A influência da resposta dos EUA à COVID-19 no contexto da Saúde Global / The influence of the U.S. response to COVID-19 in Global Health

Resumo A resposta americana à pandemia envolve um proeminente volume de recursos federais, em especial destinados ao desenvolvimento e aquisição de produtos no uso interno, como diagnósticos ou vacinas. As justificativas para esse desembolso se baseiam em mecanismos de investimentos e aspectos históricos. Assim, a construção social do nacionalismo na formação na sociedade americana prejudica o acesso a tecnologias em saúde. A revisão desses aspectos demonstra como os Estados Unidos (EUA) garantiram compra de grande quantitativo de produtos em potencial, inclusive assegurando excessiva produção local. Essa política externa unilateral tem influenciado outros países ou blocos regionais e prejudicado a cooperação e a solidariedade global com impacto na saúde coletiva de diversas nações.

Abstract The American response to the pandemic involves a prominent volume of federal resources, especially for developing and acquiring products for internal use, such as diagnostics or vaccines. Investment mechanisms and historical aspects justify this expenditure. Thus, the social construction of nationalism in American society hinders access to health technologies. The review of such aspects shows how the United States (U.S.) secured a large number of potential products, ensuring excessive local production. This unilateral foreign policy has influenced other countries or regional blocs and undermined global cooperation and solidarity, affecting the collective health of several nations.

Análise espacial das condições de enfrentamento à COVID-19: uma proposta de Índice da Infraestrutura da Saúde do Brasil / Spatial analysis of Brazil's COVID-19 response capacity: a proposal for a Healthcare Infrastructure Index

Resumo Uma das preocupações ligadas à pandemia da COVID-19 se refere à capacidade da estrutura do sistema de saúde suportar a demanda por atendimento e tratamento de pessoas acometidas por esta doença. Diante disso, o objetivo deste estudo consiste em criar e mapear o Índice de Infraestrutura de Saúde (IIS) das Unidades da Federação (UFs) brasileiras, bem como verificar a sua distribuição espacial. Para isso, foi aplicada a metodologia de Análise Fatorial por Componentes Principais. Aplicou-se os testes de Bartlett e Kaiser-Meyer-Olkin para verificação da sua adequabilidade. Em seguida procedeu-se a Análise Exploratória de Dados Espaciais. Os dados foram coletados no DATASUS, COFEN, Ministério da Saúde, Portal de Compras do Governo e Portal da Transparência. Quanto aos resultados, o índice revelou que nove estados do Norte e Nordeste registraram os menores índices e cinco estados do Sudeste e Sul apresentaram os maiores índices. Foi registrado um cluster baixo-baixo nos estados do Amazonas e Pará e um Cluster alto-alto em Minas Gerais, Rio de Janeiro, São Paulo e Paraná.

Abstract One of the concerns linked to the COVID-19 pandemic is the capacity of health systems to respond to the demand for care for people with the disease. The objective of this study was to create a COVID-19 response Healthcare Infrastructure Index (HII), calculate the index for each state in Brazil, and determine its spatial distribution within and across regions. The HII was constructed using principal component factor analysis. The adequacy of the statistical model was tested using the Kaiser-Meyer-Olkin test and Bartlett's test of sphericity. The spatial distribution of the HII was analyzed using exploratory spatial data analysis. The data were obtained from DATASUS, the Federal Nursing Council, Ministry of Health, Government Procurement Portal, and the Transparency Portal. The nine states in the country's North and Northeast regions showed the lowest indices, while the five states from the Southeast and South regions showed the highest indices. Low-low clusters were observed in Amazonas and Pará and high-high clusters were found in Minas Gerais, Rio de Janeiro, São Paulo, and Paraná.

Palliative and end-of-life care in COVID-19 management in sub-Saharan Africa: a matter of concern.

