously unknown and severe infectious disease: Severe Acute Respiratory Syndrome (SARS). SARS offers an opportunity to explore the cultural framing of a less extraordinary epidemic disease. It therefore provides an analytical counter-weight to the very extensive body of interpretation that has developed around HIV/AIDS. By analysing the total reporting on SARS of five major national newspapers during the epidemic of spring 2003, we investigate how the reporting of SARS in the UK press was framed, and how this related to media, public and governmental responses to the disease. We found that, surprisingly, militaristic language was largely absent, as was the judgemental discourse of plague. Rather, the main conceptual metaphor used was SARS as a killer. SARS as a killer was a single unified entity, not an army or force. We provide some tentative explanations for this shift in linguistic framing by relating it to local political concerns, media cultures, and spatial factors.

We review the meaning of the concept of framing, approaches to studying framing, and the effects of framing on public opinion. After defining framing and framing effects, we articulate a method for identifying frames in communication and a psychological model for understanding how such frames affect public opinion. We also discuss the relationship between framing and priming, outline future research directions, and describe the normative implications of framing.

INGSA provides the forum for policy makers, practitioners, national academies, scientific societies, and researchers to share experience, build capacities, and develop theoretical and practical approaches to the use of scientific evidence in informing policy at all levels of government.

During coronavirus (COVID-19) pandemic, healthcare professionals were particularly at high-risk of developing symptoms of mental health problems due to being on the frontline in the battle against COVID-19. This study examined the mediating roles of resilience and coronavirus fear in the relationship between perceived risk and mental health problems among healthcare professionals including doctors and nurses who were actively treating patients confirmed with COVID-19. We recruited 204 healthcare professionals (50% females) with a mean age of 32.92 years (SD=7.01). Results showed that perceived risk and coronavirus fear positively predicted depression, anxiety, and stress while resilience negatively predicted those mental health problems. Coronavirus fear mediated the relationship between perceived risk and resilience, depression, anxiety, and stress. Additionally, resilience mitigated the effect of coronavirus fear on depression, anxiety, and stress. This study is among the first indicating the importance of resilience and fear as critical mechanism that explain the relationship between perceived risk and mental health problems among health professionals directly caring for COVID-19 patients.

The key conclusions of our analysis are as follows: The UK epidemic comprises a very large number of importations due to inbound international travel2. We detect 1356 independently-introduced transmission lineages, however, we expect this number to be an under-estimate. The speed of detection of UK transmission lineages via genome sequencing has increased through time. Many UK transmission lineages now appear to be very rare or extinct, as they have not been detected by genome sequencing for >4 weeks. The rate and source of introduction of SARS-CoV-2 lineages into the UK changed substantially and rapidly through time. The rate peaked in mid-March and most introductions occurred during March 2020. We estimate that ≈34% of detected UK transmission lineages arrived via inbound travel from Spain, ≈29% from France, ≈14% from Italy, and ≈23% from other countries. The relative contributions of these locations were highly dynamic. The increasing rates and shifting source locations of SARS-CoV-2 importation were not fully captured by early contact tracing. Our results are preliminary and further analyses of these data are ongoing.

Objective: Social distancing has been one of the primary interventions used to slow the spread of COVID-19. State-wide stay-at-home orders received a large degree of attention as a public health intervention to increase social distancing, but relatively little peer-reviewed research has examined the extent to which stay-at-home orders affected people’s behavior. Method: This study used GPS-derived movement from 2,858 counties in the United States from March 1 to May 7, 2020 to test the degree to which changes in state-level stay-at-home orders were associated with movement outside the home. Results: From the first week of March to the first week of April, people in counties within states that enacted stay-at-home orders decreased their movement significantly more than people in counties within states that did not enact state-level stay-at-home orders. From the first week of April to the first week of May, people in counties within states that ended their stay-at-home orders increased their movement significantly more than people in counties within states whose stay-at-home orders remained in place. The magnitude of change in movement associated with state-level stay-at-home orders was many times smaller than the total change in movement across all counties over the same periods of time in both cases. Conclusions: Stay-at-home orders are likely insufficient to reduce people’s movement outside the home without additional public health actions. Existing research on behavior change would be useful to determine what additional interventions could support social distancing behaviors during the COVID-19 pandemic if becomes necessary to reduce movement in the future.

American officials were alarmed by fake text messages and social media posts that said President Trump was locking down the country. Experts see a convergence with Russian tactics.

SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), was first identified in December 2019 in Wuhan, China, and has since spread worldwide. On March 11, 2020, the World Health Organization declared COVID-19 a pandemic (1). That same day, the first confirmed COVID-19–associated fatality occurred in New York City (NYC). To identify confirmed COVID-19–associated deaths, defined as those occurring in persons with laboratory-confirmed SARS-CoV-2 infection, on March 13, 2020, the New York City Department of Health and Mental Hygiene (DOHMH) initiated a daily match between all deaths reported to the DOHMH electronic vital registry system (eVital) (2) and laboratory-confirmed cases of COVID-19. Deaths for which COVID-19, SARS-CoV-2, or an equivalent term is listed on the death certificate as an immediate, underlying, or contributing cause of death, but that do not have laboratory-confirmation of COVID-19 are classified as probable COVID-19–associated deaths. As of May 2, a total of 13,831 laboratory-confirmed COVID-19–associated deaths, and 5,048 probable COVID-19–associated deaths were recorded in NYC (3). Counting only confirmed or probable COVID-19–associated deaths, however, likely underestimates the number of deaths attributable to the pandemic. The counting of confirmed and probable COVID-19–associated deaths might not include deaths among persons with SARS-CoV-2 infection who did not access diagnostic testing, tested falsely negative, or became infected after testing negative, died outside of a health care setting, or for whom COVID-19 was not suspected by a health care provider as a cause of death. The counting of confirmed and probable COVID-19–associated deaths also does not include deaths that are not directly associated with SARS-CoV-2 infection. The objective of this report is to provide an estimate of all-cause excess deaths that have occurred in NYC in the setting of widespread community transmission of SARS-CoV-2. Excess deaths refer to the number of deaths above expected seasonal baseline levels, regardless of the reported cause of death. Estimation of all-cause excess deaths is used as a nonspecific measure of the severity or impact of pandemics (4) and public health emergencies (5). Reporting of excess deaths might provide a more accurate measure of the impact of the pandemic.

