Clinical characteristics, complications, and outcomes of severe COVID-19 ARDS patients supported by ECMO and triaged for lung transplantations

Objectives: More than 200 patients have benefited from lung transplantation who failed to recover from COVID-19-induced acute respiratory distress (ARDS) with conventional ventilatory support and/ or extracorporeal membrane oxygenation support (ECMO) in USA. We aim to share our experience and lessons learned at our institute through this case series. Method(s): After IRB approval, we performed a retrospective chart review and identified 37 patients who received ECMO for COVID-19 induced ARDS between May 2020 through January 2022. Out of these, 12 received a formal consultation from the transplant team. We studied patient characteristics, interventions during ECMO support, and evaluation outcomes. Result(s): Most of our patients had single organ failure i.e., lung, except for two who required dialysis after ECMO initiation. Six out of the 12 patients received bilateral lung transplant. One patient received the transplant before ECMO initiation. However, the patient required two runs of ECMO after the transplant due to postop complications from suspected COVID19 reinfection and deceased on postoperative day 101. All the patients after transplant had an expedited recovery except one who required prolonged hospitalization before starting physical therapy. The median length of hospital stay for the transplant group was 148 (89- 194) days and for the non-transplant group was 114 (58-178) days. The 30-day survival rate was 100% for the transplant group. At a median follow-up of 207 (0- 456) days after discharge, 5(83.3%) patients in the transplant group and 3(50%) patients in the nontransplant group were alive. In the non-transplant group, 4 patients received ECMO support for more than 75 days and at last follow-up 2 were alive and functioning well without needing new lungs. This asks for an objective prospective study to define the timeline of irreversibility of the lung injury. Conclusion(s): Lung transplantation is a viable salvage option in patients with COVI-19 induced irreversible lung injury. However, the irreversibility of the lung injury and the timing of lung transplant remains to be determined case-by-case. (Figure Presented).

Environmental factors are associated to hospital outcomes in COVID-19 patients during lockdown and post-lockdown in 2020: A nationwide study.

OBJECTIVE: This study analyzed, at a postcode detailed level, the relation-ship between short-term exposure to environmental factors and hospital ad-missions, in-hospital mortality, ICU admission, and ICU mortality due to COVID-19 during the lockdown and post-lockdown 2020 period in Spain. METHODS: We performed a nationwide population-based retrospective study on 208,744 patients admitted to Spanish hospitals due to COVID-19 based on the Minimum Basic Data Set (MBDS) during the first two waves of the pandemic in 2020. Environmental data were obtained from Copernicus Atmosphere Monitoring Service. The association was assessed by a generalized additive model. RESULTS: PM2.5 was the most critical environmental factor related to hospital admissions and hospital mortality due to COVID-19 during the lockdown in Spain, PM10, NO2, and SO2and also showed associations. The effect was considerably reduced during the post-lockdown period. ICU admissions in COVID-19 patients were mainly associated with PM2.5, PM10, NO2, and SO2 during the lockdown as well. During the lockdown, exposure to PM2.5 and PM10 were the most critical environmental factors related to ICU mortality in COVID-19. CONCLUSION: Short-term exposure to air pollutants impacts COVID-19 out-comes during the lockdown, especially PM2.5, PM10, NO2, and SO2. These pollutants are associated with hospital admission, hospital mortality and ICU admission, while ICU mortality is mainly associated with PM2.5 and PM10. Our findings reveal the importance of monitoring air pollutants in respiratory infectious diseases.

