Transmission risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in schools is unknown. Our investigations, especially in preschools, could not detect SARS-CoV-2 transmission despite screening of symptomatic and asymptomatic children. The data suggest that children are not the primary drivers of SARS-CoV-2 transmission in schools and could help inform exit strategies for lifting of lockdowns.

10.1093/cid/ciaa794

Novel Coronavirus 2019 Transmission Risk in Educational Settings

10.2807/1560-7917.ES.2020.25.21.2000903

As many countries begin to lift some of the restrictions to contain COVID-19 spread, lack of evidence of transmission in the school setting remains. We examined Irish notifications of SARS-CoV2 in the school setting before school closures on 12 March 2020 and identified no paediatric transmission. This adds to current evidence that children do not appear to be drivers of transmission, and we argue that reopening schools should be considered safe accompanied by certain measures.

No evidence of secondary transmission of COVID-19 from children attending school in Ireland, 2020

Background: The extent of SARS-CoV-2 transmission among pupils in primary schools and their families is unknown. Methods: Between 28-30 April 2020, a retrospective cohort study was conducted among pupils, their parents and relatives, and staff of primary schools exposed to SARS-CoV-2 in February and March 2020 in a city north of Paris, France. Participants completed a questionnaire that covered sociodemographic information and history of recent symptoms. A blood sample was tested for the presence of anti-SARS-CoV-2 antibodies using a flow-cytometry-based assay. Results: The infection attack rate (IAR) was 45/510 (8.8%), 3/42 (7.1%), 1/28 (3.6%), 76/641 (11.9%) and 14/119 (11.8%) among primary school pupils, teachers, non-teaching staff, parents, and relatives, respectively (P = 0.29). Prior to school closure on February 14, three SARS-CoV-2 infected pupils attended three separate schools with no secondary cases in the following 14 days among pupils, teachers and non-teaching staff of the same schools. Familial clustering of cases was documented by the high proportion of antibodies among parents and relatives of infected pupils (36/59 = 61.0% and 4/9 = 44.4%, respectively). In children, disease manifestations were mild, and 24/58 (41.4%) of infected children were asymptomatic. Interpretation: In young children, SARS-CoV-2 infection was largely mild or asymptomatic and there was no evidence of onwards transmission from children in the school setting.

10.1101/2020.06.25.20140178

SARS-CoV-2 infection in primary schools in northern France: A retrospective cohort study in an area of high transmission

Background: The Oise department in France has been heavily affected by COVID-19 in early 2020. Methods: Between 30 March and 4 April 2020, we conducted a retrospective closed cohort study among pupils, their parents and siblings, as well as teachers and non-teaching staff of a high-school located in Oise. Participants completed a questionnaire that covered history of fever and/or respiratory symptoms since 13 January 2020 and had blood tested for the presence of anti-SARS-CoV-2 antibodies. The infection attack rate (IAR) was defined as the proportion of participants with confirmed SARS-CoV-2 infection based on antibody detection. Blood samples from two blood donor centres collected between 23 and 27 March 2020 in the Oise department were also tested for presence of anti-SARS-CoV-2 antibodies. Findings: Of the 661 participants (median age: 37 years), 171 participants had anti-SARS-CoV-2 antibodies. The overall IAR was 25.9% (95% confidence interval (CI) = 22.6-29.4), and the infection fatality rate was 0% (one-sided 97.5% CI = 0-2.1). Nine of the ten participants hospitalised since mid-January were in the infected group, giving a hospitalisation rate of 5.3% (95% CI = 2.4-9.8). Anosmia and ageusia had high positive predictive values for SARS-CoV-2 infection (84.7% and 88.1%, respectively). Smokers had a lower IAR compared to non-smokers (7.2% versus 28.0%, P <0.001). The proportion of infected individuals who had no symptoms during the study period was 17.0% (95% CI = 11.2-23.4). The proportion of donors with anti-SARS-CoV-2 antibodies in two nearby blood banks of the Oise department was 3.0% (95% CI = 1.1-6.4). Interpretation: The relatively low IAR observed in an area where SARS-CoV-2 actively circulated weeks before confinement measures indicates that establishing herd immunity will take time, and that lifting these measures in France will be long and complex.

