The outbreak of novel coronavirus pneumonia (coronavirus disease 2019 (COVID-19)), declared as a ‘global pandemic’ by the World Health Organization (WHO), is a public health emergency of international concern (PHEIC). The outbreak in multiple locations shows a trend of accelerating spread around the world. China has taken a series of powerful measures to contain the spread of the novel coronavirus. In response to the COVID-19 pandemic, in addition to actively finding effective treatment drugs and developing vaccines, it is more important to identify the source of infection at the community level as soon as possible to block the transmission path of the virus to prevent the spread of the pandemic. The implementation of grid management in the community and the adoption of precise management and control measures to reduce unnecessary personnel movement can effectively reduce the risk of pandemic spread. This paper mainly describes that the grid management mode can promote the refinement and comprehensiveness of community management. As a management system with potential to improve the governance ability of community affairs, it may be helpful to strengthen the prevention and control of the epidemic in the community.

This study aimed to identify clinical features for prognosing mortality risk using machine-learning methods in patients with coronavirus disease 2019 (COVID-19). A retrospective study of the inpatients with COVID-19 admitted from 15 January to 15 March 2020 in Wuhan is reported. The data of symptoms, comorbidity, demographic, vital sign, CT scans results and laboratory test results on admission were collected. Machine-learning methods (Random Forest and XGboost) were used to rank clinical features for mortality risk. Multivariate logistic regression models were applied to identify clinical features with statistical significance. The predictors of mortality were lactate dehydrogenase (LDH), C-reactive protein (CRP) and age based on 500 bootstrapped samples. A multivariate logistic regression model was formed to predict mortality 292 in-sample patients with area under the receiver operating characteristics (AUROC) of 0.9521, which was better than CURB-65 (AUROC of 0.8501) and the machine-learning-based model (AUROC of 0.4530). An out-sample data set of 13 patients was further tested to show our model (AUROC of 0.6061) was also better than CURB-65 (AUROC of 0.4608) and the machine-learning-based model (AUROC of 0.2292). LDH, CRP and age can be used to identify severe patients with COVID-19 on hospital admission.

Healthcare workers (HCWs) have a theoretically increased risk of contracting severe acute respiratory coronavirus virus 2 (SARS-CoV-2) given their occupational exposure. We tested 2,167 HCWs in a London Acute Integrated Care Organisation for antibodies to SARS-CoV-2 in May and June 2020 to evaluate seroprevalence. We found a seropositivity rate of 31.6% among HCWs.

As the coronavirus disease 2019 (COVID-19) continues to circulate, testing strategies are of the utmost importance. Given national shortages of testing supplies, personal protective equipment, and other hospital resources, diagnostic stewardship is necessary to aid in resource management. We report the low utility of serial testing in a low-prevalence setting.

The worldwide coronavirus pandemic has forced health services to adapt their delivery to protect the health of all concerned, and avoid service users facing severe disruption. Improving Access to Psychological Therapies (IAPT) services in particular are having to explore remote working methods to continue functioning. Australian IAPT services have utilised remote delivery methods and disruptive technologies at their core from inception. This was to maintain fidelity and clinical governance across vast distances but has allowed training, supervision and service delivery to continue virtually uninterrupted through coronavirus restrictions. On this basis, key recommendations for remote working are outlined. Remote methods are defined as (1) real time delivery, (2) independent delivery and (3) blended delivery. These are applied across three broad areas of remote training, remote clinical supervision and remote service delivery. Recommendations may be of great benefit to IAPT training institutions, clinical supervisors and service providers considering a move towards remote delivery. Challenges, adaptations and examples of applying remote methods are outlined, including case examples of methods applied to low-intensity and high-intensity cognitive behavioural therapy. Remote methods can safeguard service continuity in times of worldwide crisis and can contribute to reducing the impact of increased mental health presentations post-COVID-19.

Healthcare employees were tested for antibodies against severe acute respiratory coronavirus virus 2 (SARS-CoV-2). Among 734 employees, the prevalence of SARS-CoV-2 antibodies was 1.6%. Employees with heavy coronavirus disease 2019 (COVID-19) exposure had similar antibody prevalence as those with limited or no exposure. Guidelines for PPE use seem effective for preventing COVID-19 infection in healthcare workers.

We implemented universal severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing of patients undergoing surgical procedures as a means to conserve personal protective equipment (PPE). The rate of asymptomatic coronavirus disease 2019 (COVID-19) was <0.5%, which suggests that early local public health interventions were successful. Although our protocol was resource intensive, it prevented exposures to healthcare team members.

Because severe acute respiratory coronavirus virus 2 (SARS-CoV-2) spreads easily and healthcare workers are at increased risk of both acquiring and transmitting infection, all healthcare facilities must rapidly and rigorously implement the full hierarchy of established infection controls: source control (removal or mitigation of infection sources), engineering and environmental controls, administrative controls, and personal protective equipment.

Households in Canada and Australia have exhibited similar trends in the gendered allocation of additional child care responsibilities resulting from policy responses to the COVID-19 pandemic. In this article, we employ survey data to analyze the extent to which policy interventions related to COVID-19 have exacerbated gender disparities in child care obligations. We find that existing asymmetrical distributions of child care obligations in Canada and Australia have been amplified during the pandemic, resulting in a disproportionate burden on women. During the pandemic we also find that, in households with children, women tend to report experiencing poorer mental health than men.

A diagnosis of Brugada pattern in paediatric or adolescent patients is rare. COVID-19 is characterised by fevers and a pro-inflammatory state, which may serve as inciting factors for Brugada pattern. Recently described in two adult patients, we report the first case of Brugada pattern in an adolescent with COVID-19.

This essay provides a critical observation of the South Korean government's distinctive management of COVID-19 with particular reference to the state of emergency. It reveals that the success of South Korea's handling of the pandemic is largely attributed by a majority of Western media to the efficient deployment of both information and communication technologies and Confucian collectivism, two components that seem contradictory yet not incompatible under the rubric of techno-Orientalism. Analyzing the intensification of surveillance and the rapid datafication of society, this essay argues that the current state of emergency is not a breakdown of normality but a continuation of the state of crisis and disaster that rules a developing country like South Korea. In doing so, the essay seeks to facilitate a critical discussion about a new mode of democracy in the era of pandemic that increasingly grapples with tensions between individual freedom and public health.