Will this be temporary or will we see a lasting shift toward a less global, less urban and less prosperous world? asks Rune Dahl Fitjar

The density and connectedness of cities now appear as weaknesses

Something has to be done about the memory-hole problem. Need to know that outlet X said Y at time T.

Explore how scientists model the spread of pandemics, and what this tells us about the policy options for managing COVID-19.

COVID-19: Pandemics, Modelling, and Policy

Phil Anderson’s article “More Is Different” describes how different levels of complexity require new ways of thinking. And as the virus multiplies and spreads, that’s just what the human race desperately needs

How a Landmark Physics Paper from the 1970s Uncannily Describes the COVID-19 Pandemic

The Expert Groups of the Swiss National COVID-19 Science Task Force address urgent issues regarding the COVID-19 crisis in Policy Briefs, which are discussed and approved by the Advisory Panel and published on our website. They reflect the thinking of the Taskforce on this topic at that time. If required, the policy briefs are updated in the light of new studies or other data.

Policy Briefs

Researchers call on government to do more to explain need for physical distancing

Young men more likely than women to break lockdown rules – UK survey

After facing the existential threat of testing positive for Covid-19, these Australians describe the reactions of their communities

Fear, judgment, hysteria: six survivors talk about life after coronavirus

Employers face a logistical nightmare as staff return

A return to work is on the cards. What are the fears and legal pitfalls?

During the COVID-19 pandemic, healthcare workers work under high workload with resource constraints and virus exposure, and hence the support to healthcare workers is crucial to lower anxiety. Based on a recently published 8-point framework of COVID-19 specific organization support, we deducted a measure of COVID-19 Organizational Support (COVID-OS) of healthcare workers. We tested the new measure with 712 healthcare workers in Bolivia, Ecuador, and Peru from April 10th to May 2nd, 2020. Our studies suggest the new measure of COVID-19 Organizational Support (COVID-OS) formed 3 factors to predict healthcare workers’ anxiety and life satisfaction during the COVID-19 pandemic. Personal support and work support each predicted anxiety at different levels. Risk support did not play a significant role in our sample. We call further studies testing the COVID-OS in other countries and settings.

Measuring COVID-19 Organizational Support of Individual Healthcare Workers – A Test with 712 Healthcare Workers in Peru, Ecuador, and Bolivia

R0 is just an average: the transmission rate varies widely, and outbreaks can be suprisingly large even when the epidemic is subcritical.

SFI TRANSMISSIONCOMPLEXITY SCIENCE FOR COVID-19

Dynamical processes, such as the diffusion of knowledge, opinions, pathogens, “fake news,” innovation, and others, are highly dependent on the structure of the social network in which they occur. However, questions on why most social networks present some particular structural features, namely, high levels of transitivity and degree assortativity, when compared to other types of networks remain open. First, we argue that every one-mode network can be regarded as a projection of a bipartite network, and we show that this is the case using two simple examples solved with the generating functions formalism. Second, using synthetic and empirical data, we reveal how the combination of the degree distribution of both sets of nodes of the bipartite network—together with the presence of cycles of lengths four and six—explain the observed values of transitivity and degree assortativity coefficients in the one-mode projected network. Bipartite networks with top node degrees that display a more right-skewed distribution than the bottom nodes result in highly transitive and degree assortative projections, especially if a large number of small cycles are present in the bipartite structure.

Transitivity and degree assortativity explained: The bipartite structure of social networks

The most widely used techniques for community detection in networks, including methods based on modularity, statistical inference, and information theoretic arguments, all work by optimizing objective functions that measure the quality of network partitions. There is a good case to be made, however, that one should not look solely at the single optimal community structure under such an objective function but rather at a selection of high-scoring structures. If one does this, one typically finds that the resulting structures show considerable variation, which could be taken as evidence that these community detection methods are unreliable, since they do not appear to give consistent answers. Here we argue that, upon closer inspection, the structures found are in fact consistent in a certain way. Specifically, we show that they can all be assembled from a set of underlying “building blocks,” groups of network nodes that are usually found together in the same community. Different community structures correspond to different arrangements of blocks, but the blocks themselves are largely invariant. We propose an information theoretic method for discovering the building blocks in specific networks and demonstrate it with several example applications. We conclude that traditional community detection does in fact give a significant amount of insight into network structure.

Consistency of community structure in complex networks

Maria Laura Ruiu is lecturer at Northumbria University (Newcastle upon Tyne). She has recently completed her second PhD in Social Sciences (Northumbria University). She also acted as post-doctoral researcher at the Desertification Research Centre (University of Sassari, Italy) investigating the adaptive capacity of some communities to climate change impact. This paper analyses the first phases of the Covid-19 (Coronavirus) outbreak management in Italy by exploring the combination of political, scientific, media and public responses. A lack of coordination between political and scientific levels, and between institutional claim-makers and the media, suggests a mismanagement of the crisis during the first phases of the outbreak. The outbreak management suffered from the five communication weaknesses identified by Reynolds, related to i) mixed messages from multiple messengers; ii) delay in releasing information; iii) paternalistic attitudes; iv) lack of immediate reaction to rumours; and v) political confusion. This supports that the communication of uncertainty around an unknown threat should be accompanied by both political and scientific cohesion. However, both political and scientific dysfunctions caused the failure of several government efforts to contain the outbreak. This paper contributes towards informing policymakers on some lessons learned from the management of the Covid-19 in one of the most affected countries in the world. The Italian case study offers the opportunity for other countries to improve the management of the outbreak by limiting the spread of both chaos and panic.

