As the COVID-19 pandemic continues, mathematical epidemiologists share their views on what models reveal about how the disease has spread, the current state of play and what work still needs to be done.

Modelling COVID-19

Social distancing and other community quarantine measures have slowed the spread of COVID-19 but have also contributed to an economic shutdown with immense cost and growing pressures to return people to work. Among various strategies, one is the use of “immune passports”, which would allow individuals with serological evidence of exposure to SARS-CoV-2 to return to work. This is premised on the belief that antibodies confer sufficient immunity to prevent COVID-19 infection, and carries both ethical and scientific challenges.

Implications of test characteristics and population seroprevalence on ‘immune passport’ strategies

Our behaviour is rarely a function of causal understanding: humans create and thrive in a world too complicated to understand, writes Michael Muthukrishna

Long read: Cultural evolution, Covid-19, and preparing for what’s next

The Association for Psychological Science has made its journal research pertaining to trauma and disasters publicly available. This augments the journal articles related to epidemics, which are already freely available to the public. It is hoped that these resources will aid in the public understanding of the impact of COVID-19.

Collective Trauma and Stress Following Disasters: APS Journal Articles Publicly Available

Coronavirus

Understanding the differences and similarities between complex datasets is an interesting challenge that often arises when working with data. One way to formalize this question is to view each dataset as a graph, a mathematical model for how items relate to each other. Graphs are widely used to model relationships between objects — the Internet graph connects pages referencing each other, social graphs link together friends, and molecule graphs connect atoms bonding with each other.

Understanding the Shape of Large-Scale Data

The COVID-19 outbreak is a global pandemic with community circulation in many countries, including the United States, with confirmed cases in all states. The course of this pandemic will be shaped by how governments enact timely policies and disseminate information and by how the public reacts to policies and information. Here, we examine information-seeking responses to the first COVID-19 case public announcement in a state. Using an event study framework for all US states, we show that such news increases collective attention to the crisis right away. However, the elevated level of attention is short-lived, even though the initial announcements are followed by increasingly strong policy measures. Specifically, searches for “coronavirus” increased by about 36% (95% CI: 27 to 44%) on the day immediately after the first case announcement but decreased back to the baseline level in less than a week or two. We find that people respond to the first report of COVID-19 in their state by immediately seeking information about COVID-19, as measured by searches for coronavirus, coronavirus symptoms, and hand sanitizer. On the other hand, searches for information regarding community-level policies (e.g., quarantine, school closures, testing) or personal health strategies (e.g., masks, grocery delivery, over-the-counter medications) do not appear to be immediately triggered by first reports. These results are representative of the study period being relatively early in the epidemic, and more-elaborate policy responses were not yet part of the public discourse. Further analysis should track evolving patterns of responses to subsequent flows of public information.

Evidence from internet search data shows information-seeking responses to news of local COVID-19 cases

We all love a good “What if…” question. What if the government stops social distancing too early? What if we hadn’t closed schools? What if I moved in with my ageing parents -- would they be safer now?

What if...

Did you start a research, publication, review or data tracker at some point? If yes, what has happened to your efforts? Has some other initiative stepped in to fill the gap you saw? Or are there still unmet demands there? @SciBeh would love to hear from you!

Being African American and Rural: A Double Jeopardy from Covid‐19

The COVID‐19 Pandemic Illuminates Persistent and Emerging Disparities among Rural Black Populations

Nudge interventions – behaviorally-motivated design changes with no financial incentives– have quickly expanded from academic studies to larger implementations in so-called NudgeUnits in governments. This provides a unique opportunity to compare interventions in researchstudies, versus at scale. In this paper, we assemble a unique data set including all trials run bytwo of the largest Nudge Units in the United States, including 126 RCTs covering over 23 millionindividuals. We compare these trials to a separate sample of nudge trials published in academicjournals from two recent meta-analyses. In papers published in academic journals, the averageimpact of a nudge is very large – an 8.7 percentage point take-up increase over the control. Inthe Nudge Unit trials, the average impact is still sizable and highly statistically significant, butsmaller at 1.4 percentage points. We show that a large share of the gap is accounted for by publi-cation bias, exacerbated by low statistical power, in the sample of published papers; in contrast,the Nudge Unit studies are well-powered, a hallmark of “at scale” interventions. Accounting forpublication bias, and some differences in characteristics, reconciles the two estimates. We alsocompare these results to the predictions of academics and practitioners. Most forecasters over-estimate the impact for the Nudge Unit interventions, though nudge practitioners are almostperfectly calibrated.

RCTs to Scale: Comprehensive Evidence from Two Nudge Units

The emergence of the 2019 novel coronavirus has led to more than a pandemic—indeed, COVID-19 is spawning myriad other concerns as it rapidly marches around the globe. One of these concerns is a surge of misinformation, which we argue should be viewed as a risk in its own right, and to which insights from decades of risk communication research must be applied. Further, when the subject of misinformation is itself a risk, as in the case of COVID-19, we argue for the utility of viewing the problem as a multi-layered risk communication problem. In such circumstances, misinformation functions as a meta-risk that interacts with and complicates publics’ perceptions of the original risk. Therefore, as the COVID-19 “misinfodemic” intensifies, risk communication research should inform the efforts of key risk communicators. To this end, we discuss the implications of risk research for efforts to fact-check COVID-19 misinformation and offer practical recommendations.