The spread of COVID-19 in the U.S. passed an inflection point in the last 2 weeks. The number of articles published about the global pandemic went from hundreds a day to a weekday average of roughly 1,400 articles. Spending endless hours reading COVID-19 updates quickly loses its marginal utility and can drive our underlying levels of anxiety, so knowing where to go for the best coverage is essential. Early on in the crisis, we looked at which outlets had the most credible stories; this week, we wanted to see which specific journalists you can rely on for credible, timely information—real updates on the global pandemic that actually matter. 

"We need to act now to avoid the worst impacts of our efforts to control the pandemic"

Background There is limited evidence of genuine equal partnership where power is shared with young people with mental health difficulties throughout all research stages, particularly in data collection and analysis. Objective To describe how our qualitative study, exploring young peoples’ perceptions on the feasibility of using technology to detect mental health deterioration, was co‐produced using principles of co‐production, whilst reflecting on impact, challenges and recommendations. Methods Young people with experience of mental health difficulties were appointed and then worked with researchers throughout all research stages. The study was evaluated against the five principles of co‐production. Reflections from researchers and young people were collected throughout. Results Seven young people formed an initial Young People's Advisory Group (YPAG); three became co‐researchers. Reflection was key throughout the process. Sharing power became easier and more evident as trust, confidence and mutual respect grew over time, particularly after a safe space was established. The safe space was crucial for open discussions, and our WhatsApp group enabled continual communication, support and shared decision‐making. The resulting co‐produced topic guide, coding framework, thematic map, papers and presentations demonstrated significant impact. Conclusions To our knowledge, this is the first qualitative mental health study to be co‐produced using the principles of co‐production. Our rigorous assessment can be utilized as an informative document to help others to produce meaningful co‐produced future research. Although co‐production takes time, it makes significant impact to the research, researchers and co‐researchers. Flexible funding for spontaneous suggestions from co‐researchers and more time for interview training is recommended.

Calls for the adoption of complex systems approaches, including agent-based modeling, in the field of epidemiology have largely centered on the potential for such methods to examine complex disease etiologies, which are characterized by feedback behavior, interference, threshold dynamics, and multiple interacting causal effects. However, considerable theoretical and practical issues impede the capacity of agent-based methods to examine and evaluate causal effects and thus illuminate new areas for intervention. We build on this work by describing how agent-based models can be used to simulate counterfactual outcomes in the presence of complexity. We show that these models are of particular utility when the hypothesized causal mechanisms exhibit a high degree of interdependence between multiple causal effects and when interference (i.e., one person's exposure affects the outcome of others) is present and of intrinsic scientific interest. Although not without challenges, agent-based modeling (and complex systems methods broadly) represent a promising novel approach to identify and evaluate complex causal effects, and they are thus well suited to complement other modern epidemiologic methods of etiologic inquiry.

We provide a description of the Epidemics on Networks (EoN) python package designed for studying disease spread in static networks. The package consists of over 100100 methods available for users to perform stochastic simulation of a range of different processes including SIS and SIR disease, and generic simple or comlex contagions.

This textbook provides an exciting new addition to the area of network science featuring a stronger and more methodical link of models to their mathematical origin and explains how these relate to each other with special focus on epidemic spread on networks. The content of the book is at the interface of graph theory, stochastic processes and dynamical systems. The authors set out to make a significant contribution to closing the gap between model development and the supporting mathematics. This is done by:Summarising and presenting the state-of-the-art in modeling epidemics on networks with results and readily usable models signposted throughout the book;Presenting different mathematical approaches to formulate exact and solvable models;Identifying the concrete links between approximate models and their rigorous mathematical representation;Presenting a model hierarchy and clearly highlighting the links between model assumptions and model complexity;Providing a reference source for advanced undergraduate students, as well as doctoral students, postdoctoral researchers and academic experts who are engaged in modeling stochastic processes on networks;Providing software that can solve differential equation models or directly simulate epidemics on networks.Replete with numerous diagrams, examples, instructive exercises, and online access to simulation algorithms and readily usable code, this book will appeal to a wide spectrum of readers from different backgrounds and academic levels. Appropriate for students with or without a strong background in mathematics, this textbook can form the basis of an advanced undergraduate or graduate course in both mathematics and other departments alike. 

Understanding and Exploring Network Epidemiology in the Time of Coronavirus (Net-COVID) was a special online workshop series presented by the University of Maryland’s COMBINE program in Network Biology in partnership with the University of Vermont’s Complex Systems Center.Videos of our Tutorials & Seminars and our Discussion/ Working Group Series are available for those who couldn't join our live sessions in April 2020. Content is aimed at the level of STEM graduate students.

In the United States and around the world, the conversation around COVID-19 is shifting toward reopening. But how do we know when it’s safe to reopen schools, businesses, communities, and countries? How do we make and follow a careful plan? And what will our new normal be when we get there? Some of the best tools we have to make these decisions are epidemiological models, which predict how the disease will spread. Alessandro Vespignani, director of the Network Science Institute and Sternberg Family distinguished university professor of physics, computer sciences, and health science, is leading one of the major modeling efforts and his work is informing the decisions being made at Northeastern, and around the world.  The university is planning a phased reopening, bringing faculty and staff back first, with the intention of opening all campuses to students in the fall. Following guidance from public health officials regarding COVID-19, the university is considering a number of safety measures, such as large-scale testing of students, faculty, and staff, as well as contact tracing for those who test positive for the virus. The priority, says Joseph E. Aoun, president of Northeastern, is “maintaining the health and wellbeing of the Northeastern University community—and the world beyond our campuses.”