Mismanagement of Covid-19: lessons learned from Italy

Fast, cheap, good – you can pick two… The UK Reproducibility Network (UKRN) is a peer-led consortium that aims to ensure the UK retains its place as a centre for world-leading research. The UKRN grew from activity across the UK seeking to understand the factors that contribute to poor research reproducibility and replicability. We aim to develop approaches to counter these problems, and thereby improve the quality of the research we produce. The COVID-19 pandemic is unprecedented in recent history, and has demonstrated the strength of the global scientific community. Resources have been rapidly diverted towards understanding the virus, modelling strategies to reduce its impact, developing vaccines and treatments, and more. Collaborations – both national and international – have emerged almost overnight, and preprint servers have experienced a surge of submissions. However, given the importance and the immediacy of the challenge, rigorous and high-quality research is more important than ever. There is an urgent need for data and knowledge, but it is critically important that data are of high quality and that knowledge truly advances: false information is worse than no information. Open research can serve as a quality-control process, protecting against bias, minimising errors in the research process, and providing greater scope for errors to be detected by the wider community. To promote the uptake of open research practices, we have produced a series of primers – on pre-registration, data sharing, open code and software, open access, and preprints. There are also challenges for research users in assimilating and critically appraising the findings of the large number of scientific publications and preprints, so that these might be deployed for the public good. We therefore welcome the collaborative engagement of the global systematic review community, and encourage them to further strengthen these collaborations to enhance the efficiency and timeliness of their work. In any human endeavour errors will occur – scientists are not infallible. And this will be particularly true when working fast or under time pressure. The fundamentals of good design, careful conduct and thoughtful interpretation apply even when there is a pressing need to understand a new phenomenon rapidly. But in addition to this, transparency is a vital – to ensure that work can be scrutinised and trusted.

UKRN Position on COVID-19 Research

The new coronavirus has already claimed the lives of hundreds of thousands of people. Different countries are taking different measures in the fight against this new threat. Many people are staying at home. But is it worth it? That’s what we wanted to find out.We created a computer model that helps us assess the effect of different measures against COVID-19. We checked for the impact on people’s health and the state of the healthcare systems in two countries: the UK and the US. We found that social distancing of the whole population, not just the elderly, would have the most beneficial effect. The combination of this measure with others would be even better.

How can we help stop theCOVID-19 pandemic?

Imperial researchers have analysed the likely impact of easing lockdown measures in Italy and the impact on transmission of coronavirus.

New report models Italy's potential exit strategy from COVID-19 lockdown

#COVID has now sent 1 out of every 150 New York City adults to the hospital since the city's first case was diagnosed nine weeks ago.

The urge to reopen society far outpaces scientific discovery. Ten scientists offer a plan to close the gap.

The World Doesn’t Yet Know Enough to Beat the Coronavirus

To help accelerate scientific discovery with visualization, last month we launched SciSight, a framework of exploratory search and visualization tools for the COVID-19 literature. The first version of SciSight supported exploring associations between biomedical concepts appearing in the literature. In preliminary user interviews, the tool was found helpful in discovery-oriented search. We now release two important updates of SciSight.

Exploring the COVID-19 network of scientific research with SciSight

Our goal is to help accelerate scientific research, with tools to visualize the emerging literature network around COVID-19. Use our exploratory search tools to find out what groups are working on what directions, see how biomedical concepts interact and evolve over time, and discover new connections.

SciSight is a tool for exploring the evolving network of science in the COVID-19 Open Research Dataset, from Semantic Scholar at the Allen Institute for AI.