10.1101/2020.04.18.20071134

Cluster of COVID-19 in northern France: A retrospective closed cohort study

In NSW, from March to mid-April 2020, 18 individuals (9 students and 9 staff) from 15 schools were confirmed as COVID-19 cases; all of these individuals had an opportunity to transmit the COVID-19 virus (SARS-CoV-2) to others in their schools. 735 students and 128 staff were close contacts of these initial 18 cases. One child from a primary school and one child from a high school may have contracted COVID-19 from the initial cases at their schools. No teacher or staff member contracted COVID-19 from any of the initial school cases.

Report: COVID-19 in schools – the experience in NSW

The COVID-19 pandemic has sparked an urgent need to uncover the underlying biology of this devastating disease. Though RNA viruses mutate more rapidly than DNA viruses, there are a relatively small number of single nucleotide polymorphisms (SNPs) that differentiate the main SARS-CoV-2 clades that have spread throughout the world. In this study, we investigated over 7,000 SARS-CoV-2 datasets to unveil both intrahost and interhost diversity. Our intrahost and interhost diversity analyses yielded three major observations. First, the mutational profile of SARS-CoV-2 highlights iSNV and SNP similarity, albeit with high variability in C>T changes. Second, iSNV and SNP patterns in SARS-CoV-2 are more similar to MERS-CoV than SARS-CoV-1. Third, a significant fraction of small indels fuel the genetic diversity of SARS-CoV-2. Altogether, our findings provide insight into SARS-CoV-2 genomic diversity, inform the design of detection tests, and highlight the potential of iSNVs for tracking the transmission of SARS-CoV-2.

10.1101/2020.07.02.184481

Hidden genomic diversity of SARS-CoV-2: implications for qRT-PCR diagnostics and transmission

Missing data is much studied in epidemiology and statistics. Theoretical development and application of methods for handling missing data have mostly been conducted in the context of prospective research data, and with a goal of description or causal explanation. However, it is now common to build predictive models using routinely collected data, where missing patterns may convey important information, and one might take a pragmatic approach to optimising prediction. Therefore, different methods to handle missing data may be preferred. Furthermore, an underappreciated issue in prediction modelling is that the missing data method used in model development may not match the method used when a model is deployed. This may lead to over-optimistic assessments of model performance.

10.1016/j.jclinepi.2020.03.028

Missing data should be handled differently for prediction than for description or causal explanation

JASP 0.13 has been released and is now available on our download page.

Introducing JASP 0.13

Dental practices are taking measures to keep patients safe. Some people are wary, however

The Dentist Will See You Now: But Will You See the Dentist?

In a previous newsletter, we gave a bearish case for the future of remote work. We spoke with the Stanford psychologist Jeremy Bailenson, whose research shows how existing technologies like Zoom are a poor substitute for face-to-face interactions. A computer screen can't match the physical office when it comes to opportunities for social bonding, managerial oversight, mentorship and support, and random collisions between colleagues that lead to new ideas. But there's also the bullish case for remote work. Brynjolfsson, who has spent years studying the intersection of technology and economics, points to its many advantages. Workers don't have to waste time or resources commuting. And they can live where they want. Companies can save money on commercial real estate, which is insanely expensive in places like Manhattan and Silicon Valley (side note: this also shifts the cost of real estate to workers, but that's another discussion). A virtual office offers a virtually unlimited labor pool for companies to recruit from. In econ jargon, there are better "matching" opportunities. "You get to tap into the best people wherever they are," Brynjolfsson says. Moreover, he argues, this shift is pushing companies to focus on performance and output as opposed to just "clocking hours."

Is Remote Work Here To Stay?

Scotland may be only weeks away from no new daily cases of coronavirus. As the nation gets close, cases from over the border will become a big problem

Scotland could eliminate the coronavirus – if it weren't for England

In Episode 2, John Lettieri sits down with Dr. Adam Ozimek, chief economist at the online talent platform Upwork. They discuss how the COVID-19 crisis could permanently influence the future of remote work, and how being an economist and small business owner in Lancaster, PA, influences Adam’s perspective on the challenges facing the U.S. in the midst of an unprecedented crisis. 

The Deep Dive with John Lettieri: What Adam Ozimek thinks about remote work, regional divergence, and the crisis facing American small businesses

The Medical Case for Reopening Schools

We need to reopen our schools—not in spite of the pandemic, because of the pandemic.

This addendum specifies statewide triage protocols for acute care facilities during the COVID-19 pandemic. It corresponds with theArizona Crisis Standards of Care Plan, 3rd edition but offers further guidance to reflectcurrent best practices and recently published evidence on COVID-19. Triage color groupings have been updated to include SOFA scores consistent with current literature. After describing the Scope and Principles, the structure of this Addendum includes Section A (Stabilization of Patients Awaiting Triage), Section B (COVID-19 Triage Protocols for Scarce Resource Allocation), Section C (Pediatric Considerations) and References.