Remote vs Local Ex-Vivo Lung Perfusion, a Single Center Experience

Ex vivo lung perfusion (EVLP) could impact waitlist morbidity and mortality by increasing the number of transplantable allografts. Remote EVLP with a centralized lung evaluation system (CLES) at a dedicated facility has been shown to be feasible. There are no reports comparing the outcomes of remote vs local EVLP. Our institution has access to both modes of EVLP. Hereby, we describe the outcomes for remote EVLP (r-EVLP) and local EVLP (l-EVLP) at Mayo Clinic Florida. We did a retrospective analysis of the demographics, clinical characteristics, and outcomes of recipients of lungs that underwent EVLP as part of a r-EVLP clinical trial (NCT02234128) or at Lung Bioengineering Jacksonville (l-EVLP) with data obtained from the patient's electronic medical record. The r-EVLP cohort (n=10) tended to be younger than the l-RVLP cohort (n=12) (57.3 vs 61.6 years), and had a lower percentage of female recipients (20% vs 41.67% respectively). 80% of recipients were white in both cohorts. Most recipients were in the diagnosis group D (restrictive lung disease) in both cohorts. Three recipients in the l-EVLP group received a lung transplant due to complications from COVID-19. There were 5 single lung transplants (SLTx) in the r-EVLP (50%) and one in l-EVLP (8.33%). Lungs from donors after circulatory death (DCD) accounted for 40% of the allografts in the r-EVLP cohort and for 16.67% in the l-EVLP group. The median cold ischemia time (CIT) 1 was 5h:27min for the r-EVLP and 4h:35min for l-EVLP. The median CIT-2 time was 4h:16min for the r-EVLP and 3h:12min for the l-EVLP. EVLP time was similar for both groups. The median total preservation time was 13h:44min for the r-EVLP and 11h:38min for the l-EVLP cohorts. One (10%) in the r-EVLP and five (42%) in the l-EVLP groups were on ECMO at 72 hours post-transplant. Most of the remaining patients in both groups had a PGD-1 at 72 hours. All patients were alive at 30 days, and there was one death on each group at 1-year. At our center, survival at 1-year appeared similar in recipients of lungs assessed on r-EVLP or l-EVLP. Postoperative ECMO was used more frequently in the l-EVLP group. Median CIT-1 and CIT-2 were longer in the r-EVLP compared to the l-EVLP group by 52 and 64 minutes, respectively. Limitations of this study include single center retrospective experience, small sample size and lack of long-term outcomes. Future research comparing r-EVLP vs l-EVLP is warranted. [ FROM AUTHOR] Copyright of Journal of Heart & Lung Transplantation is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Crisis Periods Detection on NASDAQ Index Via EEMD-AE

It is proposed to identify the beginning and end of the SARS-CoV-2 and subprime crises on the NASDAQ. The EEMD was used to decompose the index into consecutive series with the same number of components and their correlation coefficients were calculated, the power spectrum of the original series was also analyzed. Signals of instability associated with changes in both the components' correlations and the NASDAQ spectrum were identified. It is recommended to apply the procedure on other series and other crises;likewise, the method is based on the detection of discrepancies, thus being a monitoring tool, but not one of quantitative forecasts. The originality of the work lies in the use of the modified EEMD for the decomposition of consecutive series in the same number of components, and the use of the correlation coefficient between components and the spectrum of the original series as measures of system stability. The approach proved to be useful for identifying and anticipating large changes in the behavior of a time series. © 2022 The authors.

RWD114 Investigating the Impacts of Comorbid Conditions on Costs and Length of Stay in Secondary Care Among Adults Infected With Influenza in England

Objectives: The burden of influenza varies across time and is affected by variations in circulating strains, population immunity, vaccination coverage and other risk factors including comorbidities and age. This study explored the impact of the presence of comorbidities on influenza-related hospitalisation costs and length of stay (LOS) in adults. Method(s): The study analysed four years of pre-COVID HES data (September 2016 - March 2020) and extracted adult patients with an influenza diagnosis (ICD-10 code J09-J11 in the primary or secondary location) in a day case or inpatient setting, identifying all patients with primary or secondary diagnosis related to any relevant comorbidity in the influenza spell. Hospitalisation costs and LOS were analysed by age, gender, and presence of comorbidities. Multi-level regression models were run on hospitalisation LOS and costs to ensure estimates captured any within-patient effects and adjusted for age, gender and other comorbid conditions. Result(s): In total, 119,495 patients were hospitalised with influenza generating a total cost of 401m, an average of 3,159 per spell. The average spell LOS and cost increased with age and the presence of comorbidities. There was a 4-day difference in median length of stay between those with and without comorbidities (6 and 2 days, respectively). Those with comorbidities recorded average costs of 3,569 compared to 1,458 for those without. Chronic heart disease was the most common comorbid condition and increased average cost even further to 4,397. Presence of comorbidities was significantly associated with hospitalisation cost;the cost for a patient with comorbidities was 214% of the cost for a patient without [95% CI 208-221%, p<0.01]. Conclusion(s): The study demonstrates the effect of comorbid conditions on influenza-related hospitalisation costs and length of stay (LOS) in adults. It strengthens the value of annual immunization for those in at-risk clinical groups in order to reduce the clinical and economic burden. Copyright © 2022

Economic Burden of the 2020 COVID-19 Hospitalizations in Spain.

This economic evaluation reports the total and per patient costs of inpatient care for COVID-19 in Spain in 2020.