Fact-checking as risk communication: the multi-layered risk of misinformation in times of COVID-19

We present a stochastic optimization model for allocating and sharing a critical resource in the case of a pandemic. The demand for different entities peaks at different times, and an initial inventory for a central agency are to be allocated. The entities (states) may share the critical resource with a different state under a risk‐averse condition. The model is applied to study the allocation of ventilator inventory in the COVID‐19 pandemic by FEMA to different U.S. states. Findings suggest that if less than 60% of the ventilator inventory is available for non‐COVID‐19 patients, FEMA's stockpile of 20 000 ventilators (as of March 23, 2020) would be nearly adequate to meet the projected needs in slightly above average demand scenarios. However, when more than 75% of the available ventilator inventory must be reserved for non‐COVID‐19 patients, various degrees of shortfall are expected. In a severe case, where the demand is concentrated in the top‐most quartile of the forecast confidence interval and states are not willing to share their stockpile of ventilators, the total shortfall over the planning horizon (until May 31, 2020) is about 232 000 ventilator days, with a peak shortfall of 17 200 ventilators on April 19, 2020. Results are also reported for a worst‐case where the demand is at the upper limit of the 95% confidence interval. An important finding of this study is that a central agency (FEMA) can act as a coordinator for sharing critical resources that are in short supply over time to add efficiency in the system. Moreover, through properly managing risk‐aversion of different entities (states) additional efficiency can be gained. An additional implication is that ramping up production early in the planning cycle allows to reduce shortfall significantly. An optimal timing of this production ramp‐up consideration can be based on a cost‐benefit analysis.

A model of supply‐chain decisions for resource sharing with an application to ventilator allocation to combat COVID‐19

Challenges for mental health services during the 2020 Covid‐19 outbreak in Germany

Mitigating mental health consequences during the COVID‐19 outbreak: Lessons from China

A pandemic of Body, Mind, and Spirit: The Burden of “Social Distancing” in Rural Communities During an Era of Heightened Suicide Risk

In response to the increased demand to screen patients with symptoms concerning for COVID‐19, we created a risk assessment triage process for our internal medicine clinic that utilizes residents’ clinical reasoning skills without direct exposure to high‐risk patients.

COVID‐19 risk triage: Engaging residents in telephonic screening

With the outbreak of COVID‐19, maintaining the healthcare system is a crucial issue. In Japan, the number of COVID‐19 cases is increasing rapidly day by day with a risk of overshooting initial estimations (WHO, 2020a). Public health nurses (PHNs) working in public health centers in prefectures and designated centers in cities or core cities, play a critical role in controlling COVID‐19 (Yoshioka‐Maeda, Honda, Iwasaki‐Motegi, 2020). Providing care for COVID‐19 patients, their families, and the community, the workload of PHNs has been reaching the maximum limit.

Preventing the dysfunction of public health centers responding to COVID‐19 by focusing on public health nurses in Japan

The Impact of Covid‐19 Pandemic on Elderly Mental Health

COVID‐19 is a new respiratory disease that has become a pandemic, involving whole world1, 2. Hospitals are now a hub for this disease and patients are advised to avoid hospitals as far as possible3, 4. Many healthcare workers are infected with SARS‐CoV‐2. This virus can spread from an infected doctor to patients or colleagues and does not respect any boundaries. Moreover, immunocompromized patients are at a greater risk of this potentially life‐threatening contagious disease. Recommendations of social distancing and home isolation to limit the spread of coronavirus are major factors limiting patients' communication with doctors regarding their disease. This has led us to think about an alternate safe form of doctor–patient communication that is not detrimental for doctors, patients or communities; and moreover, is practical and affordable for the majority of people. WhatsApp (WhatsApp Inc., Mountain View, California, USA) is an emerging mobile messaging app familiar to many people around the world. Electronic communications including calls, messages, pictures, videos and voice messages can be sent and received by individuals or groups5. Patients can consult their doctor using phone/video calls on WhatsApp, and also share photographs of infected/diseased parts of the body, which can provide a visual clue for the doctor treating their patient. Patients' test reports can also be shared via WhatsApp. Moreover, reassurance regarding benign disease can be given to any patient and a proper management plan shared. Drug treatments can be started accordingly. Even in developing countries like Pakistan, there is usually someone within a family who can use a smartphone and communicate on WhatsApp, making telemedicine effective. Patients with complicated or serious disease, or those having problems describing their symptoms or using WhatsApp can be called for a hospital visit. This approach will limit the number of patients visiting hospitals, saving time, manpower and resources for more serious cases. Moreover, it will also limit the spread of coronavirus. This strategy also allows doctors to work from home, avoiding unnecessary hospital duties. In the wake of the COVID‐19 pandemic, Surgical Unit II at Benazir Bhutto Hospital, Rawalpindi, Pakistan has devised a telemedicine protocol under the guidance of Professor Muhammad Hanif, as follows: Patients discharged from a ward or emergency department are given two WhatsApp phone numbers to contact for follow‐up. Follow‐up is via WhatsApp and they are to come to the hospital only if advised. Patients scheduled for elective surgery which has been delayed are advised to consult via WhatsApp and will be called for surgery once the situation is controlled. OPD level doctors headed by consultants will be available for online consultation on WhatsApp and given phone numbers. Patients are advised to come to hospital only in unavoidable circumstances. Telemedicine has started on an institutional basis in various hospitals in Pakistan. Our unit has started to use WhatsApp, which is approachable and affordable to many people, to keep our patients and doctors safe while ensuring the proper provision of services.