The global impact of COVID-19 has been profound, and the public health threat it represents is the most serious seen in a respiratory virus since the 1918 H1N1 influenza pandemic. Here we present the results of epidemiological modelling which has informed policymaking in the UK and other countries in recent weeks. In the absence of a COVID-19 vaccine, we assess the potential role of a number of public health measures – so-called non-pharmaceutical interventions (NPIs) – aimed at reducing contact rates in the population and thereby reducing transmission of the virus. In the results presented here, we apply a previously published microsimulation model to two countries: the UK (Great Britain specifically) and the US. We conclude that the effectiveness of any one intervention in isolation is likely to be limited, requiring multiple interventions to be combined to have a substantial impact on transmission. Two fundamental strategies are possible: (a) mitigation, which focuses on slowing but not necessarily stopping epidemic spread – reducing peak healthcare demand while protecting those most at risk of severe disease from infection, and (b) suppression, which aims to reverse epidemic growth, reducing case numbers to low levels and maintaining that situation indefinitely. Each policy has major challenges. We find that that optimal mitigation policies (combining home isolation of suspect cases, home quarantine of those living in the same household as suspect cases, and social distancing of the elderly and others at most risk of severe disease) might reduce peak healthcare demand by 2/3 and deaths by half. However, the resulting mitigated epidemic would still likely result in hundreds of thousands of deaths and health systems (most notably intensive care units) being overwhelmed many times over. For countries able to achieve it, this leaves suppression as the preferred policy option. We show that in the UK and US context, suppression will minimally require a combination of social distancing of the entire population, home isolation of cases and household quarantine of their family members. This may need to be supplemented by school and university closures, though it should be recognised that such closures may have negative impacts on health systems due to increased absenteeism. The major challenge of suppression is that this type of intensive intervention package – or something equivalently effective at reducing transmission – will need to be maintained until a vaccine becomes available (potentially 18 months or more) – given that we predict that transmission will quickly rebound if interventions are relaxed. We show that intermittent social distancing – triggered by trends in disease surveillance – may allow interventions to be relaxed temporarily in relative short time windows, but measures will need to be reintroduced if or when case numbers rebound. Last, while experience in China and now South Korea show that suppression is possible in the short term, it remains to be seen whether it is possible long-term, and whether the social and economic costs of the interventions adopted thus far can be reduced.

As the number of new coronavirus cases continues to increase worldwide, and more than a dozen states and Puerto Rico are recording their highest averages of new cases since the pandemic began, hospitalizations in at least nine states have been on the rise since Memorial Day.

Threats to psychology’s credibility: Replicability, generalizability, and measurement validity

While recent conceptualizations of empathy have highlighted its motivated nature (eg. (Keysers & Gazzola, 2014; Zaki, 2014) little work has yet explored the specific motivations that influence one’s propensity to empathize. Commonly-used self-report metrics of empathy include items that lean heavily, if not entirely, towards ‘virtuous’ motives (e.g. concern, sympathy, caring, helping), and empathy has been explicitly linked to these motivations in many writings. However, the definition of empathy is silent to its virtuosity; and while rarely indexed, several less virtuous motivations for empathy can be readily identified: to influence, to manage, to mediate, to manipulate. Towards a more thorough investigation of the various motives underlying empathy, the present paper introduces the Motivation to Empathize scale, which was specifically designed to parse one’s propensity to consider the feelings of another into both virtuous (e.g. caring/compassionate/loving) and nonvirtuous (e.g. selfish, manipulative, sinister) motives. The paper outlines initial steps taken towards scale development and item reduction, and provides preliminary evidence of scale reliability and construct validity. Specifically, factor analytic techniques separated empathic motivations into two (high-alpha) factors, with all virtuous motives loading on latent factor one, and all nonvirtuous motives loading on latent factor two. Thus, virtuous and nonvirtuous motives to empathize appear to constitute distinct, and statistically separable, measures of the propensity to empathize. Virtuous, but not non-virtuous motives, correlated with the empathic concern subscale of the Interpersonal Reactivity Index (IRI; Davis, 1980), and each motivation type showed distinct relationships with the Compassion and Politeness aspects of Agreeableness (ie. big-five personality traits). In total, these results suggest that both virtuous and nonvirtuous motives may predict the manifestation of empathy, and that future work would do well to consider these varied motivations when considering the nature of the empathic construct.

In the absence of effective treatments or a vaccine, social distancing has been the only public health measure available to combat the COVID-19 pandemic to date. In the US, implementing this response has been left to state, county, and city officials, and many localities have issued some form of a stay-at-home order. Without existing tools and with limited resources, localities struggled to understand how their orders changed behavior. In response, several technology companies opened access to their users' location data. As part of the COVID-19 Data Mobility Data Network, we obtained access to Facebook User data and developed four key metrics and visualizations to monitor various aspects of adherence to stay at home orders. These metrics were carefully incorporated into static and interactive visualizations for dissemination to local officials. All code is open source and freely available at https://github.com/ryanlayer/COvid19

Malicious and abusive behaviors on social media have elicited massive concerns for the negative repercussions that online activity can have on personal and collective life. The spread of false information, the rise of AI-manipulated multimedia, and the emergence of various forms of harmful content are just a few of the several perils that social media users can, even unconsciously, encounter in the online ecosystem. In times of crisis, these issues can only get more pressing, with increased threats for everyday social media users. The ongoing COVID-19 pandemic makes no exception and, due to dramatically increased information needs, represents the ideal setting for the spread of a multitude of low-credibility and unverified information, and for malicious actors aiming to take advantage of the resulting chaos. In such a high-stakes scenario, the downstream effects of misinformation exposure or information landscape manipulation can manifest in attitudes and behaviors with potentially serious public health consequences.

In this paper we report results from an online study conducted in Bosnia and Herzegovina during the ongoing COVID-19 pandemic (May 2020). The study examined a range of social and behavioural responses by youth from different ethnic backgrounds and across 63 cities (N = 569). More specifically, the study focused on investigating the relationship between threat perceptions, public health behaviours, stress and social cohesion. As expected, results indicate that higher perceptions of threat were related to higher compliance to safety and health measures despite extremely extremely low levels of political trust. Surprisingly, participants reported relatively low levels of stress despite high social isolation and physical restrictions. These results could partially be explained by an increased level of family interactions. Furthermore, participants reported relatively high levels of social cohesion and common-ingroup identification in a usually segregated and conflict-ridden context.

Social distancing and hygiene practices are key to preventing the spread of Coronavirus. However, people vary in the degree to which they follow these practices. Consistent with previous findings that women adhere more to preventative health practices, in Study 1, women reported engaging in preventative practices regarding COVID-19 (e.g., social distancing, hygiene) more so than men. In Study 2, across three different Northeast U.S. locations, we observed a greater percentage of women wearing masks in public than men. In Study 3, U.S. counties with a greater percentage of women exhibited a higher reduction in movement as tracked by ~17 million GPS smart-phone coordinates. These findings may partly explain the greater infection rates among men and suggest that preventive health messages should be tuned towards men.

A multidisciplinary team of scientists, policymakers, government officials, and academics present a framework for classifying evidence used in policy

For many networks, it is useful to think of their nodes as being embedded in a latent space, and such embeddings can affect the probabilities for nodes to be adjacent to each other. In this paper, we extend existing models of synthetic networks to spatial network models by first embedding nodes in Euclidean space and then modifying the models so that progressively longer edges occur with progressively smaller probabilities. We start by extending a geographical fitness model by employing Gaussian-distributed fitnesses, and we then develop spatial versions of preferential attachment and configuration models. We define a notion of “spatial strength centrality” to help characterize how strongly a spatial embedding affects network structure, and we examine spatial strength centrality on a variety of real and synthetic networks.