COVID-19 Addendum: Allocation of Scarce Resources in Acute Care FacilitiesRecommended for Approval by State Disaster Medical Advisory Committee (SDMAC) – 6/12/2020

A historic and calamitous milestone was reached this week. WHO reported more than 10 million cases of COVID-19 and over 500 000 COVID-19 deaths. The world's political leaders have been tested and they have been found wanting. It's hard to recall a more lamentable response to a global emergency. Even the climate crisis had its Kyoto and Paris agreements. But despite the urgency of this continuing human catastrophe, despite the immediacy of the economic collapse we are witnessing, there has still been no moment when nations have been convened to reflect on lessons to be learned, to coordinate actions to protect citizens, and to plan for future spikes or waves of infection

10.1016/S0140-6736(20)31488-4

Offline: It's time to convene nations to end this pandemic

How does this relate to test positivity? I imagine testing as starting in the center and then radiating outwards. Originally, only the sickest people were getting tested, then people with mild symptoms. Now some places routinely test healthy employees. 4/11

What we see in states like Florida is a sharp rise in the numbers of new cases. It is the pace of growth that alarms me, and the fact that positivity is rising along with it. As policy hasn't changed over the last few weeks, what stops it from rising more? 11/END

All of this to say, there isn't an easy way to meaningfully compare case counts. Ideally we could calibrate test positivity to the total number of infections, using serosurveillance data. Instead of absolute numbers, I find it more helpful to examine trends. 10/11

But we can dream up settings where it's not linear. Imagine you only test a few very sick people. They are 50% positive. We test more people, and they are also 50% positive because they are like the others. We have captured more infections, but positivity hasn't changed. 9/11

The adjustment looks like this. Whatever the test positivity was (10%, 50%), multiply the number of new cases by that (10X, 50X). This assumes that there is a linear relationship between test positivity and the amount of the epidemic we are missing. 8/11

Can we adjust the numbers to make them more comparable? @foxjust proposed a simple rule of thumb approach. I think it's helpful to flag that there were likely more new infections at the mid-April peak than now, but of course nothing is easy. 7/11

As we have greater capacity for testing, we can move towards the outer tiers, and the test positivity declines. Of course it also declines with how much the virus is circulating in the area. 6/11

Each tier has its own probability of being positive. Someone with severe respiratory illness could have COVID, but they could have something else (depends on how much COVID is circulating). Let's say hypothetically 50% are positive. I added some numbers to the figure. 5/11

We hear a lot about test positivity being an important metric to track, but I think it's helpful to remind ourselves why. When I think about testing, I tend to imagine dividing the population into tiers. The center is most likely to have COVID. The outer layers less so. 3/11

At the peak of NYC's epidemic, over 50% of tests came back positive. Compare that to Florida where positivity is still below 20%. 2/11

THINK LIKE AN EPIDEMIOLOGIST: There are more new confirmed cases each day in the US than at any time during the earlier April peak. But is it really meaningful to compare those numbers? How do epidemiologists decide when to sound the alarm? A thread. 1/11

New Data on NYC Resident Deaths Outside of City On June 30, the count of New Yorkers who have died of COVID-19 increased by 692. Most of that increase is due to new information we received from the NYS Department of Health about city residents who died outside the city. The vast majority of these deaths occurred more than three weeks ago. The data presented on these pages reflect the most recent information the Health Department has collected about people who have tested positive for COVID-19 in NYC. In March, April and early May, we had discouraged people with mild and moderate symptoms from being tested, so our data primarily represent people with more severe illness. This page includes data visualizations. To view the data as csv files, click here to visit our Github repository. Unless otherwise noted, all of the below information was collected by the NYC Health Department. The data on these pages will be updated daily. All data are preliminary and subject to change.

COVID-19: Data

The Centre for Statistics (University of Edinburgh) are honoured to welcome Prof. David Spiegelhalter to discuss the challenges of communicating in the age of COVID. Can we communicate deeper uncertainty about facts, numbers, or scientific hypotheses without losing trust and credibility? It is claimed we live in a ‘post-truth’ society in which emotional responses dominate balanced consideration of evidence. This presents a strong challenge to those who value quantitative and scientific evidence: How can we communicate statistics, risks and unavoidable scientific uncertainty in a transparent and trustworthy way?

