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The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has already taken on pandemic proportions, affecting over 100 countries in a matter of weeks. A global response to prepare health systems worldwide is imperative. Although containment measures in China have reduced new cases by more than 90%, this reduction is not the case elsewhere, and Italy has been particularly affected. There is now grave concern regarding the Italian national health system's capacity to effectively respond to the needs of patients who are infected and require intensive care for SARS-CoV-2 pneumonia. The percentage of patients in intensive care reported daily in Italy between March 1 and March 11, 2020, has consistently been between 9% and 11% of patients who are actively infected. The number of patients infected since Feb 21 in Italy closely follows an exponential trend. If this trend continues for 1 more week, there will be 30 000 infected patients. Intensive care units will then be at maximum capacity; up to 4000 hospital beds will be needed by mid-April, 2020. Our analysis might help political leaders and health authorities to allocate enough resources, including personnel, beds, and intensive care facilities, to manage the situation in the next few days and weeks. If the Italian outbreak follows a similar trend as in Hubei province, China, the number of newly infected patients could start to decrease within 3–4 days, departing from the exponential trend. However, this cannot currently be predicted because of differences between social distancing measures and the capacity to quickly build dedicated facilities in China.

The Covid-19 pandemic has already stressed health care systems throughout the world, requiring rationing of medical equipment and care. The authors discuss the ethical values relevant to health care rationing and provide six recommendations to guide fair allocation of scarce medical resources during the pandemic.

How epidemiologists rushed to model the coronavirus pandemic. How epidemiologists rushed to model the coronavirus pandemic.

To mitigate the effects of coronavirus disease 2019 (COVID-19), jurisdictions worldwide ramped down nonemergent surgeries, creating a global surgical backlog. We sought to estimate the size of the nonemergent surgical backlog during COVID-19 in Ontario, Canada, and the time and resources required to clear the backlog. We used 6 Ontario or Canadian population administrative sources to obtain data covering part or all of the period between Jan. 1, 2017, and June 13, 2020, on historical volumes and operating room throughput distributions by surgery type and region, and lengths of stay in ward and intensive care unit (ICU) beds. We used time series forecasting, queuing models and probabilistic sensitivity analysis to estimate the size of the backlog and clearance time for a +10% (+1 day per week at 50% capacity) surge scenario. Between Mar. 15 and June 13, 2020, the estimated backlog in Ontario was 148 364 surgeries (95% prediction interval 124 508–174 589), an average weekly increase of 11 413 surgeries. Estimated backlog clearance time is 84 weeks (95% confidence interval [CI] 46–145), with an estimated weekly throughput of 717 patients (95% CI 326–1367) requiring 719 operating room hours (95% CI 431–1038), 265 ward beds (95% CI 87–678) and 9 ICU beds (95% CI 4–20) per week. The magnitude of the surgical backlog from COVID-19 raises serious implications for the recovery phase in Ontario. Our framework for modelling surgical backlog recovery can be adapted to other jurisdictions, using local data to assist with planning.

Increasing numbers of coronavirus disease 2019 (COVID-19) cases in Canada may create substantial demand for hospital admission and critical care. We evaluated the extent to which self-isolation of mildly ill people delays the peak of outbreaks and reduces the need for this care in each Canadian province. We developed a computational model and simulated scenarios for COVID-19 outbreaks within each province. Using estimates of COVID-19 characteristics, we projected the hospital and intensive care unit (ICU) bed requirements without self-isolation, assuming an average number of 2.5 secondary cases, and compared scenarios in which different proportions of mildly ill people practised self-isolation 24 hours after symptom onset. Without self-isolation, the peak of outbreaks would occur in the first half of June, and an average of 569 ICU bed days per 10 000 population would be needed. When 20% of cases practised self-isolation, the peak was delayed by 2–4 weeks, and ICU bed requirement was reduced by 23.5% compared with no self-isolation. Increasing self-isolation to 40% reduced ICU use by 53.6% and delayed the peak of infection by an additional 2–4 weeks. Assuming current ICU bed occupancy rates above 80% and self-isolation of 40%, demand would still exceed available (unoccupied) ICU bed capacity. At the peak of COVID-19 outbreaks, the need for ICU beds will exceed the total number of ICU beds even with self-isolation at 40%. Our results show the coming challenge for the health care system in Canada and the potential role of self-isolation in reducing demand for hospital-based and ICU care.

Purpose To quantify the numbers of critical care beds in Europe and to understand the differences in these numbers between countries when corrected for population size and gross domestic product. Methods Prospective data collection of critical care bed numbers for each country in Europe from July 2010 to July 2011. Sources were identified in each country that could provide data on numbers of critical care beds (intensive care and intermediate care). These data were then cross-referenced with data from international databases describing population size and age, gross domestic product (GDP), expenditure on healthcare and numbers of acute care beds. Results We identified 2,068,892 acute care beds and 73,585 (2.8 %) critical care beds. Due to the heterogeneous descriptions of these beds in the individual countries it was not possible to discriminate between intensive care and intermediate care in most cases. On average there were 11.5 critical care beds per 100,000 head of population, with marked differences between countries (Germany 29.2, Portugal 4.2). The numbers of critical care beds per country corrected for population size were positively correlated with GDP ( r 2  = 0.16, p  = 0.05), numbers of acute care beds corrected for population ( r 2  = 0.12, p  = 0.05) and the percentage of acute care beds designated as critical care ( r 2  = 0.59, p  < 0.0001). They were not correlated with the proportion of GDP expended on healthcare. Conclusions Critical care bed numbers vary considerably between countries in Europe. Better understanding of these numbers should facilitate improved planning for critical care capacity and utilization in the future.