Background: There is substantial disagreement about the level of asymptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in a population. The disagreement results, in part, from the interpretation of studies that report a proportion of asymptomatic people with SARS-CoV-2 detected at a single point. Review questions: 1. Amongst people who become infected with SARS-CoV-2, what proportion does not experience symptoms at all during their infection? 2. Amongst people with SARS-CoV-2 infection who are asymptomatic when diagnosed, what proportion will develop symptoms later? 3. What proportion of SARS-CoV-2 transmission is accounted for by people who are either asymptomatic throughout infection, or pre-symptomatic? Methods: Rapid living systematic review (protocol https://osf.io/9ewys/). We searched Pubmed, Embase, bioRxiv and medRxiv using a living evidence database of SARS-CoV-2 literature on 25.03.2020. We included studies of people with SARS-CoV-2 diagnosed by reverse transcriptase PCR (RT-PCR) that documented follow-up and symptom status at the beginning and end of follow-up and modelling studies. Study selection, data extraction and bias assessment were done by one reviewer and verified by a second, with disagreement resolved by discussion or a third reviewer. We used a common-effect model to synthesise proportions from comparable studies. Results: We screened 89 studies and included 11. We estimated an upper bound for the proportion of asymptomatic SARS-CoV-2 infections of 29% (95% confidence interval 23 to 37%) in eight studies. Selection bias and likely publication bias affected the family case investigation studies. One statistical modelling study estimated the true proportion of asymptomatic infections at 18% (95% credibility interval 16 to 20%). Estimates of the proportions of pre-symptomatic individual in four studies were too heterogeneous to combine. In modelling studies, 40-60% of all SARS-CoV-2 infections are the result of transmission from pre-symptomatic individuals, with a smaller contribution from asymptomatic individuals. Conclusions: An intermediate contribution of pre-symptomatic and asymptomatic infections to overall SARS-CoV-2 transmission means that combination prevention, with enhanced hand and respiratory hygiene, testing tracing and isolation strategies and social distancing, will continue to be needed. The findings of this systematic review of publications early in the pandemic suggests that most SARS-CoV-2 infections are not asymptomatic throughout the course of infection.

The role of asymptomatic SARS-CoV-2 infections: rapid living systematic review and meta-analysis

The COVID-19 pandemic is straining public health systems worldwide and major non-pharmaceutical interventions have been implemented to slow its spread. During the initial phase of the outbreak the spread was primarily determined by human mobility. Yet empirical evidence on the effect of key geographic factors on local epidemic spread is lacking. We analyse highly-resolved spatial variables for cities in China together with case count data in order to investigate the role of climate, urbanization, and variation in interventions across China. Here we show that the epidemic intensity of COVID-19 is strongly shaped by crowding, such that epidemics in dense cities are more spread out through time, and denser cities have larger total incidence. Observed differences in epidemic intensity are well captured by a metapopulation model of COVID-19 that explicitly accounts for spatial hierarchies. Densely-populated cities worldwide may experience more prolonged epidemics. Whilst stringent interventions can shorten the time length of these local epidemics, although these may be difficult to implement in many affected settings.

Crowding and the epidemic intensity of COVID-19 transmission

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can spread rapidly within skilled nursing facilities. After identification of a case of Covid-19 in a skilled nursing facility, we assessed transmission and evaluated the adequacy of symptom-based screening to identify infections in residents. MethodsWe conducted two serial point-prevalence surveys, 1 week apart, in which assenting residents of the facility underwent nasopharyngeal and oropharyngeal testing for SARS-CoV-2, including real-time reverse-transcriptase polymerase chain reaction (rRT-PCR), viral culture, and sequencing. Symptoms that had been present during the preceding 14 days were recorded. Asymptomatic residents who tested positive were reassessed 7 days later. Residents with SARS-CoV-2 infection were categorized as symptomatic with typical symptoms (fever, cough, or shortness of breath), symptomatic with only atypical symptoms, presymptomatic, or asymptomatic. ResultsTwenty-three days after the first positive test result in a resident at this skilled nursing facility, 57 of 89 residents (64%) tested positive for SARS-CoV-2. Among 76 residents who participated in point-prevalence surveys, 48 (63%) tested positive. Of these 48 residents, 27 (56%) were asymptomatic at the time of testing; 24 subsequently developed symptoms (median time to onset, 4 days). Samples from these 24 presymptomatic residents had a median rRT-PCR cycle threshold value of 23.1, and viable virus was recovered from 17 residents. As of April 3, of the 57 residents with SARS-CoV-2 infection, 11 had been hospitalized (3 in the intensive care unit) and 15 had died (mortality, 26%). Of the 34 residents whose specimens were sequenced, 27 (79%) had sequences that fit into two clusters with a difference of one nucleotide. ConclusionsRapid and widespread transmission of SARS-CoV-2 was demonstrated in this skilled nursing facility. More than half of residents with positive test results were asymptomatic at the time of testing and most likely contributed to transmission. Infection-control strategies focused solely on symptomatic residents were not sufficient to prevent transmission after SARS-CoV-2 introduction into this facility.

Presymptomatic SARS-CoV-2 Infections and Transmission in a Skilled Nursing Facility

In the United States, 567 715 people were homeless on a single night in January 2019.1 The congregate nature and hygienic challenges of shelter life create the potential for rapid transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in this vulnerable population. On March 13, 2020, the Boston Health Care for the Homeless Program (BHCHP), in partnership with city and state public health agencies and community partners, rolled out a coronavirus disease 2019 (COVID-19) response strategy that included respiratory symptom screening at shelter front doors, expedited referrals for SARS-CoV-2 testing and isolation for those with respiratory symptoms, dedicated treatment settings for individuals with positive test results, and contact tracing of confirmed COVID-19 cases. Between March 28, 2020, and April 1, 2020, BHCHP identified an increasing number of COVID-19 cases from a single large homeless shelter in Boston, prompting SARS-CoV-2 testing of all remaining shelter residents. We describe the results of this investigation.

