We show that SARS-CoV-2 spike protein interacts with cell surface heparan sulfate and angiotensin converting enzyme 2 (ACE2) through its Receptor Binding Domain. Docking studies suggest a putative heparin/heparan sulfate-binding site adjacent to the domain that binds to ACE2. In vitro, binding of ACE2 and heparin to spike protein ectodomains occurs independently and a ternary complex can be generated using heparin as a template. Contrary to studies with purified components, spike protein binding to heparan sulfate and ACE2 on cells occurs codependently. Unfractionated heparin, non-anticoagulant heparin, treatment with heparin lyases, and purified lung heparan sulfate potently block spike protein binding and infection by spike protein-pseudotyped virus and SARS-CoV-2 virus. These findings support a model for SARS-CoV-2 infection in which viral attachment and infection involves formation of a complex between heparan sulfate and ACE2. Manipulation of heparan sulfate or inhibition of viral adhesion by exogenous heparin may represent new therapeutic opportunities.

10.1101/2020.07.14.201616

SARS-CoV-2 Infection Depends on Cellular Heparan Sulfate and ACE2

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has severely affected health care workers (HCWs).1 As a result, hospital systems began testing HCWs2 and implementing infection control measures to mitigate workforce depletion and prevent disease spread.3 Mass General Brigham (MGB) is the largest health care system in Massachusetts, with 12 hospitals and more than 75 000 employees. In March 2020, MGB implemented a multipronged infection reduction strategy involving systematic testing of symptomatic HCWs and universal masking of all HCWs and patients with surgical masks.4 This study assessed the association of hospital masking policies with the SARS-CoV-2 infection rate among HCWs.

10.1001/jama.2020.12897

Association Between Universal Masking in a Health Care System and SARS-CoV-2 Positivity Among Health Care Workers

Background: Hydroxychloroquine and chloroquine have been proposed as treatments for coronavirus disease 2019 (COVID-19) on the basis of in vitro activity, uncontrolled data, and small randomized studies. Methods: The Randomised Evaluation of COVID-19 therapy (RECOVERY) trial is a randomized, controlled, open-label, platform trial comparing a range of possible treatments with usual care in patients hospitalized with COVID-19. We report the preliminary results for the comparison of hydroxychloroquine vs. usual care alone. The primary outcome was 28-day mortality. Results: 1561 patients randomly allocated to receive hydroxychloroquine were compared with 3155 patients concurrently allocated to usual care. Overall, 418 (26.8%) patients allocated hydroxychloroquine and 788 (25.0%) patients allocated usual care died within 28 days (rate ratio 1.09; 95% confidence interval [CI] 0.96 to 1.23; P=0.18). Consistent results were seen in all pre-specified subgroups of patients. Patients allocated to hydroxychloroquine were less likely to be discharged from hospital alive within 28 days (60.3% vs. 62.8%; rate ratio 0.92; 95% CI 0.85-0.99) and those not on invasive mechanical ventilation at baseline were more likely to reach the composite endpoint of invasive mechanical ventilation or death (29.8% vs. 26.5%; risk ratio 1.12; 95% CI 1.01-1.25). There was no excess of new major cardiac arrhythmia. Conclusions: In patients hospitalized with COVID-19, hydroxychloroquine was not associated with reductions in 28-day mortality but was associated with an increased length of hospital stay and increased risk of progressing to invasive mechanical ventilation or death

10.1101/2020.07.15.20151852

Effect of Hydroxychloroquine in Hospitalized Patients with COVID-19: Preliminary results from a multi-centre, randomized, controlled trial.

10.1038/s41467-020-17436-6

SARS-CoV-2 outbreak is the first pandemic of the century. SARS-CoV-2 infection is transmitted through droplets; other transmission routes are hypothesized but not confirmed. So far, it is unclear whether and how SARS-CoV-2 can be transmitted from the mother to the fetus. We demonstrate the transplacental transmission of SARS-CoV-2 in a neonate born to a mother infected in the last trimester and presenting with neurological compromise. The transmission is confirmed by comprehensive virological and pathological investigations. In detail, SARS-CoV-2 causes: (1) maternal viremia, (2) placental infection demonstrated by immunohistochemistry and very high viral load; placental inflammation, as shown by histological examination and immunohistochemistry, and (3) neonatal viremia following placental infection. The neonate is studied clinically, through imaging, and followed up. The neonate presented with neurological manifestations, similar to those described in adult patients.

