scholarly journals First month of the epidemic caused by COVID-19 in Italy: current status and real-time outbreak development forecast

2020 ◽  
Author(s):  
Rosario Megna
Keyword(s):  
Intensive Care ◽  
Real Time ◽  
Forecast Model ◽  
Cumulative Distribution ◽  
Current Status ◽  
Logistic Distribution ◽  
Infected People ◽  
The North ◽  
Heavy Burden ◽  
Collaborative Efforts

AbstractBackgroundThe first outbreaks of COVID-19 in Italy occurred during the second half of February 2020 in some areas in the North of the country. Due to the high contagiousness of the infection, further spread by asymptomatic people, Italy has become in a few weeks the country with the greatest number of infected people after China. The large number of severe cases among infected people in Italy led to the hospitalization of thousands of patients, with a heavy burden on the National Health Service.MethodsWe analyzed data provided daily by Italian Authorities for the period from 24 February 2020 to 26 March 2020. Considering such information, we developed a forecast model in real-time, based on the cumulative logistic distribution. We then produced an estimate of the overall number of potentially infected individuals and epidemic duration at a national and Regional level, for the most affected Regions.ResultsWe reported the daily distribution of performed swabs and confirmed cases, and the cumulative distribution of confirmed cases, of patients quarantined at home (42%), hospitalized in non-intensive care (31%), recovered or discharged (13%), deceased (10%), and hospitalized in intensive care (4%). The forecast model estimated a number of infected persons for Italy of 115,000 about, and a duration of the epidemic not less than 2 months.ConclusionsOnce month after the first outbreaks there seems to be the first signs of a decrease in the number of infections, showing that we could be now facing the descending phase of the epidemic. The forecast obtained thanks to our model could be used by decision-makers to implement coordinative and collaborative efforts in order to control the epidemic.

scholarly journals First month of the epidemic caused by COVID-19 in Italy: current status and real-time outbreak development forecast

2020 ◽  
Author(s):  
Rosario Megna
Keyword(s):  
Intensive Care ◽  
Real Time ◽  
Forecast Model ◽  
Cumulative Distribution ◽  
Current Status ◽  
Logistic Distribution ◽  
Infected People ◽  
The North ◽  
Heavy Burden ◽  
Collaborative Efforts

Abstract Background: The first outbreaks of COVID-19 in Italy occurred during the second half of February 2020 in some areas in the North of the country. Due to the high contagiousness of the infection, further spread by asymptomatic people, Italy has become in a few weeks the country with the greatest number of infected people in the World. The large number of severe cases among infected people in Italy led to the hospitalization of thousands of patients, with a heavy burden on the National Health Service. Methods: We analyzed data provided daily by Italian Authorities for the period from 24 February 2020 to 30 March 2020. Considering such information, we developed a forecast model in real-time, based on the cumulative logistic distribution. We then produced an estimate of the overall number of potentially infected individuals and epidemic duration at a national and Regional level, for the most affected Regions. Results: We reported the daily distribution of performed swabs and confirmed cases, and the cumulative distribution of confirmed cases, of patients quarantined at home (43.0%), hospitalized in non-intensive care (27.3%), recovered or discharged (14.4%), deceased (11.4%), and hospitalized in intensive care (3.9%). The forecast model estimated a number of infected persons for Italy of 130,000 about, and a duration of the epidemic greater than 2 months. Conclusions: Once month after the first outbreaks there seems to be the first signs of a decrease in the number of infections, showing that we could be now facing the descending phase of the epidemic. The forecast obtained thanks to our model could be used by decision-makers to implement coordinative and collaborative efforts in order to control the epidemic.

scholarly journals First month of the epidemic caused by COVID-19 in Italy: current status and real-time outbreak development forecast

2020 ◽  
Author(s):  
Rosario Megna
Keyword(s):  
Real Time ◽  
Forecast Model ◽  
Current Status ◽  
Logistic Distribution ◽  
Infected People ◽  
The North ◽  
Heavy Burden ◽  
Novel Coronavirus ◽  
Health Organization ◽  
Collaborative Efforts