Prevalence of SARS-CoV-2 Infection in Residents of a Large Homeless Shelter in Boston

SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), has spread rapidly around the world since it was first recognized in late 2019. Most early reports of person-to-person SARS-CoV-2 transmission have been among household contacts, where the secondary attack rate has been estimated to exceed 10% (1), in health care facilities (2), and in congregate settings (3). However, widespread community transmission, as is currently being observed in the United States, requires more expansive transmission events between nonhousehold contacts. In February and March 2020, the Chicago Department of Public Health (CDPH) investigated a large, multifamily cluster of COVID-19. Patients with confirmed COVID-19 and their close contacts were interviewed to better understand nonhousehold, community transmission of SARS-CoV-2. This report describes the cluster of 16 cases of confirmed or probable COVID-19, including three deaths, likely resulting from transmission of SARS-CoV-2 at two family gatherings (a funeral and a birthday party). These data support current CDC social distancing recommendations intended to reduce SARS-CoV-2 transmission. U.S residents should follow stay-at-home orders when required by state or local authorities.

Community Transmission of SARS-CoV-2 at Two Family Gatherings — Chicago, Illinois, February–March 2020

Background Elucidation of the chain of disease transmission and identification of the source of coronavirus disease 2019 (COVID-19) infections are crucial for effective disease containment. We describe an epidemiological investigation that, with use of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) serological assays, established links between three clusters of COVID-19.Methods In Singapore, active case-finding and contact tracing were undertaken for all COVID-19 cases. Diagnosis for acute disease was confirmed with RT-PCR testing. When epidemiological information suggested that people might have been nodes of disease transmission but had recovered from illness, SARS-CoV-2 IgG serology testing was used to establish past infection.Findings Three clusters of COVID-19, comprising 28 locally transmitted cases, were identified in Singapore; these clusters were from two churches (Church A and Church B) and a family gathering. The clusters in Church A and Church B were linked by an individual from Church A (A2), who transmitted SARS-CoV-2 infection to the primary case from Church B (F1) at a family gathering they both attended on Jan 25, 2020. All cases were confirmed by RT-PCR testing because they had active disease, except for A2, who at the time of testing had recovered from their illness and tested negative. This individual was eventually diagnosed with past infection by serological testing. ELISA assays showed an optical density of more than 1·4 for SARS-CoV-2 nucleoprotein and receptor binding domain antigens in titres up to 1/400, and viral neutralisation was noted in titres up to 1/320.Interpretation Development and application of a serological assay has helped to establish connections between COVID-19 clusters in Singapore. Serological testing can have a crucial role in identifying convalescent cases or people with milder disease who might have been missed by other surveillance methods.

Connecting clusters of COVID-19: an epidemiological and serological investigation

During the current worldwide pandemic, coronavirus disease 2019 (Covid-19) was first diagnosed in Iceland at the end of February. However, data are limited on how SARS-CoV-2, the virus that causes Covid-19, enters and spreads in a population. MethodsWe targeted testing to persons living in Iceland who were at high risk for infection (mainly those who were symptomatic, had recently traveled to high-risk countries, or had contact with infected persons). We also carried out population screening using two strategies: issuing an open invitation to 10,797 persons and sending random invitations to 2283 persons. We sequenced SARS-CoV-2 from 643 samples. ResultsAs of April 4, a total of 1221 of 9199 persons (13.3%) who were recruited for targeted testing had positive results for infection with SARS-CoV-2. Of those tested in the general population, 87 (0.8%) in the open-invitation screening and 13 (0.6%) in the random-population screening tested positive for the virus. In total, 6% of the population was screened. Most persons in the targeted-testing group who received positive tests early in the study had recently traveled internationally, in contrast to those who tested positive later in the study. Children under 10 years of age were less likely to receive a positive result than were persons 10 years of age or older, with percentages of 6.7% and 13.7%, respectively, for targeted testing; in the population screening, no child under 10 years of age had a positive result, as compared with 0.8% of those 10 years of age or older. Fewer females than males received positive results both in targeted testing (11.0% vs. 16.7%) and in population screening (0.6% vs. 0.9%). The haplotypes of the sequenced SARS-CoV-2 viruses were diverse and changed over time. The percentage of infected participants that was determined through population screening remained stable for the 20-day duration of screening. ConclusionsIn a population-based study in Iceland, children under 10 years of age and females had a lower incidence of SARS-CoV-2 infection than adolescents or adults and males. The proportion of infected persons identified through population screening did not change substantially during the screening period, which was consistent with a beneficial effect of containment efforts. (Funded by deCODE Genetics–Amgen.)