Coronavirus antibody studies and what they allegedly show have triggered fierce debates, further confusing public understanding. ProPublica’s health reporter Caroline Chen is here to offer some clarity around these crucial surveys.

The majority of multi-wave studies examining resilience in adulthood have involved growth mixture modeling (GMM). We critically evaluate the central conclusion from this body of work that “resilience is commonplace”. Our emphasis is on two questionable methodological assumptions underlying this conclusion: (1) the variances are the same across trajectories (i.e., homogeneity of variance) and (2) the amount of change does not differ across individuals (i.e., slope variances are zero). Seventy-seven empirical studies were included that used GMM to examine resilience to diverse adversities in adulthood. Of these 77 relevant studies, 66 (86%) assumed homogeneity of variances across trajectories and 52 (68%) set slope variances to zero; in the minority of studies where these assumptions were not applied (particularly the homogeneity of variance assumption), the resilient trajectory was among the smallest. Furthermore, 63 (82%) of the 77 studies conferred labels of resilience based on a single outcome, which is problematic as resilience is never an “across-the-board” phenomenon. Based on our conclusions, we discuss three important directions for future research: (1) replication across samples and measures, (2) illumination of processes leading to resilience, and (3) incorporation of a multidimensional approach. We conclude by outlining a resilience framework for research, practice, and policy.

The 73rd World Health Assembly convened virtually in May, 2020, in a climate of international dissent. Caught in the midst of tensions between the USA and China, WHO has been the target of US President Trump's attacks and of multiple grievances.1The EconomistAmerica and China take their rivalry to the World Health Organization.The Economist. May 17, 2020; Google Scholar,  2Gramer R Lynch C Detsch J Trump cuts US ties with World Health Organization amid pandemic.Foreign Policy. May 29, 2020; Google Scholar In recent years, WHO has often been criticised for what it should have done or did not oversee, and for the political approach3Collins M The WHO and China: dereliction of duty. Council on Foreign Relations, Feb 27, 2020https://www.cfr.org/blog/who-and-china-dereliction-dutyDate accessed: June 3, 2020Google Scholar to the agency's management by its Director-General Tedros Adhanom Ghebreyesus.

The literature on resilience and posttraumatic growth has been instrumental in highlighting the human capacity to overcome adversity by illuminating that there are different pathways individuals may follow. Although the theme of strength from adversity is attractive and central to many disciplines and certain cultural narratives, this claim lacks robust empirical evidence. Specific issues include methodological approaches of using growth-mixture modeling in resilience research and retrospective assessments of growth. Conceptually, limitations exist in the examination of which outcomes are most appropriate for studying resilience and growth. We discuss new research intended to overcome these limitations, with a focus on prospective longitudinal designs and the value of integrating these disciplines for furthering our understanding of the human capacity to overcome adversity.

The COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has resulted in more than 5·7 million confirmed cases and 350 000 deaths globally as of May 28, according to the Johns Hopkins University Coronavirus Resource Center. Despite the vast number of reports on the epidemiology, immunology, radiology, and management of COVID-19, few publications on the disease's pathology have so far been available, and most have been single-case reports or small case series.1Fox SE Akmatbekov A Harbert JL Li G Brown JQ Vander Heide RS Pulmonary and cardiac pathology in COVID-19: the first autopsy series from New Orleans.medRxiv. 2020; (published online April 10.) (preprint).DOI: 10.1101/2020.04.06.20050575Google Scholar,  2Tian S Hu W Niu L Liu H Xu H Xiao SY Pulmonary pathology of early-phase 2019 novel coronavirus (COVID-19) pneumonia in two patients with lung cancer.J Thorac Oncol. 2020; 15: 700-704Summary Full Text Full Text PDF PubMed Scopus (78) Google Scholar,  3Barton LM Duval EJ Stroberg E Ghosh S Mukhopadhyay S COVID-19 autopsies, Oklahoma, USA.Am J Clin Pathol. 2020; 153: 725-733Crossref PubMed Google ScholarInitial reports of the disease focused on older patients with comorbidities; however, we are now witnessing cases in paediatric and young adult populations. The spectrum of clinical manifestations documented in the literature mirrors this expanded view of COVID-19 as well. In addition to pneumonia and respiratory failure, thromboembolic events (sometimes clinically unsuspected at death) are common, according to a 12-case autopsy series from Germany.4Wichmann D Sperhake JP Lutgehelmann M et al.Autopsy findings and venous thromboembolism in patients with COVID-19: a prospective cohort study.Ann Intern Med. 2020; (published online May 6.)DOI:10.7326/M20-2003Crossref PubMed Google Scholar In addition, clinical studies have reported acquired coagulopathy in patients with COVID-19,5Connell NT Battinelli EM Connors JM Coagulopathy of COVID-19 and antiphospholipid antibodies.J Thromb Haemost. 2020; (published online May 7.)DOI:10.1111/jth.14893Crossref Scopus (1) Google Scholar,  6Fogarty H Townsend L Ni Cheallaigh C et al.More on COVID-19 coagulopathy in Caucasian patients.Br J Haematol. 2020; (published online May 12.)DOI:10.1111/bjh.16791Google Scholar,  7Tal S Spectre G Kornowski R Perl L Venous thromboembolism complicated with COVID-19: what do we know so far?.Acta Haematol. 2020; (published online May 12.)DOI:10.1159/000508233Crossref Scopus (0) Google Scholar and a paediatric inflammatory syndrome linked to SARS-CoV-2 can also cause life-threatening cardiac issues.8

Perspective 1: Social scientists should back off This is what the political scientist Anthony Fowler wrote the other day: The public appetite for more information about Covid-19 is understandably insatiable. Social scientists have been quick to respond. . . . While I understand the impulse, the rush to publish findings quickly in the midst of the crisis does little for the public and harms the discipline of social science. Even in normal times, social science suffers from a host of pathologies. Results reported in our leading scientific journals are often unreliable because researchers can be careless, they might selectively report their results, and career incentives could lead them to publish as many exciting results as possible, regardless of validity. A global crisis only exacerbates these problems. . . . and the promise of favorable news coverage in a time of crisis further distorts incentives. . . . Perspective 2: Social science has a lot to offer 42 people published an article that begins: The COVID-19 pandemic represents a massive global health crisis. Because the crisis requires large-scale behaviour change and places significant psychological burdens on individuals, insights from the social and behavioural sciences can be used to help align human behaviour with the recommendations of epidemiologists and public health experts. Here we discuss evidence from a selection of research topics relevant to pandemics, including work on navigating threats, social and cultural influences on behaviour, science communication, moral decision-making, leadership, and stress and coping.