BITTER ORANGES OF SEVILLE: ESSENTIAL OILS AND BIOFLAVONOIDS

Since ancient times, the different parts of the bitter orange of Seville have been used as food or for healing. One of its current main applications is the obtaining of a wide range of flavonoids which, after years of research and development, have proved to provide numerous benefits for human health including action against COVID-19, which is under research at laboratory level. Among the flavonoids found in the bitter orange of Seville naringin can be highlighted, which is very beneficial for human health. On the other hand, essential oils have been extracted and used since ancient times, from ritual and religious uses to the current uses in cosmetics, perfumery, food and health. This chapter overviews the history of the bitter oranges of Seville, the essential oils and naringin (a bioflavonoid) that can be extracted from them and their potential applications. © 2021 by Nova Science Publishers, Inc.

Neuropsychiatric symptomatology in post-COVID syndrome. Intervention proposal and referral from primary care

SARS-CoV-2 infection is a multiorgan disease with a wide spectrum of clinical mani-festations, including neurological and psychiatric, which are expressed in all stages of the disease and often has long-term symptoms, called post-COVID syndrome. Among the neuropsychiatric symptoms derived from this syndrome, in this article we focus on headache, cognitive impairment, taste and smell alterations, depression, anxiety and sleep disorders. Intervention algorithms for these symptoms in primary care establishing criteria for referral to specialized care are proposed. (C) 2021 Sociedad Espanola de Medicos de Atencion Primaria (SEMERGEN). Published by Elsevier Espana, S.L.U. All rights reserved.

Hospitalized COVID-19 Patients with Severe Acute Respiratory Syndrome: A Population-Based Registry Analysis to Assess Clinical Findings, Pharmacological Treatment and Survival.

Background and Objectives: One of the most serious clinical outcomes in hospitalized patients with COVID-19 is severe acute respiratory syndrome (SARS). The aim is to analyze pharmacological treatment, survival and the main mortality predictors. Materials and Methods: A real-world data study from COVID-19-hospitalized patients with SARS from 1 March to 31 May 2020 has been carried out. Variables such as hospital length of stay, ventilation type and clinical outcomes have been taken into account. Results: In Castile and Leon, 14.03% of the 7307 in-hospital COVID-19 patients developed SARS, with a mortality rate of 42.53%. SARS prevalence was doubled in males compared to females, and 78.54% had an age of 65 years or more. The most commonly used medicines were antibiotics (89.27%), antimalarials (68.1%) and corticosteroids (55.9%). Survival of patients developing SARS was lower compared to patients without this complication (12 vs. 13 days). The main death predictors were disseminated intravascular coagulation (DIC) (OR: 13.87) and age (>65 years) (OR: 7.35). Conclusions: Patients older than 65 years who develop DIC have a higher probability of hospital death. Tocilizumab and steroids have been linked to a lower incidence of hospital death, being the main treatment for COVID-19 hospitalized patients with SARS.

Hospitalized COVID-19 Patients with Severe Acute Respiratory Syndrome: A Population-Based Registry Analysis to Assess Clinical Findings, Pharmacological Treatment and Survival

Background and Objectives: One of the most serious clinical outcomes in hospitalized patients with COVID-19 is severe acute respiratory syndrome (SARS). The aim is to analyze pharmacological treatment, survival and the main mortality predictors. Materials and Methods: A real-world data study from COVID-19-hospitalized patients with SARS from 1 March to 31 May 2020 has been carried out. Variables such as hospital length of stay, ventilation type and clinical outcomes have been taken into account. Results: In Castile and Leon, 14.03% of the 7307 in-hospital COVID-19 patients developed SARS, with a mortality rate of 42.53%. SARS prevalence was doubled in males compared to females, and 78.54% had an age of 65 years or more. The most commonly used medicines were antibiotics (89.27%), antimalarials (68.1%) and corticosteroids (55.9%). Survival of patients developing SARS was lower compared to patients without this complication (12 vs. 13 days). The main death predictors were disseminated intravascular coagulation (DIC) (OR: 13.87) and age (>65 years) (OR: 7.35). Conclusions: Patients older than 65 years who develop DIC have a higher probability of hospital death. Tocilizumab and steroids have been linked to a lower incidence of hospital death, being the main treatment for COVID-19 hospitalized patients with SARS.