Transplacental transmission of SARS-CoV-2 infection

An effective vaccine is needed to halt the spread of the SARS-CoV-2 pandemic. Recently, we reported safety, tolerability and antibody response data from an ongoing placebo-controlled, observer-blinded phase 1/2 COVID-19 vaccine trial with BNT162b1, a lipid nanoparticle (LNP) formulated nucleoside-modified messenger RNA encoding the receptor binding domain (RBD) of the SARS-CoV-2 spike protein. Here we present antibody and T cell responses after BNT162b1 vaccination from a second, non-randomized open-label phase 1/2 trial in healthy adults, 18-55 years of age. Two doses of 1 to 50 μg of BNT162b1 elicited robust CD4+ and CD8+ T cell responses and strong antibody responses, with RBD-binding IgG concentrations clearly above those in a COVID-19 convalescent human serum panel (HCS). Day 43 SARS-CoV-2 serum neutralising geometric mean titers were 0.7-fold (1 μg) to 3.5-fold (50 μg) those of HCS. Immune sera broadly neutralised pseudoviruses with diverse SARS-CoV-2 spike variants. Most participants had TH1 skewed T cell immune responses with RBD-specific CD8+ and CD4+ T cell expansion. Interferon (IFN)γ was produced by a high fraction of RBD-specific CD8+ and CD4+ T cells. The robust RBD-specific antibody, T-cell and favourable cytokine responses induced by the BNT162b1 mRNA vaccine suggest multiple beneficial mechanisms with potential to protect against COVID-19.

10.1101/2020.07.17.20140533

Concurrent human antibody and TH1 type T-cell responses elicited by a COVID-19 RNA vaccine

As school districts around the country reveal reopening guidelines for when students return to classrooms in the fall, many parents are concerned about how the coronavirus could affect their children.The White House has provided confusing statements. Press secretary Kayleigh McEnany said Thursday "science should not stand in the way" of schools reopening, though "science is on our side."A compilation of studies and articles published in JAMA Pediatrics found most patients under the age of 18 with COVID-19, the illness caused by SARS-CoV-2, have mild symptoms and fully recover within one to two weeks – quicker than most adults. Though this may alleviate some concerns, medical experts said parents shouldn’t let their guard down.

Can kids spread the coronavirus? 'Conclusively, without a doubt – yes,' experts say

Results from trials involving three different coronavirus vaccines released Monday, all showing positive results, with evidence the vaccines can produce immune responses that would be expected to protect people against infection.They all also appeared to be safe, although it will take studies with more people to show how safe they really are and whether they can prevent infection.

Oxford's Covid-19 vaccine appears safe and induces immune response, early results suggest, but more research is needed

President Donald Trump’s extraordinary interview with “Fox News Sunday” host Chris Wallace, who frequently fact-checked the president in real time, contained a long list of false, misleading and unsubstantiated claims: The president claimed other countries, later mentioning Europe, are only testing for COVID-19 if someone is “really sick” and that the “massive” testing in the U.S. “skews the numbers.” But testing data show many countries, including in Europe, have conducted more tests per confirmed case than the U.S. Trump falsely claimed that there’s “no reason” — “[e]xcept for Nov. 3rd” — for California to pull back on reopening its economy. Multiple states, including California, have concerning trends that public health experts — including those on the White House’s coronavirus task force — say warrant business closures and other precautions. Trump claimed he “forced” Seattle officials to finally end protests near a police precinct because “they heard” that “we were going in that following day.” Seattle’s mayor said her decision had nothing to do with Trump, who she said never notified her of a plan to send in federal forces. Trump falsely claimed credit for “the biggest pay raises in the history of our military.” The largest increase in basic military pay under Trump was 3.1%. It was higher than that seven times in the last 19 years — including a high of 5% in 2002.

FactChecking Trump’s ‘Fox News Sunday’ Interview

Following announcement of the first local area lockdown – where it has been widely quoted that Leicester accounted for 10 per cent of all positive cases in the country over the last week – there has been an even greater interest in the local area data on COVID-19 cases and tests.To meet this immediate need for data in the public domain Public Health England (PHE) has published the data underlying the graphic in its weekly surveillance report. Figure 9 in the accompanying dataset provides the weekly rate of COVID-19 cases of people tested under Pillars 1 and 2 per 100,000 population by upper-tier local authority in England. The rate of cases in Leicester shown in the table (140.2 cases per 100,000 population) is more than double the rate in any other local authority area.It is likely demand for local area data on COVID-19 will continue to increase and we understand health bodies are expecting to publish further helpful data over the coming days.OSR will continue to work with producers of statistics on COVID-19 to make the case for improved data in the public domain. You can see more of our work in this area on our dedicated COVID-19 webpage.

COVID-19 Local Area Data

2007.15367

The ongoing COVID-19 pandemic has created a global crisis of massive scale. Prior research indicates that human mobility is one of the key factors involved in viral spreading. Indeed, in a connected planet, rapid world-wide spread is enabled by long-distance air-, land- and sea-transportation among countries and continents, and subsequently fostered by commuting trips within densely populated cities. While early travel restrictions contribute to delayed disease spread, their utility is much reduced if the disease has a long incubation period or if there is asymptomatic transmission. Given the lack of vaccines, public health officials have mainly relied on non-pharmaceutical interventions, including social distancing measures, curfews, and stay-at-home orders. Here we study the impact of city organization on its susceptibility to disease spread, and amenability to interventions. Cities can be classified according to their mobility in a spectrum between compact-hierarchical and decentralized-sprawled. Our results show that even though hierarchical cities are more susceptible to the rapid spread of epidemics, their organization makes mobility restrictions quite effective. Conversely, sprawled cities are characterized by a much slower initial spread, but are less responsive to mobility restrictions. These findings hold globally across cities in diverse geographical locations and a broad range of sizes. Our empirical measurements are confirmed by a simulation of COVID-19 spread in urban areas through a compartmental model. These results suggest that investing resources on early monitoring and prompt ad-hoc interventions in more vulnerable cities may prove most helpful in containing and reducing the impact of present and future pandemics.

