Fangcang shelter hospitals are a One Health approach for responding to the COVID-19 outbreak in Wuhan, China

An innovative approach for predicting pandemic hotspots in complex wastewater networks using graph theory coupled with fuzzy logic

Early prediction of COVID-19 infected communities (potential hotspots) is essential to limit the spread of virus. Diagnostic testing has limitations in big populations because it cannot deliver information at a fast enough rate to stop the spread in its early phases. Wastewater based epidemiology (WBE) experiments showed promising results for brisk detection of 'SARS CoV-2' RNA in urban wastewater. However, a systematic and targeted approach to track COVID-19 virus in the complex wastewater networks at a community level is lacking. This research combines graph network (GN) theory with fuzzy logic to determine the chances of a specific community being a COVID-19 hotspot in a wastewater network. To detect 'SARS-CoV-2' RNA, GN divides wastewater network into communities and fuzzy logic-based inference system is used to identify targeted communities. For the propose of tracking, 4000 sample cases from Minnesota (USA) were tested based on various contributing factors. With a probability score of greater than 0.8, 42% of cases were likely to be designated as COVID-19 hotspots based on multiple demographic characteristics. The research enhances the conventional WBE approach through two novel aspects, viz. (1) by integrating graph theory with fuzzy logic for quick prediction of potential hotspot along with its likelihood percentage in a wastewater network, and (2) incorporating the uncertainty associated with COVID-19 contributing factors using fuzzy membership functions. The targeted approach allows for rapid testing and implementation of vaccination campaigns in potential hotspots. Consequently, governmental bodies can be well prepared to check future pandemics and variant spreading in a more planned manner.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00477-023-02468-3.

The Effect of Fangcang Shelter Hospitals under Resource Constraints on the Spread of Epidemics

Since the outbreak of the COVID-19 pandemic, Fangcang shelter hospitals have been built and operated in several cities, and have played a huge role in epidemic prevention and control. How to use medical resources effectively in order to maximize epidemic prevention and control is a big challenge that the government should address. In this paper, a two-stage infectious disease model was developed to analyze the role of Fangcang shelter hospitals in epidemic prevention and control, and examine the impact of medical resources allocation on epidemic prevention and control. Our model suggested that the Fangcang shelter hospital could effectively control the rapid spread of the epidemic, and for a very large city with a population of about 10 million and a relative shortage of medical resources, the model predicted that the final number of confirmed cases could be only 3.4% of the total population in the best case scenario. The paper further discusses the optimal solutions regarding medical resource allocation when medical resources are either limited or abundant. The results show that the optimal allocation ratio of resources between designated hospitals and Fangcang shelter hospitals varies with the amount of additional resources. When resources are relatively sufficient, the upper limit of the proportion of makeshift hospitals is about 91%, while the lower limit decreases with the increase in resources. Meanwhile, there is a negative correlation between the intensity of medical work and the proportion of distribution. Our work deepens our understanding of the role of Fangcang shelter hospitals in the pandemic and provides a reference for feasible strategies by which to contain the pandemic.

Screening visual environment impact factors and the restorative effect of four visual environment components in large-space alternative care facilities

Alternative care facilities (ACFs) based on large-space public buildings were widely used early at the start of the coronavirus disease 2019 (COVID-19) pandemic. However, studies have shown that the indoor spatial environment of ACFs can significantly induce mental health problems among users. Thus, this study hypothesizes that improving the visual environment in the interiors of large-space ACFs may reduce mental health problems among users. To verify this hypothesis, this study used critical analysis to screen the influencing factors and used analytic hierarchy process analysis to determine the weights. Particularly, the analyses were based on ACF research in Wuhan and questionnaire surveys of patients with experience using ACFs. Subsequently, virtual reality experiments were conducted to measure physiological indicators and subjective questionnaire collection based on the orthogonal experimental design of the four screened visual environment components. The results revealed the following related to large-space ACFs: 1) Lifestyle support was the most dominant patient requirement and preference for the visual environment. 2) The visual environment can influence the participants' efficiency of psychological stress relief, emotional regulation, and subjective perception. 3) Different design characteristics of the four visual environment components were causally related to restorative effects. To the best of our knowledge, this is the first study analyzing patients' preferences and psychological needs for the visual environment of large-space ACFs and combining subjective and objective measures to investigate the restorative effects of the visual environment. Improving the quality of the visual environment in large-space ACFs presents an effective intervention for alleviating the psychological problems of admitted patients.