Spread of SARS-CoV-2 in the Icelandic Population

BACKGROUND: Since its identification on the 7th of January 2020, SARS-CoV-2 has spread to more than 180 countries worldwide, causing >11,000 deaths. At present, viral disease and transmission amongst children is incompletely understood. Specifically, there is concern that children could be an important source of SARS-CoV-2 in household transmission clusters. METHODS: We performed an observational study analysing literature published between December 2019 and March 2020 of the clinical features of SARS-CoV-2 in children and descriptions of household transmission clusters of SARS-CoV-2. In these studies the index case of each cluster defined as the individual in the household cluster who first developed symptoms. FINDINGS: Drawing on studies from China, Singapore, South Korea, Japan, and Iran a broad range of clinical symptoms were observed in children. These ranged from asymptomatic to severe disease. Of the 31 household transmission clusters that were identified, 9.7% (3/31) were identified as having a paediatric index case. This is in contrast other zoonotic infections (namely H5N1 influenza virus) where 54% (30/56) of transmission clusters identified children as the index case. INTERPRETATION: Whilst SARS-CoV-2 can cause mild disease in children, the data available to date suggests that children have not played a substantive role in the intra-household transmission of SARS-CoV-2.

Children are unlikely to have been the primary source of household SARS-CoV-2 infections

On 07/02/2020, French Health authorities were informed of a confirmed case of SARS-CoV-2 coronavirus in an Englishman infected in Singapore who had recently stayed in a chalet in the French Alps. We conducted an investigation to identify secondary cases and interrupt transmission.MethodsWe defined as a confirmed case a person linked to the chalet with a positive RT-PCR sample for SARS-CoV-2.ResultsThe index case stayed 4 days in the chalet with 10 English tourists and a family of 5 French residents; SARS-CoV-2 was detected in 5 individuals in France, 6 in England (including the index case), and 1 in Spain (overall attack rate in the chalet: 75%). One pediatric case, with picornavirus and influenza A coinfection, visited 3 different schools while symptomatic. One case was asymptomatic, with similar viral load as that of a symptomatic case. Seven days after the first cases were diagnosed, one tertiary case was detected in a symptomatic patient with a positive endotracheal aspirate; all previous and concurrent nasopharyngeal specimens were negative. Additionally, 172 contacts were monitored, including 73 tested negative for SARS-CoV-2.ConclusionsThe occurrence in this cluster of one asymptomatic case with similar viral load as a symptomatic patient, suggests transmission potential of asymptomatic individuals. The fact that an infected child did not transmit the disease despite close interactions within schools suggests potential different transmission dynamics in children. Finally, the dissociation between upper and lower respiratory tract results underscores the need for close monitoring of the clinical evolution of suspect Covid-19 cases.

Cluster of coronavirus disease 2019 (Covid-19) in the French Alps, 2020

Coronavirus disease 2019 (COVID-19) is a disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), first detected in China in December, 2019. In January, 2020, state, local, and federal public health agencies investigated the first case of COVID-19 in Illinois, USA.MethodsPatients with confirmed COVID-19 were defined as those with a positive SARS-CoV-2 test. Contacts were people with exposure to a patient with COVID-19 on or after the patient's symptom onset date. Contacts underwent active symptom monitoring for 14 days following their last exposure. Contacts who developed fever, cough, or shortness of breath became persons under investigation and were tested for SARS-CoV-2. A convenience sample of 32 asymptomatic health-care personnel contacts were also tested.FindingsPatient 1—a woman in her 60s—returned from China in mid-January, 2020. One week later, she was hospitalised with pneumonia and tested positive for SARS-CoV-2. Her husband (Patient 2) did not travel but had frequent close contact with his wife. He was admitted 8 days later and tested positive for SARS-CoV-2. Overall, 372 contacts of both cases were identified; 347 underwent active symptom monitoring, including 152 community contacts and 195 health-care personnel. Of monitored contacts, 43 became persons under investigation, in addition to Patient 2. These 43 persons under investigation and all 32 asymptomatic health-care personnel tested negative for SARS-CoV-2.InterpretationPerson-to-person transmission of SARS-CoV-2 occurred between two people with prolonged, unprotected exposure while Patient 1 was symptomatic. Despite active symptom monitoring and testing of symptomatic and some asymptomatic contacts, no further transmission was detected.

First known person-to-person transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the USA

Since December 2019, SARS-CoV-2 virus has extended to most parts of China with more than 80 thousand cases and to at least 100 countries with more than 60 thousand international cases by March 15, 2020. Here we applied household cohort study to determine the features of household transmission of COVID-19.MethodsTotal 105 index patients and 392 household contacts were enrolled. Both index patients and household members were inspected by SARS-CoV-2 RT-PCR. The information of all recruited people was extracted from medical records and confirmed or supplemented by telephone interviews. The baseline characteristics of index cases and contact patients were described. Secondary attack rates of SARS-CoV-2 to the contact members were computed and the risk factors for transmission within household were estimated.ResultsSecondary transmission of SARS-CoV-2 developed in 64 of 392 household contacts (16.3%). The secondary attack rate to children was 4% comparing with 17.1% to adults. The secondary attack rate to the contacts within the households with index patients quarantined by themselves since onset of symptoms was 0% comparing with 16.9% to the contacts without index patients quarantined. The secondary attack rate to contacts who were spouses of index cases was 27.8% comparing with 17.3% to other adult members in the households.ConclusionThe secondary attack rate of SARS-CoV-2 in household is 16.3%. Ages of household contacts and spouse relationship with index case are risk factors for transmission of SARS-CoV-2 within household. Quarantine of index patients at home since onset of symptom is useful to prevent the transmission of SARS-Co-2 within household.