Impact of urban structure on COVID-19 spread

Lockdown measures and school closures affect girls and women differently across the world and may have long-term negative consequences. Talha Burki reports.Soon after the emergence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) last winter, it became apparent that mortality rates were higher for men than for women. This remains the case but it is women who are more likely to bear the brunt of the social and economic consequences of the pandemic. Earlier this year, UN Secretary-General António Guterres noted that “COVID-19 could reverse the limited progress that has been made on gender equality and women's rights”. With the pandemic set to stretch into 2021, his words are looking less like a warning than a prediction

10.1016/S1473-3099(20)30568-5

The indirect impact of COVID-19 on women

The COVID-19 pandemic is undermining nutrition across the world, particularly in low-income and middle-income countries (LMICs).1United NationsThe impact of COVID-19 on food security and nutrition.http://www.fao.org/policy-support/tools-and-publications/resources-details/es/c/1287907/Date: 2020Date accessed: July 21, 2020Google Scholar The worst consequences are borne by young children. Some of the strategies to respond to COVID-19—including physical distancing, school closures, trade restrictions, and country lockdowns—are impacting food systems by disrupting the production, transportation, and sale of nutritious, fresh, and affordable foods, forcing millions of families to rely on nutrient-poor alternatives. Strained health systems and interruptions in humanitarian response are eroding access to essential and often life-saving nutrition services.2Roberton T Carter ED Chou VB et al.Early estimates of the indirect effects of the COVID-19 pandemic on maternal and child mortality in low-income and middle-income countries: a modelling study.Lancet Glob Health. 2020; 8: e901-e908Summary Full Text Full Text PDF PubMed Scopus (27) Google Scholar Social protection systems in many LMICs are overloaded as vulnerable families struggle to access the food and services they need in the context of an economic downturn.Malnutrition could exacerbate the effects of COVID-19 in mothers and children. At the same time, more children are becoming malnourished due to the deteriorating quality of their diets, interruptions in nutrition and other essential services, and the socioeconomic shocks created by the pandemic in LMICs. New estimates by Derek Headey and colleagues3Headey D Heidkamp R Osendarp S et al.Impacts of COVID-19 on childhood malnutrition and nutrition-related mortality.Lancet. 2020; (published online July 27.)https://doi.org/10.1016/S0140-6736(20)31647-0Google Scholar in an accompanying Comment in The Lancet suggest that without timely action, the global prevalence of child wasting could rise by a shocking 14·3%. With an estimated 47 million children younger than 5 years affected by wasting globally before the COVID-19 pandemic,4UNICEFWHOWorld Bank GroupJoint malnutrition estimates, 2020 edition.https://www.who.int/publications/i/item/jme-2020-editionDate: 2020Date accessed: July 21, 2020Google Scholar this would translate to an estimated additional 6·7 million children with wasting during the first 12 months of the pandemic—80% of them in sub-Saharan Africa and south Asia—and more than 10 000 additional child deaths per month during this same period.3

10.1016/S0140-6736(20)31648-2

Child malnutrition and COVID-19: the time to act is now

10.31234/osf.io/4m876

Social influence is an important determinant of adolescent risk-taking, but little is known about how social norms contribute to adolescents’ tendency to recommend and engage in risky behaviours. Using the Adolescent Risk-taking Questionnaire, we assessed subjects’ (n=198, age=10-26) propensity to engage in and recommend risk-taking as well as their perception of risk-norms. Adolescents recommended risk-taking more often compared to children and young adults. Perceived social norms were the most important factor predicting engagement in risky behaviours, and adolescents perceived risk-taking to be more normative than children or adults. Our findings highlight two mechanisms that contribute to adolescent risk-taking; active recommendation and perceived social norms. On this basis, we discuss potential means to attenuate excessive adolescent risk-taking.

Social norms in adolescent risk engagement and recommendation

To slow COVID-19, many countries have shut down part of the economy. Older individuals have the most to gain from slowing virus diffusion. Younger workers in sectors that are shuttered have most to lose. In this paper, we build a model in which economic activity and disease progression are jointly determined. Individuals differ by age (young, retired), by sector (basic, luxury), and health status. Disease transmission occurs in the workplace, through consumption, at home, and in hospitals. We study the optimal economic mitigation policy for a government that can redistribute across individuals, but where redistribution is costly. Optimal redistribution and mitigation policies interact, and more modest shutdowns are optimal when redistribution is more costly. We find that the shutdowns that were implemented in mid-April were too extensive, but a partial shutdown should remain in place through the fall. A deeper and longer shutdown is preferred if a vaccine is imminent.