Experiences of COVID-19 patients in a Fangcang shelter hospital in China during the first wave of the COVID-19 pandemic: a qualitative descriptive study

OBJECTIVES

This study aimed to examine COVID-19 patients' experiences in a Fangcang shelter hospital in China, to provide insights into the effectiveness of this centralised isolation strategy as a novel solution to patient management during emerging infectious disease outbreaks.

DESIGN

This study adopted a qualitative descriptive design. Data were collected by individual semistructured interviews and analysed using thematic analysis.

SETTING

This study was undertaken in 1 of the 16 Fangcang shelter hospitals in Wuhan, China between 28 February 2020 and 7 March 2020. Fangcang shelter hospitals were temporary healthcare facilities intended for large-scale centralised isolation, treatment and disease monitoring of mild-to-moderate COVID-19 cases. These hospitals were an essential component of China's response to the first wave of the COVID-19 pandemic.

PARTICIPANTS

A total of 27 COVID-19 patients were recruited by purposive sampling. Eligible participants were (1) COVID-19 patients; (2) above 18 years of age and (3) able to communicate effectively. Exclusion criteria were (1) being clinically or emotionally unstable and (2) experiencing communication difficulties.

RESULTS

Three themes and nine subthemes were identified. First, COVID-19 patients experienced a range of psychological reactions during hospitalisation, including fear, uncertainty, helplessness and concerns. Second, there were positive and negative experiences associated with communal living. While COVID-19 patients' evaluation of essential services in the hospital was overall positive, privacy and hygiene issues were highlighted as stressors during their hospital stay. Third, positive peer support and a trusting patient-healthcare professional relationship served as a birthplace for resilience, trust and gratitude in COVID-19 patients.

CONCLUSIONS

Our findings suggest that, while sacrificing privacy, centralised isolation has the potential to mitigate negative psychological impacts of social isolation in COVID-19 patients by promoting meaningful peer connections, companionship and support within the shared living space. To our knowledge, this is the first study bringing patients' perspectives into healthcare service appraisal in emergency shelter hospitals.

Factors and optimizations of healthcare workers' perception in alternative care facilities

Background

Diverse measures have been carried out worldwide to establish Alternative Care Facilities (ACFs) for different ends, such as receiving, curing or isolating patients, aiming to cope with tremendous shock in the urban medical system during the early passage of the COVID-19 epidemic. Healthcare workers always felt anxious and stressed during multiple major public health emergencies in medical facilities. Some active measures to improve healthcare workers' perceptions, such as temporary training, workflow improvement, and supplementary facilities, were proved insufficient in several past public health emergencies. Therefore, this study aims to analyze the contributing factors of the healthcare workers' perceptions of the ACFs in this pandemic, which can help find an innovative path to ensure their health, well-being and work efficiency.

Method

This paper conducted semi-structured in-depth interviews with the world's first batch of healthcare workers who have worked in ACFs through a qualitative study based on Grounded Theory. The healthcare workers interviewed from Heilongjiang, Shandong, Fujian, and Hubei provinces, have worked in one of the four different ACFs built in Wuhan. The results are obtained through the three-level codes and analyses of the interview recordings.

Results

The factors affecting the perception of healthcare workers in ACFs during the epidemic situation can be summarized into five major categories: individual characteristics, organization management, facilities and equipment, space design, and internal environment. The five major categories affecting the composition of perception can be further divided into endogenous and exogenous factors, which jointly affect the perception of healthcare workers in ACFs. Among them, individual characteristics belong to endogenous factors, which are the primary conditions, while other categories belong to exogenous factors, which are the decisive conditions.

