Early on, patients with both mild and severe Covid-19 say they can’t breathe. Now, after recovering from the infection, some of them say they can’t think. Even people who were never sick enough to go to a hospital, much less lie in an ICU bed with a ventilator, report feeling something as ill-defined as “Covid fog” or as frightening as numbed limbs. They’re unable to carry on with their lives, exhausted by crossing the street, fumbling for words, or laid low by depression, anxiety, or PTSD.

Long after the fire of a Covid-19 infection, mental and neurological effects can still smolder

Mask wearing and social distancing for COVID-19 may have cut influenza cases south of the equator

Flu Season Never Came to the Southern Hemisphere

Many of the measures cited by his doctors are reserved for patients severely affected by the coronavirus.

Trump’s Treatment Suggests Severe Covid-19, Medical Experts Say

2010.01018

We study the diffusion of a true and a false message (the rumor) in a social network. Upon hearing a message, individuals may believe it, disbelieve it, or debunk it through costly verification. Whenever the truth survives in steady state, so does the rumor. Online social communication exacerbates relative rumor prevalence as long as it increases homophily or verification costs. Our model highlights that successful policies in the fight against rumors increase individuals' incentives to verify.

Debunking Rumors in Networks

Independent SAGE - live via Restream.io

Objective To develop and validate a pragmatic risk score to predict mortality in patients admitted to hospital with coronavirus disease 2019 (covid-19).Design Prospective observational cohort study.Setting International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) World Health Organization (WHO) Clinical Characterisation Protocol UK (CCP-UK) study (performed by the ISARIC Coronavirus Clinical Characterisation Consortium—ISARIC-4C) in 260 hospitals across England, Scotland, and Wales. Model training was performed on a cohort of patients recruited between 6 February and 20 May 2020, with validation conducted on a second cohort of patients recruited after model development between 21 May and 29 June 2020.Participants Adults (age ≥18 years) admitted to hospital with covid-19 at least four weeks before final data extraction.Main outcome measure In-hospital mortality.Results 35 463 patients were included in the derivation dataset (mortality rate 32.2%) and 22 361 in the validation dataset (mortality rate 30.1%). The final 4C Mortality Score included eight variables readily available at initial hospital assessment: age, sex, number of comorbidities, respiratory rate, peripheral oxygen saturation, level of consciousness, urea level, and C reactive protein (score range 0-21 points). The 4C Score showed high discrimination for mortality (derivation cohort: area under the receiver operating characteristic curve 0.79, 95% confidence interval 0.78 to 0.79; validation cohort: 0.77, 0.76 to 0.77) with excellent calibration (validation: calibration-in-the-large=0, slope=1.0). Patients with a score of at least 15 (n=4158, 19%) had a 62% mortality (positive predictive value 62%) compared with 1% mortality for those with a score of 3 or less (n=1650, 7%; negative predictive value 99%). Discriminatory performance was higher than 15 pre-existing risk stratification scores (area under the receiver operating characteristic curve range 0.61-0.76), with scores developed in other covid-19 cohorts often performing poorly (range 0.63-0.73).Conclusions An easy-to-use risk stratification score has been developed and validated based on commonly available parameters at hospital presentation. The 4C Mortality Score outperformed existing scores, showed utility to directly inform clinical decision making, and can be used to stratify patients admitted to hospital with covid-19 into different management groups. The score should be further validated to determine its applicability in other populations.

10.1136/bmj.m3339

Risk stratification of patients admitted to hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: development and validation of the 4C Mortality Score

COVID-AGE

Covid-age is a simple, easy to use tool that helps assess an individual’s vulnerability to Covid-19. It is based on published evidence for the main identified risk factors. That evidence indicates that vulnerability to Covid-19 increases exponentially with age; for example, in comparison with a healthy person aged 20, a healthy person aged 60 has more than 30 times the risk of dying if they contract Covid-19. Covid-age summarises vulnerability for combinations of risk factors including age, sex and ethnicity and various health problems. It works by “translating” the risk associated with each factor into years which are added to (or subtracted from) an individual’s actual age.  This then gives a single overall measure of vulnerability. It can be used in people with no underlying medical conditions or multiple medical conditions. One measure combines all of an individual’s risk factors with their actual age.

Job losses from the pandemic overwhelmingly affected low-wage, minority workersmost. Seven months into the recovery, Black women, Black men and mothersof school-age children are taking the longest time to regain their employment.