Communicating statistics, risk and uncertainty in the age of Covid - Prof. David Spiegelhalter

Sage advice from an advisor to SAGE! The thing with quality is that the analyst’s job is never done. It is a moving target. In the Quality Assurance of Administrative Data guidance from the Office for Statistics Regulation (OSR), the importance of understanding where the data come from and how and why they were collected is emphasised. But this information isn’t static – systems and policies may alter. And data sources will change as a result. Being alert for this variation is an ongoing, everyday task. It includes building relationships with others in the data journey, to share insight and understanding about the data and to keep a current view about the data source. As Sir Ian went on to point out in his evidence, it should involve triangulating against other sources of data.

An analyst’s job is never done

‘We should stop chastising politicians for changing their minds, and start cheering them instead’

In defence of the U-turn – in politics and life

Younger children will no longer have to follow distancing rules when meeting other children or adults outdoors in Scotland.

Coronavirus: Distancing rules relaxed for children in Scotland

DAVIS, Calif. — The community around the University of California, Davis, used to have a population of 70,000 and a thriving economy. Rentals were tight. Downtown was jammed. Hotels were booked months in advance for commencement. Students swarmed to the town’s bar crawl, sampling the trio of signature cocktails known on campus as “the Davis Trinity.”Then came the coronavirus. When the campus closed in March, an estimated 20,000 students and faculty left town.With them went about a third of the demand for goods and services, from books to bikes to brunches. City officials are expecting most of that demand to stay gone even as the economy reopens.

Federal Eviction Moratoriums

Multifamily Properties Subject to Federal Eviction Moratoriums

There are thousands of stories like this in and around Tulsa. A few years ago a report from the Eviction Lab at Princeton University found that city had the 11th-highest eviction rate in the country. Nearly 8% of households face an eviction each year. “We knew it was bad,” said Jeff Jaynes, executive director of Restore Hope Ministries, a nonprofit rental assistance agency. “We didn’t know it was 11th-in-the-country bad.” And that was before the pandemic. While the CARES Act imposed a temporary moratorium on evictions of residents living in federally subsidized apartments or properties with federally backed mortgages, that hasn’t stopped other evictions from piling up. The Tulsa County courthouse reopened for hearings on June 1 with more than 1,200 cases pending. Tenant advocates are calling for a statewide moratorium on evictions.

In Tulsa, evictions were a crisis even before the pandemic

As eviction hearings resume, the Ohio city has turned its empty convention hall into a one-stop shop for tenants in trouble. There are plenty to go around. 

The Columbus Convention Center Is Now a Pandemic Housing Court

And now, with the unemployment rate five times greater than pre-pandemic levels and no eviction moratorium in place, he is expecting a renewed surge in evictions — a surge that could overwhelm the court system.The Charleston County Magistrate courts received 120 new eviction filings, according to public records, in the first two days after the moratorium expired.

North Charleston, S.C., Housing Court Braces For Avalanche of New Evictions 

Kermack–McKendrick theory is a hypothesis that predicts the number and distribution of cases of an infectious disease as it is transmitted through a population over time. Building on the research of Ronald Ross and Hilda Hudson, A. G. McKendrick and W. O. Kermack published their theory in a set of three articles from 1927, 1932, and 1933. While Kermack–McKendrick theory was indeed the source of SIR models and their relatives, Kermack and McKendrick were thinking of a more subtle and empirically useful problem than the simple compartmental models discussed here. The text is somewhat difficult to read, compared to modern papers, but the important feature is it was a model where the age-of-infection affected the transmission and removal rates.

Kermack–McKendrick theory

2005.13689

SARS-CoV-2 causing COVID-19 disease has moved rapidly around the globe, infecting millions and killing hundreds of thousands. The basic reproduction number, which has been widely used and misused to characterize the transmissibility of the virus, hides the fact that transmission is stochastic, is dominated by a small number of individuals, and is driven by super-spreading events (SSEs). The distinct transmission features, such as high stochasticity under low prevalence, and the central role played by SSEs on transmission dynamics, should not be overlooked. Many explosive SSEs have occurred in indoor settings stoking the pandemic and shaping its spread, such as long-term care facilities, prisons, meat-packing plants, fish factories, cruise ships, family gatherings, parties and night clubs. These SSEs demonstrate the urgent need to understand routes of transmission, while posing an opportunity that outbreak can be effectively contained with targeted interventions to eliminate SSEs. Here, we describe the potential types of SSEs, how they influence transmission, and give recommendations for control of SARS-CoV-2.