Conclusion

This paper clarifies factors affecting the perception of healthcare workers in ACFs and analyzes the mechanism of each factor. It is posited that the passive strategies are a promising solution to protect healthcare workers' health, improve their work efficiency, and help reduce the operation stress of ACFs. We should train multidisciplinary professionals for future healthcare and enhance collaborations between healthcare workers and engineers. To sum up, this paper broadens new horizons for future research on the optimization of ACFs and finds new paths for alleviating healthcare workers' adverse perceptions of ACFs.

Modeling the effect of Fangcang shelter hospitals on the control of COVID-19 epidemic

The ongoing COVID-19 pandemic has posed a tremendous threat to the public and health authorities. Wuhan, as one of the cities experiencing the earliest COVID-19 outbreak, has successfully tackled the epidemic finally. The main reason is the implementing of Fangcang shelter hospitals, which rapidly and massively scale the health system's capacity to treat COVID-19 confirmed cases with mild symptoms. To give insights on what degree Fangcang shelter hospitals have contained COVID-19 in Wuhan, we proposed a piecewise smooth model regarding the patient triage scheme and the bed capacities of Fangcang shelter hospitals and designated hospitals. We used data on the cumulative number of confirmed cases, recovered cases, deaths, and data on the number of hospitalized individuals in Fangcang shelter hospitals and designated hospitals in Wuhan to parameterize the targeted model. Our results showed that diminishing the bed capacity or delaying the opening time of Fangcang shelter hospitals, both would result in worsening the epidemic by increasing the total number of infectives and hospitalized individuals and the effective reproduction numberR e ( t ) . The findings demonstrated that Fangcang shelter hospitals avoided 17,013 critical infections and 17,823 total infections while it saved 7 days during the process of controlling the effective reproduction numberR e ( t ) < 1 . Our study highlighted the critical role of Fangcang shelter hospitals in curbing and eventually stopping COVID-19 outbreak in Wuhan, China. These findings may provide a valuable reference for decision-makers in regarding ramping up the health system capacity to isolate groups of people with mild symptoms in areas of widespread infection.

Environmental Design Strategies to Decrease the Risk of Nosocomial Infection in Medical Buildings Using a Hybrid MCDM Model

The prevention and control of nosocomial infection (NI) are becoming increasingly difficult, and its mechanism is becoming increasingly complex. A globally aging population means that an increasing proportion of patients have a susceptible constitution, and the frequent occurrence of severe infectious diseases has also led to an increase in the cost of prevention and control of NI. Medical buildings' spatial environment design for the prevention of NI has been a hot subject of considerable research, but few previous studies have summarized the design criteria for a medical building environment to control the risk of NI. Thus, there is no suitable evaluation framework to determine whether the spatial environment of a medical building is capable of inhibiting the spread of NI. In the context of the global spread of COVID-19, it is necessary to evaluate the performance of the existing medical building environment in terms of inhibiting the spread of NI and to verify current environmental improvement strategies for the efficient and rational use of resources. This study determines the key design elements for the spatial environment of medical buildings, constructs an evaluation framework using exploratory factor analysis, verifies the complex dominant influence relationship, and prioritizes criteria in the evaluation framework using the decision-making trial and evaluation laboratory- (DEMATEL-) based analytical network process (ANP) (DANP). Using representative real cases, this study uses the technique for order preference by similarity to ideal solution (TOPSIS) to evaluate and analyze the performance with the aspiration level of reducing the NI risk. A continuous and systematic transformation design strategy for these real cases is proposed. The main contributions of this study include the following: (1) it creates a systematic framework that allows hospital decision-makers to evaluate the spatial environment of medical buildings; (2) it provides a reference for making design decisions to improve the current situation using the results of a performance evaluation; (3) it draws an influential network relation map (INRM) and the training of influence weights (IWs) for criteria. The sources of practical problems can be identified by the proposed evaluation framework, and the corresponding strategy can be proposed to avoid the waste of resources for the prevention of epidemics.