The word “airborne” means different things to different scientists, and that confusion needs to be addressed.

It is nearly impossible to get the care they need to treat, or even diagnose, the coronavirus, say residents at the crisis’ center.

In California, two of the nation’s first big antibody surveys estimated that the true number of coronavirus infections is significantly higher than believed. But scientists are skeptical.

For a couple of weeks now, grocery stores have been one of the only respites from cabin fever. Despite all the lockdowns and social-distancing measures across America, people still need food. In the most restrictive states, the grocery store has become about the last place you can go where life is lived more or less as it previously was.Except now, not even grocery stores can keep up the facade of normalcy. As many health experts have feared, last week, reports began to trickle in of grocery-store workers coming down with COVID-19, the disease caused by the coronavirus.

The Trump administration has just released the model for the trajectory of the COVID-19 pandemic in America. We can expect a lot of back-and-forth about whether its mortality estimates are too high or low. And its wide range of possible outcomes is certainly confusing: What’s the right number? The answer is both difficult and simple. Here’s the difficult part: There is no right answer. But here’s the simple part: Right answers are not what epidemiological models are for.

If there is a way to stop COVID-19, it will be by blocking its proteins from hijacking, suppressing, and evading humans’ cellular machinery.

Once the worst of the coronavirus crisis is over what might 'the new normal’ have in store for us? How might our society be changed six months, a year, five years, 20 years into the future? On 5 May 2020 BPS members Dr Rowena Hill (Nottingham Trent University, currently seconded to cross-governmental Covid-19 Foresight Group), Professor Susan Michie (Professor of Health Psychology and Director of the Centre for Behaviour Change at UCL), Kathryn Scott (Director of Policy, British Psychological Society) and Dr Jon Sutton (Managing Editor, The Psychologist) hosted a webinar to address many of these questions, as well as others supplied by attendees.

Renee DiResta, technical research manager at Stanford Internet Observatory, discusses a possible executive order U.S. President Trump is proposing after his tweets were fact-checked. She speaks with Bloomberg's Emily Chang.

Some countries are considering easing coronavirus lockdowns to reopen their borders. International tourist numbers could fall by up to 80% in 2020, the World Tourism Organization says. Pre-crisis, France was the world’s most visited country.

This is a "letter to the editor" about a preprint by the UK OpenSAFELY Collaborative,

Excess mortality data avoid miscounting deaths from under-reporting of Covid-19-related deaths and other health conditions left untreated. According to EuroMOMO, which tracks excess mortality for 24 European states, England had the highest peak weekly excess mortality in total, for the over-65s, and, most strikingly, for the 15-64 age group. This column argues that research is needed into such divergent patterns. It suggests that national statistical offices should publish P-scores (excess deaths divided by ‘normal’ deaths) for states and sub-regions, and permit EuroMOMO to publish P-scores as well as their less transparent Z-scores. This would aid comparability, better inform pandemic policy, and allow lessons to be drawn across heterogeneous regions and countries. 

COVID-19 highlights the inadequacy of national driven solutions to global problems. So why is nationalism on the rise?

Influential model judged reproducible — although software engineers called its code 'horrible' and 'a buggy mess'.

I recorded a 16-minute talk on the scientific process, science communication, and how preprints fit in to the information ecosystem around COVID-19. It’s called, “How we knowCOVID-19, preprints, and the information ecosystem.” The video is on YouTube here, also embedded below, and the slides, with references, are up here.

Addressing mental health challenges related to the COVID-19 outbreak can be facilitated through research that characterizes the needs of subpopulations and identifies specific pathways to targeted intervention. Toward this aim, we examined the impact of the COVID-19 outbreak on anxiety symptoms among college students (N = 487) and explored the relative impact of coping strategies using a psychological network approach, which models complex interactions to identify potential pathways to symptom-level intervention. Although students showed several significant fluctuations in pre- to post-outbreak anxiety symptom levels measured with the GAD-7, anxiety network connectivity was not significantly different across timepoints. Consistent with hypotheses, the post-outbreak symptom+coping network revealed that increased use of the adaptive coping strategies of acceptance, behavioral activation, and values-based action was associated with lower levels of fear, restlessness, and trouble relaxing. The symptom+coping network also revealed that increased use of the maladaptive strategies of excessive cleaning, reassurance seeking, and excessive checking was associated with higher levels of irritability and fear. Surprisingly, the use of reappraisal and avoidance, two strategies with putatively opposing adaptive value, highly overlapped and showed positive associations with fear and irritability. These symptom+coping associations can guide the assessment and treatment of anxiety in the face of COVID-19.

The COVID-19 outbreak and the restrictions that have been enforced by the health authorities are having a profound psychological impact on the population. Many people, including the students, faced forced modifications to their daily lives and this prompted the need for scalable strategies to promote resilience. We designed an online community intervention for psychology students and recent alumni aimed to promote functional coping strategies through openness and cognitive flexibility. This psycho-educational intervention was delivered through a private group on social media (Facebook) and it involved the publication of exercises and quick lectures. Contents were posted regularly and people from the community were invited to share their comments. The posts included stimuli that promote open and flexible reflections on the current situation. The overall aim of this group was a cognitive reframing on the epidemic effects, promoting creative and flexible thinking. We ran a thematic analysis of the interactions, and we collected qualitative feedback at the end of the intervention. The participants’ comments dealt with changes in their perspectives, sharing discomfort, encouragement and support, and building a sense of community. Post-intervention comments were highly satisfied and confirmed the helpfulness of the stimuli to promote flexibility and openness, eventually helping to manage the negative emotions related to the COVID-19 outbreak. This study provides preliminary evidence that an online psycho-educational community stimulating flexibility and openness can help to reframe the negative psychological impact of the outbreak, improving their management.

Over the next few months, you are going to see many different predictions about COVID-19 outcomes. They won’t all agree. But just because they’re based on assumptions doesn’t mean they’re worthless. “All models are wrong, it’s striving to make them less wrong and useful in the moment,” Weir said. We’re hungry, so somebody has to do some baking. But be sure to ask what ingredients went into that pie and in what quantities.