A novel approach to discover numerical association based on the coronavirus optimization algorithm

The disease caused by the SARS-CoV-2 (COVID-19) has affected millions of people around the world since its detection in 2019. This pandemic inspired the development of the Coronavirus Optimization Algorithm (CVOA), a bio-inspired metaheuristic that was originally used to adjust deep learning models for time series forecasting, by means of a binary codification. In this paper, a integer codification for the CVOA individual is introduced and used for optimizing a novel approach for numerical association rules mining. As an application case, the prediction of earthquakes of large magnitude has been addressed. This kind of events are rare and, therefore, they can be characterized by rules with very high interest or lift and low support. Thus, the algorithm has been applied to the extraction of rules meeting specific criteria in an earthquake data set, provided by the National Geographic Institute of Spain. The results show CVOA as a promising tool for numerical association rules mining, obtaining rules with useful and meaningful information for predicting the occurrence of large earthquakes. © 2022 Owner/Author.

[Neuropsychiatric symptomatology in post-COVID syndrome. Intervention proposal and referral from primary care]. / Sintomatología neuropsiquiátrica en el síndrome post-COVID. Propuesta de manejo y derivación desde atención primaria.

SARS-CoV-2 infection is a multiorgan disease with a wide spectrum of clinical manifestations, including neurological and psychiatric, which are expressed in all stages of the disease and often has long-term symptoms, called post-COVID syndrome. Among the neuropsychiatric symptoms derived from this syndrome, in this article we focus on headache, cognitive impairment, taste and smell alterations, depression, anxiety and sleep disorders. Intervention algorithms for these symptoms in primary care establishing criteria for referral to specialized care are proposed.

A deep LSTM network for the Spanish electricity consumption forecasting

Nowadays, electricity is a basic commodity necessary for the well-being of any modern society. Due to the growth in electricity consumption in recent years, mainly in large cities, electricity forecasting is key to the management of an efficient, sustainable and safe smart grid for the consumer. In this work, a deep neural network is proposed to address the electricity consumption forecasting in the short-term, namely, a long short-term memory (LSTM) network due to its ability to deal with sequential data such as time-series data. First, the optimal values for certain hyper-parameters have been obtained by a random search and a metaheuristic, called coronavirus optimization algorithm (CVOA), based on the propagation of the SARS-Cov-2 virus. Then, the optimal LSTM has been applied to predict the electricity demand with 4-h forecast horizon. Results using Spanish electricity data during nine years and half measured with 10-min frequency are presented and discussed. Finally, the performance of the proposed LSTM using random search and the LSTM using CVOA is compared, on the one hand, with that of recently published deep neural networks (such as a deep feed-forward neural network optimized with a grid search) and temporal fusion transformers optimized with a sampling algorithm, and, on the other hand, with traditional machine learning techniques, such as a linear regression, decision trees and tree-based ensemble techniques (gradient-boosted trees and random forest), achieving the smallest prediction error below 1.5%.

Effect of angiotensin-converting enzyme inhibitors and angiotensin receptor blockers on the short-term prognosis of COVID-19 infection

Background: Questions emerged about safety renin-angiotensin system (RAS) inhibitors (angiotensin-converting enzyme (ACE) inhibitors and angiotensin-receptor blockers (ARBs)) in patients diagnosed with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Our objective was to evaluate the safety of this treatment in a Spanish cohort during 2020 pandemic. Methods: Observational study including all consecutive patients (≥40 years old) diagnosed with SARS-CoV-2 through PCR in the microbiology laboratory of our hospital, since March 2nd to 20th 2020. Clinical characteristics and drugs were recorded. Primary end-point (PE) was the combined of all-cause death or need for orotracheal intubation until 30 days of infection symptoms onset. To assess the effect of RAS inhibitors, we performed a double statistical approach, with multivariate logistic regression and propensity-score matching. Results: We included 704 patients (table). Median age was 61 years old (IQR 52.9-72.9);52.7% were female. 34.7% and 12.6% had hypertension (HTA) and diabetes (DM) respectively. 92 patients (13.1%) and 87 patients (12.4%) were taking ACEI and ARB respectively. Baseline characteristics of both subgroups are shown in the table. Patients on RAS inhibitors treatment had a worse clinical profile: were older, more males and with higher prevalence of HTA, DM, dyslipemia, ischemic heart disease and heart failure. There were no differences in terms of respiratory nor neoplasic disease. After 30 days, 112 patients (15.9%) had died, 148 (21.4%) had died or had required invasive mechanical ventilation (PE);390 patients (55.4%) had needed hospital admission. PE was reached in 33.3% patients under ACEI treatment (vs. 19.6% in control group, p=0.005) and in 41.9% patients under ARB treatment (vs. 18.5% in control group, p<0.001). In the analysis to estimate the effect of ACEI no differences between groups were found (OR 1.01 [0.55-1.85], p=0.973). Likewise, in terms of ARB treatment, there were no differences among both groups (OR 1.66 [0.91-3.03], p=0.097). Using a propensity-score approach 79 patients under ACEI treatment and 72 patients under ARB treatment were matched 1:1 with control patients (characteristics of matched population are described in the table) Logistic binary regression showed no significant differences on incidence of the PE in patients under ACEI treatment (OR 0.84, 95% CI [0.43-1.63], p=0.613) nor ARB treatment (OR 1.82, 95% CI [0.92-3.60], p=0.085). Nevertheless, there was a trend towards worse prognosis in ARB patients. Kaplan-Meier curves of survival free of death or need for mechanical ventilation in matched population (ACEI and ARB treatment) are shown in the figure. Conclusions: We have not found any correlation between the severity of the disease and the treatment with ACEI nor ARB. We do not recommend the withdrawal of these drugs during the current epidemic situation. Further studies are needed to assess this finding.