Management of and Revitalization Strategy for Megacities Under Major Public Health Emergencies: A Case Study of Wuhan

The outbreak of the COVID-19 pandemic in late 2019 has meant an uphill battle for city management. However, due to deficiencies in facilities and management experience, many megacities are less resilient when faced with such major public health events. Therefore, we chose Wuhan for a case study to examine five essential modules of urban management relevant to addressing the pandemic: (1) the medical and health system, (2) lifeline engineering and infrastructure, (3) community and urban management, (4) urban ecology and (5) economic development. The experience and deficiencies of each module in fighting the pandemic are analyzed, and strategies for revitalization and sustainable development in the future are proposed. The results show that in response to large-scale public health events, a comprehensive and coordinated medical system and good urban ecology can prevent the rapid spread of the epidemic. Additionally, good infrastructure and community management can maintain the operation of the city under the pandemic, and appropriate support policies are conducive to the recovery and development of the urban economy. These precedents provide insights and can serve as a reference for how to change the course of the pandemic in megacities that are still at risk, and they provide experience for responding to other pandemics.

Emergency Preparedness and Management of Mobile Cabin Hospitals in China During the COVID-19 Pandemic

The healthcare systems in China and globally have faced serious challenges during the coronavirus disease (COVID-19) pandemic. The shortage of beds in traditional hospitals has exacerbated the threat of COVID-19. To increase the number of available beds, China implemented a special public health measure of opening mobile cabin hospitals. Mobile cabin hospitals, also called Fangcang shelter hospitals, refer to large-scale public venues such as indoor stadiums and exhibition centers converted to temporary hospitals. This study is a mini review of the practice of mobile cabin hospitals in China. The first part is regarding emergency preparedness, including site selection, conversion, layout, and zoning before opening the hospital, and the second is on hospital management, including organization management, management of nosocomial infections, information technology support, and material supply. This review provides some practical recommendations for countries that need mobile cabin hospitals to relieve the pressure of the pandemic on the healthcare systems.

Problems with evidence assessment in COVID-19 health policy impact evaluation: a systematic review of study design and evidence strength

INTRODUCTION

Assessing the impact of COVID-19 policy is critical for informing future policies. However, there are concerns about the overall strength of COVID-19 impact evaluation studies given the circumstances for evaluation and concerns about the publication environment.

METHODS

We included studies that were primarily designed to estimate the quantitative impact of one or more implemented COVID-19 policies on direct SARS-CoV-2 and COVID-19 outcomes. After searching PubMed for peer-reviewed articles published on 26 November 2020 or earlier and screening, all studies were reviewed by three reviewers first independently and then to consensus. The review tool was based on previously developed and released review guidance for COVID-19 policy impact evaluation.

RESULTS

After 102 articles were identified as potentially meeting inclusion criteria, we identified 36 published articles that evaluated the quantitative impact of COVID-19 policies on direct COVID-19 outcomes. Nine studies were set aside because the study design was considered inappropriate for COVID-19 policy impact evaluation (n=8 pre/post; n=1 cross-sectional), and 27 articles were given a full consensus assessment. 20/27 met criteria for graphical display of data, 5/27 for functional form, 19/27 for timing between policy implementation and impact, and only 3/27 for concurrent changes to the outcomes. Only 4/27 were rated as overall appropriate. Including the 9 studies set aside, reviewers found that only four of the 36 identified published and peer-reviewed health policy impact evaluation studies passed a set of key design checks for identifying the causal impact of policies on COVID-19 outcomes.

DISCUSSION

The reviewed literature directly evaluating the impact of COVID-19 policies largely failed to meet key design criteria for inference of sufficient rigour to be actionable by policy-makers. More reliable evidence review is needed to both identify and produce policy-actionable evidence, alongside the recognition that actionable evidence is often unlikely to be feasible.

An efficiency-based interval type-2 fuzzy multi-criteria group decision making for makeshift hospital selection