The characteristics of household transmission of COVID-19

Background: As of April 2, 2020, the global reported number of COVID-19 cases has crossed over 1 million with more than 55,000 deaths. The household transmissibility of SARS-CoV-2, the causative pathogen, remains elusive. Methods: Based on a comprehensive contact-tracing dataset from Guangzhou, we estimated both the population-level effective reproductive number and individual-level secondary attack rate (SAR) in the household setting. We assessed age effects on transmissibility and the infectivity of COVID-19 cases during their incubation period. Results: A total of 195 unrelated clusters with 212 primary cases, 137 nonprimary (secondary or tertiary) cases and 1938 uninfected close contacts were traced. We estimated the household SAR to be 13.8% (95% CI: 11.1-17.0%) if household contacts are defined as all close relatives and 19.3% (95% CI: 15.5-23.9%) if household contacts only include those at the same residential address as the cases, assuming a mean incubation period of 4 days and a maximum infectious period of 13 days. The odds of infection among children (<20 years old) was only 0.26 (95% CI: 0.13-0.54) times of that among the elderly (≥60 years old). There was no gender difference in the risk of infection. COVID-19 cases were at least as infectious during their incubation period as during their illness. On average, a COVID-19 case infected 0.48 (95% CI: 0.39-0.58) close contacts. Had isolation not been implemented, this number increases to 0.62 (95% CI: 0.51-0.75). The effective reproductive number in Guangzhou dropped from above 1 to below 0.5 in about 1 week. Conclusion: SARS-CoV-2 is more transmissible in households than SARS-CoV and MERS-CoV, and the elderly ≥60 years old are the most vulnerable to household transmission. Case finding and isolation alone may be inadequate to contain the pandemic and need to be used in conjunction with heightened restriction of human movement as implemented in Guangzhou.

Household Secondary Attack Rate of COVID-19 and Associated Determinants

Rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Wuhan, China, prompted heightened surveillance in Shenzhen, China. The resulting data provide a rare opportunity to measure key metrics of disease course, transmission, and the impact of control measures.MethodsFrom Jan 14 to Feb 12, 2020, the Shenzhen Center for Disease Control and Prevention identified 391 SARS-CoV-2 cases and 1286 close contacts. We compared cases identified through symptomatic surveillance and contact tracing, and estimated the time from symptom onset to confirmation, isolation, and admission to hospital. We estimated metrics of disease transmission and analysed factors influencing transmission risk.FindingsCases were older than the general population (mean age 45 years) and balanced between males (n=187) and females (n=204). 356 (91%) of 391 cases had mild or moderate clinical severity at initial assessment. As of Feb 22, 2020, three cases had died and 225 had recovered (median time to recovery 21 days; 95% CI 20–22). Cases were isolated on average 4·6 days (95% CI 4·1–5·0) after developing symptoms; contact tracing reduced this by 1·9 days (95% CI 1·1–2·7). Household contacts and those travelling with a case were at higher risk of infection (odds ratio 6·27 [95% CI 1·49–26·33] for household contacts and 7·06 [1·43–34·91] for those travelling with a case) than other close contacts. The household secondary attack rate was 11·2% (95% CI 9·1–13·8), and children were as likely to be infected as adults (infection rate 7·4% in children <10 years vs population average of 6·6%). The observed reproductive number (R) was 0·4 (95% CI 0·3–0·5), with a mean serial interval of 6·3 days (95% CI 5·2–7·6).InterpretationOur data on cases as well as their infected and uninfected close contacts provide key insights into the epidemiology of SARS-CoV-2. This analysis shows that isolation and contact tracing reduce the time during which cases are infectious in the community, thereby reducing the R. The overall impact of isolation and contact tracing, however, is uncertain and highly dependent on the number of asymptomatic cases. Moreover, children are at a similar risk of infection to the general population, although less likely to have severe symptoms; hence they should be considered in analyses of transmission and control.FundingEmergency Response Program of Harbin Institute of Technology, Emergency Response Program of Peng Cheng Laboratory, US Centers for Disease Control and Prevention.

Epidemiology and transmission of COVID-19 in 391 cases and 1286 of their close contacts in Shenzhen, China: a retrospective cohort study

In December 2019, an outbreak of coronavirus disease 2019 (COVID-19), caused by the virus SARS-CoV-2, began in Wuhan, China (1). The disease spread widely in China, and, as of February 26, 2020, COVID-19 cases had been identified in 36 other countries and territories, including the United States. Person-to-person transmission has been widely documented, and a limited number of countries have reported sustained person-to-person spread.* On January 20, state and local health departments in the United States, in collaboration with teams deployed from CDC, began identifying and monitoring all persons considered to have had close contact† with patients with confirmed COVID-19 (2). The aims of these efforts were to ensure rapid evaluation and care of patients, limit further transmission, and better understand risk factors for transmission.