The covid-19 recession is the mostunequal in modern U.S. history

Analysis of the COVID-19 Epidemic

The virus is real, it's nasty, it's killing people, and common humanity ought to mean that we respect that. A majority of people in every country are doing their best to stay safe. The people who blithely wheel out the "99.5% will survive" argument can get in the sea. /15 /end

I don't know what governments should do about COVID-19. I don't think we can continue with lockdowns indefinitely, and perhaps we will end up having to live with it as best we can. That's not my point here. /14

And 99.5% is just for your _first_ bout of COVID-19. We don't know how long immunity lasts, and just as important, we don't know if subsequent infections will be milder (better immune response) or worse (exacerbating previous organ damage that perhaps wasn't obvious). /13

Non-white people also seem to be at higher risk, at least in Western countries. But I get the impression that a certain subset of the people telling us that "99.5% survival is fine" probably don't really care too much about that. If you get my drift. /12

About half of the 50-year-old population of most Western countries has a comorbidity that places them at higher risk. They have perfectly normal lives apart from their diabetes or hypertension. They don't want to take a 1 in 200 chance of dying, let alone a higher one. /11

99.5% seems to be the average number quoted by these trolls. For some people, the risk is a lot more than 1 in 200. And these are not just 90 year olds with dementia and cancer. /10

Think about 1,000 people accepting this deal. They're gathered in a room. They step up to the stage, one by one. They take the envelope and roll the dice. 995 people get cheered. 5 get led away. A muffled shot can be heard from behind the curtain. /9

What would I have to offer you for you to take that bet? I bet it would be a lot more than your student loan debt. /8

Now let's play a game. I offer you a deal. It can be a bottle of champagne, or your phone bill paid for a year, or your student loan debt wiped off, or your mortgage paid, or a massive yacht. You get that, but you roll three dice. If they all come up 6, you die, right there. /7

Or think of something you do every day, and get wrong twice a year. Put your t-shirt on the wrong way round. Leave the keys on the counter when you go to get the car out. That sort of thing. Not once in a blue moon events, but they don't affect you 99.5% of the time. /6

Or consider Risk. You are defending. Your opponent throws three sixes. Oops. One chance in 216. /5

In Monopoly, if you throw doubles (any doubles) three times in a row, you go to jail. One chance in 216 at the start of any turn. Anyone who has played Monopoly more than once has seen this. It's common enough that they made a rule for it, after all. /4

99.5% survival is one chance in 200 of dying. What does 1 chance in 200 look like? Let's start with board games. /3

First, this ignores the other costs of COVID-19 infection, including #LongCovid. But let's pretend that the only outcomes are death or a full recovery. 99.5% is (are?) not odds of survival that most people would take. /2

In a crowded field, my least favourite COVID-19 minimisation troll tactic is the claim that "99.5% of people survive". An angry thread. /1

Damage to the heart, liver and kidney are just a few of the long-term effects of Covid-19, according to a Oxford-based study. Academics have already warned people could suffer from the impact of having coronavirus for years, with many experiencing prolonged symptoms. Now, a joint national research programme between the EU, and private companies Innovate UK and Perspectum, called COVERSCAN is analysing the effects of Covid-19 on the body's key organs.

Long Covid: Long-term effects of coronavirus include damage to heart, liver, kidneys - Oxford study reveals

The trend in job postings was 17.5% lower than in 2019 as of September 25 — the smallest gap with last year’s trend since late March.

Coronavirus and US Job Postings Through September 25: Data from Indeed.com

Earlier this semester, a visiting professor from New York City gave a lecture to a class at Yale University. The professor later tested positive for COVID-19 — and so did two students who attended the class, according to Dr. Maritza Bond, New Haven’s director of health . Officials have not identified any other exposures in the New Haven community pertaining to the event, and no other students in the class had tested positive for COVID-19, Bond said. When asked for comment on the matter, Yale University spokeswoman Karen Peart said in an email that Yale became aware earlier this month of three COVID-19 cases “among people who had been present at an in-person class of fewer than 20 students.”

City official: 2 Yale students tested positive for COVID after visiting professor’s lecture

We can learn from parallels between the coronavirus and HIV crises

Lessons from AIDS for the COVID-19 Pandemic

The assays may not detect all cases, but they are cheap and could be used at home

Millions of Rapid COVID-19 Antigen Tests May Help Fill the Testing Gap

Information about herd immunity and empathy promote COVID-19 vaccination intentions

COVID-19 test positive and died in hospitals in England (up to 2nd Sep) - Under 60 with no pre-existing conditions 305 deaths in a popn of 56 Million.

