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coronavirus in Canada | 9 | Sex-specific differences in COVID-19 testing, cases and outcomes: a population-wide study in Ontario, Canada | In this population-wide study in Ontario, Canada we report on all 194,372 unique residents who received testing for SARS-CoV-2 between January 23, 2020 and April 28, 2020. We found that while more women than men were tested for SARS-CoV-2, men had a higher rate of laboratory-confirmed COVID-19 infection, hospitalization, ICU admission and death. These findings were consistent even with age adjustment, suggesting that the observed differences in outcomes between women and men were not explained by age or systematic differences in testing by sex. Instead, they may be due to sex-based immunological or other gendered differences, such as higher rates of smoking leading to cardiovascular disease. | n6oofe3i |
coronavirus in Canada | 9 | Association Between Nursing Home Crowding and COVID-19 Infection and Mortality in Ontario, Canada | q1ib25xr |
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coronavirus in Canada | 9 | Estimated surge in hospitalization and intensive care due to the novel coronavirus pandemic in the Greater Toronto Area, Canada: a mathematical modeling study with application at two local area hospitals | Background: A hospital-level pandemic response involves anticipating local surge in healthcare needs. Methods: We developed a mechanistic transmission model to simulate a range of scenarios of COVID-19 spread in the Greater Toronto Area. We estimated healthcare needs against 2019 daily admissions using healthcare administrative data, and applied outputs to hospital-specific data on catchment, capacity, and baseline non-COVID admissions to estimate potential surge by day 90 at two hospitals (St. Michaels Hospital [SMH] and St. Josephs Health Centre [SJHC]). We examined fast/large, default, and slow/small epidemics, wherein the default scenario (R0 2.4) resembled the early trajectory in the GTA. Results: Without further interventions, even a slow/small epidemic exceeded the citys daily ICU capacity for patients without COVID-19. In a pessimistic default scenario, for SMH and SJHC to remain below their non-ICU bed capacity, they would need to reduce non-COVID inpatient care by 70% and 58% respectively. SMH would need to create 86 new ICU beds, while SJHC would need to reduce its ICU beds for non-COVID care by 72%. Uncertainty in local epidemiological features was more influential than uncertainty in clinical severity. If physical distancing reduces contacts by 20%, maximizing the diagnostic capacity or syndromic diagnoses at the community-level could avoid a surge at each hospital. Interpretation: As distribution of the citys surge varies across hospitals over time, efforts are needed to plan and redistribute ICU care to where demand is expected. Hospital-level surge is based on community-level transmission, with community-level strategies key to mitigating each hospitals surge. Keywords: COVID-19, pandemic preparedness, mathematical model, transmission model | nbn3wox6 |
coronavirus in Canada | 9 | Determinants of self-reported symptoms and testing for COVID-19 in Canada using a nationally representative survey | In April 2020, a nationally representative sample of 4, 240 Canadians age 18 years and older were polled about COVID experience in March, early in the epidemic. We examined determinants of COVID symptoms, defined as fever plus difficulty breathing/shortness of breath, dry cough so severe that it disrupts sleep, and/or loss of sense of smell; and testing for SARS-CoV-2 by respondents and/or household members. About 8% of Canadians reported that they and/or one or more household members experienced COVID symptoms. Symptoms were more common in younger than older adults, and among visible minorities. Overall, 3% of respondents and/or household members had been tested for SARS-CoV-2. Being tested was associated with having COVID symptoms, being of Indigenous identity, and living in Quebec. Periodic nationally representative surveys, including high-risk older populations, of symptoms, as well as SARS-CoV-2 antibodies, are needed to understand the course of the Canadian epidemic and prepare for the future. | u54kja4g |
coronavirus in Canada | 9 | Reduced COVID-19-Related Critical Illness and Death, and High Risk of Epidemic Resurgence, After Physical Distancing in Ontario, Canada | We explored the impact of physical distancing measures on COVID-19 transmission in the population of Ontario, Canada using a previously described age- and health-status stratified transmission model. The model was fit to confirmed cases occupying intensive care unit (ICU) beds and mortality among hospitalized COVID-19 cases for the time period 19 March to 26 April 2020. We projected that mortality would have been 4.6-fold what was observed had physical distancing measures not been implemented in the province. Relaxation of physical distancing measures without compensatory increases in case detection, isolation, and/or contact tracing was projected to result in resurgence of disease activity. Return to normal or near-normal levels of contact would rapidly result in cases exceeding ICU capacity. Maintaining physical distancing for a longer period of time, allowing for the initial wave of infections to subside, delayed this resurgence, but the level of contacts post-restrictive distancing was the major factor determining how quickly ICU capacity was expected to be overwhelmed. Using a model, we demonstrate the marked impact strong public health measures had in reducing ICU admissions and mortality in Ontario. We also show that this hard-earned success is tenuous: relaxation of physical distancing measures in the near-term is projected to result in a rapid resurgence of disease activity. | bp2ilntr |
coronavirus in Canada | 9 | New Epidemiological Model Suggestions Revealing Size of Epidemics Based on the COVID-19 Pandemic Example: Wavelength Models | The main purpose of the study is to introduce the wavelength models developed to measure the size of outbreaks based on the COVID-19 example. In this way, the wavelengths of the outbreaks can be calculated, ensuring that the outbreaks are valid, reliable and easy to follow at the national and international level. Wavelength models consist of approved case, death, recovered case and net wavelength models. Thus, the size of the outbreak can be measured both individually and as a whole. COVID-19 cases of 181 countries were used to demonstrate the application of the models. The prominent findings in the applied wavelength models are as follows: the countries with the highest case wavelength are USA, Italy, Spain and Germany, respectively. However, Italy ranks first in the death wavelength, followed by Spain, the USA and France. On the other hand, China has taken the first place in the recovered case wavelength. This country was followed by Spain and Germany and Italy, respectively. Based on all these wavelength models mentioned, net wavelength lengths are calculated. According to the net wavelengths obtained, Canada ranked first, followed by United Kingdom, the USA and the Netherlands, respectively. | 3mmo1x2n |
coronavirus in Canada | 9 | MERS-CoV- Low risk to Canadians. | Middle East respiratory syndrome - Coronavirus (MERS-CoV) -- is a novel coronavirus that has caused a number of community-acquired cases and health care associated outbreaks in Saudi Arabia and the United Arab Emirates (UAE) as well as sporadic cases in other countries, especially in the Middle East. The evidence to date links MERS-CoV cases with exposure to camels, including camel products or to probable or confirmed human cases of MERS-CoV. It typically presents as an acute respiratory illness and is associated with a 35% mortality rate. Based on available information at this time, the current risk to Canadians for acquiring MERS-CoV infections is considered low. However, the International Health Regulations Committee concerning MERS-CoV has cautioned that the upsurge of cases seen this past spring (2014) may be predictive of an increase in cases related to the Hajj - an annual pilgrimage to Mecca in Saudi Arabia that took place in early October 2014. Although the overall risk is low, the Public Health Agency of Canada and its National Microbiology Laboratory (NML) in close collaboration with provincial and territorial partners, the Canadian Public Health Laboratory Network (CPHLN) and infection prevention and control experts have developed a number of preparedness guidance documents and protocols to address the risk of an imported case of MERS-CoV in Canada. | per78v5q |
coronavirus in Canada | 9 | Impact of COVID-19 on Canadian medical oncologists and cancer care: Canadian Association of Medical Oncologists survey report | Background: The covid-19 pandemic has presented unprecedented professional and personal challenges for the oncology community. Under the auspices of the Canadian Association of Medical Oncologists, we conducted an online national survey to better understand the impact of the pandemic on the medical oncology community in Canada. Methods: An English-language multiple-choice survey, including questions about demographics, covid-19 risk, use of personal protective equipment (ppe), personal challenges, and chemotherapy management was distributed to Canadian medical oncologists. The survey was open from 30 March to 4 April 2020, and attracted 159 responses. Results: More than 70% of medical oncologists expressed moderate-to-extreme concern about personally contracting covid-19 and about family members or patients (or both) contracting covid-19 from them. Despite that high level of concern, considerable variability in the use of ppe in direct cancer care was reported at the time of this survey, with 33% of respondents indicating no routine ppe use at their institutions and 69% indicating uncertainty about access to adequate ppe. Of the respondents, 54% were experiencing feelings of nervousness or anxiety on most days, and 52% were having feelings of depression or hopelessness on at least some days. Concern about aging parents or family and individual wellness represented the top personal challenges identified. The management of cancer patients has been affected, with adoption of telemedicine reported by 82% of respondents, and cessation of clinical trial accrual reported by 54%. The 3 factors deemed most important for treatment decision-making wereâ cancer prognosis and anticipated benefit from treatment,â risk of treatment toxicity during scarce health care access, andâ patient risk of contracting covid-19. Conclusions: This report describes the results of the first national survey assessing the impact of the covid-19 on Canadian medical oncologists and how they deliver systemic anticancer therapies. We hope that these data will provide a framework to address the challenges identified. | y8ntig41 |
coronavirus in Canada | 9 | Risk of a second wave of Covid-19 infections: using artificial intelligence to investigate stringency of physical distancing policies in North America | PURPOSE: Accurately forecasting the occurrence of future covid-19-related cases across relaxed (Sweden) and stringent (USA and Canada) policy contexts has a renewed sense of urgency. Moreover, there is a need for a multidimensional county-level approach to monitor the second wave of covid-19 in the USA. METHOD: We use an artificial intelligence framework based on timeline of policy interventions that triangulated results based on the three approaches-Bayesian susceptible-infected-recovered (SIR), Kalman filter, and machine learning. RESULTS: Our findings suggest three important insights. First, the effective growth rate of covid-19 infections dropped in response to the approximate dates of key policy interventions. We find that the change points for spreading rates approximately coincide with the timelines of policy interventions across respective countries. Second, forecasted trend until mid-June in the USA was downward trending, stable, and linear. Sweden is likely to be heading in the other direction. That is, Sweden's forecasted trend until mid-June appears to be non-linear and upward trending. Canada appears to fall somewhere in the middle-the trend for the same period is flat. Third, a Kalman filter based robustness check indicates that by mid-June the USA will likely have close to two million virus cases, while Sweden will likely have over 44,000 covid-19 cases. CONCLUSION: We show that drop in effective growth rate of covid-19 infections was sharper in the case of stringent policies (USA and Canada) but was more gradual in the case of relaxed policy (Sweden). Our study exhorts policy makers to take these results into account as they consider the implications of relaxing lockdown measures. | 1mxgmhik |
coronavirus in Canada | 9 | Health-related concerns and precautions during the COVID-19 pandemic: A comparison of Canadians with and without underlying health conditions | BACKGROUND: The risk of experiencing adverse outcomes from the coronavirus disease 2019 (COVID-19), such as hospitalization, admission to intensive care units and death, is elevated for older individuals and those with certain underlying health conditions including diabetes, chronic conditions affecting lungs, heart or kidneys, and a compromised immune system. DATA AND METHODS: Data collected between March 29 and April 3, 2020 from the Canadian Perspectives Survey Series 1: Impacts of COVID-19 (n=4,627) were used to estimate the prevalence of underlying health conditions, health concerns and precautionary behaviours among Canadians aged 15 or older living in the provinces. Multivariate analyses examined associations between these variables after accounting for age, sex and education. RESULTS: Close to 1 in 4 Canadians (24%) had an underlying health condition that increased their risk of adverse outcomes from COVID-19. Overall, 36% of the population were very or extremely concerned about the impact of COVID-19 on their own health. Individuals with underlying health conditions had higher odds (odds ratio: 2.0, 95% confidence interval: 1.6 to 2.5) of being highly concerned than those without these conditions, after adjustment for demographic characteristics. High percentages of Canadians took precautions to reduce the risk of infection regardless of whether or not they had underlying health conditions. DISCUSSION: Health status was associated with higher levels of concern for one's own health in the early period of the COVID-19 pandemic. Most Canadians were taking precautions recommended by public health authorities to protect themselves and others. | in2edn29 |
coronavirus in Canada | 9 | The Impact of Coronavirus Disease 2019 Pandemic on U.S. and Canadian PICUs | OBJECTIVES: There are limited reports of the impact of the coronavirus disease 2019 pandemic focused on U.S. and Canadian PICUs. This hypothesis-generating report aims to identify the United States and Canadian trends of coronavirus disease 2019 in PICUs. DESIGN AND SETTING: To better understand how the coronavirus disease 2019 pandemic was affecting U.S. and Canadian PICUs, an open voluntary daily data collection process of Canadian and U.S. PICUs was initiated by Virtual Pediatric Systems, LLC (Los Angeles, CA; http://www.myvps.org) in mid-March 2020. Information was made available online to all PICUs wishing to participate. A secondary data collection was performed to follow-up on patients discharged from those PICUs reporting coronavirus disease 2019 positive patients. MEASUREMENTS AND MAIN RESULTS: To date, over 180 PICUs have responded detailing 530 PICU admissions requiring over 3,467 days of PICU care with 30 deaths. The preponderance of cases was in the eastern regions. Twenty-four percent of the patients admitted to the PICUs were over 18 years old. Fourteen percent of admissions were under 2 years old. Nearly 60% of children had comorbidities at admission with the average length of stay increasing by age and by severity of comorbidity. Advanced respiratory support was necessary during 67% of the current days of care, with 69% being conventional mechanical ventilation. CONCLUSIONS: PICUs have been significantly impacted by the pandemic. They have provided care not only for children but also adults. Patients with coronavirus disease 2019 have a high frequency of comorbidities, require longer stays, more ventilatory support than usual PICU admissions. These data suggest several avenues for further exploration. | nd1gecxg |
coronavirus in Canada | 9 | Risk for COVID-19 Resurgence Related to Duration and Effectiveness of Physical Distancing in Ontario, Canada | 281pj442 |
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coronavirus in Canada | 9 | Diagnosis and Management of First Case of COVID-19 in Canada: Lessons applied from SARS | We report diagnosis and management of the first laboratory-confirmed case of coronavirus disease 2019 (COVID-19) hospitalized in Toronto, Canada. No healthcare-associated transmission occurred. In the face of a potential pandemic of COVID-19, we suggest sustainable and scalable control measures developed based on lessons learned from SARS. | h9ovovhk |