Active Monitoring of Persons Exposed to Patients with Confirmed COVID-19 — United States, January–February 2020

Abstract: Objective To estimate the infection rate of close contacts of COVID-19 cases, and to evaluate the risk of COVID-19 under different exposure conditions. Methods A prospective study was used to conduct continuous quarantine medical observations of close contacts of people infected with COVID-19, collect epidemiological, clinical manifestations, and laboratory test data to estimate the infection rate of close contacts under different exposures. Results The epidemiological curve of COVID-19 in Ningbo showed persistent human-to-human characteristics. A total of 2 147 close contacts were tracked and investigated. The total infection rate was 6.15%. The infection rates of confirmed cases and positive contacts were 6.30% and 4.11%, respectively. The difference was not statistically significant (P>0.05). Among close contacts of different relationships, friends/pilgrims (22.31%), family members (18.01%), and relatives (4.73%) have a higher infection rate, and close contacts of medical staff were not infected. Differences in infection rates among the close contacts were statistically significant (P < 0.005). Living with the case (13.26%), taking the same transportation (11.91%), and dining together (7.18%) are high risk factors for infection. Cross-infection in the hospital should not be ignored (1.94%). The median of incubation period is 5 days. Conclusion The infection rate of close contacts of COVID-19 cases is high, and isolation medical observation measures should be implemented in strict accordance with the close contact management plan.

The epidemiological characteristics of infection in close contacts of COVID-19 in Ningbo city

Conclusion 2: (a) we need to redesign our living/working spaces & rethink how to provide better, ventilated living/working environment for those who live in deprived & cramped areas; (b) avoid close, sustained contact indoors & in public transport, & maintain personal hygiene.

Addendum: While we have limited data, similar high risk transmission pattern could be seen in other crowded & connected indoor environments such as crowded office spaces, other workplace environment, packed restaurants/cafes, cramped apartment buildings etc.

20/ In conclusion, contact tracing data is crucial to understand real transmission dynamics. Cautionary note: This data & interpretation is based on the available evidence as of May 4th. Our understanding might change based on community testing/lifting lockdown measures. END

19/ Finally, these studies indicate that most transmission is caused by close contact with a symptomatic case, highest risk within first 5d of symptoms. To note: this preprint suggests that most infections are not asymptomatic during infection

18/ Although limited, these studies so far indicate that susceptibility to infection increases with age (highest >60y) and growing evidence suggests children are less susceptible, are infrequently responsible for household transmission, are not the main drivers of this epidemic.

17/ Increased rates of infection seen in enclosed & connected environments is in keeping with high infection rates seen in megacities, deprived areas, shelters. A recent preprint demonstrates that #COVID19 epidemic intensity is strongly shaped by crowding

16/ High infection rates seen in household, friend & family gatherings, transport suggest that closed contacts in congregation is likely the key driver of productive transmission. Casual, short interactions are not the main driver of the epidemic though keep social distancing!

15/ In summary: While the infectious inoculum required for infection is unknown, these studies indicate that close & prolonged contact is required for #COVID19 transmission. The risk is highest in enclosed environments; household, long-term care facilities and public transport.

14/ In a nursing home facility, 23d after the first resident with #COVID19, among 84 residents (76 tested), 48 were positive. This facilty had 64% prevalence of Covid-19 among residents. 50% of residents had no symptoms at the time of testing. https://nejm.org/doi/full/10.1056/NEJMoa2008457… (24/4/20)

9/ Among 31 household transmission clusters, 9.7% (3/31) were identified as having a paediatric index case (none was identified in Singapore), suggesting that children are unlikely to be driving the household transmission. https://medrxiv.org/content/10.1101/2020.03.26.20044826v1… (30/3/20) Preprint

12/ 15 confirmed/probable cases were identified after the index #COVID19 case attended a funeral (3h), shared a meal (2h), birthday party while having mild symptoms, suggesting family gatherings likely plays an important role in transmission https://tinyurl.com/yaswk4hh (17/04/20)

11/ In Singapore, 3 clusters of 28 cases were identified (2 churches, 1 family gathering). In all clusters, transmission accounted for 1 close contact w a symptomatic case, suggesting transmission largely occurs in close contact in congregation. https://thelancet.com/action/showPdf?pii=S1473-3099%2820%2930273-5… (21/4/20)

10/ In a population-based study in Iceland in which 9199 were tested, of the 564 children <10y, 38 (6.7%) tested positive, vs 1183/8635 (13.7%) adolescents and adults tested positive, suggesting lower incidence in children. #COVID19 https://nejm.org/doi/full/10.1056/NEJMoa2006100… (14/4/20)

8/ In a French chalet cluster, 11/15 contacts tested positive (all adult), 75% attack rate. One child (9y) was negative, attended 3 schools & ski class while symptomatic, among 172 (73 tested) contacts, 1 had #COVID19, while 33% had influenza! https://academic.oup.com/cid/advance-article/doi/10.1093/cid/ciaa424/5819060… (11/4/20)