Wales' two biggest cities have gone into lockdown, which started at 18:00.

Covid: Cardiff and Swansea go into local lockdown

The government says that it wants to learn from what went wrong with the Covid-19 response and that a public inquiry will be held. What lessons can be learnt, what are the psychological underpinnings of accountability in policy and can we balance the tension between learning lessons and apportioning blame in order to inform better decision making in the future?

Learning lessons before launching an inquiry - IfG LIVE 2020 Labour Fringe Programme

Anxiety about social distancing and infection is altering how much we dream and the nature of our dreams themselves

The COVID-19 Pandemic Is Changing Our Dreams

learning online is not always easy. How do you concentrate when staring at a screen for hours at a time? How do you manage your workload? And what is the best strategy for note-taking? Here’s our digest of the findings that could help to make online learning stick.

How To Get The Most Out Of Virtual Learning

A new nationwide study of the blood of more than 28,000 dialysis patients may help answer one of the big questions surrounding the pandemic: how many people have antibodies to SARS-CoV-2, the novel coronavirus? The answer could tell us a lot about how many people in the United States have been exposed to the virus and how much community spread there has been. Plus, the testing strategy used in the study points to a relatively easy way to track Covid-19 disease activity over the long-term, especially among vulnerable populations. The short answer to how many people had antibodies, as of July, is approximately 9.3% -- although numbers ranged from an average of 3.5% in the West to an average of 27% in the Northeast.

Fewer than 10% in the US have antibodies to the novel coronavirus

10.31234/osf.io/y25gx

The COVID-19 outbreak has forced individuals to adjust to a new order in which their liberties are restricted and uncertainty rules. The current work examined the role of other-focusedemotion regulation (ER) training in enhancing coping efficacy and reducing COVID-19 worries. For that, during the first COVID-19 lockdown in Israel, we trained 59 young individuals to perform other-focused emotion regulation, by reappraising others’ written upsetting events. We compared this procedure to a self-reappraisal training, in which 49 participants were asked to reappraise own upsetting events. Both procedures were performed every other day for three weeks. Participants’ coping efficacy was assessed at the daily level, while worries concerning theCOVID-19 effects on health, economic status, and social life were assessed following the training and at a two-month follow-up. The results demonstrated that other-focused ER surpassed self-focused ER. Specifically, participants in the other-reappraisal group exhibited an increase in coping efficacy across the training sessions and a reduction in COVID-19 worries that persisted two months after the training. These findings highlight the role of interpersonal emotion regulation at times of crisis and social isolation.

Reappraising Others' Negative Emotions as a way to Enhance Coping during the COVID-19 Outbreak

10.31234/osf.io/bmr59

Uncertainty has been shown to impact political evaluation, yet the exact mechanisms by which uncertainty affects the minds of citizens remain unclear. This experiment examines the neural underpinnings of uncertainty in political evaluation using functional MRI (fMRI). During fMRI, participants completed an experimental task where they evaluated policy positions attributed to hypothetical political candidates. Policy positions were either congruent or incongruent with candidates’ political party affiliation and presented with varying levels of certainty. Neural activity was modeled as a function of uncertainty and incongruence. Analyses suggest that neural activity in brain regions previously implicated in affective and evaluative processing (anterior cingulate cortex, insular cortex) differed as a function of the interaction between uncertainty and incongruence, such that activation in these areas was greatest when information was both certain and incongruent and uncertainty influenced processing differently as a function of the valence of the attached information. These findings suggest that individuals are attuned to uncertainty in the stated issue positions of politicians, and that the neural processing of this uncertainty is dependent on congruence of these positions with expectations based on political party identification. Implications for the study of emotion and politics and political cognition are discussed.

Political Uncertainty Moderates Neural Evaluation of Incongruent Policy Positions

10.31234/osf.io/7tme6

In response to the COVID-19 pandemic, many Governments are instituting mobile tracking technologies to perform rapid contact tracing. However, these technologies are only effective if the public is willing to use them, implying that their perceived public health benefits must outweigh personal concerns over privacy and security. The Australian federal government recently launched the `COVIDSafe' app, designed to anonymously register nearby contacts. If a contact later identifies as infected with COVID-19, health department officials can rapidly followup with their registered contacts to stop the virus' spread. The current study assessed attitudes towards three tracking technologies (telecommunication network tracking, a government app, and Apple and Google's Bluetooth exposure notification system) in two representative samples of the Australian public prior to the launch of COVIDSafe. We compared these attitudes to usage of the COVIDSafe app after its launch in a further two representative samples of the Australian public. Using Bayesian methods, we find widespread acceptance for all tracking technologies, however, observe a large intention-behaviour gap between people’s stated attitudes and actual uptake of the COVIDSafe app. We consider the policy implications of these results for Australia and the world at large.

