Guiding organisational decision-making about COVID-19 asymptomatic testing in workplaces: mixed-method study to inform an ethical framework.

BACKGROUND: Workplace programmes to test staff for asymptomatic COVID-19 infection have become common, but raise a number of ethical challenges. In this article, we report the findings of a consultation that informed the development of an ethical framework for organisational decision-making about such programmes. METHODS: We conducted a mixed-method consultation - a survey and semi-structured interviews during November-December 2020 in a UK case study organisation that had introduced asymptomatic testing for all staff working on-site in its buildings. Analysis of closed-ended survey data was conducted descriptively. An analysis approach based on the Framework Method was used for the open-ended survey responses and interview data. The analyses were then integrated to facilitate systematic analysis across themes. Inferences were based on the integrated findings and combined with other inputs (literature review, ethical analysis, legal and public health guidance, expert discussions) to develop an ethical framework. RESULTS: The consultation involved 61 staff members from the case study organisation (50 survey respondents and 11 interview participants). There was strong support for the asymptomatic testing programme: 90% of the survey respondents viewed it as helpful or very helpful. Open-ended survey responses and interviews gave insight into participants' concerns, including those relating to goal drift, risk of false negatives, and potential negative impacts for household members and people whose roles lacked contractual and financial stability. Integration of the consultation findings and the other inputs identified the importance of a whole-system approach with appropriate support for the key control measure of isolation following positive tests. The need to build trust in the testing programme, for example through effective communication from leaders, was also emphasised. CONCLUSIONS: The consultation, together with other inputs, informed an ethical framework intended to support employers. The framework may support organisational decision-making in areas ranging from design and operation of the programme through to choices about participation. The framework is likely to benefit from further consultation and refinement in new settings.

Human Centered Decision-Making for COVID-19 Testing Center Location Selection: Tamil Nadu-A Case Study.

This paper proposes a blend of three techniques to select COVID-19 testing centers. The objective of the paper is to identify a suitable location to establish new COVID-19 testing centers. Establishment of the testing center in the needy locations will be beneficial to both public and government officials. Selection of the wrong location may lead to lose both health and wealth. In this paper, location selection is modelled as a decision-making problem. The paper uses fuzzy analytic hierarchy process (AHP) technique to generate the criteria weights, monkey search algorithm to optimize the weights, and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method to rank the different locations. To illustrate the applicability of the proposed technique, a state named Tamil Nadu, located in India, is taken for a case study. The proposed structured algorithmic steps were applied for the input data obtained from the government of India website, and the results were analyzed and validated using the government of India website. The ranks assigned by the proposed technique to different locations are in aligning with the number of patients and death rate.

Public health emergency decision-making and management system sound research using rough set attribute reduction and blockchain.

Public health emergency decisions are explored to ensure the emergency response measures in an environment where various emergencies occur frequently. An emergency decision is essentially a multi-criteria risk decision-making problem. The feasibility of applying prospect theory to emergency decisions is analyzed, and how psychological behaviors of decision-makers impact decision-making results are quantified. On this basis, the cognitive process of public health emergencies is investigated based on the rough set theory. A Decision Rule Extraction Algorithm (denoted as A-DRE) that considers attribute costs is proposed, which is then applied for attribute reduction and rule extraction on emergency datasets. In this way, decision-makers can obtain reduced decision table attributes quickly. Considering that emergency decisions require the participation of multiple departments, a framework is constructed to solve multi-department emergency decisions. The technical characteristics of the blockchain are in line with the requirements of decentralization and multi-party participation in emergency management. The core framework of the public health emergency management system-plan, legal system, mechanism, and system can play an important role. When [Formula: see text], the classification accuracy under the K-Nearest Neighbor (KNN) classifier reaches 73.5%. When [Formula: see text], the classification accuracy under the Support Vector Machines (SVM) classifier reaches 86.4%. It can effectively improve China's public health emergency management system and improve the efficiency of emergency management. By taking Coronavirus Disease 2019 (COVID-19) as an example, the weight and prospect value functions of different decision-maker attributes are constructed based on prospect theory. The optimal rescue plan is finally determined. A-DRE can consider the cost of each attribute in the decision table and the ability to classify it correctly; moreover, it can reduce the attributes and extract the rules on the COVID-19 dataset, suitable for decision-makers' situation face once an emergency occurs. The emergency decision approach based on rough set attribute reduction and prospect theory can acquire practical decision-making rules while considering the different risk preferences of decision-makers facing different decision-making results, which is significant for the rapid development of public health emergency assistance and disaster relief.