Doctor–patient communication in surgical practice during the coronavirus (COVID‐19) pandemic

The presentation of COVID‐19 overlaps with common influenza symptoms. There is limited data on whether a specific symptom or collection of symptoms may be useful to predict test positivity. Methods An anonymous electronic survey was publicized through social media to query participants with COVID‐19 testing. Respondents were questioned regarding 10 presenting symptoms, demographic information, comorbidities and COVID‐19 test results. Stepwise logistic regression was used to identify predictors for COVID positivity. Selected classifiers were assessed for prediction performance using receiver operating characteristic analysis (ROC). Results One‐hundred and forty‐five participants with positive COVID‐19 testing and 157 with negative results were included. Participants had a mean age of 39 years, and 214 (72%) were female. Smell or taste change, fever, and body ache were associated with COVID‐19 positivity, and shortness of breath and sore throat were associated with a negative test result (p<0.05). A model using all 5 diagnostic symptoms had the highest accuracy with a predictive ability of 82% in discriminating between COVID‐19 results. To maximize sensitivity and maintain fair diagnostic accuracy, a combination of 2 symptoms, change in sense of smell or taste and fever was found to have a sensitivity of 70% and overall discrimination accuracy of 75%. Conclusion Smell or taste change is a strong predictor for a COVID‐19 positive test result. Using the presence of smell or taste change with fever, this parsimonious classifier correctly predicts 75% of COVID‐19 test results. A larger cohort of respondents will be necessary to refine classifier performance.

Smell and taste symptom‐based predictive model for COVID‐19 diagnosis

In response to the coronavirus disease 2019 (COVID-19) pandemic, countries are launching economic recovery programs to mitigate unemployment and stabilize core industries. Although it is understandably difficult to contemplate other hazards in the midst of this outbreak, it is important to remember that we face another major crisis that threatens human prosperity—climate change. Leveraging COVID-19 recovery programs to simultaneously advance the climate agenda presents a strategic opportunity to transition toward a more sustainable post–COVID-19 world.

A COVID-19 recovery for climate

Experts clash over research into efficacy of public wearing even homemade face coverings

Report on face masks' effectiveness for Covid-19 divides scientists

The emergence of the novel human coronavirus SARS-CoV-2 in Wuhan, China has caused a worldwide epidemic of respiratory disease (COVID-19). Vaccines and targeted therapeutics for treatment of this disease are currently lacking. Here we report a human monoclonal antibody that neutralizes SARS-CoV-2 (and SARS-CoV) in cell culture. This cross-neutralizing antibody targets a communal epitope on these viruses and may offer potential for prevention and treatment of COVID-19

A human monoclonal antibody blocking SARS-CoV-2 infection

From the time China reported a novel coronavirus to the World Health Organization (WHO) on December 31, 2019, it took barely 4 months to become a pandemic, killing hundreds of thousands, and growing daily. It is now clear that the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) had been circulating in Wuhan, China, for weeks before China reported it to the WHO, and that authorities hid information. China maintained SARS-CoV-2 was not readily transmissible between humans. The WHO published China’s data, but without independently verifying their accuracy. President Trump subsequently blamed the WHO for its slow and “China-centric” response. On April 14, 2020, he announced a suspension of US voluntary contributions to the agency. Although the WHO was unable to verify the Chinese data, it was proactive, including widely sharing the genomic sequencing of the virus with international scientists. On January 30, 2020, the WHO declared coronavirus disease 2019 (COVID-19) a global health emergency, urging rigorous containment including testing, contract tracing, and quarantine. Broad criticism of the organization is unfounded, and is particularly damaging because the pandemic is poised to deeply affect sub-Saharan Africa. That said, legitimate concerns about the WHO include its reluctance to insist China allow a robust WHO team on the ground and its praising of China’s transparency. The crisis now unfolding could also become a historic opportunity to strengthen the WHO. Reforms must start with recognizing the global public good achieved by the WHO.