STAT asked Redfield about the agency’s role, whether he was satisfied with it, the agency’s evolving thinking about whether people should wear cloth masks in public, and how he sees the pandemic unfolding. The conversation has been lightly edited for length and clarity.

This preprint is a 1000-word Viewpoint that explores methodological considerations of the COVID-19 pandemic for immunopsychiatry. It has been accepted for publication in Brain, Behavior, and Immunity for a special issue on Immunopsychiatry and COVID-19. Specifically, we discuss the treatment of COVID-19 as a confounding versus mediating variable in immunopsychiatric research. We leverage simulated data varied in sample and effect size to illustrate key considerations. Further, we highlight the statistical implications of each of these scenarios. Recommendations and key considerations for the field are briefly discussed.

Lockdowns and distancing won’t save the world from warming. But amid this crisis, we have a chance to build a better future.

The novel coronavirus, COVID-19, has led to sweeping changes in psychological practice and the concomitant rapid uptake of telepsychotherapy. Although telepsychotherapy is new to many clinical psychologists, there is considerable research on telepsychotherapy treatments. Nearly two decades of clinical research on telepsychotherapy treatments with children with neurological conditions has the potential to inform emerging clinical practice in the age of COVID-19. Toward that end, we synthesized findings from 14 clinical trials of telepsychotherapy problem solving and parent training interventions involving more than 800 children and families with diverse diagnoses including traumatic brain injury, epilepsy, brain tumors, congenital heart disease, and perinatal stroke. We summarize efficacy across studies and clinical populations and report feasibility and acceptability data from the perspectives of parents, children, and therapists. We describe adaptation for international contexts and strategies for troubleshooting technological challenges and working with families of varying socioeconomic strata. The extensive research literature reviewed and synthesized provides considerable support for the utility of telepsychotherapy with children with neurological conditions and their families and underscores its high level of acceptability with both diverse clinical populations and providers. During this period of heightened vulnerability and stress and reduced access to usual supports and services, telepsychotherapy approaches such as online family problem-solving treatment and online parenting skills training may allow psychologists to deliver traditional evidence-based treatments virtually while preserving fidelity and efficacy.

A Covid diary: This is what I saw as the pandemic engulfed our hospitals.

Objective: Somatisation is commonly associated with histories of trauma and PTSD symptoms. Although previous research has demonstrated that PTSD symptoms predict somatic symptoms, there has been no systematic examination of this at the level of symptom clusters for COVID-19 related PTSD and multi-dimensional assessment of somatic symptoms. It was aimed to test for an association between ICD-11 PTSD symptom clusters, with COVID-19 as the stressor, and somatic symptoms while controlling for potentially confounding variables. Methods: Participants were a nationally representative sample of 1,041 adults from the general population of the Republic of Ireland. Physical health problems across the domains of pain, gastrointestinal, cardiopulmonary, and fatigue were assessed by the PHQ and PTSD symptoms were assessed with the ITQ. Descriptive analyses were undertaken and a confirmatory factor analysis was conducted controlling for potentially confounding variables. Results: All ICD-11 PTSD symptom clusters predicted the presence of pain, fatigue, gastro-intestinal, and cardiovascular symptoms in the PHQ. Sense of Threat individually predicted all physical health variables, and Avoidance predicted pain. Conclusions: The study demonstrates the key role of sense of threat in the presence of COVID-19 trauma and somatisation. Findings suggest that interventions that tackle sense of threat might provide relief from somatisation.

The disease’s “long-haulers” have endured relentless waves of debilitating symptoms—and disbelief from doctors and friends.

Purpose: The purpose of this study was to identify leading sources of stress, describe rates of mental health outcomes, and examine their associations among U.S. adults during the first months of the COVID-19 pandemic. Method: In a cross-sectional, general population survey conducted from March 18 to April 4, 2020, U.S. adults (n=10,625) were recruited through Qualtrics Panels using quota sampling methods. Results: Life stressors, probable depression, past-month suicide ideation, and past-month suicide attempts were not elevated among participants subject to state-level stay-at-home orders and/or large gatherings bans. Multiple life stressors were associated with increased rates of probable depression. Past-month suicide ideation was significantly higher among participants reporting ongoing arguments with a partner and serious legal problems. Past-month suicide attempt was significantly higher among participants reporting concerns about a life-threatening illness or injury, but was significantly lower among participants reporting an unexpected bill or expense. Conclusions: Results failed to support the conclusion that physical distancing measures are correlated with worse mental health outcomes. Concerns about life-threatening illness or injury was uniquely associated with increased risk of suicide attempt.

The prevalence of posttraumatic stress disorder (PTSD) as it relates to people’s experiences of the COVID-19 pandemic has yet to determined. This study was conducted to determine rates of COVID-19 related PTSD in the Irish general population, the level of comorbidity with depression and anxiety, and sociodemographic risk factors associated with COVID-19 related PTSD. A nationally representative sample of adults from the general population of the Republic of Ireland (N = 1,041) completed self-report measures of all study variables. The rate of COVID-19 related PTSD was 17.7% (95% CI = 15.35 - 19.99%: n=184), and comorbidity with generalized anxiety (49.5%) and depression (53.8%) was high. Meeting the diagnostic requirement for COVID-19 related PTSD was associated with younger age, male sex, living in a city, living with children, moderate and high perceived risk of COVID-19 infection, and screening positive for anxiety or depression. Traumatic stress problems related to the COVID-19 pandemic are common in the general population. Our results show that health professionals responsible for responding to the COVID-19 pandemic should expect to routinely encounter traumatic stress problems.

Previous research concerning the effectiveness of public health campaigns have explored the impact of message design, message content, communication channel choice and other aspects of such campaigns. Meta analyses reported in the literature reveal, however, that the choice of endorsers in health campaigns remains unexplored. The present study addresses this gap in the literature by studying what makes doctors from public health campaigns appear trustworthy in the eyes of the receiver. The present research examines propensity for trust as well facets of trustworthiness of such expert doctors based on a survey carried out in the UK (155 respondents). Underlying factors of trustworthiness are explored to gain more insight into the understanding of how trust may affect the public’s belief updating and the formation of intentions. Exploratory factor analyses suggest four dimensions of trustworthiness. Multiple regression analyses demonstrate that these factors explain almost 70% of the variance in the participants’ expressed trust in doctors from public health campaigns. Doctors’ ethical stance and their care for the health of the general population appear to be more important for perceived trustworthiness than their actual professional background, although their abilities and competences are closely related to ethics and benevolence. For policy makers this has important implications when selecting endorsers for public health campaigns in order to design effective health related communication, for example to combat obesity.