Abstract Background : The first outbreaks of COVID-19 in Italy occurred during the second half of February 2020 in some areas in the North of the country. Due to the high contagiousness of the infection, further spread by asymptomatic people, Italy has become in a few weeks the country with the greatest number of infected people in the World. The large number of severe cases among infected people in Italy led to the hospitalization of thousands of patients, with a heavy burden on the National Health Service. Methods: We analyzed data provided daily by Italian Authorities for the period from 24 February 2020 to 30 March 2020. Considering such information, we developed a forecast model in real-time, based on the cumulative logistic distribution. We then produced an estimate of the overall number of potentially infected individuals and epidemic duration at a national and Regional level, for the most affected Regions. Results: A total of 101,739 infected individuals was confirmed until 30 March 2020, of which 75,528 active cases, 14,620 recovered or discharged, and 11,591 deaths. Until the same date patients quarantined at home were 43,752, whereas hospitalized patients were 31,776, of which 3,981 in intensive care. The forecast model estimated a number of infected persons for Italy of 130,000 about, and a duration of the epidemic greater than 2 months. Conclusions : Once month after the first outbreaks there seems to be the first signs of a decrease in the number of infections, showing that we could be now facing the descending phase of the epidemic. The forecast obtained thanks to our model could be used by decision-makers to implement coordinative and collaborative efforts in order to control the epidemic. The pandemic due to novel Coronavirus must be a warning for all countries worldwide, regarding a rapid and complete dissemination of information, surveillance, health organization, and cooperation among the states.

scholarly journals First month of the epidemic caused by COVID-19 in Italy: current status and real-time outbreak development forecast

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Rosario Megna
Keyword(s):  
Real Time ◽  
Forecast Model ◽  
Current Status ◽  
Logistic Distribution ◽  
Infected People ◽  
The North ◽  
Number Of Patients ◽  
Heavy Burden ◽  
Novel Coronavirus ◽  
Health Organization

Abstract Background The first outbreak of COVID-19 in Italy occurred during the second half of February 2020 in some areas in the North of the country. Due to the high contagiousness of the infection, further spread by asymptomatic people, Italy has become in a few weeks the country with the greatest number of infected people in the world. The large number of severe cases among infected people in Italy led to the hospitalization of thousands of patients, with a heavy burden on the National Health Service. Methods We analyzed data provided daily by Italian Authorities for the period from 24 February 2020 to 30 March 2020. Considering such information, we developed a forecast model in real-time, based on the cumulative log-logistic distribution. Results A total of 101,739 infected individuals were confirmed until 30 March 2020, of which 14,620 recovered or discharged, and 11,591 deaths. Until the same date patients quarantined at home were 43,752, whereas hospitalized patients were 31,776, of which 3981 in intensive care. The active cases (i.e. the number of patients not yet recovered until that date) were 75,528. The forecast model estimated a number of infected persons for Italy of 234,000 about, and a duration of the epidemic of approximately 4 months. Conclusions One month after the first outbreaks there seemed to be the first signs of a decrease in the number of infections, showing that we could be now facing the descending phase of the epidemic. The forecast obtained thanks to our model could be used by decision-makers to implement coordinative and collaborative efforts in order to control the epidemic. The pandemic due to novel Coronavirus must be a warning for all countries worldwide, regarding a rapid and complete dissemination of information, surveillance, health organization, and cooperation among the states.

scholarly journals First month of the epidemic caused by COVID-19 in Italy: current status and real-time outbreak development forecast

2020 ◽  
Author(s):  
Rosario Megna
Keyword(s):  
Real Time ◽  
Forecast Model ◽  
Current Status ◽  
Logistic Distribution ◽  
Infected People ◽  
The North ◽  
Number Of Patients ◽  
Heavy Burden ◽  
Novel Coronavirus ◽  
Health Organization