COVID-19 Reveals Urgent Need to Strengthen the World Health Organization

As the world grapples with accelerating cases of coronavirus disease 2019 (COVID-19), experts have called for a surge in hospital capacity to provide acute care for individuals with pneumonia and other serious complications.1 Despite efforts at mitigation, including social distancing and rapid testing and isolation of cases, hospitals in many places, including New York City, are overwhelmed with patients. Current estimates project that the US will have at least 60 000 deaths and 10 times that number requiring hospitalization. Hospitals are facing significant supply challenges of beds, staff, and equipment, including personal protective equipment. Overcrowding may be associated with higher rates of complications due to delays in care and overworked teams, increased danger of developing COVID-19 for health care workers and other patients, and emotional distress for families. Current policy solutions aim to eliminate barriers for hospitals to hire additional staff or to repurpose or expand bed capacity. One idea that has not been widely explored is hospital-at-home programs. The concept of a hospital stay in the home has been tested and proven to be effective in a wide variety of settings and clinical conditions.2 We propose expanding access to hospital-at-home programs as part of the COVID-19 response.

Hospital-at-Home to Support COVID-19 Surge—Time to Bring Down the Walls?

Taiwan is a country of about 24 million people, 81 miles off the coast of mainland China. As of late April 2020, Taiwan had about 330 confirmed cases of coronavirus disease 2019 (COVID-19) and 6 deaths. By comparison, the US had about 1 million confirmed cases of COVID-19, and 60 000 deaths. In this issue of JAMA Internal Medicine, there is a remarkable report from Taiwan on the use of contact tracing and virologic polymerase chain reaction testing to assess the transmission dynamics of COVID-19 in the country’s initial 100 confirmed cases.1 Among 2761 close contacts of the 100 cases, confirmed between January 15 and March 18, 2020, Cheng et al report that there were 22 paired-index secondary cases and an overall secondary clinical attack rate of 0.7% (95% CI, 0.4%-1.0%).1 The study has important messages for the control of COVID-19 throughout the world. First, people with COVID-19 were found to be most infectious to others before and within 5 days of symptom onset. Within 5 days of symptom onset, the attack rate was 1.0% (95% CI, 0.6%-1.5%). With exclusive presymptomatic exposures, the attack rate was 0.7% (95% CI, 0.2%-2.4%), and with exposures 6 days or more after symptom onset, there were 0 cases from 852 contacts (95% CI, 0%-0.4%).1 These findings underscore the pressing public health need for accurate and comprehensive contact tracing and testing. Testing only those people who are symptomatic will miss many infections and render contact tracing less effective. The finding that asymptomatic people and those with minimal or fewer symptoms early in infection are those most likely to transmit COVID-19 strongly argues for maintaining social distancing and having people wear face masks to reduce the potential for transmission. Solely isolating patients symptomatic with COVID-19 will fail to control transmission during the infected but asymptomatic stage. Second, the study underscores the many things that Taiwan has done right in proactively and rapidly responding to COVID-19.2 It is impressive, even astounding, that Taiwan not only conducted robust contact tracing and testing on the first 100 confirmed cases, but also quickly and comprehensively reported the results, thus meaningfully advancing knowledge of the transmission dynamics of the virus.1 Unfortunately, widespread testing was not available in the US in February 2020, hampering the ability to identify people who were COVID-19 positive. A first step for the US and other nations in “reopening” society is to have sufficient testing and contact tracing such that the outbreaks that will inevitably occur as social restrictions are removed can be successfully contained. Beyond this, even when “reopening,” social distancing throughout society and the wearing of face masks should be maintained to the maximum extent possible until there is a vaccine or effective treatment.

Contact Tracing, Testing, and Control of COVID-19—Learning From Taiwan

Key PointsQuestion  What is the transmissibility of coronavirus disease 2019 (COVID-19) to close contacts?Findings  In this case-ascertained study of 100 cases of confirmed COVID-19 and 2761 close contacts, the overall secondary clinical attack rate was 0.7%. The attack rate was higher among contacts whose exposure to the index case started within 5 days of symptom onset than those who were exposed later.Meaning  High transmissibility of COVID-19 before and immediately after symptom onset suggests that finding and isolating symptomatic patients alone may not suffice to interrupt transmission, and that more generalized measures might be required, such as social distancing. Abstract Importance  The dynamics of coronavirus disease 2019 (COVID-19) transmissibility are yet to be fully understood. Better understanding of the transmission dynamics is important for the development and evaluation of effective control policies.Objective  To delineate the transmission dynamics of COVID-19 and evaluate the transmission risk at different exposure window periods before and after symptom onset.Design, Setting, and Participants  This prospective case-ascertained study in Taiwan included laboratory-confirmed cases of COVID-19 and their contacts. The study period was from January 15 to March 18, 2020. All close contacts were quarantined at home for 14 days after their last exposure to the index case. During the quarantine period, any relevant symptoms (fever, cough, or other respiratory symptoms) of contacts triggered a COVID-19 test. The final follow-up date was April 2, 2020.Main Outcomes and Measures  Secondary clinical attack rate (considering symptomatic cases only) for different exposure time windows of the index cases and for different exposure settings (such as household, family, and health care).Results  We enrolled 100 confirmed patients, with a median age of 44 years (range, 11-88 years), including 56 men and 44 women. Among their 2761 close contacts, there were 22 paired index-secondary cases. The overall secondary clinical attack rate was 0.7% (95% CI, 0.4%-1.0%). The attack rate was higher among the 1818 contacts whose exposure to index cases started within 5 days of symptom onset (1.0% [95% CI, 0.6%-1.6%]) compared with those who were exposed later (0 cases from 852 contacts; 95% CI, 0%-0.4%). The 299 contacts with exclusive presymptomatic exposures were also at risk (attack rate, 0.7% [95% CI, 0.2%-2.4%]). The attack rate was higher among household (4.6% [95% CI, 2.3%-9.3%]) and nonhousehold (5.3% [95% CI, 2.1%-12.8%]) family contacts than that in health care or other settings. The attack rates were higher among those aged 40 to 59 years (1.1% [95% CI, 0.6%-2.1%]) and those aged 60 years and older (0.9% [95% CI, 0.3%-2.6%]).Conclusions and Relevance  In this study, high transmissibility of COVID-19 before and immediately after symptom onset suggests that finding and isolating symptomatic patients alone may not suffice to contain the epidemic, and more generalized measures may be required, such as social distancing.