The COVID-19 pandemic has strained health care systems beyond capacity resulting in many people not having access to life-sustaining measures even in well-resourced countries. Palliative and end-of-life care are therefore essential to alleviate suffering and ensure a continuum of care for patients unlikely to survive. This is challenging in sub-Saharan Africa where lack of trained teams on basic palliative care and reduced access to opioids limit implementation of palliative and end-of-life care. At the same time, health care providers have to cope with local cultural conceptions of death and absence of advance care directives.

COVID-19 and the ethical issues of justice and rationing in health care, with particular regard to the Italian experience / Az igazságosság és a besorolás etikai problémái az egészségügyben, különös tekintettel a COVID-19-járvány olaszországi tapasztalataira.

Összefoglaló. A 2020. év elején kirobbant COVID-19-világjárvány többek között ráirányította a figyelmet az életmento-életfenntartó kezelések igazságos elosztásának érzékeny kérdésére is. Európán belül elsoként Olaszországot sújtotta a katasztrófa, a válsághelyzetben pedig az érzéstelenítés, fájdalomcsillapítás, újraélesztés és intenzív ellátás területén tevékenykedo szakemberek olasz társasága, a SIAARTI 2020. március 6-án közzétett egy 15 pontos ajánlást. E szerint utilitarista megközelítéssel a rendelkezésre álló szukös eroforrásokat azon betegek kezelésére kellene fordítani, akik túlélési esélye nagyobb, valamint több életévre számíthatnak a jövoben, mert ez biztosíthatja a leheto legtöbb ember számára a leheto legnagyobb hasznot. A javaslat komoly szakmai vitát robbantott ki, amely egyértelmuvé tette, hogy az orvosi eszközök igazságos elosztására vonatkozó diskurzust feltétlenül folytatni kell, nemcsak Olaszországon belül, hanem a pandémiától sújtott többi államban is. Orv Hetil. 2020; 161(45): 1899-1907. Summary. Among other queries, the explosion of the COVID-19 pandemic at the beginning of 2020 has firmly put in focus the sensitive issue of how to allocate scarcely available life-saving treatments in a fair and just manner. The first European country to face an emergency caused by the pandemic was Italy. In a rapidly escalating crisis, on 6th March 2020, the Italian Society of Anaesthesia, Analgesia, Resuscitation, and Intensive Care (SIAARTI) issued a series of 15 recommendations, suggesting that a utilitarian approach should be adopted in Italian health care and the extremely scarce resources should be reserved for patients with a greater probability of survival and life expectancy, in order to maximize the benefits for the largest possible number of people. The recommendations generated a heated debate among health care professionals, thereby evidencing that similar discussions must be initiated and pursued in all countries affected by the pandemic. Orv Hetil. 2020; 161(45): 1899-1907.

Health-care organization for the management and surveillance of SARS-CoV-2 infection in children during pandemic in Campania region, Italy.

BACKGROUND: In comparison with adults, severe acute respiratory syndrome coronavirus (SARS-CoV-2) infection in children has a milder course. The management of children with suspected or confirmed coronavirus disease (COVID-19) needs to be appropriately targeted. METHODS: We designed a hub-and-spoke system to provide healthcare indications based on the use of telemedicine and stringent admission criteria, coordinate local stakeholders and disseminate information. RESULT: Between March 24th and September 24th 2020, the Hub Centre managed a total of 208 children (52% males, median age, 5.2, IQR 2-9.6 years) with suspected or confirmed COVID-19. Among them, 174 were managed in cooperation with family pediatricians and 34 with hospital-based physicians. One hundred-four (50%) received a final diagnosis of SARS-CoV-2 infection. Application of stringent criteria for hospital admission based on clinical conditions, risk factors and respect of biocontainment measures, allowed to manage the majority of cases (74, 71.1%) through telemedicine. Thirty children (28%) were hospitalized (median length 10 days, IQR 5-19 days), mainly due to the presence of persistent fever, mild respiratory distress or co-infection occurring in infant or children with underlying conditions. However, the reasons for admission slightly changed over time. CONCLUSION: An hub-and-spoke system is effective in coordinate territorial health-care structures involved in management paediatric COVID-19 cases through telemedicine and the definition of stringent hospital admission criteria. The management of children with COVID-19 should be based on clinical conditions, assessed on a case-by-case critical evaluation, as well as on isolation measures, but may vary according to local epidemiological changes.