The acceptability and uptake of smartphone tracking for COVID-19 in Australia

10.31234/osf.io/ucdg9

Context: Physical distancing and health measures, such as school closures and work-at-home mandates, implemented to mitigate the transmission of COVID-19, will likely have far-reaching impacts on children’s psychosocial health and well-being. Objective: We aimed to examine extant literature on pandemics to identify the expected impact of COVID-19 on children’s psychosocial health and secondary outcomes, including nutritional, financial and child safety outcomes. Data Sources: Articles were searched within the Medline, Global Health, PsycINFO, and CINAHL databases on June 11th, 2020. Gray literature was also examined from the World Health Organization (WHO) and United Nations International Fund (UNICEF) until July 24th, 2020. Study Selection: A total of 8332 articles were screened for eligibility by two independent reviewers. Of these, 7,919 and 413 articles were from academic databases and additional sources, respectively. Data Extraction: Results on child outcomes were extracted and collated. Results: Seventy-three articles met inclusion criteria. Children have faced significant challenges with 12% of total articles indicating loneliness/depression, 21% anxiety, 7% grief, 10% stress-related disorders, 25% child abuse, 8% family conflict, and 12% stigma during pandemics/epidemics. Furthermore, 25% of articles indicated economic challenges, 23% negative academic impacts, 33% improper nutrition, and 21% reduced opportunities for play/increased screen time. These challenges were exacerbated among children who were female, having a disability, or being a migrant/displaced child. Conclusion: Pandemics and epidemics have had diverse and widespread negative consequences for children. Findings can inform the development and implementation of resources during the COVID-19 pandemic to protect child health and well-being.

Potential psychosocial impact of COVID-19 on children: A scoping review of pandemics & epidemics

2009.12932

In the study of infectious diseases on networks, researchers calculate epidemic thresholds as informative measures to help forecast whether a disease will eventually infect a large fraction of a population. The structure of network typically changes in time, which fundamentally influence the dynamics of spreading processes on them and in turn affect epidemic thresholds for disease propagation. Most existing studies on epidemic thresholds in temporal networks have focused on models in discrete time, but most real-world networked systems evolve continuously in time. In our work, we encode the continuous dependency of time into the evaluation of the epidemic threshold of an susceptible--infected--susceptible (SIS) process by studying an SIS model on tie-decay networks. We formulate epidemic thresholds for an SIS compartmental model of disease spread on tie-decay networks, and we perform numerical experiments to verify the threshold condition that we derive. We also examine how different factors---the decay coefficients of the networks, the frequency of interactions, and the sparsity of the underlying social network in which interactions occur---lead to decreases or increases of the critical values of the threshold condition and hence contribute to facilitating or impeding the spread of a disease. We thereby demonstrate how the tie-decay features of these networks alter the outcome of disease spread.

Epidemic Thresholds of Infectious Diseases on Tie-Decay Networks

Ten thousand UK volunteers have been invited to join the world’s first phase three COVID-19 vaccine study to test the effectiveness of the new Novavax COVID-19 vaccine. This comes as the number of people in the UK who have signed up to take part in COVID-19 research through the NHS COVID-19 vaccine research registry hits 250,000.  Participants aged between 18-85 years will help test the safety and effectiveness of a new COVID-19 vaccine, developed by US biotechnology company Novavax, at a number of National Institute for Health Research (NIHR) regional sites across the UK, including Lancashire, the Midlands, Greater Manchester, London, Glasgow and Belfast. The Novavax trials are Phase 3, a large trial focusing on the vaccine’s effectiveness, with further checks on safety in a larger population. This followed earlier, smaller studies (phase 1 and phase 2) that reported positive results, and which focused on safety and whether there were signs the vaccine could work.