PurposeThe coronavirus disease 2019 (COVID-19) poses major challenges to health-care systems worldwide. This pandemic demonstrates the importance of timely access to intensive care and, therefore, this study aims to explore the accessibility of intensive care beds in 14 European countries and its impact on the COVID-19 case fatality ratio (CFR).MethodsWe examined access to intensive care beds by deriving (1) a regional ratio of intensive care beds to 100,000 population capita (accessibility index, AI) and (2) the distance to the closest intensive care unit. The cross-sectional analysis was performed at a 5-by-5 km spatial resolution and results were summarized nationally for 14 European countries. The relationship between AI and CFR was analyzed at the regional level.ResultsWe found national-level differences in the levels of access to intensive care beds. The AI was highest in Germany (AI = 35.3), followed by Estonia (AI = 33.5) and Austria (AI = 26.4), and lowest in Sweden (AI = 5) and Denmark (AI = 6.4). The average travel distance to the closest hospital was highest in Croatia (25.3 min by car) and lowest in Luxembourg (9.1 min). Subnational results illustrate that capacity was associated with population density and national-level inventories. The correlation analysis revealed a negative correlation of ICU accessibility and COVID-19 CFR (r = − 0.57; p < 0.001).ConclusionGeographical access to intensive care beds varies significantly across European countries and low ICU accessibility was associated with a higher proportion of COVID-19 deaths to cases (CFR). Important differences in access are due to the sizes of national resource inventories and the distribution of health-care facilities relative to the human population. Our findings provide a resource for officials planning public health responses beyond the current COVID-19 pandemic, such as identifying potential locations suitable for temporary facilities or establishing logistical plans for moving severely ill patients to facilities with available beds.

Although the number of intensive care unit (ICU) beds in the United States is increasing, it is unknown whether this trend is consistent across all regions. We sought to better characterize regional variation in ICU bed changes over time and identify regional characteristics associated with these changes. We used data from the Centers for Medicare and Medicaid Services and the U.S. Census to summarize the numbers of hospitals, hospital beds, ICU beds, and ICU occupancy at the level of Dartmouth Atlas hospital referral region from 2000 to 2009. We categorized regions into quartiles of bed change over the study interval and examined the relationship between change categories, regional characteristics, and population characteristics over time. From 2000 to 2009 the national number of ICU beds increased 15%, from 67,579 to 77,809, mirroring population. However, there was substantial regional variation in absolute changes (median, +16 ICU beds; interquartile range, -3 to +51) and population-adjusted changes (median, +0.9 ICU beds per 100,000; interquartile range, -3.8 to +5.9), with 25.0% of regions accounting for 74.8% of overall growth. At baseline, regions with increasing numbers of ICU beds had larger populations, lower ICU beds per 100,000 capita, higher average ICU occupancy, and greater market competition as measured by the Herfindahl-Hirschman Index (P < 0.001 for all comparisons). National trends in ICU bed growth are not uniformly reflected at the regional level, with most growth occurring in a small number of highly populated regions.

The outcome of patients with ruptured abdominal aortic aneurysm (rAAA) varies by country. Study of practice differences might allow the formulation of pathways to improve care. We compared data from the Hospital Episode Statistics for England and the Nationwide Inpatient Sample for the USA for patients admitted to hospital with rAAA from 2005 to 2010. Primary outcomes were in-hospital mortality, mortality after intervention, and decision to follow non-corrective treatment. In-hospital mortality and the rate of non-corrective treatment were analysed by binary logistic regression for each health-care system, after adjustment for age, sex, year, and Charlson comorbidity index. The study included 11 799 patients with rAAA in England and 23 838 patients with rAAA in the USA. In-hospital mortality was lower in the USA than in England (53·05% [95% CI 51·26–54·85] vs 65·90%; p<0·0001). Intervention (open or endovascular repair) was offered to a greater proportion of cases in the USA than in England (19 174 [80·43%] vs 6897 [58·45%]; p<0·0001) and endovascular repair was more common in the USA than in England (4003 [20·88%] vs 589 [8·54%]; p<0·0001). Postintervention mortality was similar in both countries (41·77% for England and 41·65% for USA). These observations persisted in age-matched and sex-matched comparisons. In both countries, reduced mortality was associated with increased use of endovascular repair, increased hospital caseload (volume) for rAAA, high hospital bed capacity, hospitals with teaching status, and admission on a weekday. In-hospital survival from rAAA, intervention rates, and uptake of endovascular repair are lower in England than in the USA. In England and the USA, the lowest mortality for rAAA was seen in teaching hospitals with larger bed capacities and doing a greater proportion of cases with endovascular repair. These common factors suggest strategies for improving outcomes for patients with rAAA. None.

In 2011, Fukushima was struck by a triple disaster: an earthquake, tsunamis, and a nuclear accident. In the aftermath, there was much fear among hospital staff members about radiation exposure and many staff members failed to report to work. One objective is to measure this shortage in hospital staff and another is to compare the difference in recovery by hospital types and by categories of hospital staff. The monthly records of the number of staff members from May 2011 to September 2012 were extracted anonymously from the records of 7 local hospitals in the Soso district in Fukushima. Change in the number of staff was analyzed. Staff shortages at hospitals reached a maximum within one month after the disaster (47% reported to work). The shortage of clerks was the most severe (38% reported to work), followed by nurses (48% reported to work). The shortages remained even 18 months after the disaster. After a disaster in which the damage to hospital functions surpasses the structural damage, massive support of human resources in the acute phase and a smaller volume of support in the mid-term phase appear to be required, particularly for non-medical staff.