Re-organising primary health care to respond to the Coronavirus epidemic in Cape Town, South Africa.

Cape Town is currently one of the hotspots for COVID-19 on the African continent. The Metropolitan Health Services have re-organised their primary health care (PHC) services to tackle the epidemic with a community-orientated primary care perspective. Two key goals have guided the re-organisation, the need to maintain social distancing and reduce risk to people using the services and the need to prepare for an influx of people with COVID-19. Facilities were re-organised to have 'screening and streaming' at the entrance and patients were separated into hot and cold streams. Both streams had 'see and treat' stations for the rapid treatment of minor ailments. Patients in separate streams were then managed further. If patients with chronic conditions were stable, they were provided with home delivery of medication by community health workers. Community health workers also engaged in community-based screening and testing. Initial evaluation of PHC preparedness was generally good. However, a number of key issues were identified. Additional infrastructure was required in some facilities to keep the streams separate with the onset of winter. Managers had to actively address the anxiety and fears of the primary care workforce. Attention also needed to be given to the prevention and treatment of non-COVID conditions as utilisation of these services decreased. The epidemic exposed intersectoral and intrasectoral fault lines, particularly access to social services at a time when they were most needed. Community screening and testing had to be refocused due to limited laboratory capacity and a lengthening turnaround time.

Dangerous Pathogens as a Potential Problem for Public Health.

Pathogens are various organisms, such as viruses, bacteria, fungi, and protozoa, which can cause severe illnesses to their hosts. Throughout history, pathogens have accompanied human populations and caused various epidemics. One of the most significant outbreaks was the Black Death, which occurred in the 14th century and caused the death of one-third of Europe's population. Pathogens have also been studied for their use as biological warfare agents by the former Soviet Union, Japan, and the USA. Among bacteria and viruses, there are high priority agents that have a significant impact on public health. Bacillus anthracis, Francisella tularensis, Yersinia pestis, Variola virus, Filoviruses (Ebola, Marburg), Arenoviruses (Lassa), and influenza viruses are included in this group of agents. Outbreaks and infections caused by them might result in social disruption and panic, which is why special operations are needed for public health preparedness. Antibiotic-resistant bacteria that significantly impede treatment and recovery of patients are also valid threats. Furthermore, recent events related to the massive spread of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are an example of how virus-induced diseases cannot be ignored. The impact of outbreaks, such as SARS-CoV-2, have had far-reaching consequences beyond public health. The economic losses due to lockdowns are difficult to estimate, but it would take years to restore countries to pre-outbreak status. For countries affected by the 2019 coronavirus disease (COVID-19), their health systems have been overwhelmed, resulting in an increase in the mortality rate caused by diseases or injuries. Furthermore, outbreaks, such as SARS-CoV-2, will induce serious, wide-ranging (and possibly long-lasting) psychological problems among, not only health workers, but ordinary citizens (this is due to isolation, quarantine, etc.). The aim of this paper is to present the most dangerous pathogens, as well as general characterizations, mechanisms of action, and treatments.

Development and Performance of a Clinical Decision Support Tool to Inform Resource Utilization for Elective Operations.