Since makeshift hospitals have strong ability in blocking the spread of the virus, how to design some methods to select the reasonable sites of makeshift hospitals is vitally important for containing COVID-19. This paper investigates an efficiency-based multi-criteria group decision making (MCGDM) method by combining the best-worst method (BWM) and data envelopment analysis (DEA) in trapezoidal interval type-2 fuzzy (TrIT2F) environment. This MCGDM method is called TrIT2F-BWM-DEA, where the TrIT2F-BWM is used to determine the weights of criteria and decision-makers, and the TrIT2F-DEA is employed to rank alternatives by measuring their overall efficiencies. Based on cut set theory, the expectation and average expectation (AE) of TrIT2FSs are successively defined. To solve three key issues in the development of the TrIT2F-BWM, this paper proposes a flexible ranking relation of TrIT2FSs to transform the TrIT2F constraints, initiates an efficient theorem to normalize the TrIT2F weights, and designs an input-based consistency ratio to check the reliability of the determined weights. A fully TrIT2F-DEA model is originally built to measure the TrIT2F efficiencies of alternatives. The alternatives are finally ranked according to the AEs of alternatives’ TrIT2F efficiencies. A site selection case of Fangcang hospitals and some comparative analyses are provided to confirm the validity and merits of the proposed TrIT2F-BWM-DEA.

Impact Evaluation of Coronavirus Disease 2019 Policy: A Guide to Common Design Issues

Policy responses to COVID-19, particularly those related to non-pharmaceutical interventions, are unprecedented in scale and scope. However, policy impact evaluations require a complex combination of circumstance, study design, data, statistics, and analysis. Beyond the issues that are faced for any policy, evaluation of COVID-19 policies is complicated by additional challenges related to infectious disease dynamics and a multiplicity of interventions. The methods needed for policy-level impact evaluation are not often used or taught in epidemiology, and differ in important ways that may not be obvious. Methodological complications of policy evaluations can make it difficult for decision-makers and researchers to synthesize and evaluate strength of evidence in COVID-19 health policy papers. We (1) introduce the basic suite of policy impact evaluation designs for observational data, including cross-sectional analyses, pre/post, interrupted time-series, and difference-in-differences analysis, (2) demonstrate key ways in which the requirements and assumptions underlying these designs are often violated in the context of COVID-19, and (3) provide decision-makers and reviewers a conceptual and graphical guide to identifying these key violations. The overall goal of this paper is to help epidemiologists, policy-makers, journal editors, journalists, researchers, and other research consumers understand and weigh the strengths and limitations of evidence.

Experimental study on the control effect of different ventilation systems on fine particles in a simulated hospital ward

In recent years, a large number of respiratory infectious diseases (especially COVID-19) have broken out worldwide. Respiratory infectious viruses may be released in the air, resulting in cross-infection between patients and medical workers. Indoor ventilation systems can be adjusted to affect fine particles containing viruses. This study was aimed at performing a series of experiments to evaluate the ventilation performance and assess the exposure of healthcare workers (HW) to virus-laden particles released by patients in a confined experimental chamber. In a typical ward setting, four categories (top supply and exhaust, side supply and exhaust) were evaluated, encompassing 16 different air distribution patterns. The maximum reduction in the cumulative exposure level for HW was 70.8% in ventilation strategy D (upper diffusers on the sidewall supply and lower diffusers on the same sidewall return). The minimum value of the cumulative exposure level for a patient close to the source of the contamination pertained to Strategy E (upper diffusers on the sidewall supply and lower diffusers on the opposite sidewall return). Lateral ventilation strategies can provide significant guidance for ward operation to minimizing the airborne virus contamination. This study can provide a reference for sustainable buildings to construct a healthy indoor environment.

Is One Health a Viable Strategy in Animal Health Litigation: Evidence from Civil Lawsuits in China

Simple Summary

Strategic litigation launched to protect animal welfare worldwide branches out with several tactical themes: environmental protection, child abuse, veterinarian malpractice, product liability and quasi-family member. Currently, the litigation strategy themed in One Health has been observed in legal practice in Chinese mainland. Using 1520 zoonosis related civil lawsuit judgments, this study aimed to assess the effectiveness of this litigation strategy in animal health cases from Chinese mainland. It has been confirmed that using the litigation strategy themed in One Health results in more successful outcomes and larger damage awards, so there might be a practical value in using this strategy in animal welfare lawsuits.