coronavirus in Canada | 9 | Post-Discharge Cardiac Care in the Era of Coronavirus 2019: How Should We Prepare? | The novel coronavirus 2019 disease (COVID-19) pandemic has placed intense pressure on health care organizations around the world. Among other concerns, there has been an increasing recognition of common and deleterious cardiovascular effects of COVID-19 based on preliminary studies. Furthermore, patients with preexisting cardiac disease are likely to experience a more severe disease course with COVID-19. As case numbers continue to increase exponentially, a surge in the number of patients with new or comorbid cardiovascular disease will translate into more frequent and, in some cases, prolonged rehabilitation needs after acute hospitalization. This report describes the current status of post-discharge cardiac care in Canada and provides suggestions regarding steps that policymakers and health care organizations can take to prepare for the COVID-19 pandemic. | ryh7cqwn |
coronavirus in Canada | 9 | Baseline characteristics and outcomes of patients with COVID-19 admitted to intensive care units in Vancouver, Canada: a case series | BACKGROUND: Pandemic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is associated with high intensive care unit (ICU) mortality. We aimed to describe the clinical characteristics and outcomes of critically ill patients with coronavirus disease 2019 (COVID-19) in a Canadian setting. METHODS: We conducted a retrospective case series of critically ill patients with laboratory-confirmed SARS-CoV-2 infection consecutively admitted to 1 of 6 ICUs in Metro Vancouver, British Columbia, Canada, between Feb. 21 and Apr. 14, 2020. Demographic, management and outcome data were collected by review of patient charts and electronic medical records. RESULTS: Between Feb. 21 and Apr. 14, 2020, 117 patients were admitted to the ICU with a confirmed diagnosis of COVID-19. The median age was 69 (interquartile range [IQR] 60-75) years, and 38 (32.5%) were female. At least 1 comorbidity was present in 86 (73.5%) patients. Invasive mechanical ventilation was required in 74 (63.2%) patients. The duration of mechanical ventilation was 13.5 (IQR 8-22) days overall and 11 (IQR 6-16) days for patients successfully discharged from the ICU. Tocilizumab was administered to 4 patients and hydroxychloroquine to 1 patient. As of May 5, 2020, a total of 18 (15.4%) patients had died, 12 (10.3%) remained in the ICU, 16 (13.7%) were discharged from the ICU but remained in hospital, and 71 (60.7%) were discharged home. INTERPRETATION: In our setting, mortality in critically ill patients with COVID-19 admitted to the ICU was lower than in previously published studies. These data suggest that the prognosis associated with critical illness due to COVID-19 may not be as poor as previously reported. | 7g12596l |
coronavirus in Canada | 9 | Laboratory-confirmed COVID-19 in children and youth in Canada, January 15-April 27, 2020 | Understanding the epidemiology of COVID-19 among children and youth in Canada will help to inform public health measures in settings where children gather. As of April 27, 2020, provinces and territories provided the Public Health Agency of Canada with detailed information on 24,079 cases, of which 3.9% (n=938) were younger than 20 years of age. The detection rate per 100,000 population was lower in this age group (11.9 per 100,000), compared with those aged 20-59 years (72.4 per 100,000) and 60 and older (113.6 per 100,000). The median age among those younger than 20 years of age was 13 years, and cases were distributed equally across male and female genders. Among provinces and territories with more than 100 cases, 1.6% to 9.8% of cases were younger than 20 years of age. Cases in this age group were more likely to be asymptomatic: 10.7% compared with 2.4% in those aged 20-59 years and 4.1% in those aged 60 and older. Children and youth experienced severe outcomes less often, but 2.2% (n=15/672) of cases within this age group were severe enough to require hospitalization. Based on available exposure information, 11.3% (n=59/520) of cases aged younger than 20 years had no known contact with a case. Canadian findings align with those of other countries. | bvujapf5 |
coronavirus in Canada | 9 | First imported case of 2019 novel coronavirus in Canada, presenting as mild pneumonia | cietpenq |
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coronavirus in Canada | 9 | It can be dangerous to take epidemic curves of COVID-19 at face value | During an epidemic with a new virus, we depend on modelling to plan the response: but how good are the data? The aim of our work was to better understand the impact of misclassification errors in identification of true cases of COVID-19 on epidemic curves. Data originated from Alberta, Canada (available on 28 May 2020). There is presently no information of sensitivity (Sn) and specificity (Sp) of laboratory tests used in Canada for the causal agent for COVID-19. Therefore, we examined best attainable performance in other jurisdictions and similar viruses. This suggested perfect Sp and Sn 60-95%. We used these values to re-calculate epidemic curves to visualize the potential bias due to imperfect testing. If the sensitivity improved, the observed and adjusted epidemic curves likely fall within 95% confidence intervals of the observed counts. However, bias in shape and peak of the epidemic curves can be pronounced, if sensitivity either degrades or remains poor in the 60-70% range. These issues are minor early in the epidemic, but hundreds of undiagnosed cases are likely later on. It is therefore hazardous to judge progress of the epidemic based on observed epidemic curves unless quality of testing is better understood. | hsr2ue28 |
coronavirus in Canada | 9 | Open access epidemiologic data and an interactive dashboard to monitor the COVID-19 outbreak in Canada | ep79lg0p |
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coronavirus in Canada | 9 | Estimation of COVID-19-induced depletion of hospital resources in Ontario, Canada | BACKGROUND: The global spread of coronavirus disease 2019 (COVID-19) continues in several jurisdictions, causing substantial strain to health care systems. The purpose of our study was to predict the effect of the COVID-19 pandemic on patient outcomes and use of hospital resources in Ontario, Canada. METHODS: We developed an individual-level simulation to model the flow of patients with COVID-19 through the hospital system in Ontario. We simulated different combined scenarios of epidemic trajectory and hospital health care capacity. Our outcomes included the number of patients who needed admission to the ward or to the intensive care unit (ICU) with or without the need for mechanical ventilation, number of days to resource depletion, number of patients awaiting resources and number of deaths. RESULTS: We found that with effective early public health measures, hospital system resources would not be depleted. For scenarios with late or ineffective implementation of physical distancing, hospital resources would be depleted within 14-26 days, and in the worst case scenario, 13 321 patients would die while waiting for needed resources. Resource depletion would be avoided or delayed with aggressive measures to increase ICU, ventilator and acute care hospital capacities. INTERPRETATION: We found that without aggressive physical distancing measures, the Ontario hospital system would have been inadequately equipped to manage the expected number of patients with COVID-19 despite a rapid increase in capacity. This lack of hospital resources would have led to an increase in mortality. By slowing the spread of the disease using public health measures and by increasing hospital capacity, Ontario may have avoided catastrophic stresses to its hospitals. | h6g65f9w |
coronavirus in Canada | 9 | Severity of coronavirus respiratory tract infections in adults admitted to acute care in Toronto, Ontario | BACKGROUND: The World Health Organization has highlighted the need for improved surveillance and understanding of the health burden imposed by non-influenza RNA respiratory viruses. Human coronaviruses (CoVs) are a major cause of respiratory and gastrointestinal tract infections with associated morbidity and mortality. OBJECTIVES: The objective of our study was to characterize the epidemiology of CoVs in our tertiary care centre, and identify clinical correlates of disease severity. STUDY DESIGN: A cross-sectional study was performed of 226 patients admitted with confirmed CoV respiratory tract infection between 2010 and 2016. Variables consistent with a severe disease burden were evaluated including symptoms, length of stay, intensive care unit (ICU) admission and mortality. RESULTS: CoVs represented 11.3% of all positive respiratory virus samples and OC43 was the most commonly identified CoV. The majority of infections were community-associated while 21.6% were considered nosocomial. The average length of stay was 11.8 days with 17.3% of patients requiring ICU admission and an all-cause mortality of 7%. In a multivariate model, female gender and smoking were associated with increased likelihood of admission to ICU or death. CONCLUSION: This study highlights the significant burden of CoVs and justifies the need for surveillance in the acute care setting. | i8bw7ut9 |
coronavirus in Canada | 9 | Real-time forecasts and risk assessment of novel coronavirus (COVID-19) cases: A data-driven analysis | The coronavirus disease 2019 (COVID-19) has become a public health emergency of international concern affecting 201 countries and territories around the globe. As of April 4, 2020, it has caused a pandemic outbreak with more than 11,16,643 confirmed infections and more than 59,170 reported deaths worldwide. The main focus of this paper is two-fold: (a) generating short term (real-time) forecasts of the future COVID-19 cases for multiple countries; (b) risk assessment (in terms of case fatality rate) of the novel COVID-19 for some profoundly affected countries by finding various important demographic characteristics of the countries along with some disease characteristics. To solve the first problem, we presented a hybrid approach based on autoregressive integrated moving average model and Wavelet-based forecasting model that can generate short-term (ten days ahead) forecasts of the number of daily confirmed cases for Canada, France, India, South Korea, and the UK. The predictions of the future outbreak for different countries will be useful for the effective allocation of health care resources and will act as an early-warning system for government policymakers. In the second problem, we applied an optimal regression tree algorithm to find essential causal variables that significantly affect the case fatality rates for different countries. This data-driven analysis will necessarily provide deep insights into the study of early risk assessments for 50 immensely affected countries. | d9f8lbr6 |
coronavirus in Canada | 9 | Predicting turning point, duration and attack rate of COVID-19 outbreaks in major Western countries | In this paper, we employed a segmented Poisson model to analyze the available daily new cases data of the COVID-19 outbreaks in the six Western countries of the Group of Seven, namely, Canada, France, Germany, Italy, UK and USA. We incorporated the governments' interventions (stay-at-home advises/orders, lockdowns, quarantines and social distancing) against COVID-19 into consideration. Our analysis allowed us to make a statistical prediction on the turning point (the time that the daily new cases peak), the duration (the period that the outbreak lasts) and the attack rate (the percentage of the total population that will be infected over the course of the outbreak) for these countries. | 1da6ackj |
coronavirus in Canada | 9 | Projecting demand for critical care beds during COVID-19 outbreaks in Canada | BACKGROUND: 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. METHODS: 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. RESULTS: 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. INTERPRETATION: 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. | ezirpmbd |
coronavirus in Canada | 9 | Quantification of Tomographic Patterns associated with COVID-19 from Chest CT | Purpose: To present a method that automatically segments and quantifies abnormal CT patterns commonly present in coronavirus disease 2019 (COVID-19), namely ground glass opacities and consolidations. Materials and Methods: In this retrospective study, the proposed method takes as input a non-contrasted chest CT and segments the lesions, lungs, and lobes in three dimensions, based on a dataset of 9749 chest CT volumes. The method outputs two combined measures of the severity of lung and lobe involvement, quantifying both the extent of COVID-19 abnormalities and presence of high opacities, based on deep learning and deep reinforcement learning. The first measure of (PO, PHO) is global, while the second of (LSS, LHOS) is lobewise. Evaluation of the algorithm is reported on CTs of 200 participants (100 COVID-19 confirmed patients and 100 healthy controls) from institutions from Canada, Europe and the United States collected between 2002-Present (April, 2020). Ground truth is established by manual annotations of lesions, lungs, and lobes. Correlation and regression analyses were performed to compare the prediction to the ground truth. Results: Pearson correlation coefficient between method prediction and ground truth for COVID-19 cases was calculated as 0.92 for PO (P<.001), 0.97 for PHO(P<.001), 0.91 for LSS (P<.001), 0.90 for LHOS (P<.001). 98 of 100 healthy controls had a predicted PO of less than 1%, 2 had between 1-2%. Automated processing time to compute the severity scores was 10 seconds per case compared to 30 minutes required for manual annotations. Conclusion: A new method segments regions of CT abnormalities associated with COVID-19 and computes (PO, PHO), as well as (LSS, LHOS) severity scores. | 4dnzjeyp |
coronavirus in Canada | 9 | Air pollution in Ontario, Canada during the COVID-19 State of Emergency | In March of 2020, the province of Ontario declared a State of Emergency (SOE) to reduce the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes the coronavirus disease (COVID-19). This disruption to the economy provided an opportunity to measure change in air pollution when the population spends more time at home with fewer trips. Hourly air pollution observations were obtained for fine particulate matter, nitrogen dioxide, nitrogen oxides and ozone from the Ontario air monitoring network for 2020 and the previous five years. The analysis is focused on a five-week period during the SOE with a previous five-week period used as a control. Fine particulate matter did not show any significant reductions during the SOE. Ozone concentrations at 12 of the 32 monitors were lower than any of the previous five-years; however, four locations were above average. Average ozone concentrations were 1 ppb lower during the SOE, but this ranged at individual monitors from 1.5 ppb above to 4.2 ppb below long-term conditions. Nitrogen dioxide and nitrogen oxides demonstrated a reduction across Ontario, and both pollutants displayed their lowest concentrations for 22 of 29 monitors. Individual monitors ranged from 1 ppb (nitrogen dioxide) and 5 ppb (nitrogen oxides) above average to 4.5 (nitrogen dioxide) and 7.1 ppb (nitrogen oxides) below average. Overall, both nitrogen dioxide and nitrogen oxides demonstrated a reduction across Ontario in response to the COVID-19 SOE, ozone concentrations suggested a possible reduction, and fine particulate matter has not varied from historic concentrations. | ltnnjx0x |
coronavirus in Canada | 9 | Temporal estimates of case-fatality rate for COVID-19 outbreaks in Canada and the United States | BACKGROUND: Estimates of the case-fatality rate (CFR) associated with coronavirus disease 2019 (COVID-19) vary widely in different population settings. We sought to estimate and compare the COVID-19 CFR in Canada and the United States while adjusting for 2 potential biases in crude CFR. METHODS: We used the daily incidence of confirmed COVID-19 cases and deaths in Canada and the US from Jan. 31 to Apr. 22, 2020. We applied a statistical method to minimize bias in the crude CFR by accounting for the survival interval as the lag time between disease onset and death, while considering reporting rates of COVID-19 cases less than 50% (95% confidence interval 10%-50%). RESULTS: Using data for confirmed cases in Canada, we estimated the crude CFR to be 4.9% on Apr. 22, 2020, and the adjusted CFR to be 5.5% (credible interval [CrI] 4.9%-6.4%). After we accounted for various reporting rates less than 50%, the adjusted CFR was estimated at 1.6% (CrI 0.7%-3.1%). The US crude CFR was estimated to be 5.4% on Apr. 20, 2020, with an adjusted CFR of 6.1% (CrI 5.4%-6.9%). With reporting rates of less than 50%, the adjusted CFR for the US was 1.78 (CrI 0.8%-3.6%). INTERPRETATION: Our estimates suggest that, if the reporting rate is less than 50%, the adjusted CFR of COVID-19 in Canada is likely to be less than 2%. The CFR estimates for the US were higher than those for Canada, but the adjusted CFR still remained below 2%. Quantification of case reporting can provide a more accurate measure of the virulence and disease burden of severe acute respiratory syndrome coronavirus 2. | 9hbgn66l |