Contact Tracing Assessment of COVID-19 Transmission Dynamics in Taiwan and Risk at Different Exposure Periods Before and After Symptom Onset

Coronavirus disease 2019 (COVID-19) is a respiratory infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), first detected in early December 2019 in Wuhan, China. It has since spread throughout the world. One measure of viral spread is the R0, the expected number of secondary infectious cases produced by a primary infectious case. This calculation is used to determine the potential for epidemic spread in a susceptible population. The effective reproduction number, Rt, determines the potential for epidemic spread at a specific time t under the control measures in place (Figure 1). To evaluate the effectiveness of public health interventions, the Rt should be quantified in different settings, ideally at regular and frequent intervals (eg, weekly).

Public Health Measures and the Reproduction Number of SARS-CoV-2

The United States will eventually get through the acute coronavirus disease 2019 (COVID-19) crisis but not without fundamental changes to the medical care system. Since the epidemic began, payment policy has stretched to remedy the bias of the health care system for in-person treatment provided by physicians. In response to the need for social distancing, new policies include broader payment for telemedicine, expanded scope-of-practice ability for nonphysician practitioners, and increased ability of physicians and nurses to practice across state lines. While these policy reforms address some of the immediate needs of this crisis, such as getting personnel to where they are most needed, they are not a complete solution to the COVID-19 crisis. How the aftermath of the current COVID-19 wave is handled will be just as important for the business of health care as what is happening now. Two issues about the medical system after the current wave are particularly important: What type of organizations will be available to treat patients a few months from now? And how will those patients be most effectively served?

The Business of Medicine in the Era of COVID-19

Public health and medical experts have clamored for increased coronavirus testing to control the coronavirus 2019 (COVID-19) pandemic,1 but how to implement such testing has not been carefully described. We detail a plan for aggressive community screening with the goal of controlling, if not eradicating, local severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission. For at least 2 months, access to reagents, swabs, and tests have been a bottleneck. We believe this bottleneck is abating, as evidenced by recent dramatic increases in testing. The limiting factor, then, is a matter of operations and logistics. In the absence of an effective vaccine, separating persons who are unknowingly infected from individuals with susceptibility is the best way to block transmission. Ongoing community transmission demands an aggressive approach to achieve this goal

Logistics of Aggressive Community Screening for Coronavirus 2019

Metacognition_ClimateChange

One of the oldest debates in psychological research into politicized science such as nanotechnology, vaccination, or climate change centers around the role of knowledge: Does increased knowledge of the science affect beliefs about it? While research has traditionally focused on the role of object-level knowledge, here we highlight the importance of meta-knowledge, or confidence in knowledge. Specifically, we demonstrate the importance of meta-knowledge for explaining beliefs about science with one of the most contested examples: climate change. Across two national samples from Germany (total N = 1,097), frequentist and Bayesian analyses demonstrated that climate change meta-knowledge was predictive of climate change beliefs, above and beyond object-level climate change knowledge. These results held for both the belief that climate change is risky, and the belief that climate change is anthropogenic, and when controlling for political attitude, and demographic variables. Furthermore, confidence in other-domain (biological and physical) science knowledge explained climate change beliefs considerably less compared to domain-specific knowledge, suggesting that outside the domain for which it was relevant, confidence in science knowledge was largely irrelevant for shaping beliefs. These results highlight the relevance of domain-specific metacognition for explaining beliefs about the contested science of climate change. By demonstrating the relevance of metacognitive, rather than solely object-level thought, these results add to our understanding of the cognitive mechanisms involved in the formation of beliefs about politicized science. Keywords: Politicized science, climate change, metacognition.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has only 15 genes, compared with 30 000 in the human genome. But it is a stern teacher, indeed. Answers to the questions it has raised may reshape both health care and society as a whole. No one can say with certainty what the consequences of this pandemic will be in 6 months, let alone 6 years or 60. Some “new normal” may emerge, in which novel systems and assumptions will replace many others long taken for granted. But at this early stage, it is more honest to frame the new, post–COVID-19 normal not as predictions, but as a series of choices. Specifically, the pandemic nominates at least 6 properties of care for durable change: tempo, standards, working conditions, proximity, preparedness, and equity.

