ABSTRACT
Benchmarking different aspects of air transport, and especially airport operations, is a research topic both important and complex, as proposed solutions are usually limited by data availability and underlying hypotheses. We here propose the use of two well-known statistical physics concepts, the Hurst exponent and the irreversibility, to measure the presence of interactions between landing flights from a macro-scale perspective. We firstly present a synthetic model of landings at an airport, showing how the two metrics are able to detect interactions arising from high volumes of traffic. Real landing data for twelve major European airports and ten Chinese ones are then analysed, showing that more interactions are present than what expected for the corresponding traffic. Results are nevertheless not homogeneous, with some airports (most notably Milano Malpensa, Madrid and Paris Charles de Gaulle) yielding statistically significant high values;and with Frankfurt airport having been especially impacted by the COVID-19 pandemics, which resulted in an increase in interactions in spite of a reduction in traffic. Some possible reasons behind these results, and their operational significance in terms of efficiency and safety, are finally discussed. • We characterise landing interactions using the Hurst exponent and the irreversibility. • Airports can be characterised according to the interactions between landing aircraft. • Most airports present a clear drop in complexity following March 2020. • Frankfurt airport is the exception, possibly due to changes in traffic patterns. [ FROM AUTHOR]
ABSTRACT
Benchmarking different aspects of air transport, and especially airport operations, is a research topic both important and complex, as proposed solutions are usually limited by data availability and underlying hypotheses. We here propose the use of two well-known statistical physics concepts, the Hurst exponent and the irreversibility, to measure the presence of interactions between landing flights from a macro-scale perspective. We firstly present a synthetic model of landings at an airport, showing how the two metrics are able to detect interactions arising from high volumes of traffic. Real landing data for twelve major European airports and ten Chinese ones are then analysed, showing that more interactions are present than what expected for the corresponding traffic. Results are nevertheless not homogeneous, with some airports (most notably Milano Malpensa, Madrid and Paris Charles de Gaulle) yielding statistically significant high values;and with Frankfurt airport having been especially impacted by the COVID-19 pandemics, which resulted in an increase in interactions in spite of a reduction in traffic. Some possible reasons behind these results, and their operational significance in terms of efficiency and safety, are finally discussed.
ABSTRACT
Approximately 5% of COVID-19 patients will have a severe disease requiring invasive or non-invasive mechanical ventilation. In this conditions, sedatives and analgesics are fundamental to promote tolerance, comfort and synchrony with the mechanical ventilator. High and unusual requirements for sedation, analgesics and neuromuscular blockers have been reported in these patients, contributing to prolonged exposure, a high rate of delirium and prolongation of mechanical ventilation. These factors, added to the progressive shortage of these drugs, a high demand for care and less capacity for personalized attention, have created an adverse scenario for their proper and rational use. This paper proposes different pharmacotherapeutic optimization strategies for a rational management of sedation, analgesia and neuromuscular block in critically ill patients with COVID-19, with the therapeutic alternatives available in Chile.
Subject(s)
Analgesia , COVID-19 , Chile , Critical Illness/therapy , Humans , Hypnotics and Sedatives , Respiration, Artificial , SARS-CoV-2ABSTRACT
BACKGROUND: During the first pandemic wave, Covid-19 reached Latin America cities. AIM: To report clinical features and outcomes of a group of patients with Covid-19 admitted to a Chilean regional reference Center. MATERIAL AND METHODS: Cases were identified by a compatible clinical picture and a positive PCR or serological test. Clinical features of patients were retrieved from medical records. RESULTS: Forty-seven adult patients (45 diagnosed by PCR, 2 by serology) were admitted between epidemiological weeks 13 to 33, corresponding to 4.4% of total regional cases. Hospitalization occurred at a median of 10 days after onset of symptoms. Fifty one percent of patients had 60 years or more. Hypertension, obesity and diabetes mellitus were present in 57, 45 and 32 % of cases, respectively. Nineteen percent of patients had no comorbid condition nor were elderly. Two cases were women in their second trimester of pregnancy. Positive IgM or IgM/IgG results obtained by rapid serological testing, had limited sensitivity during the first week (67%). Seventeen patients (36.2%) were transferred to an intensive care unit (ICU) due to respiratory failure. Chest imaging demonstrated a classical COVID-19 pattern in 87%. By univariate analysis, admission to ICU was significantly associated with tachypnea and higher CALL (comorbidity, age, lymphocyte count and lactate dehydrogenase) score. Four patients died (rendering a hospital mortality of 8.5%) and length of stay was ≥ 14 days in 46.8% of patients. By univariate analysis, mortality was associated with immunosuppression and ICU admission. CONCLUSIONS: In our regional Center, patients admitted with COVID-19 had usual risk factors and had a prolonged stay. Hospital mortality was associated with immunosuppression and ICU admission.