coronavirus in Canada | 9 | Using Machine Learning to Estimate Unobserved COVID-19 Infections in North America | BACKGROUND: The detection of coronavirus disease 2019 (COVID-19) cases remains a huge challenge. As of April 22, 2020, the COVID-19 pandemic continues to take its toll, with >2.6 million confirmed infections and >183,000 deaths. Dire projections are surfacing almost every day, and policymakers worldwide are using projections for critical decisions. Given this background, we modeled unobserved infections to examine the extent to which we might be grossly underestimating COVID-19 infections in North America. METHODS: We developed a machine-learning model to uncover hidden patterns based on reported cases and to predict potential infections. First, our model relied on dimensionality reduction to identify parameters that were key to uncovering hidden patterns. Next, our predictive analysis used an unbiased hierarchical Bayesian estimator approach to infer past infections from current fatalities. RESULTS: Our analysis indicates that, when we assumed a 13-day lag time from infection to death, the United States, as of April 22, 2020, likely had at least 1.3 million undetected infections. With a longer lag time-for example, 23 days-there could have been at least 1.7 million undetected infections. Given these assumptions, the number of undetected infections in Canada could have ranged from 60,000 to 80,000. Duarte's elegant unbiased estimator approach suggested that, as of April 22, 2020, the United States had up to >1.6 million undetected infections and Canada had at least 60,000 to 86,000 undetected infections. However, the Johns Hopkins University Center for Systems Science and Engineering data feed on April 22, 2020, reported only 840,476 and 41,650 confirmed cases for the United States and Canada, respectively. CONCLUSIONS: We have identified 2 key findings: (1) as of April 22, 2020, the United States may have had 1.5 to 2.029 times the number of reported infections and Canada may have had 1.44 to 2.06 times the number of reported infections and (2) even if we assume that the fatality and growth rates in the unobservable population (undetected infections) are similar to those in the observable population (confirmed infections), the number of undetected infections may be within ranges similar to those described above. In summary, 2 different approaches indicated similar ranges of undetected infections in North America. LEVEL OF EVIDENCE: Prognostic Level V. See Instructions for Authors for a complete description of levels of evidence. | mdt11ba5 |
coronavirus in Canada | 9 | Real-time Forecast of Multiphase Outbreak | We used a single equation with discrete phases to fit the daily cumulative case data from the 2003 severe acute respiratory syndrome outbreak in Toronto. This model enabled us to estimate turning points and case numbers during the 2 phases of this outbreak. The 3 estimated turning points are March 25, April 27, and May 24. The estimated case number during the first phase of the outbreak between February 23 and April 26 is 140.53 (95% confidence interval [CI] 115.88–165.17) if we use the data from February 23 to April 4; and 249 (95% CI: 246.67–251.25) at the end of the second phase on June 12 if we use the data from April 28 to June 4. The second phase can be detected by using case data just 3 days past the beginning of the phase, while the first and third turning points can be identified only ≈10 days afterwards. Our modeling procedure provides insights into ongoing outbreaks that may facilitate real-time public health responses. | h6cfru7u |
coronavirus in Canada | 9 | Canada needs to rapidly escalate public health interventions for its COVID-19 mitigation strategies | BACKGROUND: After the declaration of COVID-19 pandemic on March 11th(,) 2020, local transmission chains starting in different countries including Canada are forcing governments to take decisions on public health interventions to mitigate the spread of the epidemic. METHODS: We conduct data-driven and model-free estimations for the growth rates of the COVID-19 epidemics in Italy and Canada, by fitting an exponential curve to the daily reported cases. We use these estimates to predict epidemic trends in Canada under different scenarios of public health interventions. RESULTS: In Italy, the initial growth rate (0.22) has reduced to 0.1 two weeks after the lockdown of the country on March 8th(,) 2020. This corresponds to an increase of the doubling time from about 3.15 to almost 7 days. In comparison, the growth rate in Canada has increased from 0.13 between March 1st and 13th, to 0.25 between March 13th to 22nd. This current growth rate corresponds to a doubling time of 2.7 days, and therefore, unless further public health interventions are escalated in Canada, we project 15,000 cases by March 31st. However, the case number may be reduced to 4000 if escalated public health interventions could instantly reduce the growth rate to 0.1, the same level achieved in Italy. INTERPRETATION: Prompt and farsighted interventions are critical to counteract the very rapid initial growth of the COVID-19 epidemic in Canada. Mitigation plans must take into account the delayed effect of interventions by up to 2-weeks and the short doubling time of 3–4 days. | vwwt70mo |
coronavirus in Canada | 9 | Estimating the Maximum Capacity of COVID-19 Cases Manageable per Day Given a Health Care System's Constrained Resources | sdf2cw4g |
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coronavirus in Canada | 9 | Projecting the demand for ventilators at the peak of the COVID-19 outbreak in the USA | aj1cod3x |
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coronavirus in Canada | 9 | Human Coronavirus NL63 Infection in Canada | The isolation of human coronavirus NL63 (HCoV-NL63) in The Netherlands raised questions about its contribution to respiratory illness. In this study, a total of 525 respiratory specimens, collected in Canada primarily during the winter months of 2001–2002, were tested for HCoV-NL63; 19 tested positive for HCoV-NL63, demonstrating virus activity during January–March 2002. Patients with HCoV-NL63 were 1 month-100 years old (median age, 37 years). The main clinical presentations were fever (15/19), sore throat (5/19), and cough (9/19), and 4 patients were hospitalized. These results provide evidence for the worldwide distribution of HCoV-NL63. | nalulzfo |
coronavirus in Canada | 9 | Communication in the Toronto critical care community: important lessons learned during SARS | The SARS outbreak in 2003 pushed Toronto's health care system to its limits. Staffing shortages, transmission of SARS within the ICU, and the influx of critically ill SARS patients were some unique challenges to the delivery of critical care. Communication strategies were a key component in the critical care response to SARS. Regular teleconference calls, web-based training and education, and the rapid coordination of research studies were some of the initiatives developed within the Toronto critical care community during the SARS outbreak. Other critical care communities should consider their communication strategies in advance of similar events. | 8wlxkflg |
coronavirus in Canada | 9 | COVID-19: Pandemic Risk, Resilience and Possibilities for Aging Research | The COVID-19 global crisis is reshaping Canadian society in unexpected and profound ways. The significantly higher morbidity and mortality risks by age suggest that this is largely a “gero-pandemic,” which has thrust the field of aging onto center stage. This editorial emphasizes that vulnerable older adults are also those most affected by COVID-19 in terms of infection risk, negative health effects, and the potential deleterious outcomes on a range of social, psychological, and economic contexts – from ageism to social isolation. We also contend that the pathogenic analysis of this pandemic needs to be balanced with a salutogenic approach that examines the positive adaptation of people, systems and society, termed COVID-19 resilience. This begs the question: how and why do some older adults and communities adapt and thrive better than others? This examination will lead to the identification and response to research and data gaps, challenges, and innovative opportunities as we plan for a future in which COVID-19 has become another endemic infection in the growing list of emerging and re-emerging pathogens. | no8y1ior |
coronavirus social distancing impact | 10 | Mandatory Social Distancing Associated With Increased Doubling Time: An Example Using Hyperlocal Data | ljpd7flk |
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coronavirus social distancing impact | 10 | No Place Like Home: A Cross-National Assessment of the Efficacy of Social Distancing during the COVID-19 Pandemic. | BACKGROUND In the absence of a cure in the time of pandemics, social distancing measures seem to be the most effective intervention to slow down the spread of disease. Various simulation-based studies have been conducted in the past to investigate the effectiveness of such measures. While those studies unanimously confirm the mitigating effect of social distancing on the disease spread, the reported effectiveness varies from 10% to more than 90% reduction in the number of infections. This level of uncertainty is mostly due to the complex dynamics of epidemics and their time-variant parameters. A real transactional data, however, can reduce the uncertainty and provide a less noisy picture of social distancing effectiveness. OBJECTIVE In this paper, we integrate multiple transactional data sets (GPS mobility data from Google and Apple as well as disease statistics data from ECDC) to study the role of social distancing policies in 26 countries wherein the transmission rate of the COVID-19 pandemic is analyzed over the course of five weeks. METHODS Relying on the SIR model and official COVID-19 reports, we first calculated the weekly transmission rate (β) of the coronavirus disease in 26 countries for five consecutive weeks. Then we integrated that with the Google's and Apple's mobility data sets for the same time frame and used a machine learning approach to investigate the relationship between mobility factors and β values. RESULTS Gradient Boosted Trees (GBT) regression analysis showed that changes in mobility patterns, resulted from social distancing policies, explain around 47% of the variation in the disease transmission rate. CONCLUSIONS Consistent with simulation-based studies, real cross-national transactional data confirms the effectiveness of social distancing interventions in slowing down the spread of the disease. Apart from providing less noisy and more generalizable support for the whole social distancing idea, we provide specific insights for public health policy-makers as to what locations should be given a higher priority for enforcing social distancing measures. CLINICALTRIAL | 3nanf73b |
coronavirus social distancing impact | 10 | Timing of Community Mitigation and Changes in Reported COVID-19 and Community Mobility - Four U.S. Metropolitan Areas, February 26-April 1, 2020. | Community mitigation activities (also referred to as nonpharmaceutical interventions) are actions that persons and communities can take to slow the spread of infectious diseases. Mitigation strategies include personal protective measures (e.g., handwashing, cough etiquette, and face coverings) that persons can use at home or while in community settings; social distancing (e.g., maintaining physical distance between persons in community settings and staying at home); and environmental surface cleaning at home and in community settings, such as schools or workplaces. Actions such as social distancing are especially critical when medical countermeasures such as vaccines or therapeutics are not available. Although voluntary adoption of social distancing by the public and community organizations is possible, public policy can enhance implementation. The CDC Community Mitigation Framework (1) recommends a phased approach to implementation at the community level, as evidence of community spread of disease increases or begins to decrease and according to severity. This report presents initial data from the metropolitan areas of San Francisco, California; Seattle, Washington; New Orleans, Louisiana; and New York City, New York* to describe the relationship between timing of public policy measures, community mobility (a proxy measure for social distancing), and temporal trends in reported coronavirus disease 2019 (COVID-19) cases. Community mobility in all four locations declined from February 26, 2020 to April 1, 2020, decreasing with each policy issued and as case counts increased. This report suggests that public policy measures are an important tool to support social distancing and provides some very early indications that these measures might help slow the spread of COVID-19. | 16t5rs6j |
coronavirus social distancing impact | 10 | Social distancing: A non-pharmacological intervention for COVID-19. | Social distancing is one of the non-pharmacological measures to contain the infection of COVID-19. At this point in time, no vaccine is available to prevent the infection, no effective drugs are available to prevent and treat the disease, and none of the communities have acquired herd immunity. Various models have shown positive impact of social distancing, provided its implementation on vast majority of the population over a long period of time. Its effect is manifold. Besides flattening the curve, it impacts the political, fiscal, social, economic aspects of the society, along with socially vulnerable and economically underprivileged population. It becomes obsolete after the population develops herd immunity subsequent to widespread infection in the community, or after effective mass immunisation or specific drugs for its control, cure and prevention are available widely. | 3cke9x69 |
coronavirus social distancing impact | 10 | Strong Social Distancing Measures In The United States Reduced The COVID-19 Growth Rate. | State and local governments imposed social distancing measures in March and April of 2020 to contain the spread of novel coronavirus disease 2019 (COVID-19). These included large event bans, school closures, closures of entertainment venues, gyms, bars, and restaurant dining areas, and shelter-in-place orders (SIPOs). We evaluated the impact of these measures on the growth rate of confirmed COVID-19 cases across US counties between March 1, 2020 and April 27, 2020. An event-study design allowed each policy's impact on COVID-19 case growth to evolve over time. Adoption of government-imposed social distancing measures reduced the daily growth rate by 5.4 percentage points after 1-5 days, 6.8 after 6-10 days, 8.2 after 11-15 days, and 9.1 after 16-20 days. Holding the amount of voluntary social distancing constant, these results imply 10 times greater spread by April 27 without SIPOs (10 million cases) and more than 35 times greater spread without any of the four measures (35 million). Our paper illustrates the potential danger of exponential spread in the absence of interventions, providing relevant information to strategies for restarting economic activity. [Editor's Note: This Fast Track Ahead Of Print article is the accepted version of the peer-reviewed manuscript. The final edited version will appear in an upcoming issue of Health Affairs.]. | ereh4ub8 |
coronavirus social distancing impact | 10 | Social distancing, population density, and spread of COVID-19 in England: a longitudinal study. | BACKGROUND The UK government introduced social distancing measures between 16-22 March 2020, aiming to slow down transmission of COVID-19. AIM To explore the spreading of COVID-19 in relation to population density after the introduction of social distancing measures. DESIGN & SETTING Longitudinal design with 5-weekly COVID-19 incidence rates per 100 000 people for 149 English Upper Tier Local Authorities (UTLAs), between 16 March and 19 April 2020. METHOD Multivariable multilevel model to analyse weekly incidence rates per 100 000 people; time was level-1 unit and UTLA level-2 unit. Population density was divided into quartiles. The model included an interaction between week and population density. Potential confounders were percentage aged ≥65, percentage non-white British, and percentage in two highest classes of the National Statistics Socioeconomic Classification. Co-variates were male life expectancy at birth, and COVID-19 prevalence rate per 100 000 people on March 15. Confounders and co-variates were standardised around the mean. RESULTS Incidence rates per 100 000 people peaked in the week of March 30-April 5, showing higher adjusted incidence rate per 100 000 people (46.2; 95% confidence interval [CI] = 40.6 to 51.8) in most densely populated ULTAs (quartile 4) than in less densely populated ULTAs (quartile 1: 33.3, 95% CI = 27.4 to 37.2; quartile 2: 35.9, 95% CI = 31.6 to 40.1). Thereafter, incidence rate dropped in the most densely populated ULTAs resulting in rate of 22.4 (95% CI = 16.9 to 28.0) in the week of April 13-19; this was lower than in quartiles 1, 2, and 3, respectively 31.4 (95% CI = 26.5 to 36.3), 34.2 (95% CI = 29.9 to 38.5), and 43.2 (95% CI = 39.0 to 47.4). CONCLUSION After the introduction of social distancing measures, the incidence rates per 100 000 people dropped stronger in most densely populated ULTAs. | qrhzum9v |
