scholarly journals Forecasting the impact of the containment measures for COVID-19 in France, Italy, and Spain

2020 ◽  
Author(s):  
Omar A Almohammed ◽  
Abdullah A. Alhifany ◽  
Yazed S. Al-Ruthia
Keyword(s):  
Similar Rate ◽  
Response Strategy ◽  
Cumulative Number ◽  
The European Union ◽  
Infected People ◽  
First Response ◽  
Trained Personnel ◽  
Containment Measures ◽  
Visual Reference ◽  
The Impact

Abstract Background: The Coronavirus disease of 2019 (COVID-19) is now a major challenge for healthcare systems in many countries, including some of the G20 countries like China, Italy and France. The purpose of this paper was to estimate how this disease could impact Italy, Spain and France, in comparison to China, based on the timing of their first response to the epidemic.Methods: The study visually estimated when will the suppression strategies implemented in Italy, Spain and France would change the direction of the daily new infections curve. The study utilizes the publicly available data from the WHO website. The curve representing the response strategy from China was used as a visual reference in this case, assuming that the virus is impacting all populations in the same way, transmitted in similar rate, and the time needed from the implementation of the suppression strategies to the appearance of its impact would be identical in all countries. Then, the total number of cases and deaths will be estimated from the produced curve, based on the current death rate among all infected people in each countryResult: The response in the three countries was not as fast as it was in China. Based on the cumulative number of cases at the response time, France was the fastest responder to the epidemic; therefore, we expect it will be the least impacted among three countries with about 97,523 cases and 4,876 deaths. Followed by Spain with approximately 153,013 cases and 14,536 deaths, then Italy with 162,885 cases and 20,034 deaths. The peak date for the new confirmed cases was expected to be around April 2nd for Italy and Spain, and April 6th for France. Then, the new daily cases should be declining to around Zero by the end of April or the beginning of May.Conclusion: Italy, followed by Spain, will be the most impacted countries in the European Union. Therefore, the support for Italy and Spain at this time is very needed, especially with medically trained personnel.

scholarly journals Hospitalization as reliable indicator of second wave COVID-19 pandemic in eight European countries

2021 ◽  
Author(s):  
Mattia Allieta ◽  
Davide Rossi Sebastiano
Keyword(s):  
European Countries ◽  
Cumulative Number ◽  
Actual Number ◽  
Infected People ◽  
Containment Measures ◽  
Model Equations ◽  
The Impact ◽  
Second Wave ◽  
Early Phases ◽  
Country Specific

AbstractTime dependent reproduction number (Rt) is one of the most popular parameters to track the impact of COVID-19 pandemic. However, especially at the initial stages, Rt can be highly underestimated because of remarkable differences between the actual number of infected people and the daily incidence of people who are tested positive. Here, we present the analysis of daily cumulative number of hospitalized (HP) and intensive care unit (ICU) patients both in space and in time in the early phases of second wave COVID-19 pandemic across eight different European countries, namely Austria, Belgium, Czech Republic, France, Italy, Portugal, Spain, and United Kingdom. We derive simple model equations to fit the time dependence of these two variables where exponential behavior is observed. Growth rate constants of HP and ICU are listed, providing country-specific parameters able to estimate the burden of SARS-COV-2 infection before extensive containment measures take place. Our quantitative parameters, fully related to hospitalizations, are disentangled from the capacity range of the screening campaign, for example the number of swabs, and they cannot be directly biased by the actual number of infected people. This approach can give an array of reliable indicators which can be used by governments and healthcare systems to monitor the dynamics of COVID-19 epidemic.

scholarly journals Impact of COVID-19 on the trade of goods and services in Spain

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Asier Minondo
Keyword(s):  
Negative Impact ◽  
The European Union ◽  
Firm Level ◽  
Health Crisis ◽  
Content Type ◽  
Goods And Services ◽  
Containment Measures ◽  
Trade Of Services ◽  
The Impact