Governing the Access to COVID-19 Tools Accelerator: towards greater participation, transparency, and accountability.

The Access to COVID-19 Tools Accelerator (ACT-A) is a multistakeholder initiative quickly constructed in the early months of the COVID-19 pandemic to respond to a catastrophic breakdown in global cooperation. ACT-A is now the largest international effort to achieve equitable access to COVID-19 health technologies, and its governance is a matter of broad public importance. We traced the evolution of ACT-A's governance through publicly available documents and analysed it against three principles embedded in the founding mission statement of ACT-A: participation, transparency, and accountability. We found three challenges to realising these principles. First, the roles of the various organisations in ACT-A decision making are unclear, obscuring who might be accountable to whom and for what. Second, the absence of a clearly defined decision making body; ACT-A instead has multiple centres of legally binding decision making and uneven arrangements for information transparency, inhibiting meaningful participation. Third, the nearly indiscernible role of governments in ACT-A, raising key questions about political legitimacy and channels for public accountability. With global public health and billions in public funding at stake, short-term improvements to governance arrangements can and should now be made. Efforts to strengthen pandemic preparedness for the future require attention to ethical, legitimate arrangements for governance.

Investigating the cognitive capacity constraints of an ICU care team using a systems engineering approach.

BACKGROUND: ICU operational conditions may contribute to cognitive overload and negatively impact on clinical decision making. We aimed to develop a quantitative model to investigate the association between the operational conditions and the quantity of medication orders as a measurable indicator of the multidisciplinary care team's cognitive capacity. METHODS: The temporal data of patients at one medical ICU (MICU) of Mayo Clinic in Rochester, MN between February 2016 to March 2018 was used. This dataset includes a total of 4822 unique patients admitted to the MICU and a total of 6240 MICU admissions. Guided by the Systems Engineering Initiative for Patient Safety model, quantifiable measures attainable from electronic medical records were identified and a conceptual framework of distributed cognition in ICU was developed. Univariate piecewise Poisson regression models were built to investigate the relationship between system-level workload indicators, including patient census and patient characteristics (severity of illness, new admission, and mortality risk) and the quantity of medication orders, as the output of the care team's decision making. RESULTS: Comparing the coefficients of different line segments obtained from the regression models using a generalized F-test, we identified that, when the ICU was more than 50% occupied (patient census > 18), the number of medication orders per patient per hour was significantly reduced (average = 0.74; standard deviation (SD) = 0.56 vs. average = 0.65; SD = 0.48; p < 0.001). The reduction was more pronounced (average = 0.81; SD = 0.59 vs. average = 0.63; SD = 0.47; p < 0.001), and the breakpoint shifted to a lower patient census (16 patients) when at a higher presence of severely-ill patients requiring invasive mechanical ventilation during their stay, which might be encountered in an ICU treating patients with COVID-19. CONCLUSIONS: Our model suggests that ICU operational factors, such as admission rates and patient severity of illness may impact the critical care team's cognitive function and result in changes in the production of medication orders. The results of this analysis heighten the importance of increasing situational awareness of the care team to detect and react to changing circumstances in the ICU that may contribute to cognitive overload.

Estimating the effect of timetabling decisions on the spread of SARS-CoV-2 in medium-to-large engineering schools in Canada: an agent-based modelling study.