coronavirus social distancing impact | 10 | Evaluating the Effectiveness of Social Distancing Interventions to Delay or Flatten the Epidemic Curve of Coronavirus Disease. | By April 2, 2020, >1 million persons worldwide were infected with severe acute respiratory syndrome coronavirus 2. We used a mathematical model to investigate the effectiveness of social distancing interventions in a mid-sized city. Interventions reduced contacts of adults >60 years of age, adults 20-59 years of age, and children <19 years of age for 6 weeks. Our results suggest interventions started earlier in the epidemic delay the epidemic curve and interventions started later flatten the epidemic curve. We noted that, while social distancing interventions were in place, 20% of new cases and most hospitalizations and deaths were averted, even with modest reductions in contact among adults. However, when interventions ended, the epidemic rebounded. Our models suggest that social distancing can provide crucial time to increase healthcare capacity but must occur in conjunction with testing and contact tracing of all suspected cases to mitigate virus transmission. | x9zg7ulr |
coronavirus social distancing impact | 10 | Effects of Proactive Social Distancing on COVID-19 Outbreaks in 58 Cities, China. | Cities across China implemented stringent social distancing measures in early 2020 to curb coronavirus disease outbreaks. We estimated the speed with which these measures contained transmission in cities. A 1-day delay in implementing social distancing resulted in a containment delay of 2.41 (95% CI 0.97-3.86) days. | maxvppn8 |
coronavirus social distancing impact | 10 | Vertical social distancing policy is ineffective to contain the COVID-19 pandemic. | Considering numerical simulations, this study shows that the so-called vertical social distancing health policy is ineffective to contain the COVID-19 pandemic. We present the SEIR-Net model, for a network of social group interactions, as a development of the classic mathematical model of SEIR epidemics (Susceptible-Exposed-Infected (symptomatic and asymptomatic)-Removed). In the SEIR-Net model, we can simulate social contacts between groups divided by age groups and analyze different strategies of social distancing. In the vertical distancing policy, only older people are distanced, whereas in the horizontal distancing policy all age groups adhere to social distancing. These two scenarios are compared to a control scenario in which no intervention is made to distance people. The vertical distancing scenario is almost as bad as the control, both in terms of people infected and in the acceleration of cases. On the other hand, horizontal distancing, if applied with the same intensity in all age groups, significantly reduces the total infected people "flattening the disease growth curve". Our analysis considers the city of Belo Horizonte, Minas Gerais State, Brazil, but similar conclusions apply to other cities as well. Code implementation of the model in R-language is provided in the supplementary material. | raojr7o4 |
coronavirus social distancing impact | 10 | Estimates of regional infectivity of COVID-19 in the United Kingdom following imposition of social distancing measures | We describe regional variation in the reproduction number of SARS-CoV-2 infections observed using publicly reported data in the UK, with a view to understanding both if there are clear hot spots in viral spread in the country, or if there are any clear spatial patterns. We estimate that the viral replication number remains slightly above 1 overall but that its trend is to decrease, based on case data up to the 8 April. This suggests the peak of the first wave of COVID-19 patients is imminent. We find that there is significant regional variation in different regions of the UK and that this is changing over time. Within England currently the reproductive ratio is lowest in the Midlands (1.11 95% CI 1.07; 1.14), and highest in the North East of England (1.38 95% CI 1.33-1.42). It remains unclear whether the overall reduction in the reproductive number is a result of social distancing measures, due to the long and variable time delays between infection and positive detection of cases. As we move forwards, if we are to prevent further outbreaks, it is critical that we can both reduce the time taken for detection and improve our ability to predict the regional spread of outbreaks | fqvrlrv0 |
coronavirus social distancing impact | 10 | Sustaining Social Distancing Policies to Prevent a Dangerous Second Peak of COVID-19 Outbreak | Governments around the world have enacted strict social distancing policies in order to slow the spread of COVID-19. The next step is figuring out when to relax these restrictions and to what degree. Our results predict potentially disastrous implications of ending these policies too soon, based on projections made from a Susceptible-Exposed-Infectious-Removed (SEIR) epidemic model. Even when infection rates appear to be slowing down or decreasing, prematurely returning to "business as usual" produces a severe second peak far worse than the first. Furthermore, such a second peak is made more likely when very severe restrictions are initially enacted. Only an appropriately measured and committed set of restrictions can appropriately control COVID-19 outbreak levels. | j1ma6r50 |
coronavirus social distancing impact | 10 | Are we #stayinghome to Flatten the Curve? | The recent spread of COVID-19 across the U.S. led to concerted efforts by states to ``flatten the curve" through the adoption of stay-at-home mandates that encourage individuals to reduce travel and maintain social distance and indeed using data on travel activity we find that residents start reducing mobility early in most states. Combining data on changes in travel activity with COVID-19 health outcomes and variation in state policy adoption, we characterize the direct impact of stay-at-home mandates on mobility and social distancing and link these behavioral changes to health benefits. We find evidence of dramatic declines in mobility nationwide prior to the adoption of statewide mandates. Despite these early reductions, we find that statewide stay-at-home policies induced "mandate effects" of between 4.1 and 5.9 percentage point declines relative to pre-COVID-19 levels for the first four states to introduce such policies. These effects persist when considering all states' mandates and alternate estimation strategies that account for states' differences in travel behavior prior to policy adoption. Using previous changes in mobility, we find significant effects on current mortality, with 1% reductions in visits to non-essential businesses weeks prior being associated with 9.2 fewer deaths per 100 million per day, corresponding with over 74,000 lives saved nationwide and resulting economic benefits between $249-$745 billion for observed behavioral changes in March and April. Observed reductions in mobility indeed contribute to flattening the curve and reduce the strain on the medical system during those two months. Our findings provide evidence that statewide stay-at-home ordinances induce additional social distancing, and ultimately attenuate the negative health consequences of COVID-19, revealing themselves as important policy tools in the fight against pandemic. Further, substantial reductions in mobility prior to state-level policies convey important policy implications. | 4lgy9te8 |
coronavirus social distancing impact | 10 | Public health interventions in India slowed the spread of COVID-19 epidemic dynamics | Background The government of India implemented social distancing interventions to contain the COVID-19 epidemic. However, effects on epidemic dynamics are yet to be understood. Methods Rates of laboratory-confirmed COVID-19 infections per day and effective reproduction number (Rt) were estimated for 4 periods (Pre-lockdown and Lockdown Phases 1 to 3) according to nationally implemented phased interventions. Adoption of these interventions was estimated using Google mobility data. Estimates at the national level and for 12 Indian states most affected by COVID-19 are presented. Findings Daily case rates ranged from 0.03 to 30.05/10 million people across 4 discrete periods in India. From May 4-17, 2020, the National Capital Territory (NCT) of Delhi had the highest case rate (222/10 million people/day), whereas Kerala had the lowest (2.18/10 million/day). Average Rt was 1.99 (95% CI 1.93-2.06) for India; it ranged from 1.38 to 2.78, decreasing over time. Median mobility in India decreased in all contact domains, with the lowest being 21% in retail/recreation (95% CI 13-46%), except home which increased to 129% (95% CI 117-132%) compared to the 100% baseline value. Interpretation The Indian government imposed strict contact mitigation, followed by a phased relaxation, which slowed the spread of COVID-19 epidemic progression in India. The identified daily COVID-19 case rates and Rt will aid national and state governments in formulating ongoing COVID-19 containment plans. Furthermore, these findings may inform COVID-19 public health policy in developing countries with similar settings to India. Funding Non-funded. | nney9kuq |
coronavirus social distancing impact | 10 | Impact of social distancing measures for preventing coronavirus disease 2019 : A systematic review and meta-analysis protocol | Abstract Introduction: Social distancing measures (SDMs) protect public health from the outbreak of coronavirus disease 2019 (COVID-19). However, the impact of SDMs has been inconsistent and unclear. This study aims to assess the effects of SDMs (e.g. isolation, quarantine) for reducing the transmission of COVID-19. Methods and analysis: We will conduct a systematic review meta-analysis research of both randomised controlled trials and non-randomised controlled trials. We will search MEDLINE, EMBASE, Allied & Complementary Medicine, COVID-19 Research and WHO database on COVID-19 for primary studies assessing the enablers and barriers associated with SDMs, and will be reported in accordance with PRISMA statement. The PRISMA-P checklist will be used while preparing this protocol. We will use Joanna Briggs Institute guidelines (JBI Critical Appraisal Checklists) to assess the methodological qualities and synthesised performing thematic analysis. Two reviewers will independently screen the papers and extracted data. If sufficient data are available, the random-effects model for meta-analysis will be performed to measure the effect size of SDMs or the strengths of relationships. To assess the heterogeneity of effects, I2 together with the observed effects (Q-value, with degrees of freedom) will be used to provide the true effects in the analysis. Ethics and dissemination: Ethics approval and consent will not be required for this systematic review of the literature as it does not involve human participation. We will be able to disseminate the study findings using the following strategies: we will be publishing at least one paper in peer-reviewed journals, and an abstract will be presented at suitable national/international conferences or workshops. We will also share important information with public health authorities as well as with the World Health Organization. | 3mwx9s5x |
coronavirus social distancing impact | 10 | Estimating the effect of physical distancing on the COVID-19 pandemic using an urban mobility index | Governments around the world are implementing population-wide physical distancing measures in an effort to control transmission of COVID-19, but metrics to evaluate their effectiveness are not readily available. We used a publicly available mobility index based on the relative frequency of trips planned in a popular transit application to evaluate the effect of physical distancing on infection growth rates and reproductive number in 34 states and countries. We found that a 10% decrease in relative mobility in the 2nd week of March was associated with a 11.8% relative decrease (exp(β) = 0.882; 95% CI: 0.822, 0.946) in the average daily growth rate in the fourth week of March and a change in the instantaneous reproductive number of -0.054 (95% CI: 0.097, -0.011) in the same period. Our analysis demonstrates that decreases in urban mobility were predictive of declines in epidemic growth at national or sub-national scales. Mobility metrics offer an appealing method to calibrate population-level physical distancing policy and implementation. | radi0wlh |
coronavirus social distancing impact | 10 | Full lockdown policies in Western Europe countries have no evident impacts on the COVID-19 epidemic. | This phenomenological study assesses the impacts of full lockdown strategies applied in Italy, France, Spain and United Kingdom, on the slowdown of the 2020 COVID-19 outbreak. Comparing the trajectory of the epidemic before and after the lockdown, we find no evidence of any discontinuity in the growth rate, doubling time, and reproduction number trends. Extrapolating pre-lockdown growth rate trends, we provide estimates of the death toll in the absence of any lockdown policies, and show that these strategies might not have saved any life in western Europe. We also show that neighboring countries applying less restrictive social distancing measures (as opposed to police-enforced home containment) experience a very similar time evolution of the epidemic. | fmgj3noh |
coronavirus social distancing impact | 10 | Orthogonal Functions for Evaluating Social Distancing Impact on CoVID-19 Spread | Early CoVID-19 growth often obeys: N{t}=N/Iexp[+K/ot], with K/o=[(ln2)/(t/dbl)], where t/dbl is the pandemic doubling time, prior to society-wide Social Distancing. Previously, we modeled Social Distancing with t/dbl as a linear function of time, where N[t]=1exp[+K/A t/(1+ gamma/o t)] is used here. Additional parameters besides {K/o,gamma/o} are needed to better model different rho[t]=dN[t]/dt shapes. Thus, a new Orthogonal Function Model [OFM] is developed here using these orthogonal function series: N(Z) = sum[m=0,M/F] g/m L/m(Z) exp[-Z] , R(Z) = sum[m=0,M/F] c/m L/m(Z) exp[-Z] , where N(Z) and Z[t] form an implicit N[t]=N(Z[t]) function, giving: G/o = [K/A / gamma/o ] , Z[t] = +[ G/o / (1+ gamma/ot) ] , rho[t] = [ gamma/o / G/o ] (Z^2) R(Z) , with L/m(Z) being the Laguerre Polynomials. At large M/F values, nearly arbitrary functions for N[t] and rho[t]=dN[t]/dt can be accommodated. How to determine {K/A, gamma/o} and the {g/m; m=(0,+M/F)} constants from any given N(Z) dataset is derived, with rho[t] set by: c/(M/F - k) = sum[m=0,k] g/m . The bing.com USA CoVID-19 data was analyzed using M/F=(0,1,2) in the OFM. All results agreed to within about 10 percent, showing model robustness. Averaging over all these predictions gives the following overall estimates for the number of USA CoVID-19 cases at the pandemic end: = 5,009,677 (+/-) 269,450 (data to 5/3/20), and = 4,422,803 (+/-) 162,580 (data to 6/7/20), which compares the pre- and post-early May bing.com revisions. The CoVID-19 pandemic in Italy was examined next. The M/F=2 limit was inadequate to model the Italy rho[t] pandemic tail. Thus, regions with a quick CoVID-19 pandemic shutoff may have additional Social Distancing factors operating, beyond what can be easily modeled by just progressively lengthening pandemic doubling times (with 13 Figures). | 1exyjhj0 |
coronavirus social distancing impact | 10 | Enacting national social distancing policies corresponds with dramatic reduction in COVID19 infection rates | The outbreak the SARS-CoV-2 (CoV-2) virus has resulted in over 2.5 million cases of COVID19, greatly stressing global healthcare infrastructure. Lacking medical prophylactic measures to combat disease spread, many nations have adopted social distancing policies in order to mitigate transmission of CoV-2. While mathematical models have suggested the efficacy of social distancing to curb the spread of CoV-2, there is a lack of systematic studies to quantify the real-world efficacy of these approaches. Here, we quantify the spread rate of COVID19 before and after national social distancing measures were implemented in 26 nations and compare this to the changes in COVID19 spread rate over equivalent time periods in 27 nations that did not enact social distancing policies. We find that social distancing policies significantly reduced the COVID19 spread rate. Using mixed linear regression models we estimate that social distancing policies reduced the spread of COVID19 by 66%. These data suggest that social distancing policies may be a powerful tool to prevent spread of COVID19 in real-world scenarios. | vdrd74nz |
coronavirus social distancing impact | 10 | Estimating the impact of physical distancing measures in containing COVID-19: an empirical analysis | Background Epidemic modelling studies predict that physical distancing is critical in containing COVID-19. However, few empirical studies have validated this finding. Our study evaluates the effectiveness of different physical distancing measures in controlling viral transmission. Methods We identified three distinct physical distancing measures with varying intensity and implemented at different times - international travel controls, restrictions on mass gatherings, and lockdown-type measures - based on the Oxford COVID-19 Government Response Tracker. We also estimated the time-varying reproduction number (Rt) for 142 countries and tracked Rt temporally for two weeks following the 100th reported case in each country. We regressed Rt on the physical distancing measures and other control variables (income, population density, age structure, and temperature) and performed several robustness checks to validate our findings. Findings Complete travel bans and all forms of lockdown-type measures have been effective in reducing average Rt over the 14 days following the 100th case. Recommended stay-at-home advisories and partial lockdowns are as effective as complete lockdowns in outbreak control. However, these measures have to be implemented early to be effective. Lockdown-type measures should be instituted two weeks before the 100th case and travel bans about a week before detection of the first case. Interpretation A combination of physical distancing measures, if implemented early, can be effective in containing COVID-19 - tight border controls to limit importation of cases, encouraging physical distancing, moderately stringent measures such as working from home, and a full lockdown in the case of a probable uncontrolled outbreak. | ldeqvajo |