Importance: Hospitals ceased most elective procedures during the height of coronavirus disease 2019 (COVID-19) infections. As hospitals begin to recommence elective procedures, it is necessary to have a means to assess how resource intensive a given case may be. Objective: To evaluate the development and performance of a clinical decision support tool to inform resource utilization for elective procedures. Design, Setting, and Participants: In this prognostic study, predictive modeling was used on retrospective electronic health records data from a large academic health system comprising 1 tertiary care hospital and 2 community hospitals of patients undergoing scheduled elective procedures from January 1, 2017, to March 1, 2020. Electronic health records data on case type, patient demographic characteristics, service utilization history, comorbidities, and medications were and abstracted and analyzed. Data were analyzed from April to June 2020. Main Outcomes and Measures: Predicitons of hospital length of stay, intensive care unit length of stay, need for mechanical ventilation, and need to be discharged to a skilled nursing facility. These predictions were generated using the random forests algorithm. Predicted probabilities were turned into risk classifications designed to give assessments of resource utilization risk. Results: Data from the electronic health records of 42 199 patients from 3 hospitals were abstracted for analysis. The median length of stay was 2.3 days (range, 1.3-4.2 days), 6416 patients (15.2%) were admitted to the intensive care unit, 1624 (3.8%) received mechanical ventilation, and 2843 (6.7%) were discharged to a skilled nursing facility. Predictive performance was strong with an area under the receiver operator characteristic ranging from 0.76 to 0.93. Sensitivity of the high-risk and medium-risk groupings was set at 95%. The negative predictive value of the low-risk grouping was 99%. We integrated the models into a daily refreshing Tableau dashboard to guide decision-making. Conclusions and Relevance: The clinical decision support tool is currently being used by surgical leadership to inform case scheduling. This work shows the importance of a learning health care environment in surgical care, using quantitative modeling to guide decision-making.

Improving management of hospitalised patients with COVID-19: algorithms and tools for implementation and measurement.

BACKGROUND: The COVID-19 pandemic represents an unprecedented challenge to healthcare systems and nations across the world. Particularly challenging are the lack of agreed-upon management guidelines and variations in practice. Our hospital is a large, secondary-care government hospital in Kuwait, which has increased its capacity by approximately 28% to manage the care of patients with COVID-19. The surge in capacity has necessitated the redeployment of staff who are not well-trained to manage such conditions. There was a great need to develop a tool to help redeployed staff in decision-making for patients with COVID-19, a tool which could also be used for training. METHODS: Based on the best available clinical knowledge and best practices, an eight member multidisciplinary group of clinical and quality experts undertook the development of a clinical algorithm-based toolkit to guide training and practice for the management of patients with COVID-19. The team followed Horabin and Lewis' seven-step approach in developing the algorithms and a five-step method in writing them. Moreover, we applied Rosenfeld et al's five points to each algorithm. RESULTS: A set of seven clinical algorithms and one illustrative layout diagram were developed. The algorithms were augmented with documentation forms, data-collection online forms and spreadsheets and an indicators' reference sheet to guide implementation and performance measurement. The final version underwent several revisions and amendments prior to approval. CONCLUSIONS: A large volume of published literature on the topic of COVID-19 pandemic was translated into a user-friendly, algorithm-based toolkit for the management of patients with COVID-19. This toolkit can be used for training and decision-making to improve the quality of care provided to patients with COVID-19.

A Social Shift: COVID-19 Disparities Prompt Emphasis on Value-Based Care.

COVID-19 disparities prompt Medicare to call for stronger emphasis on value-based care.

Exploring views and experiences of how infections are detected and managed in practice by nurses, care workers and manager's in nursing homes in England and Sweden: a survey protocol.

INTRODUCTION: In order to avoid unnecessary hospital admission and associated complications, there is an urgent need to improve the early detection of infection in nursing home residents. Monitoring signs and symptoms with checklists or aids called decision support tools may help nursing home staff to detect infection in residents, particularly during the current COVID-19 pandemic.We plan to conduct a survey exploring views and experiences of how infections are detected and managed in practice by nurses, care workers and managers in nursing homes in England and Sweden. METHODS AND ANALYSIS: An international cross-sectional descriptive survey, using a pretested questionnaire, will be used to explore nurses, care workers and managers views and experiences of how infections are detected and managed in practice in nursing homes. Data will be analysed descriptively and univariate associations between personal and organisational factors explored. This will help identify important factors related to awareness, knowledge, attitudes, belief and skills likely to affect future implementation of a decision support tool for the early detection of infection in nursing home residents. ETHICS AND DISSEMINATION: This study was approved using the self-certification process at the University of Surrey and Linköping University ethics committee (Approval 2018/514-32) in 2018. Study findings will be disseminated through community/stakeholder/service user engagement events in each country, publication in academic peer-reviewed journals and conference presentations. A LAY summary will be provided to participants who indicate they would like to receive this information.This is the first stage of a plan of work to revise and evaluate the Early Detection of Infection Scale (EDIS) tool and its effect on managing infections and reducing unplanned hospital admissions in nursing home residents. Implementation of the EDIS tool may have important implications for the healthcare economy; this will be explored in cost-benefit analyses as the work progresses.