10.3386/w27046

Health versus Wealth: On the Distributional Effects of Controlling a Pandemic

We develop a heterogeneous-agents network-based model to analyze alternative policies during a pandemic outbreak, accounting for health and economic trade-offs within the same empirical framework. We leverage a variety of data sources, including data on individuals' mobility and encounters across metropolitan areas, health records, and measures of the possibility to be productively working from home. This combination of data sources allows us to build a framework in which the severity of a disease outbreak varies across locations and industries, and across individuals who differ by age, occupation, and preexisting health conditions. We use this framework to analyze the impact of different social distancing policies in the context of the COVID-19 outbreaks across US metropolitan areas. Our results highlight how outcomes vary across areas in relation to the underlying heterogeneity in population density, social network structures, population health, and employment characteristics. We find that policies by which individuals who can work from home continue to do so, or in which schools and firms alternate schedules across different groups of students and employees, can be effective in limiting the health and healthcare costs of the pandemic outbreak while also reducing employment losses.

10.3386/w27374

Socioeconomic Network Heterogeneity and Pandemic Policy Response

This short note constructs Mobility Zones to facilitate the discussion on the geographic extent of individual mobility restrictions to control the spread of Covid-19. Mobility Zones are disjoint sets of counties where a given level of individual mobility directly or indirectly connects all counties within each set. I compute Mobility Zones for the United States and each state using smartphone-based mobility data between counties. The average area and population of Mobility Zones have slightly grown at the onset of the epidemic and have sharply shrunk afterward. Pre-Covid-19 Mobility Zones may be useful in calibrating quantitative studies of targeted restriction policies, or for policymakers deciding on the adoption of specific mobility measures. Two examples suggest the use of Mobility Zones to inform within-state differences and cross-state coordination in mobility restriction policies.

10.3386/w27236

Mobility Zones

10.3386/w26918

We present a theory of Keynesian supply shocks: supply shocks that trigger changes in aggregate demand larger than the shocks themselves. We argue that the economic shocks associated to the COVID-19 epidemic—shutdowns, layoffs, and firm exits—may have this feature. In one-sector economies supply shocks are never Keynesian. We show that this is a general result that extend to economies with incomplete markets and liquidity constrained consumers. In economies with multiple sectors Keynesian supply shocks are possible, under some conditions. A 50% shock that hits all sectors is not the same as a 100% shock that hits half the economy. Incomplete markets make the conditions for Keynesian supply shocks more likely to be met. Firm exit and job destruction can amplify the initial effect, aggravating the recession. We discuss the effects of various policies. Standard fiscal stimulus can be less effective than usual because the fact that some sectors are shut down mutes the Keynesian multiplier feedback. Monetary policy, as long as it is unimpeded by the zero lower bound, can have magnified effects, by preventing firm exits. Turning to optimal policy, closing down contact-intensive sectors and providing full insurance payments to affected workers can achieve the first-best allocation, despite the lower per-dollar potency of fiscal policy.

Macroeconomic Implications of COVID-19: Can Negative Supply Shocks Cause Demand Shortages?

How should un­em­ploy­ment benefits vary in response to the economic crisis induced by the COVID-19 pandemic? We answer this question by computing the optimal un­em­ploy­ment insurance response to the COVID-​induced recession.We compare the optimal policy to the pro­vi­sions under the CARES Act—which sub­stan­tially expanded un­em­ploy­ment insurance and sparked an ongoing debate over further increases—and several al­ter­na­tive scenarios. We find that it is optimal first to raise un­em­ploy­ment benefits but then to begin lowering them as the economy starts to reopen — despite un­em­ploy­ment remaining high. We also find that the $600 UI sup­ple­ment payment im­ple­mented under CARES was close to the optimal policy. Extending this UI sup­ple­ment for another six months would hamper the recovery and reduce welfare. On the other hand, a UI extension combined with a re-​employment bonus would further increase welfare compared to CARES alone, with only minimal effects on un­em­ploy­ment.