coronavirus social distancing impact | 10 | Modelling the impact of control measures against the COVID-19 pandemic in Viet Nam | Objectives: Health care system of many countries are facing a surging burden of COVID-19. Although Vietnam has successfully controlled the COVID-19 pandemic to date, there is a sign of initial community transmission. An estimate of possible scenarios to prepare health resources in the future is needed. We used modelling methods to estimate impacts of mitigation measures on the COVID-19 pandemic in Vietnam. Methods: SEIR model built in the COVIDSIM1.1 tool was adopted using available data for estimation. The herd immunization scenario was with no intervention implemented. Other scenarios consisted of isolation and social distancing at different levels (25%, 50%, 75% and 10%, 20%, 30%, respectively). Outcomes include epidemic apex, daily new and cumulative cases, deaths, hospitalized patients and ICU beds needed. Results: By April 8, 2020, there would be 465 infected cases with COVID-19 in Viet Nam, of those 50% were detected. Cumulatively, there would be 1,400 cases and 30 deaths by end of 2020, if 75% of cases was detected and isolated, and 30% of social distancing could be maintained. The most effective intervention scenario is the detection and isolation of 75% infected cases and reduction of 10% social contacts. This will require an expansion of testing capacity at health facilities and in the community, posing a challenge to identify high-risk groups to prioritized testing. Conclusions: In a localized epidemic setting, the expansion of testing should be the key measure to control the epidemic. Social distancing plays a significant role to prevent further transmission to the community. | 0k6r5q1t |
coronavirus social distancing impact | 10 | Instantaneous R calculation for COVID-19 epidemic in Brazil | COVID-19 pandemic represents a major challenge to health systems of all countries. Brazilian regions habe been showing marked di[ff]erences in onset and number of cases. Health authorities instituted widespread social distancing and lockdown measures but their implementation has also varied. The authors used data on con[fi]rmed cases of COVID-19 in Brazil and its states to calculate the value of instantaneous reproduction number at these regions. The results show a reduction of instantaneous reproduction number with time, probably due to social distancing measures put in place in the last weeks by brazillian authorities. It seems logical to maintain restrictions to social contact until the epidemic peak has occurred in Brazil. | o5cmhvy3 |
coronavirus social distancing impact | 10 | Modelling the potential impact of social distancing on the COVID-19 epidemic in South Africa | The novel coronavirus (COVID-19) pandemic continues to be a global health problem whose impact has been significantly felt in South Africa. Social distancing has been touted as the best form of response in managing a rapid increase in the number of infected cases. In this paper, we present a deterministic model to model the impact of social distancing on the transmission dynamics of COVID-19 in South Africa. The model is fitted to the currently available data on the cumulative number of infected cases and a scenario analysis on different levels of social distancing are presented. The results show a continued rise in the number of cases in the lock down period with the current levels of social distancing albeit at a lower rate. The model shows that the number of cases will rise to above 4000 cases by the end of the lockdown. The model also looks at the impact of relaxing the social distancing measures after the initial announcement of the lock down measures. A relaxation of the social distancing by 2% can result in a 23% rise in the number of cumulative cases while on the other hand increasing the levels of social distancing by 2% would reduce the number of cumulative cases by about 18%. These results have implications on the management and policy direction in the early phases of the epidemic. | q5xc4m3j |
coronavirus social distancing impact | 10 | SHELTER IN PLACE ORDER CONTAINED COVID-19 GROWTH RATE IN GREECE | Background: The Greek authorities implemented the strong social distancing measures within the first few weeks after the first confirmed case of the virus to curtail the COVID-19 growth rate. Objectives: To estimate the effect of the two-stage strong social distancing measures, the closure of all non-essential shopping centers and businesses on March 16 and the shelter in place orders (SIPOs) on March 23 on the COVID-19 growth rate in Greece Methods: We obtained data on COVID-19 cases in Greece from February 26th through May 4th from publicly available sources. An interrupted time-series regression analysis was used to estimate the effect of the measures on the exponential growth of confirmed COVID-19 cases, controlling for the number of daily testing, and weekly fixed-effects. Results: The growth rate of the COVID-19 cases in the pre-policies implementation period was positive as expected (p=0.003). Based on the estimates of the interrupted time-series, our results indicate that the SIPO on March 23 significantly slowed the growth rate of COVID-19 in Greece (p=0.04). However, we did not find evidence on the effectiveness of standalone and partial measures such as the non-essential business closures implemented on March 16 on the COVID-19 spread reduction. Discussion: The combined social distancing measures implemented by the Greek authorities within the first few weeks after the first confirmed case of the virus reduced the COVID-19 growth rate. These findings provide evidence and highlight the effectiveness of these measures to flatten the curve and to slow the spread of the virus. | tkajjrri |
coronavirus social distancing impact | 10 | Effects of social distancing on the spreading of COVID-19 inferred from mobile phone data | A better understanding of how the COVID-19 epidemic responds to social distancing efforts is required for the control of future outbreaks and to calibrate partial lock-downs. We present quantitative relationships between key parameters characterizing the COVID-19 epidemiology and social distancing efforts of nine selected European countries. Epidemiological parameters were extracted from the number of daily deaths data, while mitigation efforts are estimated from mobile phone tracking data. The decrease of the basic reproductive number (R0) as well as the duration of the initial exponential expansion phase of the epidemic strongly correlates with the magnitude of mobility reduction. Utilizing these relationships we decipher the relative impact of the timing and the extent of social distancing on the total death burden of the epidemic. | gz18sxzc |
coronavirus social distancing impact | 10 | Social Distancing Has Merely Stabilized COVID-19 in the US | Social distancing measures, with varying degrees of restriction, have been imposed around the world in order to stem the spread of COVID-19. In this work we analyze the effect of current social distancing measures in the United States. We quantify the reduction in doubling rate, by state, that is associated with social distancing. We find that social distancing is associated with a statistically-significant reduction in the doubling rate for all but three states. At the same time, we do not find significant evidence that social distancing has resulted in a reduction in the number of daily confirmed cases. Instead, social distancing has merely stabilized the spread of the disease. We provide an illustration of our findings for each state, including point estimates of the effective reproduction number, R, both with and without social distancing. We also discuss the policy implications of our findings. | all7ocnd |
coronavirus social distancing impact | 10 | A single holiday was the turning point of the COVID-19 policy of Israel | Background: The impact of COVID-19 has been profound, and the public health challenge seem to be the most serious regarding respiratory viruses since the 1918 H1N1 influenza pandemic. In the absence of effective vaccine or biomedical treatment, the basic rules of public health measures have not changed, namely public distancing. Methods: We analyzed epidemiological investigation reports during the first month of the outbreak in Israel. In addition, we present a deterministic compartment model and simulations of several scenarios emphasizing quarantine and isolation policies given their efficiency. Results: We identify an abrupt change from controlled epidemic regime to an exponential growth (R_0= 2.19) in light of the actual policy-makers decisions and public behavior in Israel. Our analysis show that before the abrupt change, the new cases trend was due to returning citizens infected abroad. The abrupt change followed a holiday in which social distancing was clearly inefficient and many public gatherings were held. We further discuss three different modeled scenarios of quarantine efficiency: high-, medium-, and low-efficiency. Conclusions: Israel early lessons show that there is no allowance to compromise with the directive of social distancing. Even before the onset of the pandemic in Israel, fine-tuned but determined early decisions were taken by policy makers to monitor flight arrivals from Covid-19 affected regions and to limit public gatherings. Our analysis show that one particular holiday has shifted the occurrence curve from controlled regime to exponential growth. Therefore, even a short lapse in public responsiveness can have a dramatic effect. | 32hjzdum |
coronavirus social distancing impact | 10 | Flattening the curve and the effect of atypical events on mitigation measures in Mexico: a modeling perspective | On 23 and 30 March 2020 the Mexican Federal government implemented social distancing measures to mitigate the COVID-19 epidemic. We use a mathematical model to explore atypical transmission events within the confinement period, triggered by the timing and strength of short time perturbations of social distancing. We show that social distancing measures were successful in achieving a significant reduction of the effective contact rate in the early weeks of the intervention. However, "flattening the curve" had an undesirable effect, since the epidemic peak was delayed too far, almost to the government preset day for lifting restrictions (01 June 2020). If the peak indeed occurs in late May or early June, then the events of children's day and mother's day may either generate a later peak (worst case scenario), a long plateau with relatively constant but high incidence (middle case scenario) or the same peak date as in the original baseline epidemic curve, but with a post-peak interval of slower decay. | 9azl5nl8 |
coronavirus social distancing impact | 10 | Analyzing the World-Wide Impact of Public Health Interventions on the Transmission Dynamics of COVID-19 | We analyze changes in the reproduction number, R, of COVID-19 in response to public health interventions. Our results indicate that public health measures undertaken in China reduced R from 1.5 in January to 0.4 in mid-March 2020. They also suggest, however, the limitations of isolation, quarantine, and large-scale attempts to limit travel. While the world-wide reproduction number briefly dropped below 1 as China implemented extensive public health measures, the introduction of the virus to other nations swiftly led to an increasing world-wide average value of R. In Italy, the nation hardest-hit following China, social distancing measures brought the local value of R down from 3.71 to 2.51. Nonetheless, the value of R in Italy persisted at levels well above 1, allowing for ongoing transmission. By mid-March 2020, as COVID-19 spread in areas without extensive public health interventions in place, the world-wide value of R increased to a level similar to that of late January. | tc02pxt9 |
coronavirus social distancing impact | 10 | Estimates of the ongoing need for social distancing and control measures post-"lockdown" from trajectories of COVID-19 cases and mortality. | By 21st April 2020 COVID_19 had caused more than 2m cases across more than 200 countries. The majority of countries with significant outbreaks introduced social distancing or "lockdown" measures to reduce viral transmission. The key question now in many countries is when, how, and to what extent these measures can be lifted. By fitting regression models to publically available data on daily numbers of newly-confirmed cases and mortality, trajectories, doubling times and reproduction number (R0) were estimated both before and under the control measures. These data ran up to 21st April 2020, and covered 67 countries that had provided sufficient data for modelling. The estimates of R0, before lockdown, based on these data were broadly consistent with those previously published at between 2.0 and 3.7 in the countries with the largest number of cases available for analysis (USA, Italy, Spain, France and UK). There was little evidence to suggest that the restrictions had reduced R far below 1 in many places, with Spain having the most rapid reductions - R0 0.71 (95%CI 0.65-0.78) based on cases and 0.81 (95%CI 0.77-0.85) based on mortality. Intermittent lockdown has been proposed as a means of controlling the outbreak while allowing periods of increase freedom and economic activity. These data suggest that few countries could have even one week per month unrestricted without seeing resurgence of the epidemic. Similarly, restoring 20% of the activity that has been prevented by the lockdowns looks difficult to reconcile with preventing the resurgence of the disease in most countries. | nf6v5dya |
coronavirus social distancing impact | 10 | Act early, save lives: managing COVID-19 in Greece | Abstract Objectives: To assess the impact of the implemented social distancing interventions (SD) in Greece. Study Design: A dynamic, discrete time, stochastic individual-based model was developed to simulate COVID-19 transmission. Methods: We fit the transmission model to the observed trends in deaths and ICU beds use. Results: If Greece had not implemented the SD measures, the healthcare system would have been overwhelmed between 30 March and 4 of April. Additionally, the SD interventions averted 4360 deaths and prevent the healthcare system from overwhelmed. Conclusions: The fast reflexes of the Greek government limit the burden of the Covid-19 outbreak. | 7mbvxx1n |
coronavirus social distancing impact | 10 | Transmission of SARS-CoV-2 in Georgia, USA, 2020 | Objective: SARS-CoV-2 has significantly impacted Georgia, USA including two major hotspots, Metro Atlanta and Dougherty County in southwestern Georgia. With government deliberations about relaxing social distancing measures, it is important to understand the trajectory of the epidemic in the state of Georgia. Methods: We collected daily cumulative incidence of confirmed COVID-19 cases in Georgia. We estimated the reproductive number (Re) of the COVID-19 epidemic on April 18 and May 2 by characterizing the initial growth phase of the epidemic using the generalized-growth model. Results: The data presents a sub-exponential growth pattern in the cumulative incidence curves. On April 18, 2020, Re was estimated as 1.20 (95% CI: 1.10, 1.20) for the state of Georgia, 1.10 (95% CI: 1.00, 1.20) for Dougherty County, and 1.20 (95% CI: 1.10, 1.20) for Metro Atlanta. Extending our analysis to May 2, 2020, Re estimates decreased to 1.10 (95% CI: 1.10, 1.10) for the state of Georgia, 1.00 (95% CI: 1.00, 1.10) for Dougherty County, and 1.10 (95% CI: 1.10, 1.10) for Metro Atlanta. Conclusions: Transmission appeared to be decreasing after the implementation of social distancing measures. However, these results should be interpreted with caution when considering relaxing control measures due to low testing rates. | e2v9o6oa |
coronavirus social distancing impact | 10 | Diminishing Marginal Benefit of Social Distancing in Balancing COVID-19 Medical Demand-to-Supply | Social distancing has been adopted as a non-pharmaceutical intervention to prevent the COVID-19 pandemic from overwhelming the medical resources across the United States (US). The catastrophic socio-economic impacts of this intervention could outweigh its benefits if the timing and duration of implementation are left uncontrolled and ill-strategized. Here we investigate the dynamics of social distancing on age-stratified US population and benchmark its effectiveness in reducing the burden on hospital and ICU beds. Our findings highlight the diminishing marginal benefit of social distancing, characterized by a linear decrease in medical demands against an exponentially increasing social distancing duration. We determine an optimal intermittent social-to-no-distancing ratio of 5:1 corresponding to ~80% reduction in healthcare demands; beyond this ratio, benefit of social distancing diminishes to a negligible level. COVID-19 Medical Forecast: https://eece.wustl.edu/chakrabarty-group/covid/ | rzh7ja6a |