Abstract

Several litigation strategies are used to gain support from courts in order to protect animals. While the emerging litigation strategy themed in One Health stimulates judicial protection in the animal health sector, little is known about whether and how such strategies are supported by courts. In this article, we investigate how animal welfare litigation strategies influence judge’s choices within their discretion. We argue that litigators equipped with the litigation strategy themed in One Health are placed in an advantageous position in animal health cases, but that this tendency varies markedly across zoonoses. Specifically, we suggest that litigators utilizing One Health’s litigation strategy are associated with higher probabilities to win, whereas normal litigators are not. Further, we propose that litigators equipped with the One Health litigation strategy are awarded more damages from judges. We test and find support for our predictions using a cross sectional dataset of civil lawsuit cases centering on the animal health industry in Chinese mainland. Our findings indicate that courts indeed were persuaded by the One Health litigation strategy, even when bound by the discretion rules. At the same time, we suggest that for advocates who would like to litigate for animal welfare in the animal health sector, the litigation strategy themed in One Health might have potentially positive implications.

Science's Response to CoVID-19

CoVID-19 is a multi-symptomatic disease which has made a global impact due to its ability to spread rapidly, and its relatively high mortality rate. Beyond the heroic efforts to develop vaccines, which we do not discuss herein, the response of scientists and clinicians to this complex problem has reflected the need to detect CoVID-19 rapidly, to diagnose patients likely to show adverse symptoms, and to treat severe and critical CoVID-19. Here we aim to encapsulate these varied and sometimes conflicting approaches and the resulting data in terms of chemistry and biology. In the process we highlight emerging concepts, and potential future applications that may arise out of this immense effort.

Detecting SARS-CoV-2 RNA prone clusters in a municipal wastewater network using fuzzy-Bayesian optimization model to facilitate wastewater-based epidemiology

The current pandemic disease coronavirus (COVID-19) has not only become a worldwide health emergency, but also devoured the global economy. Despite appreciable research, identification of targeted populations for testing and tracking the spread of COVID-19 at a larger scale is an intimidating challenge. There is a need to quickly identify the infected individual or community to check the spread. The diagnostic testing done at large-scale for individuals has limitations as it cannot provide information at a swift pace in large populations, which is pivotal to contain the spread at the early stage of its breakouts. Recently, scientists are exploring the presence of SARS-CoV-2 RNA in the faeces discharged in municipal wastewater. Wastewater sampling could be a potential tool to expedite the early identification of infected communities by detecting the biomarkers from the virus. However, it needs a targeted approach to choose optimized locations for wastewater sampling. The present study proposes a novel fuzzy based Bayesian model to identify targeted populations and optimized locations with a maximum probability of detecting SARS-CoV-2 RNA in wastewater networks. Consequently, real time monitoring of SARS-CoV-2 RNA in wastewater using autosamplers or biosensors could be deployed efficiently. Fourteen criteria such as population density, patients with comorbidity, quarantine and hospital facilities, etc. are analysed using the data of 14 lac individuals infected by COVID-19 in the USA. The uniqueness of the proposed model is its ability to deal with the uncertainty associated with the data and decision maker's opinions using fuzzy logic, which is fused with Bayesian approach. The evidence-based virus detection in wastewater not only facilitates focused testing, but also provides potential communities for vaccine distribution. Consequently, governments can reduce lockdown periods, thereby relieving human stress and boosting economic growth.

Problems with Evidence Assessment in COVID-19 Health Policy Impact Evaluation (PEACHPIE): A systematic review of study design and evidence strength

Introduction:

Assessing the impact of COVID-19 policy is critical for informing future policies. However, there are concerns about the overall strength of COVID-19 impact evaluation studies given the circumstances for evaluation and concerns about the publication environment. This study systematically reviewed the strength of evidence in the published COVID-19 policy impact evaluation literature.

Methods:

We included studies that were primarily designed to estimate the quantitative impact of one or more implemented COVID-19 policies on direct SARS-CoV-2 and COVID-19 outcomes. After searching PubMed for peer-reviewed articles published on November 26, 2020 or earlier and screening, all studies were reviewed by three reviewers first independently and then to consensus. The review tool was based on previously developed and released review guidance for COVID-19 policy impact evaluation, assessing what impact evaluation method was used, graphical display of outcomes data, functional form for the outcomes, timing between policy and impact, concurrent changes to the outcomes, and an overall rating.