13389

Optimal Un­em­ploy­ment Benefits in the Pandemic

Barely having had the time to digest the economic and social af­ter­shocks of the Great Recession, European welfare states are con­fronted with the even more dis­rup­tive coro­n­avirus pandemic as probably, threat­en­ing the life of the more vul­ner­a­ble, while incurring job losses for many as the con­se­quence of the temporal “freezing of the economy” by lockdown measures. Before the Covid-19 virus struck, the new face of the digital trans­for­ma­tion and the rise of the ‘platform’ economy already raised ex­is­ten­tial questions for future welfare provision. The Great Lockdown – if anything – is bound to ac­cel­er­ate these trends. Greater au­toma­tion will reinforce working from home to reduce Covid-19 virus trans­mis­sion risks. At the same time, the Great Lockdown will reinforce in­equal­ity, as the poor find it more difficult to work from home, while low-paid workers in essential service in health care, su­per­mar­ket retail, postal services, security and waste disposal, continue to face contagion risks. And although popular con­jec­tures of ‘jobless growth’ and ‘routine-​biased’ job po­lar­iza­tion, driven by dig­i­ti­za­tion and ar­ti­fi­cial in­tel­li­gence, may still be overblown, intrusive change in the nature of work and em­ploy­ment relations require fun­da­men­tal re­think­ing of extant labour market reg­u­la­tion and social pro­tec­tion. Inspired more by adverse family de­mog­ra­phy than tech­no­log­i­cal change, social in­vest­ment reform has been the fil rouge of welfare re­cal­i­bra­tion since the turn of the century. Is social in­vest­ment reform still valid in the new era of ‘dis­rup­tive’ tech­no­log­i­cal trans­for­ma­tion in aftermath of Coro­n­avirus pandemic that is likely to turn into the worst recession since the second world war? Em­pir­i­cally, this chapter explores how Germany, Italy and the Nether­lands, in terms of the strengths and vul­ner­a­bil­i­ties of their labour market to dig­i­ti­za­tion, together with their re­spec­tive social in­vest­ment aptitude, are currently preparing their welfare states for the in­ten­si­fi­ca­tion of tech­no­log­i­cal change in the decade ahead.

13391

Welfare States, Labor Markets, Social In­vest­ment and the Digital Trans­for­ma­tion

We measure the effect of lockdown policies on em­ploy­ment and GDP across countries using individual-​ and sector-​level data. Em­ploy­ment effects depend on the ability to work from home, which ranges from about half of total em­ploy­ment in rich countries to around 35% in poor countries. This gap reflects dif­fer­ences in oc­cu­pa­tional com­po­si­tion, self-​employment levels, and in­di­vid­ual char­ac­ter­is­tics across countries. GDP effects of lockdown policies also depend on countries’ sectoral structure. Losses in poor countries are at­ten­u­ated by their higher value-​added share in essential sectors, notably agri­cul­ture. Overall, a realistic lockdown policy implies GDP losses of 20-25% on an an­nu­al­ized basis.

13397

Lockdown Ac­count­ing

We present findings from a novel survey of Italian, British, and American families in lockdown during the COVID-19 pandemic of spring 2020. A high per­cent­age report dis­rup­tions in the patterns of family life, man­i­fest­ing in new work patterns, chore al­lo­ca­tions and household tensions. Though men have taken a greater share of childcare and grocery shopping duties, re­al­lo­ca­tions are not nearly as stark as dis­rup­tions to work patterns might suggest, and families having to re­al­lo­cate duties report greater tensions. Our results paint a picture of tightened con­straints budging up against stable and gendered patterns of intra-​household co­op­er­a­tion. While the long-run con­se­quences of the COVID-19 lockdown on family life cannot be assessed at this stage, we point towards the likely op­por­tu­ni­ties and chal­lenges.

13398

Family Life in Lockdown

Of all things I forgot rapid genome sequencing of the virus that allows us spatiotemporally track it, ice transmission dynamics, follow evolution of the virus (which is thankfully very slow)

It's 100+ years later and we're a lot smarter, more capable. Why aren't we beating the crap out of #SARSCoV2? We will. Just a matter of time.

Behavioural Science and the Pandemic

There were two narratives that emerged in the week before we locked down on 23rd March that could go some way to explaining why the UK was relatively slow to lockdown. One was the idea of “herd immunity” - that the virus was always going to spread throughout the population to some extent, and that should be allowed to happen to build up immunity. That theory may have been based on a misunderstanding of how this particular virus behaved. The second narrative was based on the idea of “behavioural fatigue”. This centred around the notion that the public will only tolerate a lockdown for so long so it was crucial to wait for the right moment to initiate it. Go too soon, and you might find that people would not comply later on. It turns out that this theory was also wrong. And based on a fundamental misunderstanding of human behaviour. Despite photos of packed parks, crammed beaches and VE day conga lines, on the whole the British public complied beyond most people’s expectations. So what informed the government’s decision making?In this programme we ask, what is “behavioural fatigue”, where did it come from, how much influence did it have on the UK’s late lockdown, and where does Nudge theory fit into the narrative?

Most of the data available through tidycensus and the Census API is aggregated to certain geographic levels (tract, county, state, etc.). In other words, the data we get by executing get_acs() has been summarized by the Census Bureau so that we are able to learn how many people live in a particular county or what the median household income of a state is. There are thousands of individual variables that the Census aggregates and publishes in tabular form. For many purposes, these pre-aggregated tables have enough information to work with. But, the Census Bureau also releases microdata from the American Community Survey. Microdata is the individual-level responses to the ACS that is used to create the summary and detail tables the Census publishes. Instead of a getting one row per state from a table, we can get one row per respondent. For the American Community Survey, this data is called the Public Use Microdata Sample (PUMS). Using PUMS data instead of the published tables can be a very powerful tool. It can, for instance, allow you to create custom estimates that aren’t available in pre-aggregated tables. You can also use microdata to fit models on individual-level data instead of modeling block groups or census tracts. Until recently, PUMS data was only available from the Census Bureau FTP site and was somewhat cumbersome to use. Now, PUMS data is available via web API, which means you can easily access it in R by using tidycensus.