Purpose This paper aims to analyze the impact of COVID-19 on the trade of goods and services in Spain. Design/methodology/approach This paper uses monthly trade data at the product, region and firm level. Findings The COVID-19 crisis has led to the sharpest collapse in the Spanish trade of goods and services in recent decades. The containment measures adopted to arrest the spread of the virus have caused an especially intense fall of trade in services. The large share of transport equipment, capital goods, products that are consumed outdoors (i.e., outdoor goods) and tourism in Spanish exports has made the COVID-19 trade crisis more intense in Spain than in the rest of the European Union. Practical implications The nature of the collapse suggests that trade in goods can recover swiftly when the health crisis ends. However, COVID-19 may have a long-term negative impact on the trade of services that rely on the movement of people. Originality/value It contributes to understand how COVID-19 has affected the trade in goods and services in Spain.

scholarly journals Modeling analysis of a SEIQR epidemic model to assess the impact of undetected cases , and predict the early peack of the COVID-19 outbreak in Cameroon

2020 ◽  
Author(s):  
NKAGUE NKAMBA LEONTINE ◽  
MAYOMBE MANN MARTIN LUTHER ◽  
MANGA THOMAS TIMOTHEE ◽  
J. Mbang
Keyword(s):  
Severe Acute Respiratory Syndrome ◽  
Lyapunov Functions ◽  
Reproduction Number ◽  
Benign Diseases ◽  
Infected People ◽  
Modeling Analysis ◽  
Containment Measures ◽  
The Impact ◽  
Case Data ◽  
Disease Free

Abstract COVID-19 is a highly contagious disease, and the strain is severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It belongs to the coronavirus family, which can result in benign diseases in humans, such as a cold, and can also cause serious pathologies such as Severe Acute Respiratory Syndrome (SARS). In this study, we have modeled the COVID-19 epidemic in Cameroon. We used early reported case data to predict the peak, assess the impact of containment measures, and the impact of undetected infected people on the epidemic trend and characteristics of COVID-19. The basic reproduction number is computed using Lyapunov functions, and the global stability of disease-free and endemic equilibrium are demonstrated.

scholarly journals Xylella fastidiosa in Olive in Apulia: Where We Stand

2019 ◽  
Vol 109 (2) ◽  
pp. 175-186 ◽  
Author(s):  
M. Saponari ◽  
A. Giampetruzzi ◽  
G. Loconsole ◽  
D. Boscia ◽  
P. Saldarelli
Keyword(s):  
Xylella Fastidiosa ◽  
Management Strategies ◽  
Local Economy ◽  
Control Measures ◽  
Basic Knowledge ◽  
Current Status ◽  
The European Union ◽  
Containment Measures ◽  
Olive Cultivars ◽  
The Impact

A dramatic outbreak of Xylella fastidiosa decimating olive was discovered in 2013 in Apulia, Southern Italy. This pathogen is a quarantine bacterium in the European Union (EU) and created unprecedented turmoil for the local economy and posed critical challenges for its management. With the new emerging threat to susceptible crops in the EU, efforts were devoted to gain basic knowledge on the pathogen biology, host, and environmental interactions (e.g., bacterial strain(s) and pathogenicity, hosts, vector(s), and fundamental drivers of its epidemics) in order to find means to control or mitigate the impacts of the infections. Field surveys, greenhouse tests, and laboratory analyses proved that a single bacterial introduction occurred in the area, with a single genotype, belonging to the subspecies pauca, associated with the epidemic. Infections caused by isolates of this genotype turned to be extremely aggressive on the local olive cultivars, causing a new disease termed olive quick decline syndrome. Due to the initial extension of the foci and the rapid spread of the infections, eradication measures (i.e., pathogen elimination from the area) were soon replaced by containment measures including intense border surveys of the contaminated area, removal of infected trees, and mandatory vector control. However, implementation of containment measures encountered serious difficulties, including public reluctance to accept control measures, poor stakeholder cooperation, misinformation from some media outlets, and lack of robust responses by some governmental authorities. This scenario delayed and limited containment efforts and allowed the bacterium to continue its rapid dissemination over more areas in the region, as shown by the continuous expansion of the official borders of the infected area. At the research level, the European Commission and regional authorities are now supporting several programs aimed to find effective methods to mitigate and contain the impact of X. fastidiosa on olives, the predominant host affected in this epidemic. Preliminary evidence of the presence of resistance in some olive cultivars represents a promising approach currently under investigation for long-term management strategies. The present review describes the current status of the epidemic and major research achievements since 2013.

scholarly journals Control with uncertain data of socially structured compartmental epidemic models