Choices for the “New Normal”

The rapid growth in the number of patients with coronavirus disease 2019 (COVID-19) threatened to overwhelm hospital and intensive care unit capacity.1 The pandemic also raises questions about the ability of hospitals to remain financially solvent amid unprecedented changes in care delivery and billable services. To limit the spread of disease and create additional inpatient capacity and staffing, many hospitals are closing outpatient departments and postponing or canceling elective visits and procedures. These changes, while needed to respond to the COVID-19 pandemic, potentially threaten the financial viability of hospitals, especially those with preexisting financial challenges and those heavily reliant on revenue from outpatient and elective services.

COVID-19 and the Financial Health of US Hospitals

ow long will this pandemic last? When will we find a treatment or vaccine? Which drug should we give our patients? Will we run out of personal protective equipment (PPE)? When will everyone return to work? We find ourselves in a time of great economic, social, and medical uncertainty. Faced with a crisis, Lee Iacocca, the late automobile company executive, once said, “So what do we do? Anything. Something… . If we screw it up, start over. Try something else. If we wait until we’ve satisfied all the uncertainties, it may be too late.” Similarly, in the heat of the Great Depression, Franklin Roosevelt commented, “Take a method and try it. If it fails, admit it frankly and try another. But by all means, try something.” Though a trial-and-error approach may be appropriate in business and politics, should it be applied to medical decision making during a pandemic?

Covid-19 — A Reminder to Reason

Responses to Press Ganey patient experience surveys show increasing numbers of comments related to Covid-19. Patients express concerns through primarily negative comments regarding cleanliness and logistics regarding tests and treatments. The artificial intelligence–supported analysis of unstructured text reveals that despite the persistent negative trend in the patients’ experiences of receiving tests and treatments, patients are commenting increasingly positively about their interactions with clinicians as the Covid-19 pandemic continues.

Using AI to Understand the Patient Voice During the Covid-19 Pandemic

Covid-19 spreads throughout the United States, schools and child care facilities are balancing their role of helping to prevent disease transmission with ensuring access to food for children who rely on the federal nutrition safety net. Together, the U.S. Department of Agriculture (USDA) National School Lunch Program, School Breakfast Program, and Child and Adult Care Food Program serve nearly 35 million children daily, delivering vital nutrition and financial assistance to families in need.1 With such programs interrupted, an essential element of the Covid-19 response will be feeding children from low-income families.

Feeding Low-Income Children during the Covid-19 Pandemic

Traditional approaches to respiratory virus surveillance may not identify novel pathogens in time to implement crucial public health interventions.1 The Seattle Flu Study is a multi-institutional, community-wide pandemic surveillance platform that was established in November 2018.2 Persons reporting symptoms of respiratory illness provided informed consent for testing to identify influenza and other respiratory pathogens (see the Supplementary Appendix, available with the full text of this letter at NEJM.org). In one study group, persons enrolled online and were sent kits, by rapid-delivery services, for home collection of a midnasal swab; samples were returned by mail. After identification of the first case of Covid-19 in Washington State, the samples that were collected were also tested for SARS-CoV-2. After March 4, 2020, a human subjects institutional review board determined that results could be reported to public health authorities and to participants, who were notified under a public health surveillance exemption.

Early Detection of Covid-19 through a Citywide Pandemic Surveillance Platform

Having a baby or young child can be difficult at the best of times, but with parents now in lockdown it is a particularly challenging time. Educational psychologist Dr Abigail Wright, from the British Psychological Society, says the key thing for a child's development is their parents.Dr Wright, who is also the mother of a four-month-old baby and three-year-old, offers her advice and we hear from two parents who share their experiences of caring for their babies in isolation.

Coronavirus lockdown: How does it affect babies?

Exploring complex social contagion, especially the social reinforcement dynamics when exposing to multiple sources, is of vital importance for understanding the spread of complicated collective behaviors nowadays. While previous works exclusively focus on single-layer networks, the detailed impacts of multilayer reinforcement which characterizes the promoting effects among multiple social circles remain largely unknown. To this end, we incorporate multilayer reinforcement into ignorant-spreader-ignorant (SIS) model on multiplex networks. Our theoretical analysis combines pairwise method and mean-field theory and agrees well with large-scale simulations. Surprisingly, we find this complex social contagion mechanism triggers the emergence of bistability phenomena, where extinction and outbreak states coexist. Further, we show that the final state of bistable regions depends on the initial density of adopters, the critical value of which decreases as the contagion transmissibility or the multilayer reinforcement increases. In particular, we highlight two possible conditions for the outbreak of social contagion: to possess large contagion transmissibility, or to possess large initial density of adopters with strong multilayer reinforcement. Our results show the powerful and non-negligible impacts of complex dynamical mechanisms, which provides valuable insights toward the spreading behaviors in the digital age.