Working with Census microdata

We present a scalable methodology to identify Twitter handles of politicians in a given region and test our framework in the context of Indian and US politics. The main contribution of our work is the list of the curated Twitter handles of 18500 Indian and 8000 US politicians. Our work leveraged machine learning-based classification and human verification to build a data set of Indian politicians on Twitter. We built NivaDuck, a highly precise, two-staged classification pipeline that leverages Twitter description text and tweet content to identify politicians. For India, we tested NivaDuck’s recall using Twitter handles of the members of the Indian parliament while for the US we used state and local level politicians in California state and San Diego county respectively. We found that while NivaDuck has lower recall scores, it produces large, diverse sets of politicians with precision exceeding 90 percent for the US dataset. We discuss the need for an ML-based, scalable method to compile such a dataset and its myriad use cases for the research community and its wide-ranging utilities for research in political communication on social media.

10.1145/3400806.3400830

NivaDuck - A Scalable Pipeline to Build a Database of Political Twitter Handles for India and the United States

This chart shows the countries with the worst coronavirus outbreaks in the world right now. With its cases surging since mid-June, the United States is squarely in the top 10.

How the U.S. Compares With the World’s Worst Coronavirus Hot Spots

Scientists who study complex systems offer solutions to the pandemic.

The Damage We’re Not Attending To

Scottish numbers: 30 July 2020 17 new confirmed cases of COVID-19; this is 0.5% of newly tested individuals. 0 new reported death(s) of people who have tested positive. 2 people were in intensive care last night with confirmed COVID-19. 260 people were in hospital with confirmed COVID-19. 13,208 new tests for COVID-19 that reported results.

Coronavirus (COVID-19): daily data for Scotland

This paper in­ves­ti­gates the incidence, trend and de­ter­mi­nants of remote work in Greece. A crisis-​stricken country in the years preceding the Covid-19 crisis, Greece entered the first wave of the public health shock as a laggard in dig­i­tal­i­sa­tion and remote work arrange­ments among European countries. While Covid-19 induced a spike in the use of remote work arrange­ments in many countries, this paper presents evidence that working from home (WfH) in Greece was subdued in the past decade. By analysing the profile of the job tasks and skill needs of Greek home­work­ers, the paper also shows marked de­vi­a­tions in home­work­ing patterns and de­ter­mi­nants in Greece, relative to other EU countries. This includes a higher preva­lence of WfH among Greek females and non-​nationals, limited use by young workers and families with children and a stronger relation with atypical work hours. While remote workers in Greece receive a 7% monthly wage premium, their jobs are found to involve stan­dard­ised and moderate ICT tasks and to rely more on social serving tasks. The paper high­lights that there is sig­nif­i­cant scope to enhance remote work in Greece, which can amount to up to 37% of all salaried jobs, subject to changing work or­gan­i­sa­tion, norms and policies. In the coro­n­avirus era, over­com­ing barriers to remote work will be key for the Greek labour market to adapt to social distances practices and dig­i­tal­i­sa­tion.

13408

Working at Home in Greece: Un­ex­plored Potential at Times of Social Dis­tanc­ing?

Evidence from past economic crises indicates that re­ces­sions often affect men’s and women’s em­ploy­ment dif­fer­ently, with a greater impact on male-​dominated sectors. The current COVID-19 crisis presents novel char­ac­ter­is­tics that have affected economic, health and social phenomena over wide swaths of the economy. Social dis­tanc­ing measures to combat the spread of the virus, such as working from home and school closures, have placed an ad­di­tional tremen­dous burden on families. Using new survey data collected in April 2020 from a rep­re­sen­ta­tive sample of Italian women, we analyse jointly the effect of COVID-19 on the working arrange­ments, housework and childcare of couples where both partners work. Our results show that most of the ad­di­tional workload as­so­ci­ated to COVID-19 falls on women while childcare ac­tiv­i­ties are more equally shared within the couple than housework ac­tiv­i­ties. According to our empirical estimates, changes to the amount of housework done by women during the emergency do not seem to depend on their partners’ working arrange­ments. With the exception of those con­tin­u­ing to work at their usual place of work, all of the women surveyed spend more time on housework than before. In contrast, the amount of time men devote to housework does depend on their partners’ working arrange­ments: men whose partners continue to work at their usual workplace spend more time on housework than before. The link between time devoted to childcare and working arrange­ments is more symmetric, with both women and men spending less time with their children if they continue to work away from home. For home schooling, too, parents who continue to go to their usual workplace after the lockdown are less likely to spend greater amounts of time with their children than before. Similar results emerge for our sample of women not working before the emergency. Finally, analysis of work-life balance sat­is­fac­tion shows that working women with children aged 0-5 are those who say they find balancing work and family more difficult during COVID-19. The work-life balance is es­pe­cially difficult to achieve for those with partners who continue to work outside the home during the emergency.