Over 250,000 volunteers now registered for new COVID-19 vaccine trials as recruitment begins for Novavax study

Student union says move disregards mental health and ‘applies different rules from the rest of the adult population’

Hundreds of thousands of students in Scotland banned from socialising

2009.11660

This paper analyzes the human and financial costs of the COVID-19 pandemic on 92 countries. We compare country-by-country equity market dynamics to cumulative COVID-19 case and death counts and new case trajectories. First, we examine the multivariate time series of cumulative cases and deaths, particularly regarding their changing structure over time. We reveal similarities between the case and death time series, and key dates that the structure of the time series changed. Next, we classify new case time series, demonstrate five characteristic classes of trajectories, and quantify discrepancy between them with respect to the behavior of waves of the disease. Finally, we show there is no relationship between countries' equity market performance and their success in managing COVID-19. Each country's equity index has been unresponsive to the domestic or global state of the pandemic. Instead, these indices have been highly uniform, with most movement in March.

Human and financial cost of COVID-19

2009.11669

Forecasting plays a critical role in the development of organisational business strategies. Despite a considerable body of research in the area of forecasting, the focus has largely been on the financial and economic outcomes of the forecasting process as opposed to societal benefits. Our motivation in this study is to promote the latter, with a view to using the forecasting process to advance social and environmental objectives such as equality, social justice and sustainability. We refer to such forecasting practices as Forecasting for Social Good (FSG) where the benefits to society and the environment take precedence over economic and financial outcomes. We conceptualise FSG and discuss its scope and boundaries in the context of the "Doughnut theory". We present some key attributes that qualify a forecasting process as FSG: it is concerned with a real problem, it is focused on advancing social and environmental goals and prioritises these over conventional measures of economic success, and it has a broad societal impact. We also position FSG in the wider literature on forecasting and social good practices. We propose an FSG maturity framework as the means to engage academics and practitioners with research in this area. Finally, we highlight that FSG: (i) cannot be distilled to a prescriptive set of guidelines, (ii) is scalable, and (iii) has the potential to make significant contributions to advancing social objectives.

Forecasting for Social Good

10.1038/d41586-020-02620-x

Europe’s flagship science agency will be crucial to a post-coronavirus world. Slashing its budget will be a senseless act.

A pandemic is no time to cut the European Research Council’s funding

The big picture: Since the onset of pandemic-induced telework, companies have oscillated between can't-wait-to-go-back and work-from-home-forever. Now, it's becoming increasingly clear that the future of work will land somewhere in the middle — a remote/in-person hybrid.

Remote work won't kill your office

10.31234/osf.io/9gqru

In this tutorial, we descibe an expert consensus procedure for scientific projects. Following such a procedure can achieve two main aims: (1) to decrease the chance that the product will be subject to conceptual or methodological mistakes, and (2) to increase the chance that the product of the project would be acceptable by the stakeholders on the field. The expert consensus procedure (ECO) aims to facilitate consensus among a panel of experts on a target output. This is achieved through an iterative process including surveys and feedback to the panel members, at the end of which a consensus-based Target Output is created, or lack of consensus is declared. The paper provides a step-by-step guide for the implementation of the ECO.

ECO, an expert consensus procedure for developing robust scientific outputs

10.1183/13993003.03498-2020

Background The number of proposed prognostic models for COVID-19 is growing rapidly, but it is unknown whether any are suitable for widespread clinical implementation.Methods We independently externally validated the performance candidate prognostic models, identified through a living systematic review, among consecutive adults admitted to hospital with a final diagnosis of COVID-19. We reconstructed candidate models as per original descriptions and evaluated performance for their original intended outcomes using predictors measured at admission. We assessed discrimination, calibration and net benefit, compared to the default strategies of treating all and no patients, and against the most discriminating predictor in univariable analyses.Results We tested 22 candidate prognostic models among 411 participants with COVID-19, of whom 180 (43.8%) and 115 (28.0%) met the endpoints of clinical deterioration and mortality, respectively. Highest areas under receiver operating characteristic (AUROC) curves were achieved by the NEWS2 score for prediction of deterioration over 24 h (0.78; 95% CI 0.73–0.83), and a novel model for prediction of deterioration <14 days from admission (0.78; 0.74–0.82). The most discriminating univariable predictors were admission oxygen saturation on room air for in-hospital deterioration (AUROC 0.76; 0.71–0.81), and age for in-hospital mortality (AUROC 0.76; 0.71–0.81). No prognostic model demonstrated consistently higher net benefit than these univariable predictors, across a range of threshold probabilities.Conclusions Admission oxygen saturation on room air and patient age are strong predictors of deterioration and mortality among hospitalised adults with COVID-19, respectively. None of the prognostic models evaluated here offered incremental value for patient stratification to these univariable predictors.

Systematic evaluation and external validation of 22 prognostic models among hospitalised adults with COVID-19: An observational cohort study

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