Health care organizations have been challenged by the coronavirus disease 2019 (COVID-19) pandemic for some time, while in January 2020, it was not immediately suspected that it would take such a global expansion. In the past, other studies have already pointed out that health care systems, and more specifically hospitals, can be a so-called “soft target” for terrorist attacks. This report has now examined whether this is also the case in the context of the COVID-19 pandemic.

During the lockdown, hospitals turned out to be the only remaining soft targets for attacks, given that the other classic targets were closed during the lockdown. On the other hand, other important factors have limited the risk of such attacks in hospitals. The main delaying and relative risk-reducing factors were the access control on temperature and wearing a mask, no visits allowed, limited consultations, and investigations.

But even then, health care systems and hospitals were prone to (cyber)terrorism, as shown by other COVID-19-related institutions, such as pharmaceuticals involved in developing vaccines and health care facilities involved in swab testing and contact tracing. Counter-terrorism medicine (CTM) and social behavioral science can reduce the likelihood and impact of terrorism, but cannot prevent (state-driven) cyberterrorism and actions of lone wolves and extremist factions.

A fever clinic within a hospital plays a vital role in pandemic control because it serves as an outpost for pandemic discovery, monitoring and handling. As the outbreak of coronavirus disease 2019 (COVID-19) in Wuhan was gradually brought under control, the fever clinic in the West Campus of Wuhan Union Hospital introduced a new model for construction and management of temporary mobile isolation wards. A traditional battlefield hospital model was combined with pandemic control regulations, to build a complex of mobile isolation wards that used adaptive design and construction for medical operational, medical waste management and water drainage systems. The mobile isolation wards allowed for the sharing of medical resources with the fever clinic. This increased the capacity and efficiency of receiving, screening, triaging and isolation and observation of patients with fever. The innovative mobile isolation wards also controlled new sudden outbreaks of COVID-19. We document the adaptive design and construction model of the novel complex of mobile isolation wards and explain its characteristics, functions and use.

As most children infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) present with mild symptoms or they are asymptomatic, the optimal strategy for molecular testing it is not well defined. The aim of the study was to determine the extent and aetiology of molecular testing for SARS-CoV-2 in Greek paediatric departments during the first phase of the pandemic and identify possible differences in incidence, depending on the age group and geographical area. We conducted a nationwide study of molecular testing for SARS-CoV-2 of children in paediatric departments between March and June 2020. A total of 65 paediatric departments participated in the study, representing 4901 children who were tested for SARS-CoV-2 and 90 (1.8%) were positive. Most paediatric cases were associated with topical outbreaks. Adolescents 11–16 years had the highest positivity rate (3.6%) followed by children 6–10 years (1.9%). However, since the testing rate significantly differed between age groups, the modified incidence of SARS-CoV-2 infection per age group was highest in infants <1 year (19.25/105 population). Most children tested presented with fever (70.9%), respiratory (50.1%) or gastrointestinal symptoms (28.1%). Significant differences were detected between public and private hospitals regarding the positivity rate (2.34% vs. 0.39%, P-value <0.001). Significant variation in SARS-CoV-2 molecular testing positivity rate and incidence between age groups indicate discrepancies in risk factors among different age groups that shall be considered when ordering molecular testing.

Healthcare workers (HCWs) not fulfilling the coronavirus disease 2019 (COVID-19) case definition underwent severe acute respiratory coronavirus virus 2 (SARS-CoV-2) screening. Risk of exposure, adherence to personal protective equipment (PPE), and symptoms were assessed. In total, 2,000 HCWs were screened: 5.5% were positive for SARS-CoV-2 by polymerase chain reaction (PCR). There were no differences in PPE use between SARS-CoV-2–positive and –negative HCWs (adherence, >90%). Nursing and kitchen staff were independently associated with positive SARS-CoV-2 results.

Previous studies have reported the basic reproduction number (R0) of coronavirus disease from publicly reported data that lack information such as onset of symptoms, presence of importations or known super-spreading events. Using data from the Republic of Korea, we illustrated how estimates of R0 can be biased and provided improved estimates with more detailed data. We used COVID-19 contact trace system in Korea, which can provide symptom onset date and also serial intervals between contacted people. The total R0 was estimated as 2.10 (95% confidence interval (CI) 1.84–2.42). Also, early transmission of COVID-19 differed by regional or social behaviours of the population. Regions affected by a specific church cluster, which showed a rapid and silent transmission under non-official religious meetings, had a higher R0 of 2.40 (95% CI 2.08–2.77).