Abstract Background: The first outbreak of COVID-19 in Italy occurred during the second half of February 2020 in some areas in the North of the country. Due to the high contagiousness of the infection, further spread by asymptomatic people, Italy has become in a few weeks the country with the greatest number of infected people in the world. The large number of severe cases among infected people in Italy led to the hospitalization of thousands of patients, with a heavy burden on the National Health Service. Methods: We analyzed data provided daily by Italian Authorities for the period from 24 February 2020 to 30 March 2020. Considering such information, we developed a forecast model in real-time, based on the cumulative log-logistic distribution. Results: A total of 101,739 infected individuals were confirmed until 30 March 2020, of which 14,620 recovered or discharged, and 11,591 deaths. Until the same date patients quarantined at home were 43,752, whereas hospitalized patients were 31,776, of which 3,981 in intensive care. The active cases (i.e. the number of patients not yet recovered until that date) were 75,528. The forecast model estimated a number of infected persons for Italy of 234,000 about, and a duration of the epidemic of approximately 4 months. Conclusions: One month after the first outbreaks there seemed to be the first signs of a decrease in the number of infections, showing that we could be now facing the descending phase of the epidemic. The forecast obtained thanks to our model could be used by decision-makers to implement coordinative and collaborative efforts in order to control the epidemic. The pandemic due to novel Coronavirus must be a warning for all countries worldwide, regarding a rapid and complete dissemination of information, surveillance, health organization, and cooperation among the states.

scholarly journals First month of the epidemic caused by COVID-19 in Italy: current status and real-time outbreak development forecast

2020 ◽  
Author(s):  
Rosario Megna
Keyword(s):  
Real Time ◽  
Forecast Model ◽  
Current Status ◽  
Logistic Distribution ◽  
Infected People ◽  
The North ◽  
Number Of Patients ◽  
Heavy Burden ◽  
Novel Coronavirus ◽  
Health Organization

Abstract Background: The first outbreaks of COVID-19 in Italy occurred during the second half of February 2020 in some areas in the North of the country. Due to the high contagiousness of the infection, further spread by asymptomatic people, Italy has become in a few weeks the country with the greatest number of infected people in the world. The large number of severe cases among infected people in Italy led to the hospitalization of thousands of patients, with a heavy burden on the National Health Service.Methods: We analyzed data provided daily by Italian Authorities for the period from 24 February 2020 to 30 March 2020. Considering such information, we developed a forecast model in real-time, based on the cumulative log-logistic distribution. Results: A total of 101,739 infected individuals were confirmed until 30 March 2020, of which 14,620 recovered or discharged, and 11,591 deaths. Until the same date patients quarantined at home were 43,752, whereas hospitalized patients were 31,776, of which 3,981 in intensive care. The active cases (i.e. the number of patients not yet recovered until that date) were 75,528. The forecast model estimated a number of infected persons for Italy of 234,000 about, and a duration of the epidemic of approximately 4 months. Conclusions: One month after the first outbreaks there seemed to be the first signs of a decrease in the number of infections, showing that we could be now facing the descending phase of the epidemic. The forecast obtained thanks to our model could be used by decision-makers to implement coordinative and collaborative efforts in order to control the epidemic. The pandemic due to novel Coronavirus must be a warning for all countries worldwide, regarding a rapid and complete dissemination of information, surveillance, health organization, and cooperation among the states.

scholarly journals Forecasting Ultra-early Intensive Care Strain from COVID-19 in England, v1.1.4

2020 ◽  
Author(s):  
Jacob Deasy ◽  
Emma Rocheteau ◽  
Katharina Kohler ◽  
Daniel J. Stubbs ◽  
Pietro Barbiero ◽  
...  
Keyword(s):  
Intensive Care ◽  
Real Time ◽  
Exponential Growth ◽  
Short Range ◽  
Policy Decision ◽  
Epidemiological Data ◽  
Forecast Model ◽  
Model Specification ◽  
North West ◽  
North East