coronavirus social distancing impact | 10 | COVID-19 outbreak response: a first assessment of mobility changes in Italy following national lockdown | Italy is currently experiencing the largest COVID-19 outbreak in Europe so far, with more than 100,000 confirmed cases. Following the identification of the first infections, on February 21, 2020, national authorities have put in place an increasing number of restrictions aimed at containing the outbreak and delaying the epidemic peak. Since March 12, the whole country is under lockdown. Here we provide the first quantitative assessment of the impact of such measures on the mobility and the spatial proximity of Italians, through the analysis of a large-scale dataset on de-identified, geo-located smartphone users. With respect to pre-outbreak averages, we estimate a reduction of 50% of the total trips between Italian provinces, following the lockdown. In the same week, the average users' radius of gyration has declined by about 50% and the average degree of the users' proximity network has dropped by 47% at national level. | sgkuqcq6 |
coronavirus social distancing impact | 10 | Insufficient social distancing may be related to a future COVID-19 outbreak in Ijui-Brazil: Predictions of further social interventions. | The coronavirus disease that initiates in 2019 (COVID-19) has proven to be highly contagious since it became pandemic quickly and nowadays presents higher transmission rates worldwide, including small Brazilian cities, as Ijui. Located in the northwestern of the State of Rio Grande do Sul (RS) with 83,475 inhabitants, Ijui was selected to receive a population-based survey divided into four steps separated by 15 days each that involved 1,750 subjects. Subjects were tested for the presence of antibodies against coronavirus (SARS CoV-2) and answered questions about social distance adherence, daily routine, comorbidities, and sociodemographic characteristics. In parallel, the local government registered the official COVID-19 cases in Ijui. In this study, we demonstrated the levels of social distancing adherence and the beginning of COVID-19 community transmission in Ijui and showed some predictions for cases, hospitalization, and deaths. We concluded that the insufficient social distancing registered in the population-based study might be related to the rapid increase of COVID-19 cases in Ijui. Our study predicts a closer outbreak of community infection of COVID-19, which could be avoided or attenuated if the levels of the social distancing in the population increase in the next weeks. | 0w8i7l7v |
coronavirus social distancing impact | 10 | Evaluating the Efficacy of Stay-At-Home Orders: Does Timing Matter? | BACKGROUND: The many economic, psychological, and social consequences of pandemics and social distancing measures create an urgent need to determine the efficacy of non-pharmaceutical interventions (NPIs), and especially those considered most stringent, such as stay-at-home and self-isolation mandates. This study focuses specifically on the efficacy of stay-at-home orders, both nationally and internationally, in the control of COVID-19. METHODS: We conducted an observational analysis from April to May 2020 and included countries and US states with known stay-at-home orders. Our primary exposure was the time between the date of the first reported case of COVID-19 to an implemented stay-at-home mandate for each region. Our primary outcomes were the time from the first reported case to the highest number of daily cases and daily deaths. We conducted simple linear regression analyses, controlling for the case rate of the outbreak. RESULTS: For US states and countries, a larger number of days between the first reported case and stay-at-home mandates was associated with a longer time to reach the peak daily case and death counts. The largest effect was among regions classified as the latest 10% to implement a mandate, which in the US, predicted an extra 35.3 days to the peak number of cases (95 % CI: 18.2, 52.5), and 38.3 days to the peak number of deaths (95 % CI: 23.6, 53.0). CONCLUSIONS: Our study supports the potential beneficial effect of earlier stay-at-home mandates, by shortening the time to peak case and death counts for US states and countries. Regions in which mandates were implemented late experienced a prolonged duration to reaching both peak daily case and death counts. | mnt12ot2 |
coronavirus social distancing impact | 10 | COVID-19 related social distancing measures and reduction in city mobility | In the absence of any pharmacological intervention, one approach to slowing the COVID-19 pandemic is reducing the contact rate in the population through social distancing. Governments the world over have instituted different measures to increase social distancing but information on their effectiveness in reducing mobility is lacking. We analyzed the mobility data from 41 cities to look at the effect of these interventions. The median mobility across cities on March 2, 2020 was 100% (IQR: 94%, 107%), which decreased to a median of 10% (IQR: 7%, 17%) on March 26, 2020. We found that the mobility decreased on average by 3.4% (95%CI: 3.3%, 3.6%) per day from March 2 through March 26. Social distancing measures decreased the mobility by an additional 23% (95%CI: 20%, 27%). Our study provides initial evidence for the reduction in mobility in cities instituting social distancing measures. | 71b6ai77 |
coronavirus social distancing impact | 10 | SOCRATES: An online tool leveraging a social contact data sharing initiative to assess mitigation strategies for COVID-19 | Objective: Establishing a social contact data sharing initiative and an interactive tool to assess mitigation strategies for COVID-19. Results: We organized data sharing of published social contact surveys via online repositories and formatting guidelines. We analyzed this social contact data in terms of weighted social contact matrices, next generation matrices, relative incidence and R0. We incorporated location-specific isolation measures (e.g. school closure or telework) and capture their effect on transmission dynamics. All methods have been implemented in an online application based on R Shiny and applied to COVID-19 with age-specific susceptibility and infectiousness. Using our online tool with the available social contact data, we illustrate that social distancing could have a considerable impact on reducing transmission for COVID-19. The effect itself depends on assumptions made about disease-specific characteristics and the choice of intervention(s). Keywords: social contact data, user interface, transmission dynamics, infectious diseases, epidemics, social distancing, behavioral changes, data sharing initiative, open-source, COVID-19 | hs38s0vc |
coronavirus social distancing impact | 10 | Is the impact of social distancing on coronavirus growth rates effective across different settings? A non-parametric and local regression approach to test and compare the growth rate | Epidemiologists use mathematical models to predict epidemic trends, and these results are inherently uncertain when parameters are unknown or changing. In other contexts, such as climate, modellers use multi-model ensembles to inform their decision-making: when forecasts align, modellers can be more certain. This paper looks at a sub-set of alternative epidemiological models that focus on the growth rate, and it cautions against relying on the method proposed in (Pike & Saini, 2020): relying on the data for China to calculate future trajectories is likely to be subject to overfitting, a common problem in financial and economic modelling. This paper finds, surprisingly, that the data for China are double-exponential, not exponential; and that different countries are showing a range of different trajectories. The paper proposes using non-parametric and local regression methods to support epidemiologists and policymakers in assessing the relative effectiveness of social distancing policies. All works contained herein are provided free to use worldwide by the author under CC BY 2.0. | sg5uwuqc |
coronavirus social distancing impact | 10 | The effect of non-pharmaceutical interventions (NPIs) on the spread of COVID-19 pandemic in Japan: A modeling study | Non-pharmaceutical interventions (NPIs) are founded to be effective to delay epidemic spread and to reduce the number of patients. Moderate NPIs took in Japan seemed to have reduced the COVID-19 patients and to lower death rates, thus, effects of those NPIs are worthy of investigation. We used open source data and divided the data into three periods: Jan 22 to Feb 25 (Period I), Feb 26 to Apr 6 (Period II), and Apr 7 to May 14 (Period III). We developed the SIRD model and applied the Monte Carlo Simulation to estimate a combination of optimal results, including the peak of infected cases, the peak date, and R0. For Period I, the estimated peak infected cases were smaller than the observed ones, the peak date was earlier than the observed one, and the R0 was about 4.66. For the other two periods, the estimated cases were more, and the peak dates were earlier than the observed ones. The R0 was 2.50 in Period II, and 1.79 in Period III. NPIs took in Japan might have reduced more than 50% of the daily contacts per people compared to that before COVID-19. Owing to the effects of NPIs, the Japanese society had avoided collapse of medical service. Nevertheless, the capacity of daily RT-PCR may have restricted the reported confirmed cases. | 80bn2wgd |
coronavirus social distancing impact | 10 | Analysis and Prediction of the COVID-19 outbreak in Pakistan | In this study, we estimate the severity of the COVID-19 outbreak in Pakistan prior to and after lockdown restrictions were eased. We also project the epidemic curve considering realistic quarantine, social distancing, and possible medication scenarios. We use a deterministic epidemic model that includes asymptomatic, quarantined, isolated, and medicated population compartments for our analysis. We calculate the basic reproduction number R0 for the pre and post lockdown periods, noting that during this time, no medication was available. The pre-lock down the value of R0 is estimated to be 1.07, and the post lockdown value is estimated to be 1.86. We use this analysis to project the epidemic curve for a variety of lockdown, social distancing, and medication scenarios. We note that if no substantial efforts are made to contain the epidemic, it will peak in mid of September, with the maximum projected active cases being close to 700,000. In a realistic, best-case scenario, we project that the epidemic peaks in early to mid-July with the maximum active cases being around 120000.We note that social distancing measures and medication, if available, will help flatten the curve, however without the reintroduction of further lockdown, it would be very difficult to bring R0 below 1. Our study strongly supports the recent WHO recommendation of reintroducing lockdowns to control the epidemic. | 3dx6deei |
coronavirus social distancing impact | 10 | Evaluation of Turkish social distancing measures on the spread of COVID-19 | The coronavirus disease (COVID-19) affecting across the globe. The government of different countries has adopted various policies to contain this epidemic and the most common were social distancing and lockdown. We use a simple log-linear model with intercept and trend break to evaluate whether the measures are effective preventing/slowing down the spread of the disease in Turkey. We estimate the model parameters from the Johns Hopkins University (2020) epidemic data between 15th March and 16th April 2020. Our analysis revealed that the measures can slow down the outbreak. We can reduce the epidemic size and prolong the time to arrive at the epidemic peak by seriously following the measures suggested by the authorities. | uwix8ftr |
coronavirus social distancing impact | 10 | The nexus of travel restriction, air pollution and COVID-19 infection: Investigation from a megacity of the southern China | To control and prevent the spread of COVID-19, generalized social distancing measures, such as traffic control and travel restriction acted in China. Previous studies indicated that the traffic conditions had significant influence on the air quality, and which was related to the respiratory diseases. This study aimed to reveal the nexus of travel restriction, air pollution and COVID-19. Shenzhen, one of the top 4 megacities in China was considered as the study area, statistical analysis methods, including linear/nonlinear regression and bivariate correlation was conducted to evaluate the relationship of the traffic and passenger population, travel intensity, NO2, PM10, PM2.5 and the number of COVID-19 confirmed cases. The results suggested that traffic control and travel restriction had a significant correlation with the number of COVID-19 confirmed cases, which shown negative correlation with the traffic intensity of the city, NO2, PM10 and PM2.5 show significant positive correlation with the traffic intensity, traffic control and travel restriction would slow down and prevent the spread of the viruses at the outbreak period. Different study scale might results in different results, thus the research focused on the nexus of traffic control and travel restriction, air pollution and COVID-19 should been enhanced in future, and differentiated epidemic control and prevention measures should be considered according to the different situation of cities as well as countries. | tarb3zxk |
coronavirus social distancing impact | 10 | COVID-19 Control Strategies and Intervention Effects in Resource Limited Settings: A Modeling Study | Background Many countries with weaker health systems are struggling to put together a coherent strategy against the COVID-19 epidemic. We explored COVID-19 control strategies that could offer the greatest benefit in resource limited settings. Methods Using an age-structured SEIR model, we explored the effects of COVID-19 control interventions--a lockdown, physical distancing measures, and active case finding (testing and isolation, contact tracing and quarantine)-- implemented individually and in combination to control a hypothetical COVID-19 epidemic in Kathmandu (population 2.6 million), Nepal. Results A month-long lockdown that is currently in place in Nepal will delay peak demand for hospital beds by 36 days, as compared to a base scenario of no interventions (peak demand at 108 days (IQR 97-119); a 2 month long lockdown will delay it by 74 days, without any difference in annual mortality, or healthcare demand volume. Year-long physical distancing measures will reduce peak demand to 36% (IQR 23%-46%) and annual morality to 67% (IQR 48%-77%) of base scenario. Following a month long lockdown with ongoing physical distancing measures and an active case finding intervention that detects 5% of the daily infection burden could reduce projected morality and peak demand by more than 99%. Interpretation Limited resources settings are best served by a combination of early and aggressive case finding with ongoing physical distancing measures to control the COVID-19 epidemic. A lockdown may be helpful until combination interventions can be put in place but is unlikely to reduce annual mortality or healthcare demand. | 8w22yn1i |
coronavirus social distancing impact | 10 | A sub-national analysis of the rate of transmission of COVID-19 in Italy | Italy was the first European country to experience sustained local transmission of COVID-19. As of 1st May 2020, the Italian health authorities reported 28,238 deaths nationally. To control the epidemic, the Italian government implemented a suite of non-pharmaceutical interventions (NPIs), including school and university closures, social distancing and full lockdown involving banning of public gatherings and non essential movement. In this report, we model the effect of NPIs on transmission using data on average mobility. We estimate that the average reproduction number (a measure of transmission intensity) is currently below one for all Italian regions, and significantly so for the majority of the regions. Despite the large number of deaths, the proportion of population that has been infected by SARS-CoV-2 (the attack rate) is far from the herd immunity threshold in all Italian regions, with the highest attack rate observed in Lombardy (13.18% [10.66%-16.70%]). Italy is set to relax the currently implemented NPIs from 4th May 2020. Given the control achieved by NPIs, we consider three scenarios for the next 8 weeks: a scenario in which mobility remains the same as during the lockdown, a scenario in which mobility returns to pre-lockdown levels by 20%, and a scenario in which mobility returns to pre-lockdown levels by 40%. The scenarios explored assume that mobility is scaled evenly across all dimensions, that behaviour stays the same as before NPIs were implemented, that no pharmaceutical interventions are introduced, and it does not include transmission reduction from contact tracing, testing and the isolation of confirmed or suspected cases. New interventions, such as enhanced testing and contact tracing are going to be introduced and will likely contribute to reductions in transmission; therefore our estimates should be viewed as pessimistic projections. We find that, in the absence of additional interventions, even a 20% return to pre-lockdown mobility could lead to a resurgence in the number of deaths far greater than experienced in the current wave in several regions. Future increases in the number of deaths will lag behind the increase in transmission intensity and so a second wave will not be immediately apparent from just monitoring of the daily number of deaths. Our results suggest that SARS-CoV-2 transmission as well as mobility should be closely monitored in the next weeks and months. To compensate for the increase in mobility that will occur due to the relaxation of the currently implemented NPIs, adherence to the recommended social distancing measures alongside enhanced community surveillance including swab testing, contact tracing and the early isolation of infections are of paramount importance to reduce the risk of resurgence in transmission. | 32lau54s |