Calcium channel blockers and beta-blockers could increased mortality of patients with COVID-19

Background: High incidence of cardiovascular events has been described among patients with COVID-19 and since the beginning of the pandemic concerns have been expressed with medical treatments for cardiovascular disease, as they could contribute to the severity of illness in patients with COVID-19. We aim to analyze the effect of chronic treatment with calcium channel blockers and beta-blockers on COVID 19 severity in a Spanish cohort during the 2020 pandemic. Methods: Observational study including all consecutive patients (≥40 years old) diagnosed with SARS-CoV-2 through PCR in the microbiology laboratory of our hospital, from March 2nd to 20th 2020. Clinical characteristics and drugs were recorded. The Primary end-point (PE) was all-cause death and the secondary end-point (SE) was the combined of death or the need for orotracheal intubation until 30 days of infection symptoms onset. Results: We included 704 patients in our study. Baseline characteristics of the overall cohort can be seen in the table. Median age was 61 years old (IQR 52.9-72.9);52.7% were female. 34.7% and 12.6% had hypertension and diabetes respectively. After a median follow-up of 111.5 days, 58 patients (8.2%) needed orotracheal intubation and 133 patients (18.9%) died. Secondary endpoint (all-cause death or need for orotracheal intubation) was reached by 164 patients (23.3%). The table described clinical differences between survivors and deceased patients. After multivariate Cox modeling, age, male gender, diabetes, previous lung disease, BMI and the chronic intake of calcium channel blockers (HR 1.74, 95% CI (1.11-2.75), p=0.016) and beta-blockers (HR 1.71, 95% CI (1.07-2.76), p=0.026) were independently related with mortality. Other cardiovascular drugs (Antiplatelets, anticoagulants, diuretics, mineralcorticoid-receptor antagonists, angiotensin-receptor blockers, angiotensin-converting enzyme inhibitors and statins) did not influence survival after SARS-CoV 2 infection (Figure). The secondary outcome was reached by 164 patients (23.3%) and chronic treatment with calcium channel blockers remains as an independent predictor of mortality (HR 1.55, 95% CI (1.01-2.37), p=0.044). Conclusions: Chronic treatment with calcium channel blockers and betablockers are independent predictors of mortality after SARS-CoV-2 infection. Further studies are needed to confirm these results.

Cardiovascular predictors associated with poor short-term prognosis in patients diagnosed with SARS-CoV-2 in Spain