7/ Among 2761 close contacts of 100 confirmed #COVID19 pts in Taiwan, 22 secondary cases were identified, household attack rate was 4.7%, rates were higher in close family, >40y, if exposed within 5d after symptom onset (0 infection after 5d) https://jamanetwork.com/journals/jamainternalmedicine/fullarticle/2765641?utm_campaign=articlePDF%26utm_medium%3darticlePDFlink%26utm_source%3darticlePDF%26utm_content%3djamainternmed.2020.2020… (1/5/20)

6/ A symptomatic index #COVID19 case, her husband who subsequently acquired infection and their 350 close contacts were followed up, 43 developed symptoms, none tested positive, suggesting close & prolonged exposure is required for transmission. https://thelancet.com/journals/lancet/article/PIIS0140-6736(20)30607-3/fulltext… (13/3/20)

5/ Among 392 household contacts of 105 index #COVID19 cases, overall household attack rate was 16%, the secondary attack rate was highest in spouse (28%), all adults (17%) and was lower in <18 age group (4%). https://academic.oup.com/cid/advance-article/doi/10.1093/cid/ciaa450/5821281… (17/4/20)

4/ Among 349 #COVID19 cases in 195 clusters, household attack rate was very high (17%), non-household attack rate 7%. Secondary attack rate was lower in <20y (5%) and highest in >60y (18%), suggesting susceptibility increases with age. https://medrxiv.org/content/10.1101/2020.04.11.20056010v1… (15/04/20) Preprint

3/ Based on 1286 close contacts of 319 #COVID19 cases; household and transport contacts had higher risk of transmission (80% of infections caused by 9% of cases), household attack rate of 11.5%, children were as likely to be infected https://thelancet.com/journals/laninf/article/PIIS1473-3099(20)30287-5/fulltext… (27/3/20)

2/ 445 close contacts of 10 #COVID19 cases were followed up, of those 54 (12%) developed symptoms, suggesting secondary attack rate of 0.45%, household attack rate of 10.5%. No other close contacts incl community members, HCWs were positive. https://cdc.gov/mmwr/volumes/69/wr/mm6909e1.htm?s_cid=mm6909e1_w… (6/3/20)

1/ 2147 close contacts of 157 #COVID19 cases were followed up: Overall infection rate was 6%, higher infection rate among friends (22%) and household (18%), and main risk factors include contact in household (13%), transport (11%), dining (7%). http://html.rhhz.net/zhlxbx/028.htm (4/3/20)

A lot of discussion recently about transmission dynamics, most of which are extrapolated from viral loads & estimates. What does contact tracing/community testing data tell us about actual probability of #COVID19 transmission(infection rate), high risk environments/age? [thread]

In thinking about how to respond to the crisis a few months back, colleagues and I entertained the idea of "Open Think Tanks" - the idea that we might create transparent digitally mediated, fora that seek to replicate with a wider community key features of the policy advice process in order to provide additional input and support to the high-stakes decisions governments all over the world must now make.

Open policy processes for COVID-19

To inform the ongoing response to the COVID-19 pandemic, specifically, to inform the development of public health guidance to prevent the spread of COVID-19, we have created a database of COVID-19 public health guidance produced by international organisations. This database is primarily for the use of relevant stakeholders in the Health Protection Surveillance Centre, the National Public Health Emergency Team, the Department of Health, and Health Service Executive.

Database of public health guidance on COVID-19

Recommended PPE for primary, outpatient, communityand social care by setting, NHS and independent sector

Contact tracing is an effective public health measure for the control of COVID-19. The prompt identification and management of the contacts of COVID-19 cases makes it possible to rapidly identify secondary cases that may arise after transmission from the primary cases. This will enable the interruption of further onward transmission. Contact tracing, in conjunction with robust testing and surveillance systems, is central to control strategies during de-escalation. Contact tracing has been a key part of the response in several Asian countries that have successfully reduced case numbers. It is possible to scale up contact tracing by adapting traditional contact tracing approaches to available local resources and by using a number of resource-saving measures. This document outlines a number of resource measures including the use of well-trained non-public-health staff and volunteers; repurposing existing resources such as call centres; reducing the intensity of contact follow-up and using new technologies such as contact management software and mobile apps.

Contact tracing for COVID-19: current evidence, options for scale-up and an assessment of resources needed

This information sheet includes: influenza vaccination will everyone entering residential aged care facilities need to be vaccinated?  what happens if staff are not able to be vaccinated due to cultural, religious or health reasons? do residential aged care providers still need to provide free influenza vaccinations to staff and volunteers? what should residential aged care workers do if they experience symptoms after getting the flu vaccine? what are aged care providers’ obligations regarding persons entering the service? how will aged care providers know whether persons seeking to enter a service on an ad hoc basis (eg tradesmen) have been vaccinated? will aged care providers need to prove that a visitor has been vaccinated and keep records? how will compliance with these requirements be assessed? will residents still have the right to refuse vaccination? who can administer an influenza vaccination?

Coronavirus (COVID-19) – Restrictions on entry into and visitors to aged care facilities