coronavirus social distancing impact | 10 | Impact of control strategies on COVID-19 pandemic and the SIR model based forecasting in Bangladesh. | COVID-19 is transmitting worldwide drastically and infected nearly two and half million of people sofar. Till date 2144 cases of COVID-19 is confirmed in Bangladesh till 18th April though the stage-3/4 transmission is not validated yet. To project the final infection numbers in Bangladesh we used the SIR mathematical model. We also tried to demonstrate the impact of control strategies like social distancing on the COVID-19 transmission. Due to large population and socio-economic characteristics, we assumed 60% social distancing and lockdown can be possible. Assuming that, the predicated final size of infections will be 3782558 on the 92th day from the first infections. To estimate the impact of social distancing we assumed eight different scenarios, the predicted results confirmed the positive impact of this type of control strategies suggesting that by strict social distancing and lockdown, COVID-19 infection can be under control and then the infection cases will steadily decrease down to zero. | le2eifv8 |
coronavirus social distancing impact | 10 | Modeling the Transmission of Respiratory Infectious Diseases in Mass Transportation Systems | Mass transportation is one of the areas that are badly hit by respiratory infectious disease outbreaks due to moderate to high exposure risk to pathogens brought about by the interaction among commuters. Here, we formulate agent-based models that simulate the spread of a respiratory infectious disease in a train wagon in the Manila Light Rail Transit System, and in a 49-seater public utility bus. We consider preventive measures such as implementation of social distancing, and limitation of interaction or movement among the commuters to investigate how these measures will inhibit disease transmission. We also consider the effect of protective gears and practices, crowd density, and prevalence of disease in the community on the possible number of newly-infected individuals. Our simulations show that (i) individuals must have protection with more than 90% effectiveness to inhibit transmission of the disease; (ii) social or physical distancing by more than 1m distance reduces the risk of being infected; (iii) minimizing movement or interaction with other passengers reduces the risk of transmission by 50%; (iv) passenger capacity should be less than 10-50% of the maximum seating capacity to reduce the number of infections depending on the level of imposed social distancing and passenger interaction; (v) vehicles with greater number of occupied seating capacity generate higher number of infections but vehicles with smaller dimensions have faster disease transmissions; and (vi) ideal set-up for a 24-seater train wagon (49-seater bus) is to allow a maximum of 12 (24) passengers, with little to no interaction among passengers, with social distancing of more than 1m distance apart, and each person has a protection with 90% effectiveness as much as possible. These results can aid policy makers in determining optimal strategies to minimize infections while maintaining transportation services during pandemics or disease outbreaks. | n3rdxn2a |
coronavirus social distancing impact | 10 | Reacting to outbreaks at neighboring localities | We study the dynamics of epidemics in a networked metapopulation model. In each subpopulation, representing a locality, disease propagates according to a modified susceptible-exposed-infected-recovered (SEIR) dynamics. We assume that individuals reduce their number of contacts as a function of the weighted sum of cumulative number of cases within the locality and in neighboring localities. The susceptible and exposed (pre-symptomatic and infectious) individuals are allowed to travel between localities undetected. To investigate the combined effects of mobility and contact reduction on disease progression within interconnected localities, we consider a scenario with two localities where disease originates in one and is exported to the neighboring locality via travel of undetected pre-symptomatic individuals. We associate the behavior change at the disease-importing locality due to the outbreak size at the origin with the level of preparedness of the locality. Our results show that restricting mobility is valuable if the importing locality is increasing its level of preparedness with respect to the outbreak size at the origin. Moreover, increased levels of preparedness can yield lower total outbreak size by further reducing the outbreak size at the importing locality, even when the response at the origin is weak. Our results highlight that public health decisions on social distancing at localities with less severe outbreaks should strongly account for potential impact of neighbouring localities with a poor response to the outbreak rather than localities with successful responses. | ceehbhcb |
coronavirus social distancing impact | 10 | Evaluating the effectiveness of social distancing interventions against COVID-19 | SARS-CoV-2 has infected over 140,000 people as of March 14, 2020. We use a mathematical model to investigate the effectiveness of social distancing interventions lasting six weeks in a middle-sized city in the US. We explore four social distancing strategies by reducing the contacts of adults over 60 years old, adults over 60 years old and children, all adults (25, 75 or 95% compliance), and everyone in the population. Our results suggest that social distancing interventions can avert cases by 20% and hospitalizations and deaths by 90% even with modest compliance within adults as long as the intervention is kept in place, but the epidemic is set to rebound once the intervention is lifted. Our models suggest that social distancing interventions will buy crucial time but need to occur in conjunction with testing and contact tracing of all suspected cases to mitigate transmission of SARS-CoV-2. | 0a49okho |
coronavirus social distancing impact | 10 | Optimal Control applied to a SEIR model of 2019-nCoV with social distancing | Does the implementation of social distancing measures have merit in controlling the spread of the novel coronavirus? In this study, we develop a mathematical model to explore the effect of social distancing on new disease infections. Mathematical analyses of our model indicate that successful eradication of the disease is strongly dependent on the chosen preventive measure. Numerical computations of the model solution demonstrate that the ability to flatten the curve becomes easier as social distancing is strictly enforced. Based on our model, we also formulate an optimal control problem and solve it using Pontryagin's Maximum Principle and an efficient numerical iterative method. Our numerical results of an optimal 2019-nCoV treatment protocol that yields a minimum disease burden from this disease indicates that social distancing is vitally important. | qm2qvcwk |
coronavirus social distancing impact | 10 | Assessing the effect of global travel and contact reductions to mitigate the COVID-19 pandemic and resurgence | Travel and physical distancing interventions have been implemented across the World to mitigate the COVID-19 pandemic, but studies are needed to quantify the effectiveness of these measures across regions and time. Timely population mobility data were obtained to measure travel and contact reductions in 135 countries or territories. During the 10 weeks of March 22 - May 30, 2020, domestic travel in study regions has dramatically reduced to a median of 59% (interquartile range [IQR] 43% - 73%) of normal levels seen before the outbreak, with international travel down to 26% (IQR 12% - 35%). If these travel and physical distancing interventions had not been deployed across the World, the cumulative number of cases might have shown a 97-fold (IQR 79 - 116) increase, as of May 31, 2020. However, effectiveness differed by the duration and intensity of interventions and relaxation scenarios, with variations in case severity seen across populations, regions, and seasons. | 5bj2fn7g |
coronavirus hospital rationing | 11 | Clinical Ethical Challenges in the Covid-19 Crisis in South Africa | 7o3qhfk3 |
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coronavirus hospital rationing | 11 | Organising a COVID-19 Triage Unit: a Swiss Perspective. | BACKGROUND With the rapid global spread of the acute respiratory syndrome coronavirus 2, urgent health-care measures have been implemented. We describe the organizational process in setting up a coronavirus disease 2019 triage unit in a Swiss tertiary care hospital. METHODS Our triage unit was set-up outside of the main hospital building and consists of three areas: 1. Pre-triage, 2. Triage, and 3. Triage plus. The Pre-triage check-points identify any potential COVID-19-infected patients and re-direct them to the main Triage area where trained medical staff screen which patients undergo diagnostic testing. If testing is indicated, nasopharyngeal swabs are performed. If patients require further investigations, they are referred to Triage plus. At this stage, patients are then discharged home after additional testing or admitted to the hospital for management. OBSERVATIONS A total of 1,265 patients were screened between March 10th 2020 and April 12th 2020 at our Triage unit. Of these, 112 (8.9%) tested positive. 73 (65%) of the positively-tested patients were female and 39 (35%) were male. The mean age for all patients was 43.8 years (SD 16.3 years). Distinguishing between genders, mean age for females was 41.1 (SD 16.5) and mean age for males was 48.6 (SD 14.9), with females being significantly younger than males (p<0.001). CONCLUSION Our triage unit was set-up as part of a large-scale restructuring process. Current challenges include low sensitivity for test results as well as limited staff and resources. We hope that our experience will help other health care institutions develop similar triage systems. | lom4jdcj |
coronavirus hospital rationing | 11 | COVID-19: Management. | Coronavirus disease (COVID-19) has grasped the world including Pakistan. Clinical features of this disease are variable, ranging from asymptomatic to critical disease. In this unprecedented global war, the Pakistan Chest Society has written a guideline for quick review for the specialists providing care to suspected or confirmed patients. This review highlights the approach to a patient with COVID-19, including definition of the various syndromes of the disease, the abnormal laboratory parameters and outlines the therapeutic measures which are currently under investigation. | 7d3s6jo0 |
coronavirus hospital rationing | 11 | Use of Radiographic Features in COVID-19 Diagnosis: Challenges and Perspectives. | The rapid surge and wide-spread of the coronavirus disease-2019 (COVID-19) overshadows the entire medical industries worldwide. The stringent medical resources hinder the diagnostic capacity globally, while 84 thousands of new cases confirmed within a single day of 14 April 2020. Real-time reverse-transcriptase polymerase chain reaction (RT-PCR) with is the current first-line diagnosis, but the false-negative rate remains concerned. Radiographic technologies and tools, including Computed tomography (CT) and Chest X-ray (CXR), were applied for initial screening and follow-up, from which provides detail diagnosis with specific pathologic features for staging and treatment arrangement. Although the radiographic imaging is found less sensitive, numerous CT-positive patients were not screened out by RT-PCR initially and later confirmed as COVID-19 positive. Besides, the shortage of sampling kits and the longer turn-over time of PCR examinations in some areas were noticed due to logistic issues and healthcare burden. In this review, we will discuss the challenges and the future perspectives of using radiographic modalities for COVID-19 diagnosis in view of securing human lives amid the crisis. | th7o8toc |
coronavirus hospital rationing | 11 | Reorganising the pandemic triage processes to ethically maximise individuals' best interests. | PURPOSE To provide a revised definition, process and purpose of triage to maximise the number of patients receiving intensive care during a crisis. METHODS Based on the ethical principle of virtue ethics and the underlying goal of providing individual patients with treatment according to their best interests, the methodology of triage is reassessed and revised. RESULTS The decision making processes regarding treatment decisions during a pandemic are redefined and new methods of intensive care provision recommended as well as recommending the use of a 'ranking' system for patients excluded from intensive care, defining the role of non-intensive care specialists, and applying two types of triage as 'organisational triage' and 'treatment triage' based on the demand for intensive care. CONCLUSION Using a different underlying ethical basis upon which to plan for a pandemic crisis could maximise the number of patients receiving intensive care based on individual patients' best interests. | whwkv4ne |
coronavirus hospital rationing | 11 | Management Considerations for the Surgical Treatment of Colorectal Cancer During the Global Covid-19 Pandemic. | OBJECTIVE The COVID-19 pandemic requires to conscientiously weigh "timely surgical intervention" for colorectal cancer against efforts to conserve hospital resources and protect patients and health care providers. SUMMARY BACKGROUND DATA Professional societies provided ad-hoc guidance at the outset of the COVID-19 pandemic on deferral of surgical and perioperative interventions, but these lack specific parameters to determine the optimal timing of surgery. METHODS Using the GRADE system, published evidence was analyzed to generate weighted statements for stage, site, acuity of presentation and hospital setting to specify when surgery should be pursued, the time and duration of oncologically acceptable delays, and when to utilize non-surgical modalities to bridge the waiting period. RESULTS Colorectal cancer surgeries - prioritized as emergency, urgent with (a) imminent emergency or (b) oncologically urgent, or elective - were matched against the phases of the pandemic. Surgery in COVID-19 positive patients must be avoided. Emergent and imminent emergent cases should mostly proceed unless resources are exhausted. Standard practices allow for postponement of elective cases and deferral to nonsurgical modalities of stage II/III rectal and metastatic colorectal cancer. Oncologically urgent cases may be delayed for 6(-12) weeks without jeopardizing oncological outcomes. Outside established principles, administration of nonsurgical modalities is not justified and increases the vulnerability of patients. CONCLUSION The COVID-19 pandemic has stressed already limited health care resources and forced rationing, triage and prioritization of care in general, specifically of surgical interventions. Established guidelines allow for modifications of optimal timing and type of surgery for colorectal cancer during an unrelated pandemic. | j3n1etkr |
coronavirus hospital rationing | 11 | [COVID-19 Triage: Who is an inpatient? The Essen triage model]. | INTRODUCTION Data about optimal initial assessment in patients with suspicion for COVID19-infection or already confirmed infection are sparse. Especially, in preparation for expected mass casualty incident it is necessary to distinguish early and efficiently between outpatient and inpatient treatment including the need for intensive care therapy. METHODS We present a model for a safe and efficient triage, which is established and used in the university hospital of Essen, Germany. It is intended for a non-disaster situation. This model is a combination of clinical assessment by using vital parameters and Manchester triage scale (MTS). Possible additional parameters are POCT (point-of-care-testing) values, electrocardiogram, CT pulmonary angiography, SARS-Cov2-PCR as well as detailed diagnostic of laboratory values. The model was validated by 100 consecutive patients. We demonstrate three patients to illustrate this model. RESULTS During the first two weeks after implementing this model in our normal operation at the emergency department, we had an efficient selectivity between need for inpatient and outpatient treatment. 16 patients were classified as "inpatients" according to initial assessment. Among 84 patients who were initially classified as "outpatients", 7 patients returned to our emergency department within 14 days. Three of these patients returned due to complaints other than COVID19. One female patient had to be admitted due to progressive dyspnea. CONCLUSIONS This introduced triage-model seems to be an efficient concept. Adjustment might be necessary after further experience and after a growing number of patients. | hrqwt37s |