Complex social contagion induces bistability on multiplex networks

2005.00906

We analyze the curriculum of the early common-years of engineering in our institute using tools of statistical physics of complex networks. Naturally, a course programme is structured in a networked form (temporal dependency and prerequisites). In this approach, each topic within each programme is associated with a node, which in turn is joined by links representing the dependence of a topic for the understanding of another in a different discipline. As a course programme is a time-dependent structure, we propose a simple model to assign links between nodes, taking into account only two ingredients of the teaching-learning process: recursiveness and accumulation of knowledge. Since we already know the programmes, our objective is to verify if the proposed model is able to capture their particularities and to identify implications of different sequencing on the student learning in the early years of engineering degrees. Our model can be used as a systematic tool assisting the construction of a more interdisciplinary curriculum, articulating between disciplines of the undergraduate early-years in exact sciences.

Analyzing course programmes using complex networks

The COVID-19 pandemic may be one of the greatest modern societal challenges that requires widespread collective action and cooperation. While a handful of actions can help reduce pathogen transmission, the most critical behavior is to self-isolate. But what types of public health messages can aid compliance with such extreme social distancing measures? Public health messages designed to facilitate compliance have often used emotional language, ranging from negative fear appeals (e.g., millions of people will die) to positive prosocial appeals (e.g., everyone’s actions help society). Understanding how these types of messages tap into the different dimensions of emotion—a mechanism documented in other domains to be an essential component of behavior change—is critical for creating successful public health campaigns related to COVID-19. In a U.S. representative sample (N = 955), we presented two messages that leveraged either fear or prosocial language, and asked participants to report their emotional reactions and their willingness to self-isolate. While results show that both types of interventions increased willingness to self-isolate (Cohen’s d = .41), compared to the fear message, the success of the prosocial message was more dependent on the magnitude of emotional response on both the arousal and valence dimensions. Our results suggest that prosocial interventions have the potential to be associated with greater compliance if they evoke highly positive emotional responses.

Emotional responses to prosocial messages increase willingness to self-isolate during the COVID-19 pandemic

Objectives The COVID-19 pandemic is one of the greatest global health threats facing humanity in recent memory. This study aimed to explore influences on hygienic practices, a set of key transmission behaviours, in relation to the Capability, Opportunity, Motivation-Behaviour (COM-B) model of behaviour change (Michie et al., 2011). Design Data from the first wave of a longitudinal survey study was used, launched in the early stages of the UK COVID-19 pandemic. Methods Participants were 2025 adults aged 18 and older, representative of the UK population, recruited by a survey company from a panel of research participants. Participants self-reported motivation, capability and opportunity to enact hygienic practices during the COVID-19 outbreak. Results Using regression models, we found that all three COM-B components significantly predicted good hygienic practices, with motivation having the greatest influence on behaviour. Breaking this down further, the sub-scales psychological capability, social opportunity and reflective motivation positively influenced behaviour. Reflective motivation was largely driving behaviour, with those highest in reflective motivation scoring 51% more on the measure of hygienic practices compared with those with the lowest scores. Conclusions Our findings have clear implications for the design of behaviour change interventions to promote hygienic practices. Interventions should focus on increasing and maintaining motivation to act and include elements that promote and maintain social support and knowledge of COVID-19 transmission. Groups in particular need of targeting for interventions to increase hygienic practices are males and those living in cities and suburbs.

Capability, opportunity and motivation to enact hygienic practices in the early stages of the COVID-19 outbreak in the UK

Drawing on a scientific national survey (N = 3,933; including 3,188 registered voters), this report describes Americans’ coronavirus knowledge, attitudes, vulnerabilities, protective behaviors, and communication needs in an effort to inform the public health community, policymakers, and the public.

American Public Responses to COVID-19, April 2020

Background The COVID-19 pandemic has created an unprecedented global crisis necessitating drastic changes to living conditions, social life, personal freedom and economic activity. No study has yet examined the presence of psychiatric symptoms in the UK population in similar conditions. Aims We investigated the prevalence of COVID-19 related anxiety, generalised anxiety, depression and trauma symptoms in a representative sample of the UK population during an early phase of the pandemic, and estimated associations with variables likely to influence these symptoms. Method Between March 23rd and March 28th 2020, a quota sample of 2025 UK adults 18 years and older, stratified by age, sex and household income, was recruited by online survey company Qualtrics. Participants completed measures of depression (PHQ9), generalised anxiety (GAD7), and trauma symptoms relating to the pandemic (ITQ). Bivariate and multivariate associations were calculated for age, gender, rural vs urban environment, presence of children in the household, income, loss of income, pre-existing health conditions in self and someone close, infection in self and someone close, and perceived risk of infection over the next month. Results Higher levels of anxiety, depression and trauma symptoms were reported compared to previous population studies, but not dramatically so. Meeting the criteria for either anxiety or depression, and trauma symptoms was predicted by young age, presence of children in the home, and high estimates of personal risk. Anxiety and depression symptoms were also predicted by low income, loss of income, and pre-existing health conditions in self and other. Specific anxiety about COVID-19 was greater in older participants. Conclusions The UK population, especially older citizens, were largely resilient in the early stages of the pandemic. However, several specific COVID-related variables are associated with psychological distress: particularly having children at home, loss of income because of the pandemic, as well as having a pre-existing health condition, exposure to the virus and high estimates of personal risk. Further similar surveys, particularly of those with children at home, are required as the pandemic progresses.