COVID-19, although a respiratory illness, has been clinically associated with non-respiratory symptoms. We conducted a negative case–control study to identify the symptoms associated with SARS-CoV-2-positive results in Portugal. Twelve symptoms and signs included in the clinical notification of COVID-19 were selected as predictors, and the dependent variable was the RT-PCR test result. The χ2 tests were used to compare notified cases on sex, age group, health region and presence of comorbidities. The best-fit prediction model was selected using a backward stepwise method with an unconditional logistic regression. General and gastrointestinal symptoms were strongly associated with a positive test (P < 0.001). In this sense, the inclusion of general symptoms such as myalgia, headache and fatigue, as well as diarrhoea, together with actual clinical criteria for suspected cases, already updated and included in COVID-19 case definition, can lead to increased identification of cases and represent an effective strength for transmission control.

The 2020 COVID-19 pandemic has had a profound impact on the clinical research enterprises at the 60 Clinical and Translational Science Award (CTSA) Hubs throughout the nation. There was simultaneously a need to expand research to obtain crucial data about disease prognosis and therapy and enormous limitations on conducting research as localities and institutions limited travel and person-to-person contact. These imperatives resulted in major changes in the way research was conducted, including expediting Institutional Review Board review, shifting to remote interactions with participants, centralizing decision-making in prioritizing research protocols, establishing biobanks, adopting novel informatics platforms, and distributing study drugs in unconventional ways. National CTSA Steering Committee meetings provided an opportunity to share best practices and develop the idea of capturing the CTSA program experiences in a series of papers. Here we bring together the recommendations from those papers in a list of specific actions that research sites can take to strengthen operations and prepare for similar future public health emergencies. Most importantly, creative innovations developed in response to the COVID-19 pandemic deserve serious consideration for adoption as new standards, thus converting the painful trauma of the pandemic into “post-traumatic growth” that makes the clinical research enterprise stronger, more resilient, and more effective.

We report the development of a regression model to predict the prevalence of severe acute respiratory syndrome coronavirus (SARS-CoV-2) antibodies on a population level based on self-reported symptoms. We assessed participant-reported symptoms in the past 12 weeks, as well as the presence of SARS-CoV-2 antibodies during a study conducted in April 2020 in Ischgl, Austria. We conducted multivariate binary logistic regression to predict seroprevalence in the sample. Participants (n = 451) were on average 47.4 years old (s.d. 16.8) and 52.5% female. SARS-CoV-2 antibodies were found in n = 197 (43.7%) participants. In the multivariate analysis, three significant predictors were included and the odds ratios (OR) for the most predictive categories were cough (OR 3.34, CI 1.70–6.58), gustatory/olfactory alterations (OR 13.78, CI 5.90–32.17) and limb pain (OR 2.55, CI 1.20–6.50). The area under the receiver operating characteristic curve was 0.773 (95% CI 0.727–0.820). Our regression model may be used to estimate the seroprevalence on a population level and a web application is being developed to facilitate the use of the model.

Although Canada's first documented case of COVID-19 appeared in mid-January 2020, it was not until March that messaging about the need to contain the virus heightened. In this research note, we document the use of the media's construction of risk through framing in the early stages of the pandemic. We analyze three dimensions of the health risk narratives related to COVID-19 that dominated Canadians’ concerns about the virus. To capture these narratives, we examine print and online news coverage from two nationally distributed media sources. We assess these frames alongside epidemiological data and find there is a clear link between media coverage, epidemiological data and risk frames in the early stages of the pandemic. It appears that the media relied on health expertise and political sources to guide their coverage and was responsive to the public health data presented to Canadians.

Alternate care sites (ACS) are locations that can be converted to provide either in-patient and/or out-patient health care services when existing facilities are compromised by a hazard impact or the volume of patients exceeds available capacity and/or capabilities. In March through May of 2020, Michigan Medicine (MM), the affiliated health system of the University of Michigan, planned a 500 bed ACS at an off-site location. Termed the Michigan Medicine Field Hospital (MMFH), this ACS was intended to be a step-down care facility for low-acuity COVID-19 positive MM patients who could be transitioned from the hospital setting and safely cared for prior to discharge home, while also allowing increased bed capacity in the remaining MM hospitals for additional critical patient care. The planning was organized into six units: personnel and labor, security, clinical operations, logistics and supply, planning and training, and communications. The purpose of this report is to describe the development and planning of an ACS within the MM academic medical center (AMC) to discuss anticipated barriers to success and to suggest guidance for health systems in future planning.

Coronavirus disease 2019 (COVID-19) is a newly emerged disease with various clinical manifestations and imaging features. The diagnosis of COVID-19 depends on a positive nucleic acid amplification test by real-time reverse transcription-polymerase chain reaction (RT-PCR) for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, the clinical manifestations and imaging features of COVID-19 are non-specific, and nucleic acid test for SARS-CoV-2 can have false-negative results. It is presently believed that detection of specific antibodies to SARS-CoV-2 is an effective screening and diagnostic indicator for SARS-CoV-2 infection. Thus, a combination of nucleic acid and specific antibody tests for SARS-CoV-2 will be more effective to diagnose COVID-19, especially to exclude suspected cases.