BACKGROUND: During the COVID-19 pandemic, universities transitioned to primarily online delivery, and it is important to understand what implications the transition back to in-person activities may have on spread of SARS-CoV-2 in the student population. The specific aim of our study was to provide insights into the effect of timetabling decisions on the spread of SARS-CoV-2 in a population of undergraduate engineering students. METHODS: We developed an agent-based modelling simulation that used a Canadian first-year undergraduate engineering program with an enrolment of 180 students in 5 courses of 12.7 weeks in length. Each course involved 150 minutes of lectures and 110 minutes of tutorials or laboratories per week. We considered several online and in-person timetabling scenarios with different scheduling frequencies and section sizes, in combination with surveillance and testing interventions. The study was conducted from May 1 to Aug. 31, 2021. RESULTS: When timetabling interventions were applied, we found a reduction in the mean number of students who were infected and that a containment of widespread outbreaks could be achieved. Timetables with online lectures and small (1/6 class capacity) tutorial or laboratory sections reduced the mean number of students who were infected by 83% and reduced the risk of large outbreaks that occurred with in-person lectures. We also found that spread of SARS-CoV-2 was less sensitive to class size than to contact frequency when a biweekly timetable was implemented (i.e., alternating online and in-person sections on a biweekly basis). Including a contact-tracing policy and randomized testing to the timetabling interventions helped to contain the spread of SARS-CoV-2 further. Vaccination coverage had the largest effect on reducing the number of students who were infected. INTERPRETATION: Our modelling showed that by taking advantage of timetabling opportunities and applying appropriate interventions (contact tracing, randomized testing and vaccination), SARS-CoV-2 infections may be averted and disruptions (case isolations) reduced. However, given the emergence of SARS-CoV-2 variants, transitions from online to in-person classes should proceed cautiously from small biweekly classes, for example, to manage risk.

Ethical Principles in Personal Protective Equipment Inventory Management Decisions and Partnerships Across State Lines During the COVID-19 Pandemic.

The COVID-19 pandemic created unprecedented strain on the personal protective equipment (PPE) supply chain. Given the dearth of PPE and consequences for transmission, GetMePPE Chicago (GMPC) developed a PPE allocation framework and system, distributing 886 900 units to 274 institutions from March 2020 to July 2021 to address PPE needs. As the pandemic evolved, GMPC made difficult decisions about (1) building reserve inventory (to balance present and future, potentially higher clinical acuity, needs), (2) donating to other states/out-of-state organizations, and (3) receiving donations from other states. In this case study, we detail both GMPC's experience in making these decisions and the ethical frameworks that guided these decisions. We also reflect on lessons learned and suggest which values may have been in conflict (eg, maximizing benefits vs duty to mission, defined in the context of PPE allocation) in each circumstance, which values were prioritized, and when that prioritization would change. Such guidance can promote a values-based approach to key issues concerning distribution of PPE and other scarce medical resources in response to the COVID-19 pandemic and related future pandemics.

[The disaster task force medical officer as a pivotal decision maker in the superordinate pandemic hospital capacity management : A field report covering the initial COVID-19 surge in a Bavarian district]. / Der Ärztliche Leiter Führungsgruppe Katastrophenschutz als zentrale Entscheidungsinstanz bei der Steuerung regionaler Krankenhauskapazitäten in der Pandemie : Ein Erfahrungsbericht zur ersten Welle der COVID-19-Pandemie in einem bayerischen Regierungsbezirk.

BACKGROUND AND OBJECTIVE: During the initial phase of the COVID-19 pandemic the government of the state of Bavaria, Germany, declared a state of emergency for its entire territory for the first time in history. Some areas in eastern Bavaria were among the most severely affected communities in Germany, prompting authorities and hospitals to build up capacities for a surge of COVID-19 patients. In some areas, intensive care unit (ICU) capacities were heavily engaged, which occasionally made a redistribution of patients necessary. MATERIAL AND METHODS: For managing COVID-19-related hospital capacities and patient allocation, crisis management squads in Bavaria were expanded by disaster task force medical officers ("Ärztlicher Leiter Führungsgruppe Katastrophenschutz" [MO]) with substantial executive authority. The authors report their experiences as MO concerning the superordinate patient allocation management in the district of Upper Palatinate (Oberpfalz) in eastern Bavaria. RESULTS: By abandoning routine patient care and building up additional ICU resources, surge capacity for the treatment of COVID-19 patients was generated in hospitals. In parts of the Oberpfalz, ICU capacities were almost entirely occupied by patients with corona virus infections, making reallocation to other hospitals within the district and beyond necessary. The MO managed patient pathways in an escalating manner by defining local (within the region of responsibility of a single MO), regional (within the district), and cross-regional (over district borders) reallocation lanes, as needed. When regional or cross-regional reallocation lanes had to be established, an additional management level located at the district government was involved. Within the determined reallocation lanes, emitting and receiving hospitals mutually agreed on any patient transfer without explicitly involving the MO, thereby maintaining the established interhospital routine transfer procedures. The number of patients and available treatment resources at each hospital were monitored with the help of a web-based treatment capacity registry. If indicated, reallocation lanes were dynamically revised according to the present situation. To oppose further virus spreading in nursing homes, the state government prohibited patient allocation to these facilities, which led to considerably longer hospital length of stay of convalescent elderly and/or dependent patients. In parallel to the flattening of the COVID-19 incidence curve, routine hospital patient care could be re-established in a stepwise manner. CONCLUSION: Patient allocation during the state of emergency by the MO sought to keep up routine interhospital reallocation procedures as much as possible, thereby reducing management time and effort. Occasionally, difficulties were observed during patient allocations crossing district borders, if other MO followed different management principles. The nursing home blockade and conflicting financial interests of hospitals posed challenges to the work of the disaster task force medical officers.