Physicians are perfectionists who suffer in silence.

A Stanford whistleblower complaint alleges that the controversial John Ioannidis study failed to disclose important financial ties and ignored scientists’ concerns that their antibody test was inaccurate.

Nationwide forced isolation, along with media coverage of the pandemic’s toll in U.S. jails and prisons, could shift public perceptions of carceral punishment.

So far, all available evidence suggests that few Americans were infected in the first weeks of the year. It would be next to impossible to find out who they were.

The pandemic’s disruption shows how much academia could learn from the disability community.

The mental toll of intensive care can be more severe than the physical one.

By now you’ve probably heard about or even seen the video “Plandemic” that’s been spreading like wildfire through social media networks. This article is not the one you should give to your friend or relative or coworker who shared the video. (If you want that article, you won’t find a better one than this one from Beth Skwarecki at Lifehacker: “If You Found That ‘Plandemic’ Video Convincing, Read This Too.”) This is an article for those who recognized the video as rife with conspiracy theories, misinformation and false claims, those who are frustrated and unsettled and disappointed in who they see sharing it, and those who want to know what to say when they see it. It explains why the video is successful, how to recognize propaganda like this for what it is, and explain why it is so, so, so important to speak up about this particular video.

Want to know why wild conspiracism can be so irresistible? Ask a 14-year-old girl.

Even after big parties are safe, smaller, intimate ceremonies are likely to persist.

The coronavirus pandemic has brought disproportionate suffering to Black communities, but it doesn’t have to continue that way.

Instead of an all-or-nothing approach to risk prevention, Americans need a manual on how to have a life in a pandemic.

When I think of a collective sense of grief, I think of how easily I became distant from my mother’s family, including my uncle, during those months and years after her death. As we all mourned, I watched us retreat into ourselves.

Objectives Public health interventions designed to interrupt COVID-19 transmission could have deleterious impacts on primary healthcare access. We sought to identify whether implementation of the nationwide lockdown (shelter-in-place) order in South Africa affected ambulatory clinic visitation in rural Kwa-Zulu Natal (KZN). Design Prospective, longitudinal cohort study Setting Data were analyzed from the Africa Health Research Institute Health and Demographic Surveillance System, which includes prospective data capture of clinic visits at eleven primary healthcare clinics in northern KwaZulu-Natal Participants A total of 36,291 individuals made 55,545 clinic visits during the observation period. Exposure of Interest We conducted an interrupted time series analysis with regression discontinuity methods to estimate changes in outpatient clinic visitation from 60 days before through 35 days after the lockdown period. Outcome Measures Daily clinic visitation at ambulatory clinics. In stratified analyses we assessed visitation for the following sub-categories: child health, perinatal care and family planning, HIV services, non-communicable diseases, and by age and sex strata. Results We found no change in total clinic visits/clinic/day from prior to and during the lockdown (-6.9 visits/clinic/day, 95%CI -17.4, 3.7) or trends in clinic visitation over time during the lockdown period (-0.2, 95%CI -3.4, 3.1). We did detect a reduction in child healthcare visits at the lockdown (-7.2 visits/clinic/day, 95%CI -9.2, -5.3), which was seen in both children <1 and children 1-5. In contrast, we found a significant increase in HIV visits immediately after the lockdown (8.4 visits/clinic/day, 95%CI 2.4, 14.4). No other differences in clinic visitation were found for perinatal care and family planning, non-communicable diseases, or among adult men and women. Conclusions In rural KZN, the ambulatory healthcare system was largely resilient during the national-wide lockdown order. A major exception was child healthcare visitation, which declined immediately after the lockdown but began to normalize in the weeks thereafter. Future work should explore efforts to decentralize chronic care for high-risk populations and whether catch-up vaccination programs might be required in the wake of these findings.

Governments around the world are responding to the novel coronavirus (COVID-19) pandemic1 with unprecedented policies designed to slow the growth rate of infections. Many actions, such as closing schools and restricting populations to their homes, impose large and visible costs on society, but their benefits cannot be directly observed and are currently understood only through process-based simulations2–4. Here, we compile new data on 1,717 local, regional, and national non-pharmaceutical interventions deployed in the ongoing pandemic across localities in China, South Korea, Italy, Iran, France, and the United States (US). We then apply reduced-form econometric methods, commonly used to measure the effect of policies on economic growth5,6, to empirically evaluate the effect that these anti-contagion policies have had on the growth rate of infections. In the absence of policy actions, we estimate that early infections of COVID-19 exhibit exponential growth rates of roughly 38% per day. We find that anti-contagion policies have significantly and substantially slowed this growth. Some policies have different impacts on different populations, but we obtain consistent evidence that the policy packages now deployed are achieving large, beneficial, and measurable health outcomes. We estimate that across these six countries, interventions prevented or delayed on the order of 62 million confirmed cases, corresponding to averting roughly 530 million total infections. These findings may help inform whether or when these policies should be deployed, intensified, or lifted, and they can support decision-making in the other 180+ countries where COVID-19 has been reported

We introduce the problem of explaining graph generation, formulated as controlling the generative process to produce graphs of explainable desired structures. By directing this generative process, we can measure and explain the observed outcomes. We propose SHADOWCAST, a controllable generative model capable of mimicking real-world networks and directing the generation, as a novel approach to this problem. The proposed model is based on a conditional generative adversarial network for graph data. We design it with the capability to maintain generation control by managing the conditions. Comprehensive experiments on three real-world network datasets demonstrate our model's competitive performance in the graph generation task. Furthermore, we direct SHADOWCAST to generate explainable graphs of different structures to show its effective controllability. As the first work to pose the problem of explaining generated graphs by controlling the generation, SHADOWCAST paves the way for future research in this exciting area.

This week, Project Syndicate catches up with Lucrezia Reichlin, a former director of research at the European Central Bank.