2020 ◽  
Author(s):  
Giacomo Albi ◽  
Lorenzo Pareschi ◽  
Mattia Zanella
Keyword(s):  
Optimal Control ◽  
Uncertain Data ◽  
Compartmental Models ◽  
Global Strategy ◽  
Peak Reduction ◽  
Infected People ◽  
Instantaneous Approximation ◽  
Containment Measures ◽  
High Degree ◽  
The Impact

AbstractThe adoption of containment measures to reduce the amplitude of the epidemic peak is a key aspect in tackling the rapid spread of an epidemic. Classical compartmental models must be modified and studied to correctly describe the effects of forced external actions to reduce the impact of the disease. In addition, data are often incomplete and heterogeneous, so a high degree of uncertainty must naturally be incorporated into the models. In this work we address both these aspects, through an optimal control formulation of the epidemiological model in presence of uncertain data. After the introduction of the optimal control problem, we formulate an instantaneous approximation of the control that allows us to derive new feedback controlled compartmental models capable of describing the epidemic peak reduction. The need for long-term interventions shows that alternative actions based on the social structure of the system can be as effective as the more expensive global strategy. The importance of the timing and intensity of interventions is particularly relevant in the case of uncertain parameters on the actual number of infected people. Simulations related to data from the recent COVID-19 outbreak in Italy are presented and discussed.

scholarly journals COVID-19 in India: State-wise Analysis and Prediction

2020 ◽  
Author(s):  
Palash Ghosh ◽  
Rik Ghosh ◽  
Bibhas Chakraborty
Keyword(s):  
Infectious Disease ◽  
West Bengal ◽  
Preventive Measures ◽  
Growth Models ◽  
Limited Resources ◽  
Cumulative Number ◽  
Infected People ◽  
The World ◽  
Entire Country ◽  
The Impact

AbstractCoronavirus disease 2019 (COVID-19), a highly infectious disease, was first detected in Wuhan, China, in December 2019. The disease has spread to 212 countries and territories around the world and infected (confirmed) more than three million people. In India, the disease was first detected on 30 January 2020 in Kerala in a student who returned from Wuhan. The total (cumulative) number of confirmed infected people is more than 37000 till now across India (3 May 2020). Most of the research and newspaper articles focus on the number of infected people in the entire country. However, given the size and diversity of India, it may be a good idea to look at the spread of the disease in each state separately, along with the entire country. For example, currently, Maharashtra has more than 10000 confirmed cumulative infected cases, whereas West Bengal has less than 800 confirmed infected cases (1 May 2020). The approaches to address the pandemic in the two states must be different due to limited resources. In this article, we will focus the infected people in each state (restricting to only those states with enough data for prediction) and build three growth models to predict infected people for that state in the next 30 days. The impact of preventive measures on daily infected-rate is discussed for each state.

scholarly journals Control with uncertain data of socially structured compartmental epidemic models

2021 ◽  
Vol 82 (7) ◽  
Author(s):  
Giacomo Albi ◽  
Lorenzo Pareschi ◽  
Mattia Zanella
Keyword(s):  
Optimal Control ◽  
Social Structure ◽  
Uncertain Data ◽  
Compartmental Models ◽  
Global Strategy ◽  
Peak Reduction ◽  
Infected People ◽  
Containment Measures ◽  
High Degree ◽  
The Impact

AbstractThe adoption of containment measures to reduce the amplitude of the epidemic peak is a key aspect in tackling the rapid spread of an epidemic. Classical compartmental models must be modified and studied to correctly describe the effects of forced external actions to reduce the impact of the disease. The importance of social structure, such as the age dependence that proved essential in the recent COVID-19 pandemic, must be considered, and in addition, the available data are often incomplete and heterogeneous, so a high degree of uncertainty must be incorporated into the model from the beginning. In this work we address these aspects, through an optimal control formulation of a socially structured epidemic model in presence of uncertain data. After the introduction of the optimal control problem, we formulate an instantaneous approximation of the control that allows us to derive new feedback controlled compartmental models capable of describing the epidemic peak reduction. The need for long-term interventions shows that alternative actions based on the social structure of the system can be as effective as the more expensive global strategy. The timing and intensity of interventions, however, is particularly relevant in the case of uncertain parameters on the actual number of infected people. Simulations related to data from the first wave of the recent COVID-19 outbreak in Italy are presented and discussed.