AbstractThe COVID-19 pandemic has led to unprecedented strain on intensive care unit (ICU) admission in parts of the world. Strategies to create surge ICU capacity require complex local and national service reconfiguration and reduction or cancellation of elective activity. These measures have an inevitable lag-time before additional capacity comes on-line. An accurate short-range forecast would be helpful in guiding such difficult, costly, and ethically challenging decisions.At the time this work began, cases in England were starting to increase. If this represents a true spread in disease then ICU demand could increase rapidly. Here we present a short-range forecast based on published real-time COVID-19 case data from the seven National Health Service (NHS) commissioning regions in England (East of England, London, Midlands, North East and Yorkshire, North West, South East and South West). We use a Monte Carlo approach to model the likely impact of current diagnoses on regional ICU capacity over a 14-day horizon under the assumption that the increase in cases represents the start of an exponential growth in infections. Our model is designed to be parsimonious and based on available epidemiological data from the literature at the moment.On the basis of the modelling assumptions made, ICU occupancy is likely to increase dramatically in the days following the time of modelling. If the current exponential growth continues, case numbers will be comparable to current ICU bed numbers within weeks. Despite variable growth in absolute patients, all commissioning regions are forecast to be heavily burdened under the assumptions used.Whilst, like any forecast model, there remain uncertainties both in terms of model specification and robust epidemiological data in this early prospective phase, it would seem that surge capacity will be required in the very near future. Our findings should be interpreted with caution, but we hope that our model will help policy decision makers with their preparations. The uncertainties in the data highlight the urgent need for ongoing real-time surveillance to allow forecasts to be constantly updated using high quality local patient-facing data as it emerges.

Contrast-enhanced ultrasound of the abdominal aorta – current status and future perspectives

VASA ◽  
2019 ◽  
Vol 48 (2) ◽  
pp. 115-125 ◽  
Author(s):  
Xin Li ◽  
Daniel Staub ◽  
Vasileios Rafailidis ◽  
Mohammed Al-Natour ◽  
Sanjeeva Kalva ◽  
...  
Keyword(s):  
Real Time ◽  
Vascular Diseases ◽  
Aneurysm Rupture ◽  
Vasa Vasorum ◽  
Current Status ◽  
Contrast Enhanced Ultrasound ◽  
Aortic Diseases ◽  
Cross Sectional ◽  
Vascular Abnormalities ◽  
Contrast Enhanced

Abstract. Ultrasound has been established as an important diagnostic tool in assessing vascular abnormalities. Standard B-mode and Doppler techniques have inherent limitations with regards to detection of slow flow and small vasculature. Contrast-enhanced ultrasound (CEUS) is a complementary tool and is useful in assessing both the macro- and microvascular anatomy of the aorta. CEUS can also provide valuable physiological information in real-time scanning sessions due to the physical and safety profiles of the administered microbubbles. From a macrovascular perspective, CEUS has been used to characterize aortic aneurysm rupture, dissection and endoleaks post-EVAR repair. With regard to microvasculature CEUS enables imaging of adventitial vasa vasorum thereby assessing aortic inflammation processes, such as monitoring treatment response in chronic periaortitis. CEUS may have additional clinical utility since adventitial vasa vasorum has important implications in the pathogenesis of aortic diseases. In recent years, there have been an increasing number of studies comparing CEUS to cross-sectional imaging for aortic applications. For endoleak surveillance CEUS has been shown to be equal or in certain cases superior in comparison to CT angiography. The recent advancement of CEUS software along with the ongoing development of drug-eluting contrast microbubbles has allowed improved targeted detection and real-time ultrasound guided therapy for aortic vasa vasorum inflammation and neovascularization in animal models. Therefore, CEUS is uniquely suited to comprehensively assess and potentially treat aortic vascular diseases in the future.