Anxiety, Depression, Traumatic Stress, and COVID-19 Related Anxiety in the UK General Population During the COVID-19 Pandemic.

On April 3 2020, the U.S. Centers for Disease Control and Prevention (CDC) recommended that all Americans wear face masks to prevent the spread of COVID-19. The announcement came during the fielding of a large, nationally-representative survey (N = 3,933) of Americans’ COVID-19-related knowledge, attitudes, and behaviors, providing an opportunity to measure the impact of the CDC’s recommendation on public reported mask wearing and buying behavior. The study found significant increases in reported mask wearing (+12 percentage points) and mask buying (+8 points). These findings indicate the speed with which government recommendations can affect the adoption of protective behaviors by the public. The results demonstrate the importance of national leadership and communication during a public health crisis.

Mask-wearing increases after a government recommendation: A natural experiment in the U.S. during the COVID-19 pandemic

Beyond public health and economic costs, the COVID-19 pandemic adds strain, disrupts daily routines, and complicates mental health and medical service delivery for those with mental health and medical conditions. Bipolar disorder can increase vulnerability to infection; it can also enhance stress, complicate treatment, and heighten interpersonal stigma. Yet there are successes when people proactively improve social connections, prioritize self-care, and learn to use mobile and telehealth effectively.

Working with Bipolar Disorder During the COVID-19 Pandemic: Both Crisis and Opportunity

Experts estimate that there could be millions of cases of COVID-19 in the US, leading to potentially 100,000 or more deaths. Beliefs about the severity of the spread of COVID-19 and one's own likelihood of being infected have implications for individual behavior and consequently for the spread of the virus. The current research explores key factors that enter into these beliefs. Using nationally representative surveys with more than 3,800 participants, we find that key factors epidemiological models typically use in their predictions (e.g., concentration of cases in a given area) do not meaningfully enter into individuals' beliefs. We draw on the reality that we currently face not only a health crisis, but a financial crisis as well to identify financial fragility as a key factor influencing beliefs.

A Tale of Two Crises: Financial Fragility and Beliefs about the Spread of COVID-19

Background: The COVID-19 pandemic in the Republic of Ireland precipitated the temporary closure of all non-essential services and a nationwide quarantine as of March 27th, 2020. This study represents the first assessment of the mental health of the nation during the initial phase of the COVID-19 response, as part of a multi-wave investigation into the social, behavioural, and psychological impact of the pandemic. Aims: First, estimate prevalence rates of depression, generalized anxiety disorder, and combined anxiety and depression, and identify risk factors associated with screening positive for anxiety/depression. Second, determine if COVID-19-related anxiety was highest amongst those identified with the greatest mortality risk from the virus. Method: Self-report data from a nationally representative Irish sample (N = 1,041) was collected online between March 31 and April 5; the first week of the Republic of Ireland’s nationwide quarantine measures. Results: A substantial proportion of people screened positive for depression (22.77%), generalized anxiety (20.00%), and anxiety/depression (27.67%). Screening positive for anxiety/depression was associated with younger age, female sex, loss of income due to COVID-19, COVID-19 infection, and higher perceived risk of COVID-19 infection. Citizens aged 65 and older reported significantly higher levels of COVID-19 anxiety than adults aged 18-34. Sex, underlying health conditions, and proximity to COVID-19 deaths were not associated with COVID-19 anxiety. Conclusions: Government responses to the current pandemic should ensure that measures protect not only the population’s physical health, but its mental health also, as an equally important component of health and wellbeing.

Anxiety and depression in the Republic of Ireland during the COVID-19 pandemic

The COVID-19 pandemic substantially changed daily life in ways that may impact mental health. This study compared a nationally representative online sample of 2,032 U.S. adults in late April 2020 to 19,330 U.S. adult internet users who participated in the 2018 National Health Interview Survey (NHIS) using the Kessler-6 scale of mental distress in the last 30 days. Compared to the 2018 NHIS sample, U.S. adults in April 2020 were eight times more likely to fit criteria for serious mental illness (27.7% vs. 3.4%) and three times more likely to fit criteria for moderate or serious mental illness (70.4% vs. 22.0%). Differences between the 2018 and 2020 samples appeared across all demographic groups, with larger differences among younger adults and those with children in the household. These considerable levels of mental distress may portend substantial increases in diagnosed mental disorders and in the morbidity and mortality associated with them.

Mental distress among U.S. adults during the COVID-19 pandemic