scholarly journals Long-Term Predictions of COVID-19 in Some Countries by the SIRD Model

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Lijun Pei ◽  
Mengyu Zhang
Keyword(s):  
Time Delay ◽  
Infection Rate ◽  
Cumulative Number ◽  
Death Rates ◽  
Containment Measures ◽  
The Finite Difference Method ◽  
The Impact ◽  
Nonautonomous Dynamic System ◽  
Piecewise Functions

As COVID-19 in some countries has increasingly become more severe, there have been significant efforts to develop models that forecast its evolution there. These models can help to control and prevent the outbreak of these infections. In this paper, we make long-term predictions based on the number of current confirmed cases, accumulative recovered cases, and dead cases of COVID-19 in some countries by the modeling approach. We use the SIRD (S: susceptible, I: infected, R: recovered, D: dead) epidemic model which is a nonautonomous dynamic system with incubation time delay to study the evolution of COVID-19 in some countries. From the analysis of the recent data, we find that the cure and death rates may not be constant and, in some countries, they are piecewise functions. They can be estimated from the delayed SIRD model by the finite difference method. According to the recent data and its subsequent cure and death rates, we can accurately estimate the parameters of the model and then predict the evolution of COVID-19 there. Through the predicted results, we can obtain the turning points, the plateau period, and the maximum number of COVID-19 cases. The predicted results suggest that the epidemic situation in some countries is very serious. It is advisable for the governments of these countries to take more stringent and scientific containment measures. Finally, we studied the impact of the infection rate β on COVID-19. We find that when the infection rate β decreases, the cumulative number of confirmed cases and the maximum number of currently infected cases will greatly decrease. The results further affirm that the containment techniques taken by these countries to curb the spread of COVID-19 should be strengthened further.

The Mental Health and Social Exclusion European Network

2000 ◽  
Vol 5 (3) ◽  
pp. 245-251 ◽  
Author(s):  
Luigi Leonori ◽  
Manuel Muñoz ◽  
Carmelo Vázquez ◽  
José J. Vázquez ◽  
Mary Fe Bravo ◽  
...  
Keyword(s):  
Mental Health ◽  
European Union ◽  
Social Exclusion ◽  
Mentally Ill ◽  
Outcome Evaluation ◽  
World Federation ◽  
The European Union ◽  
Capital Cities ◽  
Homeless Mentally Ill ◽  
The Impact

This report concerns the activities developed by the Mental Health and Social Exclusion (MHSE) Network, an initiative supported by the Mental Health Europe (World Federation of Mental Health). We report some data from the preliminary survey done in five capital cities of the European Union (Madrid, Copenhagen, Brussels, Lisbon, and Rome). The main aim of this survey was to investigate, from a mostly qualitative point of view, the causal and supportive factors implicated in the situation of the homeless mentally ill in Europe. The results point out the familial and childhood roots of homelessness, the perceived causes of the situation, the relationships with the support services, and the expectations of future of the homeless mentally ill. The analysis of results has helped to identify the different variables implicated in the social rupture process that influences homelessness in major European cities. The results were used as the basis for the design of a more ambitious current research project about the impact of the medical and psychosocial interventions in the homeless. This project is being developed in 10 capital cities of the European Union with a focus on the program and outcome evaluation of the health and psychosocial services for the disadvantaged.

Russia - European Union: The continuation ofthe sanctions standoff

2017 ◽  
pp. 114-127
Author(s):  
M. Klinova ◽  
E. Sidorova
Keyword(s):  
European Union ◽  
Economic Recession ◽  
Economic Sanctions ◽  
Current Data ◽  
The State ◽  
The European Union ◽  
The Impact ◽  
The Eu ◽  
Year 2013

The article deals with economic sanctions and their impact on the state and prospects of the neighboring partner economies - the European Union (EU) and Russia. It provides comparisons of current data with that of the year 2013 (before sanctions) to demonstrate the impact of sanctions on both sides. Despite the fact that Russia remains the EU’s key partner, it came out of the first three partners of the EU. The current economic recession is caused by different reasons, not only by sanctions. Both the EU and Russia have internal problems, which the sanctions confrontation only exacerbates. The article emphasizes the need for a speedy restoration of cooperation.

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