Current Status of Anserinae Wintering in Azov-Black Sea Region of Ukraine

2019 ◽  
Vol 53 (4) ◽  
pp. 297-312
Author(s):  
Yu. O. Andryushchenko ◽  
V. S. Gavrilenko ◽  
V. A. Kostiushyn ◽  
V. N. Kucherenko ◽  
A. S. Mezinov ◽  
...  
Keyword(s):  
Black Sea ◽  
Current Status ◽  
Anser Anser ◽  
Scientific Publications ◽  
Climate Conditions ◽  
Black Sea Region ◽  
Chen Caerulescens ◽  
Branta Bernicla ◽  
The North ◽  
Different Seasons

Abstract In the article is analyzed own field data of the authors and scientific publications on the wintering of Anserinae in the Azov-Black Sea region of Ukraine in 1900–2017, but the main data was obtained in frame of international mid-winter counts (IWC) in 2005–2017. It was found that 9 species of Anserinae occur in this region during the different seasons of the year: Anser anser — nesting, wintering and migrating; Rufibrenta ruficollis, A. albifrons, A. erythropus, A. fabalis — migrating and wintering; Branta canadensis, Branta leucopsis, Branta bernicla, Chen caerulescens — vagrant or birds which flew away from captivity (zoo etc.). Eulabeia indica — is possible vagrant species. The most numerous wintering species is A. albifrons, common — Rufibrenta ruficollis, not numerous — Anser anser, the other species are not met annually and registered in a very small number. There was almost tenfold drop in number of wintering geese in the Azov-Black Sea region of Ukraine during the period of counts. The main reasons of such reducing of geese amount are the followwing: weather and climate conditions, changes in the forage acessibility, hunting and poaching pressure, poisoning as a result of deratization of agricultural lands, and from 2014 — the militarization of the Syvash area and stop of water supplying of Crimea through the North Crimean channell. It is likely that the factors mentioned above led to relocating of wintering areas of Anserinae, and resulted in decreasing of their amount in this region.

scholarly journals Characterisation of Textile Embedded Electrodes for Use in a Neonatal Smart Mattress Electrocardiography System

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 999
Author(s):  
Henry Dore ◽  
Rodrigo Aviles-Espinosa ◽  
Zhenhua Luo ◽  
Oana Anton ◽  
Heike Rabe ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Heart Rate ◽  
Intensive Care ◽  
High Resolution ◽  
Neonatal Intensive Care Unit ◽  
Real Time ◽  
Neonatal Intensive Care ◽  
Delivery Room ◽  
Proof Of Concept ◽  
Heart Rate Monitoring

Heart rate monitoring is the predominant quantitative health indicator of a newborn in the delivery room. A rapid and accurate heart rate measurement is vital during the first minutes after birth. Clinical recommendations suggest that electrocardiogram (ECG) monitoring should be widely adopted in the neonatal intensive care unit to reduce infant mortality and improve long term health outcomes in births that require intervention. Novel non-contact electrocardiogram sensors can reduce the time from birth to heart rate reading as well as providing unobtrusive and continuous monitoring during intervention. In this work we report the design and development of a solution to provide high resolution, real time electrocardiogram data to the clinicians within the delivery room using non-contact electric potential sensors embedded in a neonatal intensive care unit mattress. A real-time high-resolution electrocardiogram acquisition solution based on a low power embedded system was developed and textile embedded electrodes were fabricated and characterised. Proof of concept tests were carried out on simulated and human cardiac signals, producing electrocardiograms suitable for the calculation of heart rate having an accuracy within ±1 beat per minute using a test ECG signal, ECG recordings from a human volunteer with a correlation coefficient of ~ 87% proved accurate beat to beat morphology reproduction of the waveform without morphological alterations and a time from application to heart rate display below 6 s. This provides evidence that flexible non-contact textile-based electrodes can be embedded in wearable devices for assisting births through heart rate monitoring and serves as a proof of concept for a complete neonate electrocardiogram monitoring system.

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