Results:

After 102 articles were identified as potentially meeting inclusion criteria, we identified 36 published articles that evaluated the quantitative impact of COVID-19 policies on direct COVID-19 outcomes. The majority (n=23/36) of studies in our sample examined the impact of stay-at-home requirements. Nine studies were set aside because the study design was considered inappropriate for COVID-19 policy impact evaluation (n=8 pre/post; n=1 cross-section), and 27 articles were given a full consensus assessment. 20/27 met criteria for graphical display of data, 5/27 for functional form, 19/27 for timing between policy implementation and impact, and only 3/27 for concurrent changes to the outcomes. Only 1/27 studies passed all of the above checks, and 4/27 were rated as overall appropriate. Including the 9 studies set aside, reviewers found that only four of the 36 identified published and peer-reviewed health policy impact evaluation studies passed a set of key design checks for identifying the causal impact of policies on COVID-19 outcomes.

Discussion:

The reviewed literature directly evaluating the impact of COVID-19 policies largely failed to meet key design criteria for inference of sufficient rigor to be actionable by policymakers. This was largely driven by the circumstances under which policies were passed making it difficult to attribute changes in COVID-19 outcomes to particular policies. More reliable evidence review is needed to both identify and produce policy-actionable evidence, alongside the recognition that actionable evidence is often unlikely to be feasible.

Mental health needs of the COVID-19 patients and staff in the Fangcang shelter hospital: a qualitative research in Wuhan, China

BACKGROUND

During the coronavirus disease 2019 (COVID-19) pandemic, Fangcang shelter hospitals were opened in Wuhan, China, to isolate and care for patients with mild or moderate symptoms. The patients and staff in the hospitals faced mental health challenges. This paper reports the experiences and mental health needs from them.

METHOD

Following the qualitative design, semi-structured interviews were conducted in the EastWest Lake Fangcang Shelter Hospital, Wuhan on March 2020. Data collection and analysis was based on grounded theory. Open coding was adapted and a structured codebook was developed through coding seminars. The themes and subthemes were then confirmed through thematic analysis. The findings were further explained and integrated in a theoretical framework.

RESULTS

A total of 10 COVID-19 patients and 13 staff, including doctors, nurses, psychiatrists, and policemen participated in the interviews. They have common needs, as well as their own needs. The perspectives from the staff also did complement for needs of the patients. The mental health needs were generalized into four themes, that is, basic needs, information and communication, emotional needs, and social support, each with several subthemes. In addition, there were some external factors that regulated the internal needs, which were summarized in a theoretical framework.

CONCLUSIONS

The study indicates the directions on hospital management, mental health services, policy making, and social work to meet the mental health needs of the inpatients and staff from temporary shelter hospitals like Fangcang in Wuhan during the COVID-19 pandemic.

One Health in the context of coronavirus outbreaks: A systematic literature review

The ongoing coronavirus disease 2019 (COVID-19) pandemic threatens global health thereby causing unprecedented social, economic, and political disruptions. One way to prevent such a pandemic is through interventions at the human-animal-environment interface by using an integrated One Health (OH) approach. This systematic literature review documented the three coronavirus outbreaks, i.e. SARS, MERS, COVID-19, to evaluate the evolution of the OH approach, including the identification of key OH actions taken for prevention, response, and control. The OH understandings identified were categorized into three distinct patterns: institutional coordination and collaboration, OH in action/implementation, and extended OH (i.e. a clear involvement of the environmental domain). Across all studies, OH was most often framed as OH in action/implementation and least often in its extended meaning. Utilizing OH as institutional coordination and collaboration and the extended OH both increased over time. OH actions were classified into twelve sub-groups and further categorized as classical OH actions (i.e. at the human-animal interface), classical OH actions with outcomes to the environment, and extended OH actions. The majority of studies focused on human-animal interaction, giving less attention to the natural and built environment. Different understandings of the OH approach in practice and several practical limitations might hinder current efforts to achieve the operationalization of OH by combining institutional coordination and collaboration with specific OH actions. The actions identified here are a valuable starting point for evaluating the stage of OH development in different settings. This study showed that by moving beyond the classical OH approach and its actions towards a more extended understanding, OH can unfold its entire capacity thereby improving preparedness and mitigating the impacts of the next outbreak.