How achievable are COVID-19 clinical trial recruitment targets? A UK observational cohort study and trials registry analysis.

OBJECTIVES: To analyse enrolment to interventional trials during the first wave of the COVID-19 pandemic in England and describe the barriers to successful recruitment in the circumstance of a further wave or future pandemics. DESIGN: We analysed registered interventional COVID-19 trial data and concurrently did a prospective observational study of hospitalised patients with COVID-19 who were being assessed for eligibility to one of the RECOVERY, C19-ACS or SIMPLE trials. SETTING: Interventional COVID-19 trial data were analysed from the clinicaltrials.gov and International Standard Randomized Controlled Trial Number databases on 12 July 2020. The patient cohort was taken from five centres in a respiratory National Institute for Health Research network. Population and modelling data were taken from published reports from the UK government and Medical Research Council Biostatistics Unit. PARTICIPANTS: 2082 consecutive admitted patients with laboratory-confirmed SARS-CoV-2 infection from 27 March 2020 were included. MAIN OUTCOME MEASURES: Proportions enrolled, and reasons for exclusion from the aforementioned trials. Comparisons of trial recruitment targets with estimated feasible recruitment numbers. RESULTS: Analysis of trial registration data for COVID-19 treatment studies enrolling in England showed that by 12 July 2020, 29 142 participants were needed. In the observational study, 430 (20.7%) proceeded to randomisation. 82 (3.9%) declined participation, 699 (33.6%) were excluded on clinical grounds, 363 (17.4%) were medically fit for discharge and 153 (7.3%) were receiving palliative care. With 111 037 people hospitalised with COVID-19 in England by 12 July 2020, we determine that 22 985 people were potentially suitable for trial enrolment. We estimate a UK hospitalisation rate of 2.38%, and that another 1.25 million infections would be required to meet recruitment targets of ongoing trials. CONCLUSIONS: Feasible recruitment rates, study design and proliferation of trials can limit the number, and size, that will successfully complete recruitment. We consider that fewer, more appropriately designed trials, prioritising cooperation between centres would maximise productivity in a further wave.

Three Levels of Autonomy and One Long-Term Solution for Native American Health Care.

Native Americans have twice the poverty rate of the general US population, suffer significant health inequity, and are chronically underrepresented, at only 0.08%, in the US physician workforce. The COVID-19 pandemic has illuminated key ethical, clinical, and economic complexities in health decision making among Native patients. This article discusses 3 levels of autonomy relevant to health decisions, including taking care of our own by increasing numbers of Native medical students.

Medical costs of keeping the US economy open during COVID-19.

We use an individual based model and national level epidemic simulations to estimate the medical costs of keeping the US economy open during COVID-19 pandemic under different counterfactual scenarios. We model an unmitigated scenario and 12 mitigation scenarios which differ in compliance behavior to social distancing strategies and in the duration of the stay-home order. Under each scenario we estimate the number of people who are likely to get infected and require medical attention, hospitalization, and ventilators. Given the per capita medical cost for each of these health states, we compute the total medical costs for each scenario and show the tradeoffs between deaths, costs, infections, compliance and the duration of stay-home order. We also consider the hospital bed capacity of each Hospital Referral Region (HRR) in the US to estimate the deficit in beds each HRR will likely encounter given the demand for hospital beds. We consider a case where HRRs share hospital beds among the neighboring HRRs during a surge in demand beyond the available beds and the impact it has in controlling additional deaths.