Women’s Work, Housework and Childcare, before and during COVID-19

13409

The goal of this piece is to survey the emerging and rapidly growing lit­er­a­ture on the economic con­se­quences of COVID-19 and gov­ern­ment response, and to syn­thetize the insights emerging from a very large number of studies. This survey (i) provides an overview of the data sets used to measure social dis­tanc­ing and COVID-19 cases and deaths; (ii) reviews the lit­er­a­ture on the de­ter­mi­nants of com­pli­ance and ef­fec­tive­ness of social dis­tanc­ing; (iii) sum­ma­rizes the lit­er­a­ture on the socio-​economic con­se­quences of COVID-19 and gov­ern­ment in­ter­ven­tions, focusing on labor, health, gender, dis­crim­i­na­tion and en­vi­ron­men­tal aspects; and (iv) discusses policy proposals.

13411

A Lit­er­a­ture Review of the Economics of COVID-19

We study the impact of short-​term exposure to ambient air pollution on the spread and severity of COVID-19 in Germany. We combine data on county-​by-day level on confirmed cases and deaths with in­for­ma­tion on local air quality and weather con­di­tions and exploit short-​term variation in the con­cen­tra­tion of par­tic­u­late matter (PM10) and ozone (O3). We apply fixed effects re­gres­sions con­trol­ling for global time-​varying con­found­ing factors and regional time-​invariant con­found­ing factors on the county level, as well as po­ten­tially con­found­ing weather con­di­tions and the regional stage of the pandemic. We find sig­nif­i­cant positive effects of PM10 con­cen­tra­tion after the onset of the illness on COVID-19 deaths specif­i­cally for elderly patients (80+ years): higher levels of air pollution by one standard deviation 3 to 12 days after de­vel­op­ing symptoms increase deaths by 30 percent (males) and 35 percent (females) of the mean. In addition, air pollution raises the number of confirmed cases of COVID-19. The timing of results supports mech­a­nisms of air pollution affecting the severity of already realized in­fec­tions. Air pollution appears not to affect the prob­a­bil­ity of infection itself.

13418

Pandemic Meets Pollution: Poor Air Quality Increases Deaths by COVID-19

Early non-​pharmaceutical in­ter­ven­tions (NPI) sig­nif­i­cantly reduced the death toll of the COVID-19 pandemic. Yet, there are vast dif­fer­ences in how quickly gov­ern­ments im­ple­mented NPIs. In this paper, we analyze the role of public attention, measured as the share of daily Google searches in a country related to COVID-19, in the timing of the NPI responses. We first show that public attention depends strongly on whether there are cases in own country. We then show that countries with high levels of public attention are more likely to implement NPIs, even after con­trol­ling for the number of cases and deaths. Finally, we show that the extent to which a gov­ern­ment responds to public attention is highly dependent on the country’s in­sti­tu­tional quality. The positive effect of public attention on policy im­ple­men­ta­tion is driven entirely by countries with good in­sti­tu­tions.

13427

Public Attention and Policy Responses to COVID-19 Pandemic

10.31222/osf.io/b6ywe

Scholars traditionally receive career credit for a paper based on where in the author list they appear, but position in an author list often carries little information about what the contribution of each researcher was. “Contributorship” refers to a movement to formally document the nature of each researcher’s contribution to a project. We discuss the emerging CRediT standard for documenting contributions and describe a web-based app and R package, tenzing, that is designed to facilitate its use. tenzing can make it easier for researchers on a project to plan and record their planned contributions and to document those contributions in a journal article.

Tenzing: documenting contributorship using CRediT

A framework for tax compliance is suggested in which both the power of tax authorities and trust in the tax authorities are relevant dimensions for understanding enforced and voluntary compliance. Dynamic interactions between power and trust are considered. Using the framework as a conceptual tool, factors studied in previous research, such as fines, audit probabilities, tax rate, knowledge, attitudes, norms and fairness are reviewed and discussed with reference to the power and trust dimensions. Using the framework as an operational tool, approaches of responsive regulation to increase tax compliance are discussed.

10.1016/j.joep.2007.05.004

Enforced versus voluntary tax compliance: The “slippery slope” framework

10.3386/w27505

COVID-19 has created a dual set of stresses on health care systems worldwide: a rise in expensive intensive care services and a dramatic decline in elective services. The U.S. government has responded with both grant and loan programs to help health care providers weather the storm. But the optimal size and nature of such programs are hard to evaluate without an understanding of the ability of providers to make up their lost elective service revenues over time. In this paper, we study the closest relevant parallel to the reduction in elective services seen under COVID-19: hurricanes. We match information on hurricanes to data on Medicare hospital elective visits and charges from 1997-2013, comparing counties impacted by hurricanes to nearby unaffected counties. We find that the average hurricane reduces elective services by about 7% in the month it makes landfall. For the most severe hurricanes, we estimate a reduction of more than 20%. Services return to baseline fairly rapidly, but for severe hurricanes it takes a year or more to make up lost revenues. Projections based on variation in hurricane severity suggest that it will take over 3 years for providers to make up the lost revenue from COVID-19.