coronavirus hospital rationing | 11 | The formation and design of the TRIAGE study--baseline data on 6005 consecutive patients admitted to hospital from the emergency department. | BACKGROUND Patient crowding in emergency departments (ED) is a common challenge and associated with worsened outcome for the patients. Previous studies on biomarkers in the ED setting has focused on identification of high risk patients, and and the ability to use biomarkers to identify low-risk patients has only been sparsely examined. The broader aims of the TRIAGE study are to develop methods to identify low-risk patients appropriate for early ED discharge by combining information from a wide range of new inflammatory biomarkers and vital signs, the present baseline article aims to describe the formation of the TRIAGE database and characteristize the included patients. METHODS We included consecutive patients ≥ 17 years admitted to hospital after triage staging in the ED. Blood samples for a biobank were collected and plasma stored in a freezer (-80 °C). Triage was done by a trained nurse using the Danish Emergency Proces Triage (DEPT) which categorizes patients as green (not urgent), yellow (urgent), orange (emergent) or red (rescusitation). Presenting complaints, admission diagnoses, comorbidities, length of stay, and 'events' during admission (any of 20 predefined definitive treatments that necessitates in-hospital care), vital signs and routine laboratory tests taken in the ED were aslo included in the database. RESULTS Between September 5(th) 2013 and December 6(th) 2013, 6005 patients were included in the database and the biobank (94.1 % of all admissions). Of these, 1978 (32.9 %) were categorized as green, 2386 (39.7 %) yellow, 1616 (26.9 %) orange and 25 (0.4 %) red. Median age was 62 years (IQR 46-76), 49.8 % were male and median length of stay was 1 day (IQR 0-4). No events were found in 2658 (44.2 %) and 158 (2.6 %) were admitted to intensive or intermediate-intensive care unit and 219 (3.6 %) died within 30 days. A higher triage acuity level was associated with numerous events, including acute surgery, endovascular intervention, i.v. treatment, cardiac arrest, stroke, admission to intensive care, hospital transfer, and mortality within 30 days (p < 0.001). CONCLUSION The TRIAGE database has been completed and includes data and blood samples from 6005 unselected consecutive hospitalized patients. More than 40 % experienced no events and were therefore potentially unnecessary hospital admissions. | 1nkpmw5a |
coronavirus hospital rationing | 11 | Extracorporeal Membrane Oxygenation for Pediatric Patients With Coronavirus Disease 2019-Related Illness. | OBJECTIVE To describe current hospital guidelines and the opinions of extracorporeal membrane oxygenation leaders at U.S. children's hospitals concerning the use of extracorporeal membrane oxygenation for coronavirus disease 2019-positive pediatric patients. DESIGN Confidential, self-administered questionnaire. SETTING One hundred twenty-seven U.S. pediatric extracorporeal membrane oxygenation centers. SUBJECTS Extracorporeal membrane oxygenation center program directors and coordinators. INTERVENTIONS None. MEASUREMENTS AND MAIN RESULTS In March 2020, a survey was sent to 127 pediatric extracorporeal membrane oxygenation centers asking them to report their current hospital extracorporeal membrane oxygenation guidelines for coronavirus disease 2019-positive patients. Respondents were also asked their opinion on three ethical dilemmas including: prioritization of children over adults for extracorporeal membrane oxygenation use, institution of do-not-resuscitate orders, and the use of extracorporeal cardiopulmonary resuscitation for coronavirus disease 2019-positive patients. Forty-seven extracorporeal membrane oxygenation centers had enacted guidelines including 46 (100%) that offer venovenous-extracorporeal membrane oxygenation and 42 (89%) that offer venoarterial-extracorporeal membrane oxygenation for coronavirus disease 2019-positive pediatric patients. Forty-four centers (94%) stated that the indications for extracorporeal membrane oxygenation candidacy in coronavirus disease 2019 disease were similar to those used in other viral illnesses, such as respiratory syncytial virus or influenza. Most program directors (98%) did not endorse that children hospitalized with coronavirus disease 2019 should be made do-not-resuscitate and had variable opinions on whether children should be given higher priority over adults when rationing extracorporeal membrane oxygenation. Over half of program directors (60%) did not support the use of extracorporeal cardiopulmonary resuscitation for coronavirus disease 2019. CONCLUSIONS The majority of pediatric extracorporeal membrane oxygenation centers have proactively established guidelines for the use of extracorporeal membrane oxygenation for coronavirus disease 2019-related illnesses. Further work is needed to help guide the fair allocation of extracorporeal membrane oxygenation resources and to determine the appropriateness of extracorporeal cardiopulmonary resuscitation. | f7ylxcog |
coronavirus hospital rationing | 11 | Immersion in an emergency department triage center during the Covid-19 outbreak: first report of the Liège University hospital experience. | OBJECTIVES Since the beginning of the novel coronavirus outbreak, different strategies have been explored to stem the spread of the disease and appropriately manage patient flow. Triage, an effective solution proposed in disaster medicine, also works well to manage Emergency Department (ED) flow. The aim of this study was to describe the role of an ED Triage Center for patients with suspected novel coronavirus disease (Covid-19) and characterize the patient flow. Methods. In March 2020, we established a Covid-19 triage center close to the Liège University EDs. From March 2 to March 23, we planned to analyze the specific flow of patients admitted to this triage zone and their characteristics in terms of inner specificities, work-up and management. During this period, all patients presented to the ED with symptoms suggestive of Covid-19 were included in the study. RESULTS A total amount of 1071 patients presented to the triage center during the study period. 41.50% of the patients presented with flu-like symptoms. In 82.00% of the cases, no risk factor of virus transmission was found. The SARS-Cov2 positive patients represented 29.26% of the screened patients. 83.00% of patients were discharged home while 17.00% were admitted to the hospital. CONCLUSION Our experience suggests that triage centers for the assessment and management of Covid-19 suspected patients is an essential key strategy to prevent the spread of the disease among non-symptomatic patients who present to the EDs for care. This allows for a disease-centered work-up and safer diversion of Covid-19 patients to specific hospital units. | gyghpk64 |
coronavirus hospital rationing | 11 | Response of a comprehensive cancer center to the COVID-19 pandemic: the experience of the Fondazione IRCCS-Istituto Nazionale dei Tumori di Milano. | BACKGROUND The rapid spread of coronavirus disease (COVID-19) is affecting many countries. While healthcare systems need to cope with the need to treat a large number of people with different degrees of respiratory failure, actions to preserve aliquots of the healthcare system to guarantee treatment to patients are mandatory. METHODS In order to protect the Fondazione IRCCS-Istituto Nazionale dei Tumori di Milano from the spread of COVID-19, a number of to-hospital and within-hospital filters were applied. Among others, a triage process to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positivity in patients with cancer was developed consisting of high-resolution low-dose computed tomography (CT) scan followed by reverse transcription polymerase chain reaction (RT-PCR) detection of SARS-CoV-2 in nose-throat swabs whenever CT was suggestive of lung infection. To serve symptomatic patients who were already admitted to the hospital or in need of hospitalization while waiting for RT-PCR laboratory confirmation of infection, a COVID-19 surveillance zone was set up. RESULTS A total of 301 patients were screened between March 6 and April 3, 2020. Of these, 47 were hospitalized, 53 needed a differential diagnosis to continue with their cancer treatment, and 201 were about to undergo surgery. RT-PCR was positive in 13 of 40 hospitalized patients (32%), 14 of 52 day hospital patients (27%), and 6 of 201 surgical patients (3%). CONCLUSION Applying filters to protect our comprehensive cancer center from COVID-19 spread contributed to guaranteeing cancer care during the COVID-19 crisis in Milan. A surveillance area and surgical triage allowed us to protect the hospital from as many as 33 patients infected with SARS-CoV-2. | r4r1a6fd |
coronavirus hospital rationing | 11 | Simple, fast and affordable triaging pathway for COVID-19. | Coronavirus disease 2019 has caused a global pandemic. The majority of patients will experience mild disease, but others will develop a severe respiratory infection that requires hospitalisation. This is causing a significant strain on health services. Patients are presenting at emergency departments with symptoms of dyspnoea, dry cough and fever with varying severity. The appropriate triaging of patients will assist in preventing health services becoming overwhelmed during the pandemic. This is assisted through clinical assessment and various imaging and laboratory investigations, including chest X-ray, blood analysis and identification of viral infection with SARS-CoV-2. Here, a succinct triaging pathway that aims to be fast, reliable and affordable is presented. The hope is that such a pathway will assist health services in appropriately combating the pandemic. | ba5x3ysq |
coronavirus hospital rationing | 11 | Analysis and suggestions for the preview and triage screening of children with suspected COVID-19 outside the epidemic area of Hubei Province | Background: Since December 2019, a number of patients infected with COVID-19 (SARS-CoV-2) have been identified in Wuhan, Hubei, China. As the epidemic has spread, similar cases have also been found in other parts of mainland China and abroad. The main reason for this spread is the highly contagious nature of the virus and the fact that children can also become infected during its incubation period. This has made the virus a substantial challenge for the outpatient triage staff of children's hospitals outside the epidemic area of the Hubei Province. It is very important for the preview and triage personnel to accurately grasp the epidemiology of the virus and identify children's symptoms in the fever clinic. Methods: We performed an analysis of our early preview and triage of suspected COVID-19 in 36 children presenting at fever clinics. Two specialists either excluded suspected cases or referred cases to the isolation ward for new nucleic acid testing. Results: All 14 children who were transferred to the isolation ward had a fever, and 71.43% of them had a cough. Their nucleic acid testing results were negative. The suspected cases and excluded suspected cases had similar epidemiology history as well as complete blood count results. With reference to the diagnostic criteria in existing pediatric guidelines, we have further improved the triage screening questionnaire for children with fever in our hospital. Conclusions: According to the situation in our city and hospital, an evaluation questionnaire that is suitable for use with children in our hospital has been formulated to achieve the goals of early detection, isolation, diagnosis, and treatment. We provided an important basis for the next step in developing accurate preview and triage screening standards and appropriate guidelines for pediatric patients. | macqp9k1 |
coronavirus hospital rationing | 11 | “Daily Work in the Fever Clinics of Wuhan Union Hospital During the Novel Coronavirus Pneumonia Epidemic: A Special Spring Festival in Wuhan, China”Extracorporeal Membrane Oxygenation for Pediatric Patients With Coronavirus Disease 2019–Related Illness | Objective: To describe current hospital guidelines and the opinions of extracorporeal membrane oxygenation leaders at U S children’s hospitals concerning the use of extracorporeal membrane oxygenation for coronavirus disease 2019–positive pediatric patients Design: Confidential, self-administered questionnaire Setting: One hundred twenty-seven U S pediatric extracorporeal membrane oxygenation centers Subjects: Extracorporeal membrane oxygenation center program directors and coordinators Interventions: None Measurements and Main Results: In March 2020, a survey was sent to 127 pediatric extracorporeal membrane oxygenation centers asking them to report their current hospital extracorporeal membrane oxygenation guidelines for coronavirus disease 2019–positive patients Respondents were also asked their opinion on three ethical dilemmas including: prioritization of children over adults for extracorporeal membrane oxygenation use, institution of do-not-resuscitate orders, and the use of extracorporeal cardiopulmonary resuscitation for coronavirus disease 2019–positive patients Forty-seven extracorporeal membrane oxygenation centers had enacted guidelines including 46 (100%) that offer venovenous-extracorporeal membrane oxygenation and 42 (89%) that offer venoarterial-extracorporeal membrane oxygenation for coronavirus disease 2019–positive pediatric patients Forty-four centers (94%) stated that the indications for extracorporeal membrane oxygenation candidacy in coronavirus disease 2019 disease were similar to those used in other viral illnesses, such as respiratory syncytial virus or influenza Most program directors (98%) did not endorse that children hospitalized with coronavirus disease 2019 should be made do-not-resuscitate and had variable opinions on whether children should be given higher priority over adults when rationing extracorporeal membrane oxygenation Over half of program directors (60%) did not support the use of extracorporeal cardiopulmonary resuscitation for coronavirus disease 2019 Conclusions: The majority of pediatric extracorporeal membrane oxygenation centers have proactively established guidelines for the use of extracorporeal membrane oxygenation for coronavirus disease 2019–related illnesses Further work is needed to help guide the fair allocation of extracorporeal membrane oxygenation resources and to determine the appropriateness of extracorporeal cardiopulmonary resuscitation Drs MacGregor and Antiel are co-first authors Supplemental digital content is available for this article Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s website (http://journals lww com/pccmjournal) The authors have disclosed that they do not have any potential conflicts of interest For information regarding this article, E-mail: baddr@wustl edu ©2020The Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies | q2xjx56v |
coronavirus hospital rationing | 11 | Predicting individual risk for COVID19 complications using EMR data | Background: The global pandemic of COVID-19 has challenged healthcare organizations and caused numerous deaths and hospitalizations worldwide. The need for data-based decision support tools for many aspects of controlling and treating the disease is evident but has been hampered by the scarcity of real-world reliable data. Here we describe two approaches: a. the use of an existing EMR-based model for predicting complications due to influenza combined with available epidemiological data to create a model that identifies individuals at high risk to develop complications due to COVID-19 and b. a preliminary model that is trained using existing real world COVID-19 data. Methods: We have utilized the computerized data of Maccabi Healthcare Services a 2.3 million member state-mandated health organization in Israel. The age and sex matched matrix used for training the XGBoost ILI-based model included, circa 690,000 rows and 900 features. The available dataset for COVID-based model included a total 2137 SARS-CoV-2 positive individuals who were either not hospitalized (n=1658), or hospitalized and marked as mild (n=332), or as having moderate (n=83) or severe (n=64) complications. Findings: The AUC of our models and the priors on the 2137 COVID-19 patients for predicting moderate and severe complications as cases and all other as controls, the AUC for the ILI-based model was 0.852[0.824-0.879] for the COVID19-based model - 0.872[0.847-0.879].. Interpretation: These models can effectively identify patients at high-risk for complication, thus allowing optimization of resources and more focused follow up and early triage these patients if once symptoms worsen. | lir8ht2i |