Stochasticity and heterogeneity in the transmission dynamics of SARS-CoV-2

Deaths and new infections from covid-19 are falling to low levels in Scotland. Devi Sridhar and Adriel Chen look at how the country is on course to eliminating the virus

Devi Sridhar and Adriel Chen: Scotland’s slow and steady approach to covid-19 may lead to a more sustainable future

Gerald L. Neuman discusses new book on populism and what the pandemic means for populist governments

Human Rights in a Time of Populism and COVID-19

Simple Writing pros & cons in Argdown is as simple as writing a Twitter message. You don't have to learn anything new, except a few simple rules that will feel very natural. Expressive With these simple rules you will be able to define more complex relations between arguments or dive into the details of their logical premise-conclusion structures. Powerful Your document is transformed into an argument map while you are typing. You can export your analysis as HTML, SVG, PDF, PNG or JSON. If that is not enough, you can easily extend Argdown with your own plugin.

Argdown

2006.16140

Personal data is not discrete in socially-networked digital environments. A single user who consents to allow access to their own profile can thereby expose the personal data of their network connections to non-consented access. The traditional (informed individual) consent model is therefore not appropriate in online social networks where informed consent may not be possible for all users affected by data processing and where information is shared and distributed across many nodes. Here, we introduce a model of "distributed consent" where individuals and groups can coordinate by giving consent conditional on that of their network connections. We model the impact of distributed consent on the observability of social networks and find that relatively low adoption of even the simplest formulation of distributed consent would allow macroscopic subsets of online networks to preserve their connectivity and privacy. Distributed consent is of course not a silver bullet, since it does not follow data as it flows in and out of the system, but it is one of the most straightforward non-traditional models to implement and it better accommodates the fuzzy, distributed nature of online data.

Distributed consent and its impact on privacy and observability in social networks

As restaurants and bars dramatically expand their outdoor seating, questions are emerging about who gets to occupy the streets.

What Happens to Public Space When Everything Moves Outside

10.31234/osf.io/m23v4

We examined the evidence for heterogeneity (of effect sizes) when only minor changes to sample population and settings were made between studies and explored the association between heterogeneity and average effect size in a sample of 68 meta-analyses from thirteen pre-registered multi-lab direct replication projects in social and cognitive psychology. Amongst the many examined effects, examples include the Stroop effect, the “verbal overshadowing” effect, and various priming effects such as “anchoring” effects. We found limited heterogeneity; 48/68 (71%) meta-analyses had non-significant heterogeneity, and most (49/68; 72%) were most likely to have zero to small heterogeneity. Power to detect small heterogeneity (as defined by Higgins, 2003) was low for all projects (mean 43%), but good to excellent for medium and large heterogeneity. Our findings thus show little evidence of widespread heterogeneity in direct replication studies in social and cognitive psychology, suggesting that minor changes in sample population and settings are unlikely to affect research outcomes in these fields of psychology. We also found strong correlations between observed average effect sizes (standardized mean differences and log odds ratios) and heterogeneity in our sample. Our results suggest that heterogeneity and moderation of effects is unlikely for a zero average true effect size, but increasingly likely for larger average true effect size.

Postprint - Heterogeneity in direct replications in psychology and its association with effect size

"More and more businesses that definitely don't want to close again need to understand that they are our biggest enforcement army right now."

88 People Got Sick With The Coronavirus From One Bar Reopening In Michigan

Studies aimed at characterizing the evolution of COVID-19 disease often rely on case-based surveillance data publicly released by health authorities, that can be incomplete and prone to errors. Here, we quantify the biases caused by the use of inaccurate data in the estimation of the Time-Varying Reproduction Number R(t). By focusing on Italy and Spain, two of the hardest-hit countries in Europe and worldwide, we show that if the symptoms' onset time-series is inferred from the notification date series, the R(t) curve cannot capture nor describe accurately the early dynamics of the epidemic. Furthermore, the effectiveness of the containment measures that were implemented, such as national lockdowns, can be properly evaluated only when R(t) is estimated using the real time-series of dates of symptoms' onset. Our findings show that extreme care should be taken when a pivotal quantity like R(t) is used to make decisions and to evaluate different alternatives.

10.1101/2020.06.26.20140871

Impact of the accuracy of case-based surveillance data on the estimation of time-varying reproduction numbers