One can point to a variety of historical milestones for gender equality in STEM (science, technology, engineering, and mathematics), however, practical effects are incremental and ongoing. It is important to quantify gender differences in subdomains of scientific work in order to detect potential biases and monitor progress. In this work, we study the relevance of gender in scientific collaboration patterns in the Institute for Operations Research and the Management Sciences (INFORMS), a professional society with sixteen peer-reviewed journals. Using their publication data from 1952 to 2016, we constructed a large temporal bipartite network between authors and publications, and augmented the author nodes with gender labels. We characterized differences in several basic statistics of this network over time, highlighting how they have changed with respect to relevant historical events. We find a steady increase in participation by women (e.g., fraction of authorships by women and of new women authors) starting around 1980. However, women still comprise less than 25% of the INFORMS society and an even smaller fraction of authors with many publications. Moreover, we describe a methodology for quantifying the structural role of an authorship with respect to the overall connectivity of the network, using it to measure subtle differences between authorships by women and by men. Specifically, as measures of structural importance of an authorship, we use effective resistance and contraction importance, two measures related to diffusion throughout a network. As a null model, we propose a degree-preserving temporal and geometric network model with emergent communities. Our results suggest the presence of systematic differences between the collaboration patterns of men and women that cannot be explained by only local statistics.

Due to the interconnectedness of financial entities, estimating certain key properties of a complex financial system, including the implied level of systemic risk, requires detailed information about the structure of the underlying network of dependencies. However, since data about financial linkages are typically subject to confidentiality, network reconstruction techniques become necessary to infer both the presence of connections and their intensity. Recently, several 'horse races' have been conducted to compare the performance of the available financial network reconstruction methods. These comparisons were based on arbitrarily chosen metrics of similarity between the real network and its reconstructed versions. Here we establish a generalized maximum-likelihood approach to rigorously define and compare weighted reconstruction methods. Our generalization uses the maximization of a certain conditional entropy to solve the problem represented by the fact that the density-dependent constraints required to reliably reconstruct the network are typically unobserved and, therefore, cannot enter directly, as sufficient statistics, in the likelihood function. The resulting approach admits as input any reconstruction method for the purely binary topology and, conditionally on the latter, exploits the available partial information to infer link weights. We find that the most reliable method is obtained by 'dressing' the best-performing binary method with an exponential distribution of link weights having a properly density-corrected and link-specific mean value and propose two safe (i.e. unbiased in the sense of maximum conditional entropy) variants of it. While the one named CReM A is perfectly general (as a particular case, it can place optimal weights on a network if the bare topology is known), the one named CReM B is recommended both in case of full uncertainty about the network topology and if the existence of some links is certain. In these cases, the CReM B is faster and reproduces empirical networks with highest generalized likelihood among the considered competing models.

Motifs are the fundamental components of complex systems. The topological structure of networks representing complex systems and the frequency and distribution of motifs in these networks are intertwined. The complexities associated with graph and subgraph isomorphism problems, as the core of frequent subgraph mining, have direct impacts on the performance of motif discovery algorithms. To cope with these complexities, researchers have adopted different strategies for candidate generation and enumeration, and frequency computation. In the past few years, there has been an increasing interest in the analysis and mining of temporal networks. These networks, in contrast to their static counterparts, change over time in the form of insertion, deletion, or substitution of edges or vertices or their attributes. In this paper, we provide a survey of motif discovery algorithms proposed in the literature for mining static and temporal networks and review the corresponding algorithms based on their adopted strategies for candidate generation and frequency computation. As we witness the generation of a large amount of network data in social media platforms, bioinformatics applications, and communication and transportation networks and the advance in distributed computing and big data technology, we also conduct a survey on the algorithms proposed to resolve the CPU-bound and I/O bound problems in mining static and temporal networks.

The current study examined anxiety and distress among members of the first community to be quarantined in the United States due to the COVID-19 pandemic. In addition to being historically significant, the current sample was unusual in that those quarantined were all members of a Modern Orthodox Jewish community and were connected via religious institutions at which exposure may have occurred. We sought to explore the community and religious factors unique to this sample, as they relate to the psychological and public health impact of quarantine. Community organizations were trusted more than any other source of COVID 19-related information, including federal, state, and other government agencies, including the CDC, WHO and media news sources. This was supported qualitatively with open-ended responses in which participants described the range of supports organized by community organizations. These included tangible needs (i.e. food delivery), social support, virtual religious services, and dissemination of COVID-19 related information. The overall levels of distress and anxiety were elevated and directly associated with what was reported to be largely inadequate and inconsistent health related information received from local departments of health. In addition, the majority of participants felt that perception of or concern about future stigma related to a COVID-19 diagnosis or association of COVID-19 with the Jewish community was high and also significantly predicted distress and anxiety. The current study demonstrates the ways in which religious institutions can play a vital role in promoting the well-being of their constituents. During this unprecedented pandemic, public health authorities have an opportunity to form partnerships with religious institutions in the common interests of promoting health, relaying accurate information and supporting the psychosocial needs of community members, as well as protecting communities against stigma and discrimination.

SAPEA (Science Advice for Policy by European Academies) has launched a new video, in cooperation with the European Commission’s Group of Chief Scientific Advisors.  The video highlights two reports that examine best practices in science advice.  SAPEA conducted a comprehensive evidence review, published as Making Sense of Science for Policy under Conditions of Complexity and Uncertainty.   The SAPEA report informs the Advisors’ recommendations in their Scientific Opinion, Scientific Advice to European Policy in a Complex World.

A diary by Royal Free Hospital chief executive Kate Slemeck, reflecting on Britain’s first coronavirus cases, hosting camera crews and the prospect of a second wave.

The Guardian’s 29 May article (‘Soas to slash budgets and staff as debt crisis worsens in a pandemic’) has brought attention to a worrying development, which risks seeing losses of livelihoods and expertise at a unique and world-renowned institution. The danger is that framing SOAS’s financial difficulties in isolation obscures the fact that this is a sector-wide crisis that will only be resolved by a turnaround in government policy. In a highly marketized education sector, speculation about a university’s future can impact student numbers, the institution’s lifeline. This is the Catch-22 that university sector workers are now trapped in: to name a crisis is to make it worse.

Concerns about the next pandemic should spark a push for good city planning and policy rather than a backlash against density and transit upgrades.

As a scientist, it’s clear to me that the collective action vital to success relies on leaders being honest about their strategy

An epidemiologist points to new stresses in the U.S. mental health system that may persist from the novel coronavirus pandemic

Evidence informs guidance and public health decisions. In disease outbreaks, evidence is often scarce but accumulates rapidly. We need solutions to keep track of the emerging evidence. One of these solutions was suggested by Elliot et al.: the living systematic review. A review that is updated as soon as new information becomes available.

The social-media giant internally studied how it polarizes users, then largely shelved the research