A review of studies on the COVID-19 epidemic crisis disease with a preventive approach.

BACKGROUND: COVID-19 is a highly contagious acute respiratory syndrome and has been declared a pandemic in more than 209 countries worldwide. At the time of writing, no preventive vaccine has been developed and tested in the community. This study was conducted to review studies aimed at preventing the spread of the coronavirus worldwide. METHODS: This study was a review of the evidence-based literature and was conducted by searching databases, including Google Scholar, PubMed, and ScienceDirect, until April 2020. The search was performed based on keywords including "coronavirus", "COVID-19", and "prevention". The list of references in the final studies has also been re-reviewed to find articles that might not have been obtained through the search. The guidelines published by trustworthy organizations such as the World Health Organization and Center for Disease Control have been used in this study. CONCLUSION: So far, no vaccine or definitive treatment for COVID-19 has been invented, and the disease has become a pandemic. Therefore, observation of hand hygiene, disinfection of high-touch surfaces, observation of social distance, and lack of presence in public places are recommended as preventive measures. Moreover, to control the situation and to reduce the incidence of the virus, some of the measures taken by the decision-making bodies and the guidelines of the deterrent institutions to strengthen telecommuting of employees and reduce the presence of people in the community and prevent unnecessary activities, are very important.

COVID-19, Workforce Autonomy and the Health Supply Chain.

During the COVID-19 pandemic, the rapid surge in demand for critical supplies and public health efforts needed to guard against virus transmission have placed enormous pressure on health systems worldwide. These pressures and the uncertainty they have created have impacted the health workforce in a substantial way. This paper examines the relationship between health supply chain capacity and the impact of the COVID-19 pandemic on Canada's health workforce. The findings of this research also highlight the impact of the pandemic on health workers, specifically the relationship between the health supply chain and the autonomy of the health workforce.

Mental Health Clinician Leaders in "Lockstep" as a Necessary Means to Address Care Challenges during the Pandemic.

Clinical environments that provide mental health and addictions care have been challenged during the COVID-19 pandemic due to health human resource shortages. This paper provides some insights gleaned from nurse and physician leaders working together during the pandemic in the mental health context to tackle some of these challenges. Key takeaways are provided.

Considerations for development of pharmacy support models for COVID-19 alternate care sites.

PURPOSE: Guidance on alternate care site planning based on the experience of a health-system pharmacy department in preparing for an expected surge in coronavirus disease 2019 (COVID-19) cases is provided. SUMMARY: In disaster response situations such as the COVID-19 pandemic, healthcare institutions may be compelled to transition to a contingency care model in which staffing and supply levels are no longer consistent with daily practice norms and, while usual patient care practices are maintained, establishment of alternate care sites (eg, a convention center) may be necessitated by high patient volumes. Available resources to assist hospitals and health systems in alternate care site planning include online guidance posted within the COVID-19 resources section of the US Army Corps of Engineers website, which provides recommended medication and supply lists; and the Federal Healthcare Resilience Task Force's alternate care site toolkit, a comprehensive resource for all aspects of alternate care site planning, including pharmacy services. Important pharmacy planning issues include security and storage of drugs, state board of pharmacy and Drug Enforcement Administration licensing considerations, and staff credentialing, education, and training. Key medication management issues to be addressed in alternate site care planning include logistical challenges of supply chain maintenance, optimal workflow for compounded sterile preparations (eg, on-site preparation vs off-site preparation and delivery from a nearby hospital), and infusion pump availability and suitability to patient acuity levels. CONCLUSION: Planning for and operation of alternate care sites in disaster response situations should include involvement of pharmacists in key decision-making processes at the earliest planning stages.