Background: On January 2020, the first patient with coronavirus 2 (SARSCoV- 2) was detected in Spain. Since then, 3 280 000 cases have been confirmed and 75.305 people have died. We aimed to clarify the epidemiological and clinical characteristics related with poor short-term prognosis in patients diagnosed with SARS-CoV-2. Methods: Observational, retrospective single-center study including consecutive patients (≥40yo) diagnosed with SARS-CoV-2 through PCR, since March 2nd to 20th 2020 in our center in Spain. The primary endpoint (PE) was the combined of all-cause death or need for orotracheal intubation within the first 30 days of infection symptoms. Results: 704 patients were included (table). A follow-up period of thirtydays was fully completed in 692 of 704 patients (98.3%). At the end of this period, 148 patients (21.4%) met the PE;they were older, more frequently male, obese and smokers. Patients who met the PE had a higher prevalence of hypertension, diabetes, dyslipidemia, ischemic heart disease, heart failure, peripheral and cerebrovascular disease, cancer and lung pathologies. They received more frequently therapies with reninangiotensin system inhibitors, betablockers, calcium channel blockers and statins, as well as antiplatelet and anticoagulant therapies Multivariate analysis showed that age (OR 1.99 for every 10 years, 95% CI [1.637-2.4], p<0.001), female sex (OR 0.49, [0.30-0.80], p=0.004), diabetes (OR 2.09, [1.17-3.71], p=0.012), lung disease (OR 1.99, [1.14- 3.44], p=0.014) and body mass index (OR 1.33 for each 5 kg/m2 increased, [1.05-1.68], p=0.017) were predictors of the PE. Hypertension was not significantly related to the PE (OR 1.55, [0.93-2.60], p=0.09) Conclusion: In our group of patients with SARS-CoV-2, age, male sex, diabetes, lung disease and obesity were found to be independent predictors of the combined of all case death or need for orotracheal intubation within the first 30 days of infection symptoms. Larger studies are needed to confirm these results. (Figure Presented).

The teaching-learning process in specific engineering subjects through different technology-based teaching methodologies applied during the State of Alarm

The safety measures contemplated in Real Decreto 463/2020, of March 14, which declares the State of Alarm for the management of the health crisis situation caused by COVID-19, determine the temporary suspension of the face-to-face educational activities and establish that these will have to be developed through distance and online modalities. This fact, which conditions traditional face-to-face teaching, forced us to look for new alternatives to meet the teaching objectives. This article presents the results and qualifications obtained by the students in the application of three different teaching methodologies in the teaching of the subject Manufacturing Processes II, of the University Center of Mérida in the Degree in Engineering in Industrial Design and Product Development (GIDIDP). The main objective has been to evaluate the influence of the different methodologies on the qualification of the students and the skills acquired. In the analysis of the results, in the application of the different methodologies, no significant differences have been obtained. The students assimilated the required competencies in a satisfactory way.

Simple planning problem for COVID-19 lockdown

We study the optimal lockdown policy for a planner who wants to control the fatalities of a pandemic while minimizing the output costs of the lockdown. We use the SIR epidemiology model and a linear economy to formalize the planner's dynamic control problem. The optimal policy depends on the fraction of infected and susceptible in the population. We parametrize the model using data on the COVID19 pandemic and the economic breadth of the lockdown. The quantitative analysis identifies the features that shape the intensity and duration of the optimal lockdown policy. Our baseline parametrization is conditional on a 1% of infected agents at the outbreak, no cure for the disease, and the possibility of testing. The optimal policy prescribes a severe lockdown beginning two weeks after the outbreak, covers 60% of the population after a month, and is gradually withdrawn covering 20% of the population after 3 months. The intensity of the lockdown depends on the gradient of the fatality rate as a function of the infected, and on the assumed value of a statistical life. The absence of testing increases the economic costs of the lockdown, and shortens the duration of the optimal lockdown which ends more abruptly. Welfare under the optimal policy with testing is higher, equivalent to a one-time payment of 2% of GDP.

A Simple Planning Problem for COVID-19 Lock-down, Testing, and Tracing

We study the optimal lock-down for a planner who controls the fatalities of COVID-19 while minimizing the output costs of the lockdown. The policy prescribes a severe lock-down beginning a few weeks after the outbreak, covering almost 50 percent of the population after a month, with a total duration shy of 4 months. The intensity of the optimal lock-down depends on the gradient of the fatality rate with respect to the infected and the availability of antibody testing, which yields a welfare gain of 2 percent of GDP. We also study test-tracing-quarantine, which we show to be complementary to lock-down.

Tips for a reduction of false positives in manual RT-PCR diagnostics of SARS-CoV-2

RT-PCR is the standard gold technique for testing the presence of RNA of the coronavirus causing Severe Acute Respiratory Syndrome (SARS-CoV-2) due to its high specificity and sensitivity. Despite its general use and reliability, no lab in the world is immune to the generation of false positives. These errors cause a loss of confidence in the technique's power and damage the image of laboratories. More importantly, they can take a toll on tested individuals and have economic, psychological, and health-associated effects. Most false positives are caused during a manual operation inside the laboratory. However, not much has been published about the errors associated with particular laboratory techniques used to detect the virus since the beginning of the actual pandemic. This work precisely reflects on events that occur during manual RT-PCR diagnostics in a COVID-19 laboratory, providing tips for reducing false-positive results. © 2021 Revista Bionatura. All rights reserved.