Natural Disasters and Elective Medical Services: How Big is the Bounce-Back?

10.3386/w27039

This paper considers a modification of the standard Susceptible-Infected-Recovered (SIR) model of epidemic that allows for different degrees of compulsory as well as voluntary social distancing. It is shown that the fraction of population that self-isolates varies with the perceived probability of contracting the disease. Implications of social distancing both on the epidemic and recession curves are investigated and their trade off is simulated under a number of different social distancing and economic participation scenarios. We show that mandating social distancing is very effective at flattening the epidemic curve, but is costly in terms of employment loss. However, if targeted towards individuals most likely to spread the infection, the employment loss can be somewhat reduced. We also show that voluntary self-isolation driven by individual’s perceived risk of becoming infected kicks in only towards the peak of the epidemic and has little or no impact on flattening the epidemic curve. Using available statistics and correcting for measurement errors, we estimate the rate of exposure to COVID-19 for 21 Chinese provinces and a selected number of countries. The exposure rates are generally small, but vary considerably between Hubei and other Chinese provinces as well as across countries. Strikingly, the exposure rate in Hubei province is around 40 times larger than the rates for other Chinese provinces, with the exposure rates for some European countries being 3-5 times larger than Hubei (the epicenter of the epidemic). The paper also provides country-specific estimates of the recovery rate, showing it to be about 21 days (a week longer than the 14 days typically assumed), and relatively homogeneous across Chinese provinces and for a selected number of countries.

Voluntary and Mandatory Social Distancing: Evidence on COVID-19 Exposure Rates from Chinese Provinces and Selected Countries

10.3386/w27355

We study liquidity conditions in the corporate bond market since the onset of the COVID-19 pandemic. We find that in mid-March 2020, as selling pressure surged, dealers were wary of accumulating inventory on their balance sheets, perhaps out of concern for violating regulatory requirements. As a result, the cost to investors of trading immediately with a dealer surged. A portion of transactions migrated to a slower, less costly process wherein dealers arranged for trades directly between customers without using their own balance sheet space. Interventions by the Federal Reserve appear to have relaxed balance sheet constraints: soon after they were announced, dealers began absorbing inventory, bid-ask spreads declined, and market liquidity started to improve. Interestingly, liquidity conditions improved for bonds that were eligible for the Fed’s lending/purchase programs and for bonds that were ineligible. Hence, by allowing dealers to unload certain assets from their balance sheet, the Fed’s interventions may have helped dealers to better intermediate a wide variety of assets, including those not directly targeted.

Corporate Bond Liquidity During the COVID-19 Crisis

10.3386/w27028

We develop an analytically tractable method to estimate the fraction of unreported infections in epidemics with a known epicenter and estimate the number of unreported COVID-19 infections in the US during the first half of March 2020. Our method utilizes the covariation in initial reported infections across US regions and the number of travelers to these regions from the epicenter, along with the results of an early randomized testing study in Iceland. Using our estimates of the number of unreported infections, which are substantially larger than the number of reported infections, we also provide estimates for the infection fatality rate using data on reported COVID-19 fatalities from U.S. counties.

Estimating the Fraction of Unreported Infections in Epidemics with a Known Epicenter: an Application to COVID-19

This paper presents a procedure for estimating and forecasting disease scenarios for COVID-19 using a structural SIR model of the pandemic. Our procedure combines the flexibility of noteworthy reduced-form approaches for estimating the progression of the COVID-19 pandemic to date with the benefits of a simple SIR structural model for interpreting these estimates and constructing forecast and counterfactual scenarios. We present forecast scenarios for a devastating second wave of the pandemic as well as for a long and slow continuation of current levels of infections and daily deaths. In our counterfactual scenarios, we find that there is no clear answer to the question of whether earlier mitigation measures would have reduced the long run cumulative death toll from this disease. In some cases, we find that it would have, but in other cases, we find the opposite — earlier mitigation would have led to a higher long-run death toll.

10.3386/w27335

Estimating and Forecasting Disease Scenarios for COVID-19 with an SIR Model

10.3386/w27378

Disease spread is in part a function of individual behavior. We examine the factors predicting individual behavior during the Covid-19 pandemic in the United States using novel data collected by Belot et al. (2020). Among other factors, we show that people with lower income, less flexible work arrangements (e.g., an inability to tele-work) and lack of outside space at home are less likely to engage in behaviors, such as social distancing, that limit the spread of disease. We also find evidence that region, gender and beliefs predict behavior. Broadly, our findings align with typical relationships between health and socio-economic status. Moreover, they suggest that the burden of measures designed to stem the pandemic are unevenly distributed across socio-demographic groups in ways that affect behavior and thus potentially the spread of illness. Policies that assume otherwise are unlikely to be effective or sustainable.