Mathematical modeling of the transmission of SARS-CoV-2-Evaluating the impact of isolation in São Paulo State (Brazil) and lockdown in Spain associated with protective measures on the epidemic of CoViD-19.

Coronavirus disease 2019 (CoViD-19), with the fatality rate in elder (60 years old or more) being much higher than young (60 years old or less) patients, was declared a pandemic by the World Health Organization on March 11, 2020. A mathematical model considering young and elder subpopulations under different fatality rates was formulated based on the natural history of CoViD-19 to study the transmission of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The model considered susceptible, exposed, asymptomatic, pre-symptomatic, mild CoViD-19, severe CoViD-19, and recovered compartments, besides compartments of isolated individuals and those who were caught by test. This model was applied to study the epidemiological scenario resulting from the adoption of quarantine (isolation or lockdown) in many countries to control the rapid propagation of CoViD-19. We chose as examples the isolation adopted in São Paulo State (Brazil) in the early phase but not at the beginning of the epidemic, and the lockdown implemented in Spain when the number of severe CoViD-19 cases was increasing rapidly. Based on the data collected from São Paulo State and Spain, the model parameters were evaluated, and we obtained a higher estimation for the basic reproduction number R0 (9.24 for São Paulo State, and 8 for Spain) compared to the currently accepted estimation of R0 around 2 using the SEIR (susceptible, exposed, infectious, and recovered compartments) model. In comparison with the lockdown in Spain, the relatively early adoption of the isolation in São Paulo State resulted in enlarging the period of the first wave of the epidemic and delaying its peak. The model allowed to explain the flattening of the epidemic curves by quarantine when associated with the protective measures (face mask, washing hands with alcohol and gel, and social distancing) adopted by the population. The description of the epidemic under quarantine and protections can be a background to foreseen the epidemiological scenarios from the release strategies, which can help guide public health policies by decision-makers.

Upgrades to intensive care: The effects of COVID-19 on decision-making in the emergency department.

INTRODUCTION: The initial surge of critically ill patients in the COVID-19 pandemic severely disrupted processes at acute care hospitals. This study examines the frequency and causes for patients upgraded to intensive care unit (ICU) level care following admission from the emergency department (ED) to non-critical care units. METHODS: The number of ICU upgrades per month was determined, including the percentage of upgrades noted to have non-concordant diagnoses. Charts with non-concordant diagnoses were examined in detail as to the ED medical decision-making, clinical circumstances surrounding the upgrade, and presence of a diagnosis of COVID-19. For each case, a cognitive bias was assigned. RESULTS: The percentage of upgraded cases with non-concordant diagnoses increased from a baseline range of 14-20% to 41.3%. The majority of upgrades were due to premature closure (72.2%), anchoring (61.1%), and confirmation bias (55.6%). CONCLUSION: Consistent with the behavioral literature, this suggests that stressful ambient conditions affect cognitive reasoning processes.

Using Community Feedback to Guide the COVID-19 Response in Sub-Saharan Africa: Red Cross and Red Crescent Approach and Lessons Learned from Ebola.

Risk communication and community engagement are critical elements of epidemic response. Despite progress made in this area, few examples of regional feedback mechanisms in Africa provide information on community concerns and perceptions in real time. To enable humanitarian responders to move beyond disseminating messages, work in partnership with communities, listen to their ideas, identify community-led solutions, and support implementation of solutions systems need to be in place for documenting, analyzing, and acting on community feedback. This article describes how the International Federation of Red Cross and Red Crescent Societies and its national societies in sub-Saharan Africa have worked to establish and strengthen systems to ensure local intelligence and community insights inform operational decision making. As part of the COVID-19 response, a system was set up to collect, compile, and analyze unstructured community feedback from across the region. We describe how this system was set up based on a system piloted in the response to Ebola in the Democratic Republic of the Congo, which tools were adapted and shared across the region, and how the information gathered was used to shape and adapt the response of the Red Cross and Red Crescent Societies and the broader humanitarian response.